WorldWideScience

Sample records for hadley climate model

  1. The Dynamics of Hadley Circulation Variability and Change

    Science.gov (United States)

    Davis, Nicholas Alexander

    The Hadley circulation exerts a dominant control on the surface climate of earth's tropical belt. Its converging surface winds fuel the tropical rains, while subsidence in the subtropics dries and stabilizes the atmosphere, creating deserts on land and stratocumulus decks over the oceans. Because of the strong meridional gradients in temperature and precipitation in the subtropics, any shift in the Hadley circulation edge could project as major changes in surface climate. While climate model simulations predict an expansion of the Hadley cells in response to greenhouse gas forcings, the mechanisms remain elusive. An analysis of the climatology, variability, and response of the Hadley circulation to radiative forcings in climate models and reanalyses illuminates the broader landscape in which Hadley cell expansion is realized. The expansion is a fundamental response of the atmosphere to increasing greenhouse gas concentrations as it scales with other key climate system changes, including polar amplification, increasing static stability, stratospheric cooling, and increasing global-mean surface temperatures. Multiple measures of the Hadley circulation edge latitudes co-vary with the latitudes of the eddy-driven jets on all timescales, and both exhibit a robust poleward shift in response to forcings. Further, across models there is a robust coupling between the eddy-driving on the Hadley cells and their width. On the other hand, the subtropical jet and tropopause break latitudes, two common observational proxies for the tropical belt edges, lack a strong statistical relationship with the Hadley cell edges and have no coherent response to forcings. This undermines theories for the Hadley cell width predicated on angular momentum conservation and calls for a new framework for understanding Hadley cell expansion. A numerical framework is developed within an idealized general circulation model to isolate the mean flow and eddy responses of the global atmosphere to

  2. Climate Variability over India and Bangladesh from the Perturbed UK Met Office Hadley Model: Impacts on Flow and Nutrient Fluxes in the Ganges Delta System

    Science.gov (United States)

    Whitehead, P. G.; Caesar, J.; Crossman, J.; Barbour, E.; Ledesma, J.; Futter, M. N.

    2015-12-01

    A semi-distributed flow and water quality model (INCA- Integrated Catchments Model) has been set up for the whole of the Ganges- Brahmaputra- Meghna (GBM) River system in India and Bangladesh. These massive rivers transport large fluxes of water and nutrients into the Bay of Bengal via the GBM Delta system in Bangladesh. Future climate change will impact these fluxes with changing rainfall, temperature, evapotranspiration and soil moisture deficits being altered in the catchment systems. In this study the INCA model has been used to assess potential impacts of climate change using the UK Met Office Hadley Centre GCM model linked to a regionally coupled model of South East Asia, covering India and Bangladesh. The Hadley Centre model has been pururbed by varying the parameters in the model to generate 17 realisations of future climates. Some of these reflect expected change but others capture the more extreme potential behaviour of future climate conditions. The 17 realisations have been used to drive the INCA Flow and Nitrogen model inorder to generate downstream times series of hydrology and nitrate- nitrogen. The variability of the climates on these fluxes are investigated and and their likley impact on the Bay of Begal Delta considered. Results indicate a slight shift in the monsoon season with increased wet season flows and increased temperatures which alter nutrient fluxes. Societal Importance to Stakeholders The GBM Delta supports one of the most densely populated regions of people living in poverty, who rely on ecosystem services provided by the Delta for survival. These ecosystem services are dependent upon fluxes of water and nutrients. Freshwater for urban, agriculture, and aquaculture requirements are essential to livelihoods. Nutrient loads stimulate estuarine ecosystems, supporting fishing stocks, which contribute significantly the economy of Bangladesh. Thus the societal importance of upstream climate driven change change in Bangladesh are very

  3. Possible Role of Hadley Circulation Strengthening in Interdecadal Intensification of Snowfalls Over Northeastern China Under Climate Change

    Science.gov (United States)

    Zhou, Botao; Wang, Zunya; Shi, Ying

    2017-11-01

    This article revealed that strengthening of winter Hadley circulation in the context of climate change may partially contribute to interdecadal increasing of snowfall intensity over northeastern China in recent decades. This hypothesis is well supported by the process-based linkage between Hadley circulation and atmospheric circulations over the Asian-Pacific region on the interdecadal time scale. The strengthening of winter Hadley circulation corresponds to a weakening of the Siberian high, an eastward shifting of the Aleutian low, a reduction of the East Asian trough, and anomalous southwesterly prevailing over northeastern China. These atmospheric situations weaken the East Asian winter monsoon and lead to an increase of air temperature over northeastern China. Increased local evaporation due to the increase of air temperature, concurrent with more water vapor transported from the Pacific Ocean, can significantly enhance atmospheric water vapor content in the target region. Meanwhile, the ascending of airflows is also strengthened over northeastern China. All of these provide favorable interdecadal backgrounds for the occurrence of intense snowfalls, and thus, snowfall intensity is intensified over northeastern China after the 1980s. Further analysis suggests that the circum-Pacific-like teleconnection pattern may play an important role in connecting Hadley circulation strengthening signal and atmospheric circulation anomalies favoring interdecadal intensification of snowfalls over northeastern China.

  4. The Interplay of Internal and Forced Modes of Hadley Cell Expansion: Lessons from the Global Warming Hiatus

    Science.gov (United States)

    Amaya, D. J.; Siler, N.; Xie, S. P.; Miller, A. J.

    2017-12-01

    The poleward branches of the Hadley Cells show a robust shift poleward shift during the satellite era, leading to concerns over the possible encroachment of the globe's subtropical dry zones into currently temperate climates. The extent to which this trend is caused by anthropogenic forcing versus internal variability remains the subject of considerable debate. In this study, we us a joint EOF method to identify two distinct modes of Hadley Cell variability: (i) an anthropogenically-forced mode, which we identify using a 20-member simulation of the historical climate, and (ii) an internal mode, which identify using a 1000-year pre-industrial control simulation with a global climate model. The forced mode is found to be closely related to the TOA radiative imbalance and exhibits a long-term trend since 1860, while the internal mode is found to be essentially indistinguishable from the El Niño Southern Oscillation (ENSO). Together these two modes explain an average of 70% of the interannual variability seen in model "edge indices" over the historical period. Since 1980, the superposition of forced and internal modes has resulted in a period of accelerated Hadley Cell expansion and decelerated global warming (i.e., the "hiatus"). A comparison of the change in these modes since 1980 indicates that by 2013 the signal has emerged above the noise of internal variability in the Southern Hemisphere (SH), but not in the Northern Hemisphere (NH), with the latter also exhibiting strong zonal asymmetry, particularly in the North Atlantic. Our results highlight the important interplay of internal and forced modes of Hadley Cell width change and improve our understanding of the interannual variability and long-term trend seen in observations.

  5. Analysis of bullwhip effect on supply chain with Q model using Hadley-Within approach

    Science.gov (United States)

    Siregar, I.; Nasution, A. A.; Matondang, N.; Persada, M. R.; Syahputri, K.

    2018-02-01

    This research held on a tapioca flour industry company that uses cassava as raw material to produce tapioca starch product. Problems that occur in this company is inaccurate planning, consequently there is a shortage of variation between the number of requests with the total supply is met, so it is necessary to do research with the formulation of the problem that is how to analyze the Bullwhip Effect on the supply chain using Q model through Hadley-Within approach so as not to disturb the product distribution system at the company. Product distribution system at the company, obtained by the number of requests. The 2015 forecast result is lower than actual demand for distributors and manufactures in 2016 with average percentage difference for Supermarket A distributor, Supermarket B and manufacturing respectively 38.24%, 89.57% and 43.11%. The occurrence of information distortion to the demand of this product can identify the existence of bullwhip effect on the supply chain. The proposed improvement to overcome the bullwhip effect is by doing inventory control policy with Q model using Hadley-Within approach.

  6. Quantifying the effects of climate change on water resources in Denmark

    DEFF Research Database (Denmark)

    Van Roosmalen, Lieke Petronella G; Sonnenborg, Torben O.; Christensen, Jens H.

    2007-01-01

    climatological output data from the regional climate model HIRHAM (Danish Meteorological Institute), which dynamically downscales the climate change signals from the coarser resolution global climate model HadAM3H (Hadley Centre), with the concentrations of greenhouse gases and aerosols based on the IPCC SRES A2...

  7. A Robust Response of the Hadley Circulation to Global Warming

    Science.gov (United States)

    Lau, William K M.; Kim, Kyu-Myong

    2014-01-01

    Tropical rainfall is expected to increase in a warmer climate. Yet, recent studies have inferred that the Hadley Circulation (HC), which is primarily driven by latent heating from tropical rainfall, is weakened under global warming. Here, we show evidence of a robust intensification of the HC from analyses of 33 CMIP5 model projections under a scenario of 1 per year CO2 emission increase. The intensification is manifested in a deep-tropics squeeze, characterized by a pronounced increase in the zonal mean ascending motion in the mid and upper troposphere, a deepening and narrowing of the convective zone and enhanced rainfall in the deep tropics. These changes occur in conjunction with a rise in the region of maximum outflow of the HC, with accelerated meridional mass outflow in the uppermost branch of the HC away from the equator, coupled to a weakened inflow in the return branches of the HC in the lower troposphere.

  8. Geoengineering by stratospheric SO2 injection: results from the Met Office HadGEM2 climate model and comparison with the Goddard Institute for Space Studies ModelE

    Directory of Open Access Journals (Sweden)

    B. Kravitz

    2010-07-01

    Full Text Available We examine the response of the Met Office Hadley Centre's HadGEM2-AO climate model to simulated geoengineering by continuous injection of SO2 into the lower stratosphere, and compare the results with those from the Goddard Institute for Space Studies ModelE. Despite the differences between the models, we find a broadly similar geographic distribution of the response to geoengineering in both models in terms of near-surface air temperature and mean June–August precipitation. The simulations also suggest that significant changes in regional climate would be experienced even if geoengineering was successful in maintaining global-mean temperature near current values, and both models indicate rapid warming if geoengineering is not sustained.

  9. Socioeconomic impacts of climate change on U.S. water supplies

    Science.gov (United States)

    Frederick, K.D.; Schwarz, G.E.

    1999-01-01

    A greenhouse warming would have major effects on water supplies and demands. A framework for examining the socioeconomic impacts associated with changes in the long-term availability of water is developed and applied to the hydrologic implications of the Canadian and British Hadley2 general circulation models (GCMs) for the 18 water resource regions in the conterminous United States. The climate projections of these two GCMs have very different implications for future water supplies and costs. The Canadian model suggests most of the nation would be much drier in the year 2030. Under the least-cost management scenario the drier climate could add nearly $105 billion to the estimated costs of balancing supplies and demands relative to the costs without climate change. Measures to protect instream flows and irrigation could result in significantly higher costs. In contrast, projections based on the Hadley model suggest water supplies would increase throughout much of the nation, reducing the costs of balancing water supplies with demands relative to the no-climate-change case.

  10. Global high resolution versus Limited Area Model climate change projections over Europe

    DEFF Research Database (Denmark)

    Déqué, Michel; Jones, R. G.; Wild, M.

    2005-01-01

    the 2071-2100 and the 1961-1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly......, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs - in particular in terms of precipitation - is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes...... errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs....

  11. Volcano and ship tracks indicate excessive aerosol-induced cloud water increases in a climate model.

    Science.gov (United States)

    Toll, Velle; Christensen, Matthew; Gassó, Santiago; Bellouin, Nicolas

    2017-12-28

    Aerosol-cloud interaction is the most uncertain mechanism of anthropogenic radiative forcing of Earth's climate, and aerosol-induced cloud water changes are particularly poorly constrained in climate models. By combining satellite retrievals of volcano and ship tracks in stratocumulus clouds, we compile a unique observational dataset and confirm that liquid water path (LWP) responses to aerosols are bidirectional, and on average the increases in LWP are closely compensated by the decreases. Moreover, the meteorological parameters controlling the LWP responses are strikingly similar between the volcano and ship tracks. In stark contrast to observations, there are substantial unidirectional increases in LWP in the Hadley Centre climate model, because the model accounts only for the decreased precipitation efficiency and not for the enhanced entrainment drying. If the LWP increases in the model were compensated by the decreases as the observations suggest, its indirect aerosol radiative forcing in stratocumulus regions would decrease by 45%.

  12. Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

    Science.gov (United States)

    Ruane, Alex C.; Goldberg, Richard; Chryssanthacopoulos, James

    2014-01-01

    The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

  13. An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

    Science.gov (United States)

    Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

    2003-12-01

    Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

  14. Interannual Variability of Regional Hadley Circulation Intensity Over Western Pacific During Boreal Winter and Its Climatic Impact Over Asia-Australia Region

    Science.gov (United States)

    Huang, Ruping; Chen, Shangfeng; Chen, Wen; Hu, Peng

    2018-01-01

    This study investigates interannual variability of boreal winter regional Hadley circulation over western Pacific (WPHC) and its climatic impacts. A WPHC intensity index (WPHCI) is defined as the vertical shear of the divergent meridional winds. It shows that WPHCI correlates well with the El Niño-Southern Oscillation (ENSO). To investigate roles of the ENSO-unrelated part of WPHCI (WPHCIres), variables that are linearly related to the Niño-3 index have been removed. It reveals that meridional sea surface temperature gradient over the western Pacific plays an essential role in modulating the WPHCIres. The climatic impacts of WPHCIres are further investigated. Below-normal (above-normal) precipitation appears over south China (North Australia) when WPHCIres is stronger. This is due to the marked convergence (divergence) anomalies at the upper troposphere, divergence (convergence) at the lower troposphere, and the accompanied downward (upward) motion over south China (North Australia), which suppresses (enhances) precipitation there. In addition, a pronounced increase in surface air temperature (SAT) appears over south and central China when WPHCIres is stronger. A temperature diagnostic analysis suggests that the increase in SAT tendency over central China is primarily due to the warm zonal temperature advection and subsidence-induced adiabatic heating. In addition, the increase in SAT tendency over south China is primarily contributed by the warm meridional temperature advection. Further analysis shows that the correlation of WPHCIres with the East Asian winter monsoon (EAWM) is weak. Thus, this study may provide additional sources besides EAWM and ENSO to improve understanding of the Asia-Australia climate variability.

  15. Hadley Rille, lava tubes and mare volcanism at the Apollo 15 site

    International Nuclear Information System (INIS)

    Greeley, R.; Spudis, P.D.

    1985-01-01

    Hadley Rille appears to be a collapsed lava tube/channel, whose formation history may be more intimately related to the mare units sampled at 15 than was previously thought. More work is needed relating samples and observations from Apollo 15 to the rille and its geologic evolution. As the only sinuous rille visited during the Apollo missions, Hadley Rille represents a data source that is directly applicable to the deciphering of processes involved in lunar mare volcanism

  16. Geologic history of quartz-normative and olivine-normative basalts in the vicinity of Hadley Rille (Apollo 15)

    International Nuclear Information System (INIS)

    Grove, T.L.

    1985-01-01

    The geologic history of the quartz normative (QNB) and olivine normative (ONB) basalt types at Hadley Rille are discussed. A model for the geology of the mare basalts was constructed from a combination of field observations, sample chemistry, sample petrology and personal bias from terrestrial experience. The model proposes that the QNBs are the only mare lava type that is present as outcrop in the area traversed by the astronauts during the Apollo 15 mission. The returned QNB samples formed during a single eruptive phase of the Hadley Rille lava tube system. The ONB lavas are an exotic component transported to the site by a cratering event, or the ONBs are samples excavated from older are bedrock that was partly covered by the QNB lavas

  17. Variability of the extent of the Hadley circulation in the southern hemisphere: a regional perspective

    Science.gov (United States)

    Nguyen, H.; Hendon, H. H.; Lim, E.-P.; Boschat, G.; Maloney, E.; Timbal, B.

    2018-01-01

    In order to understand the regional impacts of variations in the extent of the Hadley circulation in the Southern Hemisphere, regional Hadley circulations are defined in three sectors centered on the main tropical heat sources over Africa, Asia-Pacific (Maritime Continent) and the Americas. These regional circulations are defined by computing a streamfunction from the divergent component of the meridional wind. A major finding from this study is that year-to-year variability in the extent of the hemispheric Hadley circulation in the Southern Hemisphere is primarily governed by variations of the extent of the Hadley circulation in the Asia-Pacific sector, especially during austral spring and summer when there is little co-variability with the African sector, and the American sector exhibits an out of phase behavior. An expanded Hadley circulation in the Southern Hemisphere (both hemispherically and in the Asia-Pacific sector) is associated with La Niña conditions and a poleward expansion of the tropical wet zone in the Asia-Pacific sector. While La Niña also promotes expansion in the American and African sectors during austral winter, these tropical conditions tend to promote contraction in the two sectors during austral summer as a result of compensating convergence over the Americas and Africa sectors: a process driven by variations in the Walker circulation and Rossby wave trains emanating from the tropical Indian Ocean.

  18. Climate change projections for Tamil Nadu, India: deriving high-resolution climate data by a downscaling approach using PRECIS

    Science.gov (United States)

    Bal, Prasanta Kumar; Ramachandran, A.; Geetha, R.; Bhaskaran, B.; Thirumurugan, P.; Indumathi, J.; Jayanthi, N.

    2016-02-01

    In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments.

  19. Investigating the impacts of climate change on Chinese agriculture. China-UK collaboration project

    Energy Technology Data Exchange (ETDEWEB)

    Erda, Lin (ed.)

    2004-04-15

    The impact of climate change in China is expected to be considerable. A regional climate change model (PRECIS), developed by the UK's Hadley Centre for Climate Prediction and Research, was used to simulate China's climate and to develop climate change scenarios for the country. Results from this project suggest that, depending on the level of future emissions, the average temperature increase in China by the end of the 21st century may be between 3 and 4C.

  20. Representation of Northern Hemisphere winter storm tracks in climate models

    Energy Technology Data Exchange (ETDEWEB)

    Greeves, C.Z.; Pope, V.D.; Stratton, R.A.; Martin, G.M. [Met Office Hadley Centre for Climate Prediction and Research, Exeter (United Kingdom)

    2007-06-15

    Northern Hemisphere winter storm tracks are a key element of the winter weather and climate at mid-latitudes. Before projections of climate change are made for these regions, it is necessary to be sure that climate models are able to reproduce the main features of observed storm tracks. The simulated storm tracks are assessed for a variety of Hadley Centre models and are shown to be well modelled on the whole. The atmosphere-only model with the semi-Lagrangian dynamical core produces generally more realistic storm tracks than the model with the Eulerian dynamical core, provided the horizontal resolution is high enough. The two models respond in different ways to changes in horizontal resolution: the model with the semi-Lagrangian dynamical core has much reduced frequency and strength of cyclonic features at lower resolution due to reduced transient eddy kinetic energy. The model with Eulerian dynamical core displays much smaller changes in frequency and strength of features with changes in horizontal resolution, but the location of the storm tracks as well as secondary development are sensitive to resolution. Coupling the atmosphere-only model (with semi-Lagrangian dynamical core) to an ocean model seems to affect the storm tracks largely via errors in the tropical representation. For instance a cold SST bias in the Pacific and a lack of ENSO variability lead to large changes in the Pacific storm track. Extratropical SST biases appear to have a more localised effect on the storm tracks. (orig.)

  1. Potential impacts of climate change on rainfall erosivity and water availability in China in the next 100 years

    Science.gov (United States)

    Ge Sun; Steven G. McNulty; Jennifer Moore; Corey Bunch; Jian Ni

    2002-01-01

    Soil erosion and water shortages threaten China’s social and economic development in the 21st century. This paper examines how projected climate change could affect soil erosion and water availability across China. We used both historical climate data (1961-1980) and the UKMO Hadley3 climate scenario (1960-2099) to drive regional hydrology and soil erosivity models....

  2. A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

    Science.gov (United States)

    Geller, Marvin A.; Alexadner, M. Joan; Love, Peter T.; Bacmeister, Julio; Ern, Manfred; Hertzog, Albert; Manzini, Elisa; Preusse, Peter; Sato, Kaoru; Scaife, Adam A.; hide

    2013-01-01

    For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations,MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.

  3. Tropospheric jet response to Antarctic ozone depletion: An update with Chemistry-Climate Model Initiative (CCMI) models

    Science.gov (United States)

    Son, Seok-Woo; Han, Bo-Reum; Garfinkel, Chaim I.; Kim, Seo-Yeon; Park, Rokjin; Abraham, N. Luke; Akiyoshi, Hideharu; Archibald, Alexander T.; Butchart, N.; Chipperfield, Martyn P.; Dameris, Martin; Deushi, Makoto; Dhomse, Sandip S.; Hardiman, Steven C.; Jöckel, Patrick; Kinnison, Douglas; Michou, Martine; Morgenstern, Olaf; O’Connor, Fiona M.; Oman, Luke D.; Plummer, David A.; Pozzer, Andrea; Revell, Laura E.; Rozanov, Eugene; Stenke, Andrea; Stone, Kane; Tilmes, Simone; Yamashita, Yousuke; Zeng, Guang

    2018-05-01

    The Southern Hemisphere (SH) zonal-mean circulation change in response to Antarctic ozone depletion is re-visited by examining a set of the latest model simulations archived for the Chemistry-Climate Model Initiative (CCMI) project. All models reasonably well reproduce Antarctic ozone depletion in the late 20th century. The related SH-summer circulation changes, such as a poleward intensification of westerly jet and a poleward expansion of the Hadley cell, are also well captured. All experiments exhibit quantitatively the same multi-model mean trend, irrespective of whether the ocean is coupled or prescribed. Results are also quantitatively similar to those derived from the Coupled Model Intercomparison Project phase 5 (CMIP5) high-top model simulations in which the stratospheric ozone is mostly prescribed with monthly- and zonally-averaged values. These results suggest that the ozone-hole-induced SH-summer circulation changes are robust across the models irrespective of the specific chemistry-atmosphere-ocean coupling.

  4. High-resolution global climate modelling: the UPSCALE project, a large-simulation campaign

    Directory of Open Access Journals (Sweden)

    M. S. Mizielinski

    2014-08-01

    Full Text Available The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk project constructed and ran an ensemble of HadGEM3 (Hadley Centre Global Environment Model 3 atmosphere-only global climate simulations over the period 1985–2011, at resolutions of N512 (25 km, N216 (60 km and N96 (130 km as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe in 2012, with additional resources supplied by the Natural Environment Research Council (NERC and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the High Performance Computing Center Stuttgart (HLRS, and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE data set. This data set is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.

  5. A New Model Hierarchy to Understand the Impact of Radiation and Convection on the Extratropical Circulation Response to Climate Change

    Science.gov (United States)

    Tan, Z.; Shaw, T.

    2017-12-01

    State-of-the-art climate models exhibit a large spread in the magnitude of projected poleward jet shift and Hadley cell expansion in response to warming. Interestingly, some idealized gray radiation models with simplified convective schemes produce an equatorward jet shift in response to warming. In order to understand the impact of radiation and convection on the circulation response and resolve the discrepancies across the model hierarchy, we introduce a new model radiation-convection hierarchy. The hierarchy spans idealized (gray) through sophisticated (RRTMG) radiation, and idealized (Betts-Miller) through sophisticated (eddy-diffusivity mass-flux scheme) convection schemes in the same general circulation model. It is used to systematically explore the impact of radiation and convection on the extratropical circulation response to climate change independent of mean surface temperature and meridional temperature gradient responses. With a gray radiation scheme, the jet stream shift depends on the prescribed stratospheric optical depth, which controls the climatological jet regime. A large optical depth leads to a split jet and an equatorward shift. A small optical depth leads to a poleward shift. The different shifts are connected to the vertical extent of tropical long wave cooling that impacts the subtropical jet and Hadley circulation. In spite of these sensitivities, the storm track position, defined by the meridonal eddy heat flux and moist static energy flux maxima, shifts robustly poleward. In contrast to gray radiation, with a comprehensive radiation scheme, the jet and storm track shift robustly poleward irrespective of radiative assumptions (clear sky versus cloudy sky, ozone versus no ozone). This response is reproduced by adding more spectral bands and including the water vapor feedback in the gray scheme. Dynamical sensitivities to convective assumption are also explored. Overall the new hierarchy highlights the importance of radiative and

  6. Amazon collapse in the next century: exploring the sensitivity to climate and model formulation uncertainties

    Science.gov (United States)

    Booth, B.; Collins, M.; Harris, G.; Chris, H.; Jones, C.

    2007-12-01

    A number of recent studies have highlighted the risk of abrupt dieback of the Amazon Rain Forest as the result of climate changes over the next century. The recent 2005 Amazon drought brought wider acceptance of the idea that that climate drivers will play a significant role in future rain forest stability, yet that stability is still subject to considerable degree of uncertainty. We present a study which seeks to explore some of the underlying uncertainties both in the climate drivers of dieback and in the terrestrial land surface formulation used in GCMs. We adopt a perturbed physics approach which forms part of a wider project which is covered in an accompanying abstract submitted to the multi-model ensembles session. We first couple the same interactive land surface model to a number of different versions of the Hadley Centre atmosphere-ocean model that exhibit a wide range of different physical climate responses in the future. The rainforest extent is shown to collapse in all model cases but the timing of the collapse is dependent on the magnitude of the climate drivers. In the second part, we explore uncertainties in the terrestrial land surface model using the perturbed physics ensemble approach, perturbing uncertain parameters which have an important role in the vegetation and soil response. Contrasting the two approaches enables a greater understanding of the relative importance of climatic and land surface model uncertainties in Amazon dieback.

  7. Modelling Snowmelt Runoff under Climate Change Scenarios in an Ungauged Mountainous Watershed, Northwest China

    Directory of Open Access Journals (Sweden)

    Yonggang Ma

    2013-01-01

    Full Text Available An integrated modeling system has been developed for analyzing the impact of climate change on snowmelt runoff in Kaidu Watershed, Northwest China. The system couples Hadley Centre Coupled Model version 3 (HadCM3 outputs with Snowmelt Runoff Model (SRM. The SRM was verified against observed discharge for outlet hydrological station of the watershed during the period from April to September in 2001 and generally performed well for Nash-Sutcliffe coefficient (EF and water balance coefficient (RE. The EF is approximately over 0.8, and the water balance error is lower than ± 10%, indicating reasonable prediction accuracy. The Statistical Downscaling Model (SDSM was used to downscale coarse outputs of HadCM3, and then the downscaled future climate data were used as inputs of the SRM. Four scenarios were considered for analyzing the climate change impact on snowmelt flow in the Kaidu Watershed. And the results indicated that watershed hydrology would alter under different climate change scenarios. The stream flow in spring is likely to increase with the increased mean temperature; the discharge and peck flow in summer decrease with the decreased precipitation under Scenarios 1 and 2. Moreover, the consideration of the change in cryosphere area would intensify the variability of stream flow under Scenarios 3 and 4. The modeling results provide useful decision support for water resources management.

  8. Spectral reflectance study of the Hadley-Appenine (Apollo 15) region

    International Nuclear Information System (INIS)

    Lucey, P.G.; Hawke, B.R.

    1985-01-01

    Twenty three near infrared spectra were obtained from the Mauna Kea Observatory 2.2 m telescope. Results of an analysis of near infrared spectra obtained for surface units in the Hadley-Apennine region were presented. Compositional trends from the interior to exterior of the Imbrium are discussed

  9. How positive is the feedback between climate change and the carbon cycle?

    International Nuclear Information System (INIS)

    Friedlingstein, P.; Rayner, P.

    2003-01-01

    Future climate change induced by atmospheric emissions of greenhouse gases is believed to have a large impact on the global carbon cycle. Several offline studies focusing either on the marine or on the terrestrial carbon cycle highlighted such potential effects. Two recent online studies, using ocean-atmosphere general circulation models coupled to land and ocean carbon cycle models, investigated in a consistent way the feedback between the climate change and the carbon cycle. These two studies used observed anthropogenic CO 2 emissions for the 1860-1995 period and IPCC scenarios for the 1995-2100 period to force the climate - carbon cycle models. The study from the Hadley Centre group showed a very large positive feedback, atmospheric CO 2 reaching 980 ppmv by 2100 if future climate impacts on the carbon cycle, but only about 700 ppmv if the carbon cycle is included but assumed to be insensitive to the climate change. The IPSL coupled climate - carbon cycle model simulated a much smaller positive feedback: climate impact on the carbon cycle leads by 2100 to an addition of less than 100 ppmv in the atmosphere. Here we perform a detailed feedback analysis to show that such differences are due to two key processes that are still poorly constrained in these coupled models: first Southern Ocean circulation, which primarily controls the geochemical uptake of CO 2 , and second vegetation and soil carbon response to global warming. Our analytical analysis reproduces remarkably the results obtained by the fully coupled models. Also it allows us to identify that, amongst the two processes mentioned above, the latter (the land response to global warming) is the one that essentially explains the differences between the IPSL and the Hadley results

  10. Spanning the Pacific Ocean through Voice-Over Internet Protocol Chat with the Hadley School for the Blind--China

    Science.gov (United States)

    Gilson, Christie L.; Rongqiang, Xia

    2007-01-01

    Founded in 1920, the Hadley School for the Blind is known worldwide for its tuition-free distance-education courses for people who are visually impaired. Hadley's main school in the United States serves more than 9,000 students, and the overseas school in the People's Republic of China provides vital educational services to more than 1,000 Chinese…

  11. Idealized climate change simulations with a high-resolution physical model: HadGEM3-GC2

    Science.gov (United States)

    Senior, Catherine A.; Andrews, Timothy; Burton, Chantelle; Chadwick, Robin; Copsey, Dan; Graham, Tim; Hyder, Pat; Jackson, Laura; McDonald, Ruth; Ridley, Jeff; Ringer, Mark; Tsushima, Yoko

    2016-06-01

    Idealized climate change simulations with a new physical climate model, HadGEM3-GC2 from The Met Office Hadley Centre are presented and contrasted with the earlier MOHC model, HadGEM2-ES. The role of atmospheric resolution is also investigated. The Transient Climate Response (TCR) is 1.9 K/2.1 K at N216/N96 and Effective Climate Sensitivity (ECS) is 3.1 K/3.2 K at N216/N96. These are substantially lower than HadGEM2-ES (TCR: 2.5 K; ECS: 4.6 K) arising from a combination of changes in the size of climate feedbacks. While the change in the net cloud feedback between HadGEM3 and HadGEM2 is relatively small, there is a change in sign of its longwave and a strengthening of its shortwave components. At a global scale, there is little impact of the increase in atmospheric resolution on the future climate change signal and even at a broad regional scale, many features are robust including tropical rainfall changes, however, there are some significant exceptions. For the North Atlantic and western Europe, the tripolar pattern of winter storm changes found in most CMIP5 models is little impacted by resolution but for the most intense storms, there is a larger percentage increase in number at higher resolution than at lower resolution. Arctic sea-ice sensitivity shows a larger dependence on resolution than on atmospheric physics.

  12. The Mechanisms of Natural Variability and its Interaction with Anthropogenic Climate Change Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Vallis, Geoffrey K. [Princeton Univ., NJ (United States)

    2015-01-30

    The project had two main components. The first concerns estimating the climate sensitivity in the presence of forcing uncertainty and natural variability. Climate sensitivity is the increase in the average surface temperature for a given increase in greenhouse gases, for example a doubling of carbon dioxide. We have provided new, probabilistic estimates of climate sensitivity using a simple climate model an the observed warming in the 20th century, in conjunction with ideas in data assimilation and parameter estimation developed in the engineering community. The estimates combine the uncertainty in the anthropogenic aerosols with the uncertainty arising because of natural variability. The second component concerns how the atmospheric circulation itself might change with anthropogenic global warming. We have shown that GCMs robustly predict an increase in the length scale of eddies, and we have also explored the dynamical mechanisms whereby there might be a shift in the latitude of the jet stream associated with anthropogenic warming. Such shifts in the jet might cause large changes in regional climate, potentially larger than the globally-averaged signal itself. We have also shown that the tropopause robustly increases in height with global warming, and that the Hadley Cell expands, and that the expansion of the Hadley Cell is correlated with the polewards movement of the mid-latitude jet.

  13. Impact of Tropical Volcanic Eruptions on Hadley Circulation Using a High-Resolution AGCM

    KAUST Repository

    Dogar, Muhammad Mubashar

    2018-03-31

    The direct radiative effects of volcanic eruptions resulting in solar dimming, stratospheric warming, global surface cooling and reduction in rainfall are well documented. However, eruptions also cause indirect climatic impacts that are not well understood. For example, solar dimming induced by volcanic aerosols could cause changes in tropical Hadley circulation that in turn largely affect evaporation and precipitation patterns. Therefore, understanding the sensitivity of HC to volcanism is essential, as this circulation is directly related to precipitation changes in the tropics and with other large-scale circulations. Hence, to better understand the post-eruption sensitivity of HC and associated changes in the hydrologic cycle, simulations for the El Chichón and Pinatubo tropical eruptions were conducted using a high-resolution atmospheric model (HIRAM), effectively at 25 and 50 km grid spacing. The model simulated results are then compared with observational and reanalysis products. Both the model and observational analysis show posteruption weakening, shrinking and equatorward displacement of the updraft branch of HC caused by the equatorward shift of midlatitude jets and hemispheric land-sea thermal gradient. The Intertropical Convergence Zone (ITCZ) is tightly coupled to the rising branch of HC, hence, post-eruption weakening and equatorward displacement of HC cause weakening of ITCZ that adversely affects rainfall distribution in the monsoon-fed regions, especially the South Asian and African tropical rain-belt regions. The modelproduced post-eruption distribution of cloud contents suggests a southward shift of ITCZ. The HIRAM results are largely in agreement with the reanalysis, observations and previous studies indicating that this model performs reasonably well in reproducing the global and regional-scale dynamic changes caused by volcanic radiative forcing.

  14. Impact of Tropical Volcanic Eruptions on Hadley Circulation Using a High-Resolution AGCM

    KAUST Repository

    Dogar, Muhammad Mubashar

    2018-01-01

    The direct radiative effects of volcanic eruptions resulting in solar dimming, stratospheric warming, global surface cooling and reduction in rainfall are well documented. However, eruptions also cause indirect climatic impacts that are not well understood. For example, solar dimming induced by volcanic aerosols could cause changes in tropical Hadley circulation that in turn largely affect evaporation and precipitation patterns. Therefore, understanding the sensitivity of HC to volcanism is essential, as this circulation is directly related to precipitation changes in the tropics and with other large-scale circulations. Hence, to better understand the post-eruption sensitivity of HC and associated changes in the hydrologic cycle, simulations for the El Chichón and Pinatubo tropical eruptions were conducted using a high-resolution atmospheric model (HIRAM), effectively at 25 and 50 km grid spacing. The model simulated results are then compared with observational and reanalysis products. Both the model and observational analysis show posteruption weakening, shrinking and equatorward displacement of the updraft branch of HC caused by the equatorward shift of midlatitude jets and hemispheric land-sea thermal gradient. The Intertropical Convergence Zone (ITCZ) is tightly coupled to the rising branch of HC, hence, post-eruption weakening and equatorward displacement of HC cause weakening of ITCZ that adversely affects rainfall distribution in the monsoon-fed regions, especially the South Asian and African tropical rain-belt regions. The modelproduced post-eruption distribution of cloud contents suggests a southward shift of ITCZ. The HIRAM results are largely in agreement with the reanalysis, observations and previous studies indicating that this model performs reasonably well in reproducing the global and regional-scale dynamic changes caused by volcanic radiative forcing.

  15. Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5

    Science.gov (United States)

    Zhao, Wenjie; Peng, Yiran; Wang, Bin; Yi, Bingqi; Lin, Yanluan; Li, Jiangnan

    2018-05-01

    A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4 °C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.

  16. Modelling soil borne fungal pathogens of arable crops under climate change.

    Science.gov (United States)

    Manici, L M; Bregaglio, S; Fumagalli, D; Donatelli, M

    2014-12-01

    Soil-borne fungal plant pathogens, agents of crown and root rot, are seldom considered in studies on climate change and agriculture due both to the complexity of the soil system and to the incomplete knowledge of their response to environmental drivers. A controlled chamber set of experiments was carried out to quantify the response of six soil-borne fungi to temperature, and a species-generic model to simulate their response was developed. The model was linked to a soil temperature model inclusive of components able to simulate soil water content also as resulting from crop water uptake. Pathogen relative growth was simulated over Europe using the IPCC A1B emission scenario derived from the Hadley-CM3 global climate model. Climate scenarios of soil temperature in 2020 and 2030 were compared to the baseline centred in the year 2000. The general trend of the response of soil-borne pathogens shows increasing growth in the coldest areas of Europe; however, a larger rate of increase is shown from 2020 to 2030 compared to that of 2000 to 2020. Projections of pathogens of winter cereals indicate a marked increase of growth rate in the soils of northern European and Baltic states. Fungal pathogens of spring sowing crops show unchanged conditions for their growth in soils of the Mediterranean countries, whereas an increase of suitable conditions was estimated for the areals of central Europe which represent the coldest limit areas where the host crops are currently grown. Differences across fungal species are shown, indicating that crop-specific analyses should be ran.

  17. Maritime Continent seasonal climate biases in AMIP experiments of the CMIP5 multimodel ensemble

    Science.gov (United States)

    Toh, Ying Ying; Turner, Andrew G.; Johnson, Stephanie J.; Holloway, Christopher E.

    2018-02-01

    The fidelity of 28 Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating mean climate over the Maritime Continent in the Atmospheric Model Intercomparison Project (AMIP) experiment is evaluated in this study. The performance of AMIP models varies greatly in reproducing seasonal mean climate and the seasonal cycle. The multi-model mean has better skill at reproducing the observed mean climate than the individual models. The spatial pattern of 850 hPa wind is better simulated than the precipitation in all four seasons. We found that model horizontal resolution is not a good indicator of model performance. Instead, a model's local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon. The comparison with coupled models in CMIP5 shows that AMIP models generally performed better than coupled models in the simulation of the global monsoon and local Hadley circulation but less well at simulating the Maritime Continent annual cycle of precipitation. To characterize model systematic biases in the AMIP runs, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I models are able to capture both the winter monsoon and summer monsoon shift, but they overestimate the precipitation; especially during the JJA and SON seasons. Cluster II models simulate weaker seasonal migration than observed, and the maximum rainfall position stays closer to the equator throughout the year. The tropics-wide properties of these clusters suggest a connection between the skill of simulating global properties of the monsoon circulation and the skill of simulating the regional scale of Maritime Continent precipitation.

  18. Acidification at the Surface in the East Sea: A Coupled Climate-carbon Cycle Model Study

    Science.gov (United States)

    Park, Young-Gyu; Seol, Kyung-Hee; Boo, Kyung-On; Lee, Johan; Cho, Chunho; Byun, Young-Hwa; Seo, Seongbong

    2018-05-01

    This modeling study investigates the impacts of increasing atmospheric CO2 concentration on acidification in the East Sea. A historical simulation for the past three decades (1980 to 2010) was performed using the Hadley Centre Global Environmental Model (version 2), a coupled climate model with atmospheric, terrestrial and ocean cycles. As the atmospheric CO2 concentration increased, acidification progressed in the surface waters of the marginal sea. The acidification was similar in magnitude to observations and models of acidification in the global ocean. However, in the global ocean, the acidification appears to be due to increased in-situ oceanic CO2 uptake, whereas local processes had stronger effects in the East Sea. pH was lowered by surface warming and by the influx of water with higher dissolved inorganic carbon (DIC) from the northwestern Pacific. Due to the enhanced advection of DIC, the partial pressure of CO2 increased faster than in the overlying air; consequently, the in-situ oceanic uptake of CO2 decreased.

  19. ENSO, IOD and Indian Summer Monsoon in NCEP climate forecast system

    Energy Technology Data Exchange (ETDEWEB)

    Pokhrel, Samir; Chaudhari, H.S.; Saha, Subodh K.; Dhakate, Ashish; Yadav, R.K.; Salunke, Kiran; Mahapatra, S.; Rao, Suryachandra A. [Indian Institute of Tropical Meteorology, Pashan, Pune (India)

    2012-11-15

    El Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Indian Summer Monsoon rainfall features are explored statistically and dynamically using National Centers for Environment Prediction (NCEP) Climate Forecast System (CFSv1) freerun in relation to observations. The 100 years of freerun provides a sufficiently long homogeneous data set to find out the mean state, periodicity, coherence among these climatic events and also the influence of ENSO and IOD on the Indian monsoon. Differences in the occurrence of seasonal precipitation between the observations and CFS freerun are examined as a coupled ocean-atmosphere system. CFS simulated ENSO and IOD patterns and their associated tropical Walker and regional Hadley circulation in pure ENSO (PEN), pure IOD (PIO) and coexisting ENSO-IOD (PEI) events have some similarity to the observations. PEN composites are much closer to the observation as compared to PIO and PEI composites, which suggest a better ENSO prediction and its associated teleconnections as compared to IOD and combined phenomenon. Similar to the observation, the model simulation also show that the decrease in the Indian summer monsoon rainfall during ENSO phases is associated with a descending motion of anomalous Walker circulation and the increase in the Indian summer monsoon rainfall during IOD phase is associated with the ascending branch of anomalous regional Hadley circulation. During co-existing ENSO and IOD years, however, the fate of Indian summer monsoon is dictated by the combined influence of both of them. The shift in the anomalous descending and ascending branches of the Walker and Hadley circulation may be somewhat attributed to the cold (warm) bias over eastern (western) equatorial Indian Ocean basin, respectively in the model. This study will be useful for identifying some of the limitations of the CFS model and consequently it will be helpful in improving the model to unravel the realistic coupled ocean-atmosphere interactions

  20. Modelling climate change effects on Atlantic salmon: Implications for mitigation in regulated rivers.

    Science.gov (United States)

    Sundt-Hansen, L E; Hedger, R D; Ugedal, O; Diserud, O H; Finstad, A G; Sauterleute, J F; Tøfte, L; Alfredsen, K; Forseth, T

    2018-08-01

    Climate change is expected to alter future temperature and discharge regimes of rivers. These regimes have a strong influence on the life history of most aquatic river species, and are key variables controlling the growth and survival of Atlantic salmon. This study explores how the future abundance of Atlantic salmon may be influenced by climate-induced changes in water temperature and discharge in a regulated river, and investigates how negative impacts in the future can be mitigated by applying different regulated discharge regimes during critical periods for salmon survival. A spatially explicit individual-based model was used to predict juvenile Atlantic salmon population abundance in a regulated river under a range of future water temperature and discharge scenarios (derived from climate data predicted by the Hadley Centre's Global Climate Model (GCM) HadAm3H and the Max Plank Institute's GCM ECHAM4), which were then compared with populations predicted under control scenarios representing past conditions. Parr abundance decreased in all future scenarios compared to the control scenarios due to reduced wetted areas (with the effect depending on climate scenario, GCM, and GCM spatial domain). To examine the potential for mitigation of climate change-induced reductions in wetted area, simulations were run with specific minimum discharge regimes. An increase in abundance of both parr and smolt occurred with an increase in the limit of minimum permitted discharge for three of the four GCM/GCM spatial domains examined. This study shows that, in regulated rivers with upstream storage capacity, negative effects of climate change on Atlantic salmon populations can potentially be mitigated by release of water from reservoirs during critical periods for juvenile salmon. Copyright © 2018. Published by Elsevier B.V.

  1. Robust Hadley Circulation Changes and Increasing Global Dryness Due to CO2 Warming from CMIP-5 Model Projections

    Science.gov (United States)

    Lau, William K. M.; Kim, K. M.

    2015-01-01

    In this paper, we investigate changes in the Hadley Circulation (HC) and their connections to increased global dryness under CO2 warming from CMIP-5 model projections. We find a strengthening of the ascending branch of the HC manifested in a deep-tropics squeeze (DTS), i.e., a deepening and narrowing of the convective zone, increased high clouds, and a rise of the level of maximum meridional mass outflow in the upper troposphere (200-100 hectopascals) of the deep tropics. The DTS induces atmospheric moisture divergence, reduces tropospheric relative humidity in the tropics and subtropics, in conjunction with a widening of the subsiding branches of the HC, resulting in increased frequency of dry events in preferred geographic locations worldwide. Among water cycle parameters examined, global dryness has the highest signal-to-noise ratio. Our results provide scientific bases for inferring that the observed tend of prolonged droughts in recent decades is likely attributable to greenhouse warming.

  2. Decadal climate prediction (project GCEP).

    Science.gov (United States)

    Haines, Keith; Hermanson, Leon; Liu, Chunlei; Putt, Debbie; Sutton, Rowan; Iwi, Alan; Smith, Doug

    2009-03-13

    Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.

  3. Modelling the mid-Pliocene Warm Period climate with the IPSL coupled model and its atmospheric component LMDZ5A

    Directory of Open Access Journals (Sweden)

    C. Contoux

    2012-06-01

    Full Text Available This paper describes the experimental design and model results of the climate simulations of the mid-Pliocene Warm Period (mPWP, ca. 3.3–3 Ma using the Institut Pierre Simon Laplace model (IPSLCM5A, in the framework of the Pliocene Model Intercomparison Project (PlioMIP. We use the IPSL atmosphere ocean general circulation model (AOGCM, and its atmospheric component alone (AGCM, to simulate the climate of the mPWP. Boundary conditions such as sea surface temperatures (SSTs, topography, ice-sheet extent and vegetation are derived from the ones imposed by the Pliocene Model Intercomparison Project (PlioMIP, described in Haywood et al. (2010, 2011. We first describe the IPSL model main features, and then give a full description of the boundary conditions used for atmospheric model and coupled model experiments. The climatic outputs of the mPWP simulations are detailed and compared to the corresponding control simulations. The simulated warming relative to the control simulation is 1.94 °C in the atmospheric and 2.07 °C in the coupled model experiments. In both experiments, warming is larger at high latitudes. Mechanisms governing the simulated precipitation patterns are different in the coupled model than in the atmospheric model alone, because of the reduced gradients in imposed SSTs, which impacts the Hadley and Walker circulations. In addition, a sensitivity test to the change of land-sea mask in the atmospheric model, representing a sea-level change from present-day to 25 m higher during the mid-Pliocene, is described. We find that surface temperature differences can be large (several degrees Celsius but are restricted to the areas that were changed from ocean to land or vice versa. In terms of precipitation, impact on polar regions is minor although the change in land-sea mask is significant in these areas.

  4. Global response to solar radiation absorbed by phytoplankton in a coupled climate model

    Energy Technology Data Exchange (ETDEWEB)

    Patara, Lavinia [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Helmholtz Centre for Ocean Research Kiel (GEOMAR), Kiel (Germany); Vichi, Marcello; Masina, Simona [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Istituto Nazionale di Geofisica e Vulcanologia (INGV), Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Fogli, Pier Giuseppe [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Manzini, Elisa [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Max-Planck-Institut fuer Meteorologie, Hamburg (Germany)

    2012-10-15

    The global climate response to solar radiation absorbed by phytoplankton is investigated by performing multi-century simulations with a coupled ocean-atmosphere-biogeochemistry model. The absorption of solar radiation by phytoplankton increases radiative heating in the near-surface ocean and raises sea surface temperature (SST) by overall {approx}0.5 C. The resulting increase in evaporation enhances specific atmospheric humidity by 2-5%, thereby increasing the Earth's greenhouse effect and the atmospheric temperatures. The Hadley Cell exhibits a weakening and poleward expansion, therefore reducing cloudiness at subtropical-middle latitudes and increasing it at tropical latitudes except near the Equator. Higher SST at polar latitudes reduces sea ice cover and albedo, thereby increasing the high-latitude ocean absorption of solar radiation. Changes in the atmospheric baroclinicity cause a poleward intensification of mid-latitude westerly winds in both hemispheres. As a result, the North Atlantic Ocean meridional overturning circulation extends more northward, and the equatorward Ekman transport is enhanced in the Southern Ocean. The combination of local and dynamical processes decreases upper-ocean heat content in the Tropics and in the subpolar Southern Ocean, and increases it at middle latitudes. This study highlights the relevance of coupled ocean-atmosphere processes in the global climate response to phytoplankton solar absorption. Given that simulated impacts of phytoplankton on physical climate are within the range of natural climate variability, this study suggests the importance of phytoplankton as an internal constituent of the Earth's climate and its potential role in participating in its long-term climate adjustments. (orig.)

  5. Global response to solar radiation absorbed by phytoplankton in a coupled climate model

    International Nuclear Information System (INIS)

    Patara, Lavinia; Vichi, Marcello; Masina, Simona; Fogli, Pier Giuseppe; Manzini, Elisa

    2012-01-01

    The global climate response to solar radiation absorbed by phytoplankton is investigated by performing multi-century simulations with a coupled ocean-atmosphere-biogeochemistry model. The absorption of solar radiation by phytoplankton increases radiative heating in the near-surface ocean and raises sea surface temperature (SST) by overall ∼0.5 C. The resulting increase in evaporation enhances specific atmospheric humidity by 2-5%, thereby increasing the Earth's greenhouse effect and the atmospheric temperatures. The Hadley Cell exhibits a weakening and poleward expansion, therefore reducing cloudiness at subtropical-middle latitudes and increasing it at tropical latitudes except near the Equator. Higher SST at polar latitudes reduces sea ice cover and albedo, thereby increasing the high-latitude ocean absorption of solar radiation. Changes in the atmospheric baroclinicity cause a poleward intensification of mid-latitude westerly winds in both hemispheres. As a result, the North Atlantic Ocean meridional overturning circulation extends more northward, and the equatorward Ekman transport is enhanced in the Southern Ocean. The combination of local and dynamical processes decreases upper-ocean heat content in the Tropics and in the subpolar Southern Ocean, and increases it at middle latitudes. This study highlights the relevance of coupled ocean-atmosphere processes in the global climate response to phytoplankton solar absorption. Given that simulated impacts of phytoplankton on physical climate are within the range of natural climate variability, this study suggests the importance of phytoplankton as an internal constituent of the Earth's climate and its potential role in participating in its long-term climate adjustments. (orig.)

  6. Global warming and climate change in Amazonia: Climate-vegetation feedback and impacts on water resources

    Science.gov (United States)

    Marengo, José; Nobre, Carlos A.; Betts, Richard A.; Cox, Peter M.; Sampaio, Gilvan; Salazar, Luis

    This chapter constitutes an updated review of long-term climate variability and change in the Amazon region, based on observational data spanning more than 50 years of records and on climate-change modeling studies. We start with the early experiments on Amazon deforestation in the late 1970s, and the evolution of these experiments to the latest studies on greenhouse gases emission scenarios and land use changes until the end of the twenty-first century. The "Amazon dieback" simulated by the HadCM3 model occurs after a "tipping point" of CO2 concentration and warming. Experiments on Amazon deforestation and change of climate suggest that once a critical deforestation threshold (or tipping point) of 40-50% forest loss is reached in eastern Amazonia, climate would change in a way which is dangerous for the remaining forest. This may favor a collapse of the tropical forest, with a substitution of the forest by savanna-type vegetation. The concept of "dangerous climate change," as a climate change, which induces positive feedback, which accelerate the change, is strongly linked to the occurrence of tipping points, and it can be explained as the presence of feedback between climate change and the carbon cycle, particularly involving a weakening of the current terrestrial carbon sink and a possible reversal from a sink (as in present climate) to a source by the year 2050. We must, therefore, currently consider the drying simulated by the Hadley Centre model(s) as having a finite probability under global warming, with a potentially enormous impact, but with some degree of uncertainty.

  7. The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection

    Energy Technology Data Exchange (ETDEWEB)

    Hourdin, Frederic; Musat, Ionela; Bony, Sandrine; Codron, Francis; Dufresne, Jean-Louis; Fairhead, Laurent; Grandpeix, Jean-Yves; LeVan, Phu; Li, Zhao-Xin; Lott, Francois [CNRS/UPMC, Laboratoire de Meteorologie Dynamique (LMD/IPSL), Paris Cedex 05 (France); Braconnot, Pascale; Friedlingstein, Pierre [Laboratoire des Sciences du Climat et de l' Environnement (LSCE/IPSL), Saclay (France); Filiberti, Marie-Angele [Institut Pierre Simon Laplace (IPSL), Paris (France); Krinner, Gerhard [Laboratoire de Glaciologie et Geophysique de l' Environnement, Grenoble (France)

    2006-12-15

    The LMDZ4 general circulation model is the atmospheric component of the IPSL-CM4 coupled model which has been used to perform climate change simulations for the 4th IPCC assessment report. The main aspects of the model climatology (forced by observed sea surface temperature) are documented here, as well as the major improvements with respect to the previous versions, which mainly come form the parametrization of tropical convection. A methodology is proposed to help analyse the sensitivity of the tropical Hadley-Walker circulation to the parametrization of cumulus convection and clouds. The tropical circulation is characterized using scalar potentials associated with the horizontal wind and horizontal transport of geopotential (the Laplacian of which is proportional to the total vertical momentum in the atmospheric column). The effect of parametrized physics is analysed in a regime sorted framework using the vertical velocity at 500 hPa as a proxy for large scale vertical motion. Compared to Tiedtke's convection scheme, used in previous versions, the Emanuel's scheme improves the representation of the Hadley-Walker circulation, with a relatively stronger and deeper large scale vertical ascent over tropical continents, and suppresses the marked patterns of concentrated rainfall over oceans. Thanks to the regime sorted analyses, these differences are attributed to intrinsic differences in the vertical distribution of convective heating, and to the lack of self-inhibition by precipitating downdraughts in Tiedtke's parametrization. Both the convection and cloud schemes are shown to control the relative importance of large scale convection over land and ocean, an important point for the behaviour of the coupled model. (orig.)

  8. The effects of climate, permafrost and fire on vegetation change in Siberia in a changing climate

    Energy Technology Data Exchange (ETDEWEB)

    Tchebakova, N M; Parfenova, E [V N Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Sciences, Academgorodok, Krasnoyarsk, 660036 (Russian Federation); Soja, A J, E-mail: ncheby@forest.akadem.r, E-mail: Amber.J.Soja@nasa.go [National Institute of Aerospace (NIA), NASA Langley Research Center, Climate Sciences, 21 Langley Boulevard, Mail Stop 420, Hampton, VA 23681-2199 (United States)

    2009-10-15

    Observations and general circulation model projections suggest significant temperature increases in Siberia this century that are expected to have profound effects on Siberian vegetation. Potential vegetation change across Siberia was modeled, coupling our Siberian BioClimatic Model with several Hadley Centre climate change scenarios for 2020, 2050 and 2080, with explicit consideration of permafrost and fire activity. In the warmer and drier climate projected by these scenarios, Siberian forests are predicted to decrease and shift northwards and forest-steppe and steppe ecosystems are predicted to dominate over half of Siberia due to the dryer climate by 2080. Despite the large predicted increases in warming, permafrost is not predicted to thaw deep enough to sustain dark (Pinus sibirica, Abies sibirica, and Picea obovata) taiga. Over eastern Siberia, larch (Larix dahurica) taiga is predicted to continue to be the dominant zonobiome because of its ability to withstand continuous permafrost. The model also predicts new temperate broadleaf forest and forest-steppe habitats by 2080. Potential fire danger evaluated with the annual number of high fire danger days (Nesterov index is 4000-10 000) is predicted to increase by 2080, especially in southern Siberia and central Yakutia. In a warming climate, fuel load accumulated due to replacement of forest by steppe together with frequent fire weather promotes high risks of large fires in southern Siberia and central Yakutia, where wild fires would create habitats for grasslands because the drier climate would no longer be suitable for forests.

  9. The annual cycle of African climate and its variability | Jury | Water SA

    African Journals Online (AJOL)

    low) annual cycle correspond with La Nina (El Nino) and increased (decreased) inter-annual fluctuations of the African climate. A composite analysis shows that the South Atlantic Hadley cell and standing waves in the subtropical jet may connect ...

  10. Using Maps of City Analogues to Display and Interpret Climate Change scenarios and their uncertainty

    International Nuclear Information System (INIS)

    Kopf, S.; Minh, Ha-Duong; Hallegatte, St.

    2008-02-01

    We describe a method to represent the results of climate simulation models with analogues. An analogue to a city A is a city B whose climate today represents A's simulated future climate. Climates were characterized and compared non-parametrically, using the 30-years distribution of three indicators: Aridity Index, Heating Degree Days and Cooling Degree Days. Analogy was evaluated statistically with the two-samples Kolmogorov-Smirnov test, generalized to 3 dimensions. We looked at the climate of 12 European cities at the end of the century under an A2 climate change scenario. We used two datasets produced with high-resolution regional climate simulation models from the Hadley Center and Meteo France. Climate analogues were generally found southward of present locations, a clear warming trend even if much model and scenario uncertainty remains. Climate analogues provide an intuitive way to show the possible effects of climate change on urban areas, offering a holistic approach to think about how cities adapt to different climates. Evidence of its communication value comes from the reuse of our maps in teaching and in several European mass-media. (authors)

  11. Simulated trends of extreme climate indices for the Carpathian basin using outputs of different regional climate models

    Science.gov (United States)

    Pongracz, R.; Bartholy, J.; Szabo, P.; Pieczka, I.; Torma, C. S.

    2009-04-01

    Regional climatological effects of global warming may be recognized not only in shifts of mean temperature and precipitation, but in the frequency or intensity changes of different climate extremes. Several climate extreme indices are analyzed and compared for the Carpathian basin (located in Central/Eastern Europe) following the guidelines suggested by the joint WMO-CCl/CLIVAR Working Group on climate change detection. Our statistical trend analysis includes the evaluation of several extreme temperature and precipitation indices, e.g., the numbers of severe cold days, winter days, frost days, cold days, warm days, summer days, hot days, extremely hot days, cold nights, warm nights, the intra-annual extreme temperature range, the heat wave duration, the growing season length, the number of wet days (using several threshold values defining extremes), the maximum number of consecutive dry days, the highest 1-day precipitation amount, the greatest 5-day rainfall total, the annual fraction due to extreme precipitation events, etc. In order to evaluate the future trends (2071-2100) in the Carpathian basin, daily values of meteorological variables are obtained from the outputs of various regional climate model (RCM) experiments accomplished in the frame of the completed EU-project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). Horizontal resolution of the applied RCMs is 50 km. Both scenarios A2 and B2 are used to compare past and future trends of the extreme climate indices for the Carpathian basin. Furthermore, fine-resolution climate experiments of two additional RCMs adapted and run at the Department of Meteorology, Eotvos Lorand University are used to extend the trend analysis of climate extremes for the Carpathian basin. (1) Model PRECIS (run at 25 km horizontal resolution) was developed at the UK Met Office, Hadley Centre, and it uses the boundary conditions from the HadCM3 GCM. (2) Model Reg

  12. Estimation of the global climate effect of brown carbon

    Science.gov (United States)

    Zhang, A.; Wang, Y.; Zhang, Y.; Weber, R. J.; Song, Y.

    2017-12-01

    Carbonaceous aerosols significantly affect global radiative forcing and climate through absorption and scattering of sunlight. Black carbon (BC) and brown carbon (BrC) are light-absorbing carbonaceous aerosols. The global distribution and climate effect of BrC is uncertain. A recent study suggests that BrC absorption is comparable to BC in the upper troposphere over biomass burning region and that the resulting heating tends to stabilize the atmosphere. Yet current climate models do not include proper treatments of BrC. In this study, we derived a BrC global biomass burning emission inventory from Global Fire Emissions Database 4 (GFED4) and developed a BrC module in the Community Atmosphere Model version 5 (CAM5) of Community Earth System Model (CESM) model. The model simulations compared well to BrC observations of the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry Project (DC-3) campaigns and includes BrC bleaching. Model results suggested that BrC in the upper troposphere due to convective transport is as important an absorber as BC globally. Upper tropospheric BrC radiative forcing is particularly significant over the tropics, affecting the atmosphere stability and Hadley circulation.

  13. Large scale atmospheric tropical circulation changes and consequences during global warming

    International Nuclear Information System (INIS)

    Gastineau, G.

    2008-01-01

    The changes of the tropical large scale circulation during climate change can have large impacts on human activities. In a first part, the meridional atmospheric tropical circulation was studied in the different coupled models. During climate change, we find, on the one hand, that the Hadley meridional circulation and the subtropical jet are significantly shifted poleward, and on the other hand, that the intensity of the tropical circulation weakens. The slow down of the atmospheric circulation results from the dry static stability changes affecting the tropical troposphere. Secondly, idealized simulations are used to explain the tropical circulation changes. Ensemble simulation using the model LMDZ4 are set up to study the results from the coupled model IPSLCM4. The weakening of the large scale tropical circulation and the poleward shift of the Hadley cells are explained by both the uniform change and the meridional gradient change of the sea surface temperature. Then, we used the atmospheric model LMDZ4 in an aqua-planet configuration. The Hadley circulation changes are explained in a simple framework by the required poleward energy transport. In a last part, we focus on the water vapor distribution and feedback in the climate models. The Hadley circulation changes were shown to have a significant impact on the water vapour feedback during climate change. (author)

  14. View of Commemorative plaque left on moon at Hadley-Apennine landing site

    Science.gov (United States)

    1971-01-01

    A close-up view of a commemorative plaque left on the Moon at the Hadley-Apennine landing site in memory of 14 NASA astronauts and USSR cosmonauts, now deceased. Their names are inscribed in alphabetical order on the plaque. The plaque was stuck in the lunar soil by Astronauts David R. Scott and James B. Irwin during their Apollo 15 lunar surface extravehicular activity. The tin, man-like object represents the figure of a fallen astronaut/cosmonaut.

  15. Avaliação de mudanças na frequência de sistemas frontais sobre o sul da América do Sul em projeções do clima futuro Changes in frequency of frontal systems over southern of South America in projections of future climate

    Directory of Open Access Journals (Sweden)

    Kelen Martins Andrade

    2012-06-01

    Full Text Available A frequência de sistemas frontais sobre o sul da América do Sul identificada na reanálise do NCEP/NCAR é comparada com as simulações dos modelos GFDL e Hadley e projetadas no clima futuro. As análises para identificar casos de sistemas frontais foram feitas em três regiões que cobrem áreas do Brasil, Uruguai, Paraguai e Argentina. Esta análise foi realizada com o fim de investigar as características de eventos extremos no clima presente e em projeções do clima futuro. Para o clima presente observou-se que os modelos analisados simularam bem as características sinóticas dos sistemas frontais. No entanto, quando se compara a frequência de ocorrência das frentes entre a reanálise e as simulações, observa-se que os modelos GFDL e Hadley superestimam seu número e apenas o GFDL consegue reproduzir a variabilidade mensal. O modelo Hadley superestima ainda mais em relação ao NCEP e GFDL no clima presente. A tendência positiva no número de frentes observada na área 3 (65ºW-60ºW, 33ºS-38ºS nos resultados da reanálise não é simulada pelos modelos. Quando os casos mais intensos são selecionados, o modelo GFDL é o que superestima mais o número de sistemas frontais. Os dois modelos indicam aumento na frequência de sistemas frontais no futuro nas três áreas, porém em menor proporção na área 3.The frequency of frontal systems reaching the south of South America is compared with reanalysis NCEP/NCAR and results of GFDL and Hadley models for the future climate. Three regions were analyzed to identify the frontal systems, in areas of Brazil, Uruguay, Paraguay and Argentina. The following criteria were used: increase of sea surface pressure, reduction of the temperature and change of the meridional wind at 850hPa, in two consecutive days. Selected cases with temperature drop above five degrees, considered the most intense, were also analyzed. For the present climate it was observed that the models simulated well the

  16. A zonally symmetric model for the monsoon-Hadley circulation with stochastic convective forcing

    Science.gov (United States)

    De La Chevrotière, Michèle; Khouider, Boualem

    2017-02-01

    Idealized models of reduced complexity are important tools to understand key processes underlying a complex system. In climate science in particular, they are important for helping the community improve our ability to predict the effect of climate change on the earth system. Climate models are large computer codes based on the discretization of the fluid dynamics equations on grids of horizontal resolution in the order of 100 km, whereas unresolved processes are handled by subgrid models. For instance, simple models are routinely used to help understand the interactions between small-scale processes due to atmospheric moist convection and large-scale circulation patterns. Here, a zonally symmetric model for the monsoon circulation is presented and solved numerically. The model is based on the Galerkin projection of the primitive equations of atmospheric synoptic dynamics onto the first modes of vertical structure to represent free tropospheric circulation and is coupled to a bulk atmospheric boundary layer (ABL) model. The model carries bulk equations for water vapor in both the free troposphere and the ABL, while the processes of convection and precipitation are represented through a stochastic model for clouds. The model equations are coupled through advective nonlinearities, and the resulting system is not conservative and not necessarily hyperbolic. This makes the design of a numerical method for the solution of this system particularly difficult. Here, we develop a numerical scheme based on the operator time-splitting strategy, which decomposes the system into three pieces: a conservative part and two purely advective parts, each of which is solved iteratively using an appropriate method. The conservative system is solved via a central scheme, which does not require hyperbolicity since it avoids the Riemann problem by design. One of the advective parts is a hyperbolic diagonal matrix, which is easily handled by classical methods for hyperbolic equations, while

  17. An intercomparison of regional climate simulations for Europe

    DEFF Research Database (Denmark)

    Déqué, M.; Rowell, D. P.; Lüthi, D.

    2007-01-01

    Ten regional climate models (RCM) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre boundary conditions. The response over Europe, calculated as the difference between the 2071-2100 and the 1961-1990 means can be viewed...... as an average over a finite number of years (30). Model uncertainty is due to the fact that the models use different techniques to discretize the equations and to represent sub-grid effects. Radiative uncertainty is due to the fact that IPCC-SRES A2 is merely one hypothesis. Some RCMs have been run with another...... scenario of greenhouse gas concentration (IPCC-SRES B2). Boundary uncertainty is due to the fact that the regional models have been run under the constraint of the same global model. Some RCMs have been run with other boundary forcings. The contribution of the different sources varies according...

  18. Support for global climate reorganization during the ''Medieval Climate Anomaly''

    Energy Technology Data Exchange (ETDEWEB)

    Graham, N.E. [Hydrologic Research Center, San Diego, CA (United States); Scripps Institution of Oceanography, La Jolla, CA (United States); Ammann, C.M. [National Center for Atmospheric Research, Boulder, CO (United States); Fleitmann, D. [University of Bern, Institute of Geological Sciences, Bern (Switzerland); University of Bern, Oeschger Centre for Climatic Change Research, Bern (Switzerland); Cobb, K.M. [Georgia Institute of Technology, Atlanta, GA (United States); Luterbacher, J. [Justus-Liebig-University, Giessen (Germany)

    2011-09-15

    Widely distributed proxy records indicate that the Medieval Climate Anomaly (MCA; {proportional_to}900-1350 AD) was characterized by coherent shifts in large-scale Northern Hemisphere atmospheric circulation patterns. Although cooler sea surface temperatures in the central and eastern equatorial Pacific can explain some aspects of medieval circulation changes, they are not sufficient to account for other notable features, including widespread aridity through the Eurasian sub-tropics, stronger winter westerlies across the North Atlantic and Western Europe, and shifts in monsoon rainfall patterns across Africa and South Asia. We present results from a full-physics coupled climate model showing that a slight warming of the tropical Indian and western Pacific Oceans relative to the other tropical ocean basins can induce a broad range of the medieval circulation and climate changes indicated by proxy data, including many of those not explained by a cooler tropical Pacific alone. Important aspects of the results resemble those from previous simulations examining the climatic response to the rapid Indian Ocean warming during the late twentieth century, and to results from climate warming simulations - especially in indicating an expansion of the Northern Hemisphere Hadley circulation. Notably, the pattern of tropical Indo-Pacific sea surface temperature (SST) change responsible for producing the proxy-model similarity in our results agrees well with MCA-LIA SST differences obtained in a recent proxy-based climate field reconstruction. Though much remains unclear, our results indicate that the MCA was characterized by an enhanced zonal Indo-Pacific SST gradient with resulting changes in Northern Hemisphere tropical and extra-tropical circulation patterns and hydroclimate regimes, linkages that may explain the coherent regional climate shifts indicated by proxy records from across the planet. The findings provide new perspectives on the nature and possible causes of the MCA

  19. Emissions pathways, climate change, and impacts on California

    Science.gov (United States)

    Hayhoe, Katharine; Cayan, Daniel; Field, Christopher B.; Frumhoff, Peter C.; Maurer, Edwin P.; Miller, Norman L.; Moser, Susanne C.; Schneider, Stephen H.; Cahill, Kimberly Nicholas; Cleland, Elsa E.; Dale, Larry; Drapek, Ray; Hanemann, R. Michael; Kalkstein, Laurence S.; Lenihan, James; Lunch, Claire K.; Neilson, Ronald P.; Sheridan, Scott C.; Verville, Julia H.

    2004-01-01

    The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50–75%; and Sierra snowpack is reduced 30–70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75–90%; and snowpack declines 73–90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades. PMID:15314227

  20. Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

    Science.gov (United States)

    Beranová, Romana; Kyselý, Jan; Hanel, Martin

    2018-04-01

    The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May-September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.

  1. Responses of the Tropical Atmospheric Circulation to Climate Change and Connection to the Hydrological Cycle

    Science.gov (United States)

    Ma, Jian; Chadwick, Robin; Seo, Kyong-Hwan; Dong, Changming; Huang, Gang; Foltz, Gregory R.; Jiang, Jonathan H.

    2018-05-01

    This review describes the climate change–induced responses of the tropical atmospheric circulation and their impacts on the hydrological cycle. We depict the theoretically predicted changes and diagnose physical mechanisms for observational and model-projected trends in large-scale and regional climate. The tropical circulation slows down with moisture and stratification changes, connecting to a poleward expansion of the Hadley cells and a shift of the intertropical convergence zone. Redistributions of regional precipitation consist of thermodynamic and dynamical components, including a strong offset between moisture increase and circulation weakening throughout the tropics. This allows other dynamical processes to dominate local circulation changes, such as a surface warming pattern effect over oceans and multiple mechanisms over land. To improve reliability in climate projections, more fundamental understandings of pattern formation, circulation change, and the balance of various processes redistributing land rainfall are suggested to be important.

  2. Future Climate Impacts of Direct Radiative Forcing Anthropogenic Aerosols, Tropospheric Ozone, and Long-lived Greenhouse Gases

    Science.gov (United States)

    Chen, Wei-Ting; Liao, Hong; Seinfeld, John H.

    2007-01-01

    Long-lived greenhouse gases (GHGs) are the most important driver of climate change over the next century. Aerosols and tropospheric ozone (O3) are expected to induce significant perturbations to the GHG-forced climate. To distinguish the equilibrium climate responses to changes in direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and GHG between present day and year 2100, four 80-year equilibrium climates are simulated using a unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 110. Concentrations of sulfate, nitrate, primary organic (POA) carbon, secondary organic (SOA) carbon, black carbon (BC) aerosols, and tropospheric ozone for present day and year 2100 are obtained a priori by coupled chemistry-aerosol GCM simulations, with emissions of aerosols, ozone, and precursors based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) A2. Changing anthropogenic aerosols, tropospheric ozone, and GHG from present day to year 2100 is predicted to perturb the global annual mean radiative forcing by +0.18 (considering aerosol direct effects only), +0.65, and +6.54 W m(sup -2) at the tropopause, and to induce an equilibrium global annual mean surface temperature change of +0.14, +0.32, and +5.31 K, respectively, with the largest temperature response occurring at northern high latitudes. Anthropogenic aerosols, through their direct effect, are predicted to alter the Hadley circulation owing to an increasing interhemispheric temperature gradient, leading to changes in tropical precipitation. When changes in both aerosols and tropospheric ozone are considered, the predicted patterns of change in global circulation and the hydrological cycle are similar to those induced by aerosols alone. GHG-induced climate changes, such as amplified warming over high latitudes, weakened Hadley circulation, and increasing precipitation over the

  3. Predicting climate change

    Indian Academy of Sciences (India)

    These projections are deduced from separate models which take into account population growth, energy use, economics, technological developments, and so forth. We do not carry out this stage at the Hadley Centre, but we take future scenarios of these emissions from others, particularly IPCC. Having obtained projections ...

  4. Climate change and potato cropping in the Peruvian Altiplano

    Science.gov (United States)

    Sanabria, J.; Lhomme, J. P.

    2013-05-01

    The potential impacts of climate change on potatoes cropping in the Peruvian highlands (Altiplano) is assessed using climate projections for 2071-2100, obtained from the HadRM3P regional atmospheric model of the Hadley Centre. The atmospheric model is run under two different special report on emission scenarios: high CO2 concentration (A2) and moderate CO2 concentration (B2) for four locations situated in the surroundings of Lake Titicaca. The two main varieties of potato cultivated in the area are studied: the Andean potato ( Solanum tuberosum) and the bitter potato ( Solanum juzepczukii). A simple process-oriented model is used to quantify the climatic impacts on crops cycles and yields by combining the effects of temperature on phenology, of radiation and CO2 on maximum yield and of water balance on yield deficit. In future climates, air temperature systematically increases, precipitation tends to increase at the beginning of the rainy season and slightly decreases during the rest of the season. The direct effects of these climatic changes are earlier planting dates, less planting failures and shorter crop cycles in all the four locations and for both scenarios. Consequently, the harvesting dates occur systematically earlier: roughly in January for the Andean potato instead of March in the current situation and in February for the bitter potato instead of April. Overall, yield deficits will be higher under climate change than in the current climate. There will be a strong negative impact on yields for S. tuberosum (stronger under A2 scenario than under B2); the impact on S. juzepczukii yields, however, appears to be relatively mixed and not so negative.

  5. The Martian climate and energy balance models with CO2/H2O atmospheres

    Science.gov (United States)

    Hoffert, M. I.

    1986-01-01

    The analysis begins with a seasonal energy balance model (EBM) for Mars. This is used to compute surface temperature versus x = sin(latitude) and time over the seasonal cycle. The core model also computes the evolving boundaries of the CO2 icecaps, net sublimational/condensation rates, and the resulting seasonal pressure wave. Model results are compared with surface temperature and pressure history data at Viking lander sites, indicating fairly good agreement when meridional heat transport is represented by a thermal diffusion coefficient D approx. 0.015 W/sq. m/K. Condensational wind distributions are also computed. An analytic model of Martian wind circulation is then proposed, as an extension of the EMB, which incorporates vertical wind profiles containing an x-dependent function evaluated by substitution in the equation defining the diffusion coefficient. This leads to a parameterization of D(x) and of the meridional circulation which recovers the high surface winds predicted by dynamic Mars atmosphere models (approx. 10 m/sec). Peak diffusion coefficients, D approx. 0.6 w/sq m/K, are found over strong Hadley zones - some 40 times larger than those of high-latitude baroclinic eddies. When the wind parameterization is used to find streamline patterns over Martian seasons, the resulting picture shows overturning hemispheric Hadley cells crossing the equator during solstices, and attaining peak intensities during the south summer dust storm season, while condensational winds are most important near the polar caps.

  6. Climate change, humidity, and mortality in the United States

    Science.gov (United States)

    Barreca, Alan I.

    2014-01-01

    This paper estimates the effects of humidity and temperature on mortality rates in the United States (c. 1973–2002) in order to provide an insight into the potential health impacts of climate change. I find that humidity, like temperature, is an important determinant of mortality. Coupled with Hadley CM3 climate-change predictions, I project that mortality rates are likely to change little on the aggregate for the United States. However, distributional impacts matter: mortality rates are likely to decline in cold and dry areas, but increase in hot and humid areas. Further, accounting for humidity has important implications for evaluating these distributional effects. PMID:25328254

  7. Late Pleistocene climate change and the global expansion of anatomically modern humans

    Science.gov (United States)

    Eriksson, Anders; Betti, Lia; Friend, Andrew D.; Lycett, Stephen J.; Singarayer, Joy S.; von Cramon-Taubadel, Noreen; Valdes, Paul J.; Balloux, Francois; Manica, Andrea

    2012-01-01

    The extent to which past climate change has dictated the pattern and timing of the out-of-Africa expansion by anatomically modern humans is currently unclear [Stewart JR, Stringer CB (2012) Science 335:1317–1321]. In particular, the incompleteness of the fossil record makes it difficult to quantify the effect of climate. Here, we take a different approach to this problem; rather than relying on the appearance of fossils or archaeological evidence to determine arrival times in different parts of the world, we use patterns of genetic variation in modern human populations to determine the plausibility of past demographic parameters. We develop a spatially explicit model of the expansion of anatomically modern humans and use climate reconstructions over the past 120 ky based on the Hadley Centre global climate model HadCM3 to quantify the possible effects of climate on human demography. The combinations of demographic parameters compatible with the current genetic makeup of worldwide populations indicate a clear effect of climate on past population densities. Our estimates of this effect, based on population genetics, capture the observed relationship between current climate and population density in modern hunter–gatherers worldwide, providing supporting evidence for the realism of our approach. Furthermore, although we did not use any archaeological and anthropological data to inform the model, the arrival times in different continents predicted by our model are also broadly consistent with the fossil and archaeological records. Our framework provides the most accurate spatiotemporal reconstruction of human demographic history available at present and will allow for a greater integration of genetic and archaeological evidence. PMID:22988099

  8. TRACKING CLIMATE MODELS

    Data.gov (United States)

    National Aeronautics and Space Administration — CLAIRE MONTELEONI*, GAVIN SCHMIDT, AND SHAILESH SAROHA* Climate models are complex mathematical models designed by meteorologists, geophysicists, and climate...

  9. Uncertainties

    Indian Academy of Sciences (India)

    To reflect this uncertainty in the climate scenarios, the use of AOGCMs that explicitly simulate the carbon cycle and chemistry of all the substances are needed. The Hadley Centre has developed a version of the climate model that allows the effect of climate change on the carbon cycle and its feedback into climate, to be ...

  10. Satellite Sounder Observations of Contrasting Tropospheric Moisture Transport Regimes: Saharan Air Layers, Hadley Cells, and Atmospheric Rivers

    Energy Technology Data Exchange (ETDEWEB)

    Nalli, Nicholas R.; Barnet, Christopher D.; Reale, Tony; Liu, Quanhua; Morris, Vernon R.; Spackman, J. Ryan; Joseph, Everette; Tan, Changyi; Sun, Bomin; Tilley, Frank; Leung, L. Ruby; Wolfe, Daniel

    2016-12-01

    This paper examines the performance of satellite sounder atmospheric vertical moisture proles (AVMP) under tropospheric conditions encompassing moisture contrasts driven by convection and advection transport mechanisms, specifically Atlantic Ocean Saharan air layers (SALs) and Pacific Ocean moisture conveyer belts (MCBs) commonly referred to as atmospheric rivers (ARs), both of these being mesoscale to synoptic meteorological phenomena within the vicinity of subtropical Hadley subsidence zones. Operational AVMP environmental data records retrieved from the Suomi National Polar-orbiting Partnership (SNPP) NOAA-Unique Combined Atmospheric Processing System (NUCAPS) are collocated with dedicated radiosonde observations (RAOBs) obtained from ocean-based intensive field campaigns; these RAOBs provide uniquely independent correlative truth data not assimilated into numerical weather prediction models for satellite sounder validation over open ocean. Using these marine-based data, we empirically assess the performance of the operational NUCAPS AVMP product for detecting and resolving these tropospheric moisture features over otherwise RAOB-sparse regions.

  11. Climate change impacts on crop yield and quality with CO2 fertilization in China

    Science.gov (United States)

    Erda, Lin; Wei, Xiong; Hui, Ju; Yinlong, Xu; Yue, Li; Liping, Bai; Liyong, Xie

    2005-01-01

    A regional climate change model (PRECIS) for China, developed by the UK's Hadley Centre, was used to simulate China's climate and to develop climate change scenarios for the country. Results from this project suggest that, depending on the level of future emissions, the average annual temperature increase in China by the end of the twenty-first century may be between 3 and 4 °C. Regional crop models were driven by PRECIS output to predict changes in yields of key Chinese food crops: rice, maize and wheat. Modelling suggests that climate change without carbon dioxide (CO2) fertilization could reduce the rice, maize and wheat yields by up to 37% in the next 20–80 years. Interactions of CO2 with limiting factors, especially water and nitrogen, are increasingly well understood and capable of strongly modulating observed growth responses in crops. More complete reporting of free-air carbon enrichment experiments than was possible in the Intergovernmental Panel on Climate Change's Third Assessment Report confirms that CO2 enrichment under field conditions consistently increases biomass and yields in the range of 5–15%, with CO2 concentration elevated to 550 ppm Levels of CO2 that are elevated to more than 450 ppm will probably cause some deleterious effects in grain quality. It seems likely that the extent of the CO2 fertilization effect will depend upon other factors such as optimum breeding, irrigation and nutrient applications. PMID:16433100

  12. Climate models and scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Fortelius, C; Holopainen, E; Kaurola, J; Ruosteenoja, K; Raeisaenen, J [Helsinki Univ. (Finland). Dept. of Meteorology

    1997-12-31

    In recent years the modelling of interannual climate variability has been studied, the atmospheric energy and water cycles, and climate simulations with the ECHAM3 model. In addition, the climate simulations of several models have been compared with special emphasis in the area of northern Europe

  13. Climate models and scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Fortelius, C.; Holopainen, E.; Kaurola, J.; Ruosteenoja, K.; Raeisaenen, J. [Helsinki Univ. (Finland). Dept. of Meteorology

    1996-12-31

    In recent years the modelling of interannual climate variability has been studied, the atmospheric energy and water cycles, and climate simulations with the ECHAM3 model. In addition, the climate simulations of several models have been compared with special emphasis in the area of northern Europe

  14. An assessment of irrigation needs and crop yield for the United States under potential climate changes

    Science.gov (United States)

    Brumbelow, Kelly; Georgakakos, Aris P.

    2000-01-01

    Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous U.S., and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the U.S. where they have traditionally been grown. Physiologically-based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data is used to calibrate model parameters and determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern U.S. and decreased irrigation demands in the northern and western U.S. Crop yields typically increase except for winter wheat in the southern U.S. and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher variability in future climatic forcing and, consequently

  15. Integrating biomass, sulphate and sea-salt aerosol responses into a microphysical chemical parcel model: implications for climate studies.

    Science.gov (United States)

    Ghosh, S; Smith, M H; Rap, A

    2007-11-15

    Aerosols are known to influence significantly the radiative budget of the Earth. Although the direct effect (whereby aerosols scatter and absorb solar and thermal infrared radiation) has a large perturbing influence on the radiation budget, the indirect effect (whereby aerosols modify the microphysical and hence the radiative properties and amounts of clouds) poses a greater challenge to climate modellers. This is because aerosols undergo chemical and physical changes while in the atmosphere, notably within clouds, and are removed largely by precipitation. The way in which aerosols are processed by clouds depends on the type, abundance and the mixing state of the aerosols concerned. A parametrization with sulphate and sea-salt aerosol has been successfully integrated within the Hadley Centre general circulation model (GCM). The results of this combined parametrization indicate a significantly reduced role, compared with previous estimates, for sulphate aerosol in cloud droplet nucleation and, consequently, in indirect radiative forcing. However, in this bicomponent system, the cloud droplet number concentration, N(d) (a crucial parameter that is used in GCMs for radiative transfer calculations), is a smoothly varying function of the sulphate aerosol loading. Apart from sea-salt and sulphate aerosol particles, biomass aerosol particles are also present widely in the troposphere. We find that biomass smoke can significantly perturb the activation and growth of both sulphate and sea-salt particles. For a fixed salt loading, N(d) increases linearly with modest increases in sulphate and smoke masses, but significant nonlinearities are observed at higher non-sea-salt mass loadings. This non-intuitive N(d) variation poses a fresh challenge to climate modellers.

  16. Climate in the absence of ocean heat transport

    Science.gov (United States)

    Rose, B. E. J.

    2017-12-01

    The energy transported by the oceans to mid- and high latitudes is small compared to the atmosphere, yet exerts an outsized influence on climate. A key reason is the strong interaction between ocean heat transport (OHT) and sea ice extent. I quantify the absolute climatic impact of OHT using the state-of-the-art CESM simulations by comparing a realistic control climate against a slab ocean simulation in which OHT is disabled. The absence of OHT leads to a massive expansion of sea ice into the subtropics in both hemispheres, and a 24 K global cooling. Analysis of the transient simulation after setting the OHT to zero reveals a global cooling process fueled by a runaway sea ice albedo feedback. This process is eventually self-limiting in the cold climate due to a combination of subtropical cloud feedbacks and surface wind effects that are both connected to a massive spin-up of the atmospheric Hadley circulation. A parameter sensitivity study shows that the simulated climate is far more sensitive to small changes in ice surface albedo in the absence of OHT. I conclude that the oceans are responsible for an enormous global warming by mitigating an otherwise very potent sea ice albedo feedback, but that the magnitude of this effect is rather uncertain. These simulations provide a graphic illustration of how the intimate coupling between sea ice and ocean circulation governs the present-day climate, and by extension, highlight the importance of modeling ocean - sea ice interaction with high fidelity.

  17. Climate Impacts of CALIPSO-Guided Corrections to Black Carbon Aerosol Vertical Distributions in a Global Climate Model

    International Nuclear Information System (INIS)

    Kovilakam, Mahesh; Mahajan, Salil; Saravanan, R.; Chang, Ping

    2017-01-01

    Here, we alleviate the bias in the tropospheric vertical distribution of black carbon aerosols (BC) in the Community Atmosphere Model (CAM4) using the Cloud-Aerosol and Infrared Pathfinder Satellite Observations (CALIPSO)-derived vertical profiles. A suite of sensitivity experiments are conducted with 1x, 5x, and 10x the present-day model estimated BC concentration climatology, with (corrected, CC) and without (uncorrected, UC) CALIPSO-corrected BC vertical distribution. The globally averaged top of the atmosphere radiative flux perturbation of CC experiments is ~8–50% smaller compared to uncorrected (UC) BC experiments largely due to an increase in low-level clouds. The global average surface temperature increases, the global average precipitation decreases, and the ITCZ moves northward with the increase in BC radiative forcing, irrespective of the vertical distribution of BC. Further, tropical expansion metrics for the poleward extent of the Northern Hemisphere Hadley cell (HC) indicate that simulated HC expansion is not sensitive to existing model biases in BC vertical distribution.

  18. Linked models to assess the impacts of climate change on nitrogen in a Norwegian river basin and fjord system

    International Nuclear Information System (INIS)

    Kaste, O.; Wright, R.F.; Barkved, L.J.; Bjerkeng, B.; Engen-Skaugen, T.; Magnusson, J.; Saelthun, N.R.

    2006-01-01

    Dynamically downscaled data from two Atmosphere-Ocean General Circulation Models (AOGCMs), ECHAM4 from the Max-Planck Institute (MPI), Germany and HadAm3H from the Hadley Centre (HAD), UK, driven with two scenarios of greenhouse gas emissions (IS92a and A2, respectively) were used to make climate change projections. These projections were then used to drive four effect models linked to assess the effects on hydrology, and nitrogen (N) concentrations and fluxes, in the Bjerkreim river basin (685-km 2 ) and its coastal fjord, southwestern Norway. The four effect models were the hydrological model HBV, the water quality models MAGIC, INCA-N and the NIVA FJORD model. The downscaled climate scenarios project a general temperature increase in the study region of approximately 1 deg. C by 2030-2049 (MPI IS92a) and approximately 3 deg. C by 2071-2100 (HAD A2). Both scenarios imply increased winter precipitation, whereas the projections of summer and autumn precipitation are quite different, with the MPI scenario projecting a slight increase and the HAD scenario a significant decrease. As a response to increased winter temperature, the HBV model simulates a dramatic reduction of snow accumulation in the upper parts of the catchment, which in turn lead to higher runoff during winter and lower runoff during snowmelt in the spring. With the HAD scenario, runoff in summer and early autumn is substantially reduced as a result of reduced precipitation, increased temperatures and thereby increased evapotranspiration. The water quality models, MAGIC and INCA-N project no major changes in nitrate (NO 3 - ) concentrations and fluxes within the MPI scenario, but a significant increase in concentrations and a 40-50% increase in fluxes in the HAD scenario. As a consequence, the acidification of the river could increase, thus offsetting ongoing recovery from acidification due to reductions in acid deposition. Additionally, the increased N loading may stimulate growth of N-limited benthic

  19. Climate Change Scenarios in the Yucatan Peninsula to the year 2020

    Science.gov (United States)

    Orellana, R.; Espadas, C.; Conde, C.; Gay, C.

    2010-03-01

    A topic that has not been sufficiently analyzed is that the global warming is already affecting, and that it will have worst consequences in those regions with transitional climates, which have more sensibility to changes. This is the case of the Yucatan Peninsula which is semi-arid in their northern portion, and toward the south is subhumid, with a tendency to be more rainy toward the south. To have an estimation of what could happen in the future, the Intergovernmental Panel of Climatic Change (IPCC) has promoted the use of General Circulation Models (GCM), as well as the construction of possible emission scenarios that integrate different global and regional socioeconomic and demographic conditions, which project then a possible increase of emissions of greenhouse gases. These conditions are recognized as the decisive forces that will determine the variations of temperature and of precipitation. These projections are useful for the analysis of climatic change, and in particular for the assessments of the possible impacts and of the initiatives of adaptation and of mitigation that should be implemented in every country or region. In Mexico, most of those evaluations of climate change have been carried out generally at country level. For that reason, it is necessary to direct the research at regional level. In this work, we evaluated the potential climatic changes on the Yucatan Peninsula, considering the different changes of temperature and precipitation as a consequence for different emission scenarios and for the horizon 2020. To project the environmental responses of the region, we used as a base scenario the available temperature and precipitation information of the period 1961-1990, registered in 85 meteorological stations of the peninsula. With these data, we generated climate change scenarios using the outputs of four General Circulation Models: HADLEY, ECHAM, GFDL and CGCM, and the emission scenarios A1FI, A2, B1 and B2. The outputs of these models were

  20. The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate

    Energy Technology Data Exchange (ETDEWEB)

    Flato, G.M.; Boer, G.J.; Lee, W.G.; McFarlane, N.A.; Ramsden, D.; Reader, M.C. [Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); Weaver, A.J. [School of Earth and Ocean Sciences, University of Victoria, BC (Canada)

    2000-06-01

    A global, three-dimensional climate model, developed by coupling the CCCma second-generation atmospheric general circulation model (GCM2) to a version of the GFDL modular ocean model (MOM1), forms the basis for extended simulations of past, current and projected future climate. The spin-up and coupling procedures are described, as is the resulting climate based on a 200 year model simulation with constant atmospheric composition and external forcing. The simulated climate is systematically compared to available observations in terms of mean climate quantities and their spatial patterns, temporal variability, and regional behavior. Such comparison demonstrates a generally successful reproduction of the broad features of mean climate quantities, albeit with local discrepancies. Variability is generally well-simulated over land, but somewhat underestimated in the tropical ocean and the extratropical storm-track regions. The modelled climate state shows only small trends, indicating a reasonable level of balance at the surface, which is achieved in part by the use of heat and freshwater flux adjustments. The control simulation provides a basis against which to compare simulated climate change due to historical and projected greenhouse gas and aerosol forcing as described in companion publications. (orig.)

  1. An idealized study of the impact of extratropical climate change on El Nino-Southern Oscillation

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Qiong [Chinese Academy of Sciences, LASG, Institute of Atmospheric Science, Beijing (China); Yang, Haijun [Peking University, Department of Atmospheric Science and Laboratory for Severe Storm and Flood Disasters, Beijing (China); Zhong, Yafang [University of Wisconsin-Madison, Center for Climatic Research and Department of Atmospheric and Oceanic Sciences, Madison, WI (United States); Wang, Dongxiao [Chinese Academy of Sciences, Laboratory of Tropical Marine Environmental Dynamics, Guangzhou (China); South China Sea Institute of Oceanology, Guangzhou (China)

    2005-12-01

    Extratropical impacts on the tropical El Nino-Southern Oscillation (ENSO) are studied in a coupled climate model. Idealized experiments show that the remote impact of the extratropics on the equatorial thermocline through oceanic tunnel can substantially modulate the ENSO in both magnitude and frequency. First of all, an extratropical warming can be conveyed to the equator by the mean subduction current, resulting in a warming of the equatorial thermocline. Second, the extratropical warming can weaken the Hadley cells, which in turn slow down the mean shallow meridional overturning circulations in the upper Pacific, reducing the equatorward cold water supply and the equatorial upwelling. These oceanic dynamic processes would weaken the stratification of the equatorial thermocline and retard a buildup (purge) of excess heat content along the equator, and finally result in a weaker and longer ENSO cycle. This study highlights a nonlocal mechanism in which ENSO behavior is related to the extratropical climate conditions. (orig.)

  2. Climate Model Diagnostic Analyzer

    Science.gov (United States)

    Lee, Seungwon; Pan, Lei; Zhai, Chengxing; Tang, Benyang; Kubar, Terry; Zhang, Zia; Wang, Wei

    2015-01-01

    The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

  3. Climate change effects on hydropower potential of the Alcantara river basin in Sicily (Italy)

    Science.gov (United States)

    Tito Aronica, Giuseppe; Bonaccorso, Brunella

    2013-04-01

    In recent years an increasing attention has been paid to hydropower generation, since it is a renewable, efficient, and reliable source of energy, as well as an effective tool to reduce the atmospheric concentrations of greenhouse gases resulting from human activities. At the same time, however, hydropower is high vulnerable to global warming, because water resources are closely linked to climate changes. Indeed, the effects of climate change on water availability are expected to affect hydropower generation with special reference to Southern countries which are supposed to face dryer conditions in the next decades. The aim of this paper is to assess the impact of future climate change on the hydrological regime of the Alcantara river basin, Eastern Sicily (Italy), based on Monte Carlo simulations. Synthetic series of daily rainfall and temperature are generated, based on observed data, through a first order Markov chain and an ARMA model respectively, for the current scenario and two future scenarios at 2025. In particular, the mean and standard deviation values of daily rainfall and temperature at 2025, calculated using simulations of the Hadley Centre Ocean-Atmosphere General Circulation Model (HadCM3), are adopted to generate future scenarios of precipitation and temperature. Synthetic series for the two climatic scenarios are, then, introduced as input into the IHACRES model to simulate the hydrological response of the basin. The effects of climate change are, then, investigated by analysing potential modification of the resulting flow duration curves and utilisation curves, which allow to estimate a site's energy potential for the design of run-of-river hydropower plants.

  4. Now, Here's the Weather Forecast...

    Science.gov (United States)

    Richardson, Mathew

    2013-01-01

    The Met Office has a long history of weather forecasting, creating tailored weather forecasts for customers across the world. Based in Exeter, the Met Office is also home to the Met Office Hadley Centre, a world-leading centre for the study of climate change and its potential impacts. Climate information from the Met Office Hadley Centre is used…

  5. An observational and modeling study of the regional impacts of climate variability

    Science.gov (United States)

    Horton, Radley M.

    ) a statistically significant negative relationship exists between malaria cases and ENSO. The final chapter adds climate change to the climate variability story. Under high CO2, the model able to capture ENSO dynamics---an atmospheric model coupled to the Cane-Zebiak ocean model ('C4' here)---generates more El Nino-like mean conditions in the tropical Pacific. These changes produce a 4x larger increase in maximum precipitation with warming in C4 than an atmospheric model with a slab ocean (Q4), dramatically enhancing the Pacific Hadley and Walker circulations, and through positive feedbacks, increasing the global temperature. Near Nordeste warming alone (Q4) produces added rainfall, which in C4 is partially cancelled out by El Nino-like changes in the Walker Cell. Both Q4 and C4 produce small changes in Indonesia, although C4 generates large circulation and precipitation anomalies over the Western Indian Ocean. C4 changes in the midlatitudes produce a very strong Pacific North American pattern (PNA) response that dominates a small positive AO change associated with Q4. These PNA changes produce increased rainfall over the Southeastern United States (SEUS) in C4. AO and NAO-like variability are also found to increase with enhanced CO2. This thesis highlights how climate variability influences regional climate variability, with an emphasis on four regions: Nordeste, Brazil, Western Indonesia, the Southeastern United States (SEUS), and the Mediterranean. It links El Nino-driven delay in the onset of rainy season drivers in Western Indonesia to decision-making about when to plant the year's largest crop. In a coupled configuration, the GISS GCM produces strong El Nino-like changes with global warming. This result suggests that the impacts---climatological and agricultural---of climate change may ultimately exceed the impacts of current variability. Somewhat paradoxically, these results indicate that one of the central manifestations of climate change is likely to be

  6. Modeling glacial climates

    Science.gov (United States)

    North, G. R.; Crowley, T. J.

    1984-01-01

    Mathematical climate modelling has matured as a discipline to the point that it is useful in paleoclimatology. As an example a new two dimensional energy balance model is described and applied to several problems of current interest. The model includes the seasonal cycle and the detailed land-sea geographical distribution. By examining the changes in the seasonal cycle when external perturbations are forced upon the climate system it is possible to construct hypotheses about the origin of midlatitude ice sheets and polar ice caps. In particular the model predicts a rather sudden potential for glaciation over large areas when the Earth's orbital elements are only slightly altered. Similarly, the drift of continents or the change of atmospheric carbon dioxide over geological time induces radical changes in continental ice cover. With the advance of computer technology and improved understanding of the individual components of the climate system, these ideas will be tested in far more realistic models in the near future.

  7. The effects of future nationwide forest transition to discharge in the 21st century with regard to general circulation model climate change scenarios.

    Science.gov (United States)

    Mouri, Goro; Nakano, Katsuhiro; Tsuyama, Ikutaro; Tanaka, Nobuyuki

    2016-08-01

    Forest disturbance (or land-cover change) and climatic variability are commonly recognised as two major drivers interactively influencing hydrology in forested watersheds. Future climate changes and corresponding changes in forest type and distribution are expected to generate changes in rainfall runoff that pose a threat to river catchments. It is therefore important to understand how future climate changes will effect average rainfall distribution and temperature and what effect this will have upon forest types across Japan. Recent deforestation of the present-day coniferous forest and expected increases in evergreen forest are shown to influence runoff processes and, therefore, to influence future runoff conditions. We strongly recommend that variations in forest type be considered in future plans to ameliorate projected climate changes. This will help to improve water retention and storage capacities, enhance the flood protection function of forests, and improve human health. We qualitatively assessed future changes in runoff including the effects of variation in forest type across Japan. Four general circulation models (GCMs) were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields: the Model for Interdisciplinary Research on Climate (MIROC), the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), the Hadley Centre Global Environment Model (HadGEM), and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model. The simulations consisted of an ensemble including multiple physics configurations and different reference concentration pathways (RCP2.6, 4.5, and 8.5), the results of which have produced monthly data sets for the whole of Japan. The impacts of future climate changes on forest type in Japan are based on the balance amongst changes in rainfall distribution, temperature and hydrological factors. Methods for assessing the impact of such changes include the

  8. Linking models of human behaviour and climate alters projected climate change

    Science.gov (United States)

    Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; Carr, Eric; Metcalf, Sara S.; Winter, Jonathan M.; Howe, Peter D.; Fefferman, Nina; Franck, Travis; Zia, Asim; Kinzig, Ann; Hoffman, Forrest M.

    2018-01-01

    Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4-6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with the largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.

  9. Deriving user-informed climate information from climate model ensemble results

    Science.gov (United States)

    Huebener, Heike; Hoffmann, Peter; Keuler, Klaus; Pfeifer, Susanne; Ramthun, Hans; Spekat, Arne; Steger, Christian; Warrach-Sagi, Kirsten

    2017-07-01

    Communication between providers and users of climate model simulation results still needs to be improved. In the German regional climate modeling project ReKliEs-De a midterm user workshop was conducted to allow the intended users of the project results to assess the preliminary results and to streamline the final project results to their needs. The user feedback highlighted, in particular, the still considerable gap between climate research output and user-tailored input for climate impact research. Two major requests from the user community addressed the selection of sub-ensembles and some condensed, easy to understand information on the strengths and weaknesses of the climate models involved in the project.

  10. National Scale Prediction of Soil Carbon Sequestration under Scenarios of Climate Change

    Science.gov (United States)

    Izaurralde, R. C.; Thomson, A. M.; Potter, S. R.; Atwood, J. D.; Williams, J. R.

    2006-12-01

    Carbon sequestration in agricultural soils is gaining momentum as a tool to mitigate the rate of increase of atmospheric CO2. Researchers from the Pacific Northwest National Laboratory, Texas A&M University, and USDA-NRCS used the EPIC model to develop national-scale predictions of soil carbon sequestration with adoption of no till (NT) under scenarios of climate change. In its current form, the EPIC model simulates soil C changes resulting from heterotrophic respiration and wind / water erosion. Representative modeling units were created to capture the climate, soil, and management variability at the 8-digit hydrologic unit (USGS classification) watershed scale. The soils selected represented at least 70% of the variability within each watershed. This resulted in 7,540 representative modeling units for 1,412 watersheds. Each watershed was assigned a major crop system: corn, soybean, spring wheat, winter wheat, cotton, hay, alfalfa, corn-soybean rotation or wheat-fallow rotation based on information from the National Resource Inventory. Each representative farm was simulated with conventional tillage and no tillage, and with and without irrigation. Climate change scenarios for two future periods (2015-2045 and 2045-2075) were selected from GCM model runs using the IPCC SRES scenarios of A2 and B2 from the UK Hadley Center (HadCM3) and US DOE PCM (PCM) models. Changes in mean and standard deviation of monthly temperature and precipitation were extracted from gridded files and applied to baseline climate (1960-1990) for each of the 1,412 modeled watersheds. Modeled crop yields were validated against historical USDA NASS county yields (1960-1990). The HadCM3 model predicted the most severe changes in climate parameters. Overall, there would be little difference between the A2 and B2 scenarios. Carbon offsets were calculated as the difference in soil C change between conventional and no till. Overall, C offsets during the first 30-y period (513 Tg C) are predicted to

  11. The Monash University Interactive Simple Climate Model

    Science.gov (United States)

    Dommenget, D.

    2013-12-01

    The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

  12. On coupling global biome models with climate models

    International Nuclear Information System (INIS)

    Claussen, M.

    1994-01-01

    The BIOME model of Prentice et al. (1992), which predicts global vegetation patterns in equilibrium with climate, is coupled with the ECHAM climate model of the Max-Planck-Institut fuer Meteorologie, Hamburg. It is found that incorporation of the BIOME model into ECHAM, regardless at which frequency, does not enhance the simulated climate variability, expressed in terms of differences between global vegetation patterns. Strongest changes are seen only between the initial biome distribution and the biome distribution computed after the first simulation period, provided that the climate-biome model is started from a biome distribution that resembles the present-day distribution. After the first simulation period, there is no significant shrinking, expanding, or shifting of biomes. Likewise, no trend is seen in global averages of land-surface parameters and climate variables. (orig.)

  13. Influence of enhanced Asian NOx emissions on ozone in the upper troposphere and lower stratosphere in chemistry–climate model simulations

    Directory of Open Access Journals (Sweden)

    C. Roy

    2017-01-01

    78.5 mW m−2 respectively. These elevated NOx emissions produce significant warming over the Tibetan Plateau and increase precipitation over India due to a strengthening of the monsoon Hadley circulation. However, increase in NOx emissions over India by 73 % (similar to the observed increase over China results in large ozone production over the Indo-Gangetic Plain and Tibetan Plateau. The higher ozone concentrations, in turn, induce a reversed monsoon Hadley circulation and negative precipitation anomalies over India. The associated subsidence suppresses vertical transport of NOx and ozone into the ASM anticyclone.

  14. Regionalizing global climate models

    NARCIS (Netherlands)

    Pitman, A.J.; Arneth, A.; Ganzeveld, L.N.

    2012-01-01

    Global climate models simulate the Earth's climate impressively at scales of continents and greater. At these scales, large-scale dynamics and physics largely define the climate. At spatial scales relevant to policy makers, and to impacts and adaptation, many other processes may affect regional and

  15. Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

    Directory of Open Access Journals (Sweden)

    K. Steffens

    2014-02-01

    Full Text Available Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in south-western Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM, greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set (1970–1999 for an important agricultural production area in south-western Sweden based on monthly change factors for 2070–2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.

  16. Modelling climate impact on floods under future emission scenarios using an ensemble of climate model projections

    Science.gov (United States)

    Wetterhall, F.; Cloke, H. L.; He, Y.; Freer, J.; Pappenberger, F.

    2012-04-01

    Evidence provided by modelled assessments of climate change impact on flooding is fundamental to water resource and flood risk decision making. Impact models usually rely on climate projections from Global and Regional Climate Models, and there is no doubt that these provide a useful assessment of future climate change. However, cascading ensembles of climate projections into impact models is not straightforward because of problems of coarse resolution in Global and Regional Climate Models (GCM/RCM) and the deficiencies in modelling high-intensity precipitation events. Thus decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs, such as selection of downscaling methods and application of Model Output Statistics (MOS). In this paper a grand ensemble of projections from several GCM/RCM are used to drive a hydrological model and analyse the resulting future flood projections for the Upper Severn, UK. The impact and implications of applying MOS techniques to precipitation as well as hydrological model parameter uncertainty is taken into account. The resultant grand ensemble of future river discharge projections from the RCM/GCM-hydrological model chain is evaluated against a response surface technique combined with a perturbed physics experiment creating a probabilisic ensemble climate model outputs. The ensemble distribution of results show that future risk of flooding in the Upper Severn increases compared to present conditions, however, the study highlights that the uncertainties are large and that strong assumptions were made in using Model Output Statistics to produce the estimates of future discharge. The importance of analysing on a seasonal basis rather than just annual is highlighted. The inability of the RCMs (and GCMs) to produce realistic precipitation patterns, even in present conditions, is a major caveat of local climate impact studies on flooding, and this should be a focus for future development.

  17. On coupling global biome models with climate models

    OpenAIRE

    Claussen, M.

    1994-01-01

    The BIOME model of Prentice et al. (1992; J. Biogeogr. 19: 117-134), which predicts global vegetation patterns in equilibrium with climate, was coupled with the ECHAM climate model of the Max-Planck-Institut fiir Meteorologie, Hamburg, Germany. It was found that incorporation of the BIOME model into ECHAM, regardless at which frequency, does not enhance the simulated climate variability, expressed in terms of differences between global vegetation patterns. Strongest changes are seen only betw...

  18. Potential change in forest types and stand heights in central Siberia in a warming climate

    International Nuclear Information System (INIS)

    Tchebakova, N M; Parfenova, E I; Korets, M A; Conard, S G

    2016-01-01

    Previous regional studies in Siberia have demonstrated climate warming and associated changes in distribution of vegetation and forest types, starting at the end of the 20th century. In this study we used two regional bioclimatic envelope models to simulate potential changes in forest types distribution and developed new regression models to simulate changes in stand height in tablelands and southern mountains of central Siberia under warming 21st century climate. Stand height models were based on forest inventory data (2850 plots). The forest type and stand height maps were superimposed to identify how heights would change in different forest types in future climates. Climate projections from the general circulation model Hadley HadCM3 for emission scenarios B1 and A2 for 2080s were paired with the regional bioclimatic models. Under the harsh A2 scenario, simulated changes included: a 80%–90% decrease in forest-tundra and tundra, a 30% decrease in forest area, a ∼400% increase in forest-steppe, and a 2200% increase in steppe, forest-steppe and steppe would cover 55% of central Siberia. Under sufficiently moist conditions, the southern and middle taiga were simulated to benefit from 21st century climate warming. Habitats suitable for highly-productive forests (≥30–40 m stand height) were simulated to increase at the expense of less productive forests (10–20 m). In response to the more extreme A2 climate the area of these highly-productive forests would increase 10%–25%. Stand height increases of 10 m were simulated over 35%–50% of the current forest area in central Siberia. In the extremely warm A2 climate scenario, the tall trees (25–30 m) would occur over 8%–12% of area in all forest types except forest-tundra by the end of the century. In forest-steppe, trees of 30–40 m may cover some 15% of the area under sufficient moisture. (letter)

  19. Sensitivity of climate models: Comparison of simulated and observed patterns for past climates

    International Nuclear Information System (INIS)

    Prell, W.L.; Webb, T. III.

    1992-08-01

    Predicting the potential climatic effects of increased concentrations of atmospheric carbon dioxide requires the continuing development of climate models. Confidence in the predictions will be much enhanced once the models are thoroughly tested in terms of their ability to simulate climates that differ significantly from today's climate. As one index of the magnitude of past climate change, the global mean temperature increase during the past 18,000 years is similar to that predicted for carbon dioxide--doubling. Simulating the climatic changes of the past 18,000 years, as well as the warmer-than-present climate of 6000 years ago and the climate of the last interglacial, around 126,000 years ago, provides an excellent opportunity to test the models that are being used in global climate change research. During the past several years, we have used paleoclimatic data to test the accuracy of the National Center for Atmospheric Research, Community Climate Model, Version 0, after changing its boundary conditions to those appropriate for past climates. We have assembled regional and near-global paleoclimatic data sets of pollen, lake level, and marine plankton data and calibrated many of the data in terms of climatic variables. We have also developed methods that permit direct quantitative comparisons between the data and model results. Our research has shown that comparing the model results with the data is an evolutionary process, because the models, the data, and the methods for comparison are continually being improved. During 1992, we have completed new modeling experiments, further analyzed previous model experiments, compiled new paleodata, made new comparisons between data and model results, and participated in workshops on paleoclimatic modeling

  20. Climate simulations for 1880-2003 with GISS modelE

    International Nuclear Information System (INIS)

    Hansen, J.; Lacis, A.; Miller, R.; Schmidt, G.A.; Russell, G.; Canuto, V.; Del Genio, A.; Hall, T.; Hansen, J.; Sato, M.; Kharecha, P.; Nazarenko, L.; Aleinov, I.; Bauer, S.; Chandler, M.; Faluvegi, G.; Jonas, J.; Ruedy, R.; Lo, K.; Cheng, Y.; Lacis, A.; Schmidt, G.A.; Del Genio, A.; Miller, R.; Cairns, B.; Hall, T.; Baum, E.; Cohen, A.; Fleming, E.; Jackman, C.; Friend, A.; Kelley, M.

    2007-01-01

    We carry out climate simulations for 1880-2003 with GISS modelE driven by ten measured or estimated climate forcing. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcing, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcing are due to model deficiencies, inaccurate or incomplete forcing, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880-2003 forcing, we aim to provide a benchmark against which the effect of improvements in the model, climate forcing, and observations can be tested. Principal model deficiencies include unrealistic weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. Greatest uncertainties in the forcing are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds. (authors)

  1. Coupling Climate Models and Forward-Looking Economic Models

    Science.gov (United States)

    Judd, K.; Brock, W. A.

    2010-12-01

    Authors: Dr. Kenneth L. Judd, Hoover Institution, and Prof. William A. Brock, University of Wisconsin Current climate models range from General Circulation Models (GCM’s) with millions of degrees of freedom to models with few degrees of freedom. Simple Energy Balance Climate Models (EBCM’s) help us understand the dynamics of GCM’s. The same is true in economics with Computable General Equilibrium Models (CGE’s) where some models are infinite-dimensional multidimensional differential equations but some are simple models. Nordhaus (2007, 2010) couples a simple EBCM with a simple economic model. One- and two- dimensional ECBM’s do better at approximating damages across the globe and positive and negative feedbacks from anthroprogenic forcing (North etal. (1981), Wu and North (2007)). A proper coupling of climate and economic systems is crucial for arriving at effective policies. Brock and Xepapadeas (2010) have used Fourier/Legendre based expansions to study the shape of socially optimal carbon taxes over time at the planetary level in the face of damages caused by polar ice cap melt (as discussed by Oppenheimer, 2005) but in only a “one dimensional” EBCM. Economists have used orthogonal polynomial expansions to solve dynamic, forward-looking economic models (Judd, 1992, 1998). This presentation will couple EBCM climate models with basic forward-looking economic models, and examine the effectiveness and scaling properties of alternative solution methods. We will use a two dimensional EBCM model on the sphere (Wu and North, 2007) and a multicountry, multisector regional model of the economic system. Our aim will be to gain insights into intertemporal shape of the optimal carbon tax schedule, and its impact on global food production, as modeled by Golub and Hertel (2009). We will initially have limited computing resources and will need to focus on highly aggregated models. However, this will be more complex than existing models with forward

  2. Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model

    Directory of Open Access Journals (Sweden)

    N. Mahowald

    2011-02-01

    Full Text Available Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climate feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.

  3. Construction of a novel economy-climate model

    Institute of Scientific and Technical Information of China (English)

    CHOU JieMing; DONG WenJie; YE DuZheng

    2007-01-01

    An attempt has been made to construct a novel economy-climate model by combining climate change research with agricultural economy research to evaluate the influence of global climate change on grain yields. The insertion of a climate change factor into the economic C-D (Cobb-Dauglas) production function model yields a novel evaluation model, which connects the climate change factor to the economic variation factor, and the performance and reasonableness of the novel evaluation model are also preliminarily simulated and verified.

  4. Validating predictions from climate envelope models

    Science.gov (United States)

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

    Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

  5. Validating predictions from climate envelope models.

    Directory of Open Access Journals (Sweden)

    James I Watling

    Full Text Available Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species' distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967-1971 (t1 and evaluated using occurrence data from 1998-2002 (t2. Model sensitivity (the ability to correctly classify species presences was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on

  6. Climate forcings and climate sensitivities diagnosed from atmospheric global circulation models

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Bruce T. [Boston University, Department of Geography and Environment, Boston, MA (United States); Knight, Jeff R.; Ringer, Mark A. [Met Office Hadley Centre, Exeter (United Kingdom); Deser, Clara; Phillips, Adam S. [National Center for Atmospheric Research, Boulder, CO (United States); Yoon, Jin-Ho [University of Maryland, Cooperative Institute for Climate and Satellites, Earth System Science Interdisciplinary Center, College Park, MD (United States); Cherchi, Annalisa [Centro Euro-Mediterraneo per i Cambiamenti Climatici, and Istituto Nazionale di Geofisica e Vulcanologia, Bologna (Italy)

    2010-12-15

    Understanding the historical and future response of the global climate system to anthropogenic emissions of radiatively active atmospheric constituents has become a timely and compelling concern. At present, however, there are uncertainties in: the total radiative forcing associated with changes in the chemical composition of the atmosphere; the effective forcing applied to the climate system resulting from a (temporary) reduction via ocean-heat uptake; and the strength of the climate feedbacks that subsequently modify this forcing. Here a set of analyses derived from atmospheric general circulation model simulations are used to estimate the effective and total radiative forcing of the observed climate system due to anthropogenic emissions over the last 50 years of the twentieth century. They are also used to estimate the sensitivity of the observed climate system to these emissions, as well as the expected change in global surface temperatures once the climate system returns to radiative equilibrium. Results indicate that estimates of the effective radiative forcing and total radiative forcing associated with historical anthropogenic emissions differ across models. In addition estimates of the historical sensitivity of the climate to these emissions differ across models. However, results suggest that the variations in climate sensitivity and total climate forcing are not independent, and that the two vary inversely with respect to one another. As such, expected equilibrium temperature changes, which are given by the product of the total radiative forcing and the climate sensitivity, are relatively constant between models, particularly in comparison to results in which the total radiative forcing is assumed constant. Implications of these results for projected future climate forcings and subsequent responses are also discussed. (orig.)

  7. Selecting representative climate models for climate change impact studies : An advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; ter Maat, Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.|info:eu-repo/dai/nl/290472113

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change

  8. Selecting representative climate models for climate change impact studies: an advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; Maat, ter Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change

  9. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    DEFF Research Database (Denmark)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian

    2016-01-01

    Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes...... use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared...... to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice...

  10. LINKING MICROBES TO CLIMATE: INCORPORATING MICROBIAL ACTIVITY INTO CLIMATE MODELS COLLOQUIUM

    Energy Technology Data Exchange (ETDEWEB)

    DeLong, Edward; Harwood, Caroline; Reid, Ann

    2011-01-01

    This report explains the connection between microbes and climate, discusses in general terms what modeling is and how it applied to climate, and discusses the need for knowledge in microbial physiology, evolution, and ecology to contribute to the determination of fluxes and rates in climate models. It recommends with a multi-pronged approach to address the gaps.

  11. Modeling Uncertainty in Climate Change: A Multi-Model Comparison

    Energy Technology Data Exchange (ETDEWEB)

    Gillingham, Kenneth; Nordhaus, William; Anthoff, David; Blanford, Geoffrey J.; Bosetti, Valentina; Christensen, Peter; McJeon, Haewon C.; Reilly, J. M.; Sztorc, Paul

    2015-10-01

    The economics of climate change involves a vast array of uncertainties, complicating both the analysis and development of climate policy. This study presents the results of the first comprehensive study of uncertainty in climate change using multiple integrated assessment models. The study looks at model and parametric uncertainties for population, total factor productivity, and climate sensitivity and estimates the pdfs of key output variables, including CO2 concentrations, temperature, damages, and the social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting pdfs also provide insight on tail events.

  12. Hydrological response to climate change for Gilgel Abay River, in the Lake Tana Basin -Upper Blue Nile Basin of Ethiopia.

    Science.gov (United States)

    Dile, Yihun Taddele; Berndtsson, Ronny; Setegn, Shimelis G

    2013-01-01

    Climate change is likely to have severe effects on water availability in Ethiopia. The aim of the present study was to assess the impact of climate change on the Gilgel Abay River, Upper Blue Nile Basin. The Statistical Downscaling Tool (SDSM) was used to downscale the HadCM3 (Hadley centre Climate Model 3) Global Circulation Model (GCM) scenario data into finer scale resolution. The Soil and Water Assessment Tool (SWAT) was set up, calibrated, and validated. SDSM downscaled climate outputs were used as an input to the SWAT model. The climate projection analysis was done by dividing the period 2010-2100 into three time windows with each 30 years of data. The period 1990-2001 was taken as the baseline period against which comparison was made. Results showed that annual mean precipitation may decrease in the first 30-year period but increase in the following two 30-year periods. The decrease in mean monthly precipitation may be as much as about -30% during 2010-2040 but the increase may be more than +30% in 2070-2100. The impact of climate change may cause a decrease in mean monthly flow volume between -40% to -50% during 2010-2040 but may increase by more than the double during 2070-2100. Climate change appears to have negligible effect on low flow conditions of the river. Seasonal mean flow volume, however, may increase by more than the double and +30% to +40% for the Belg (small rainy season) and Kiremit (main rainy season) periods, respectively. Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River. The increase in flow is likely to have considerable importance for local small scale irrigation activities. Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin.

  13. Hydrological response to climate change for Gilgel Abay River, in the Lake Tana Basin -Upper Blue Nile Basin of Ethiopia.

    Directory of Open Access Journals (Sweden)

    Yihun Taddele Dile

    Full Text Available Climate change is likely to have severe effects on water availability in Ethiopia. The aim of the present study was to assess the impact of climate change on the Gilgel Abay River, Upper Blue Nile Basin. The Statistical Downscaling Tool (SDSM was used to downscale the HadCM3 (Hadley centre Climate Model 3 Global Circulation Model (GCM scenario data into finer scale resolution. The Soil and Water Assessment Tool (SWAT was set up, calibrated, and validated. SDSM downscaled climate outputs were used as an input to the SWAT model. The climate projection analysis was done by dividing the period 2010-2100 into three time windows with each 30 years of data. The period 1990-2001 was taken as the baseline period against which comparison was made. Results showed that annual mean precipitation may decrease in the first 30-year period but increase in the following two 30-year periods. The decrease in mean monthly precipitation may be as much as about -30% during 2010-2040 but the increase may be more than +30% in 2070-2100. The impact of climate change may cause a decrease in mean monthly flow volume between -40% to -50% during 2010-2040 but may increase by more than the double during 2070-2100. Climate change appears to have negligible effect on low flow conditions of the river. Seasonal mean flow volume, however, may increase by more than the double and +30% to +40% for the Belg (small rainy season and Kiremit (main rainy season periods, respectively. Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River. The increase in flow is likely to have considerable importance for local small scale irrigation activities. Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin.

  14. A comparative study of large-scale atmospheric circulation in the context of a future scenario (RCP4.5 and past warmth (mid-Pliocene

    Directory of Open Access Journals (Sweden)

    Y. Sun

    2013-07-01

    Full Text Available The mid-Pliocene warm period (~ 3.3–3.0 Ma is often considered as the last sustained warm period with close enough geographic configurations compared to the present one associated with atmospheric CO2 concentration (405 ± 50 ppm higher than the modern level. For this reason, this period is often considered as a potential analogue for the future climate warming, with the important advantage that for mid-Pliocene many marine and continental data are available. To investigate this issue, we selected the RCP4.5 scenario, one of the current available future projections, to compare the pattern of tropical atmospheric response with the past warm mid-Pliocene climate. We use three Atmosphere-Ocean General Circulation Model (AOGCM simulations (RCP4.5 scenario, mid-Pliocene and present-day simulation carried out with the IPSL-CM5A model and investigate atmospheric tropical dynamics through Hadley and Walker cell responses to warmer conditions, considering that the analysis can provide some assessment of how these circulations will change in the future. Our results show that there is a damping of the Hadley cell intensity in the northern tropics and an increase in both subtropics. Moreover, northern and southern Hadley cells expand poleward. The response of the Hadley cells is stronger for the RCP4.5 scenario than for the mid-Pliocene, but in very good agreement with the fact that the atmospheric CO2 concentration is higher in the future scenario than in the mid-Pliocene (543 versus 405 ppm. Concerning the response of the Walker cell, we show that despite very large similarities, there are also some differences. Common features to both scenarios are: weakening of the ascending branch, leading to a suppression of the precipitation over the western tropical Pacific. The response of the Walker cell is stronger in the RCP4.5 scenario than in the mid-Pliocene but also depicts some major differences, as an eastward shift of its rising branch in the future

  15. Downscaling of South America present climate driven by 4-member HadCM3 runs

    Energy Technology Data Exchange (ETDEWEB)

    Chou, Sin Chan; Marengo, Jose A.; Lyra, Andre A.; Sueiro, Gustavo; Pesquero, Jose F.; Alves, Lincoln M.; Chagas, Diego J.; Gomes, Jorge L.; Bustamante, Josiane F.; Tavares, Priscila [National Institute for Space Research (INPE), Sao Paulo (Brazil); Kay, Gillian; Betts, Richard [UK Met Office Hadley Centre, Devon (United Kingdom)

    2012-02-15

    The objective of this work is to evaluate climate simulations over South America using the regional Eta Model driven by four members of an ensemble of the UK Met Office Hadley Centre HadCM3 global model. The Eta Model has been modified with the purpose of performing long-term decadal integrations and has shown to reproduce ''present climate'' - the period 1961-1990 - reasonably well when forced by HadCM3. The global model lateral conditions with a resolution of 2.5 latitude x 3.75 longitude were provided at a frequency of 6 h. Each member of the global model ensemble has a different climate sensitivity, and the four members were selected to span the range of uncertainty encompassed by the ensemble. The Eta Model nested in the HadCM3 global model was configured with 40-km horizontal resolution and 38 layers in the vertical. No large-scale internal nudging was applied. Results are shown for austral summer and winter at present climate defined as 1961-90. The upper and low-level circulation patterns produced by the Eta-CPTEC/HadCM3 experiment set-up show good agreement with reanalysis data and the mean precipitation and temperature with CRU observation data. The spread in the downscaled mean precipitation and temperature is small when compared against model errors. On the other hand, the benefits in using an ensemble is clear in the improved representation of the seasonal cycle by the ensemble mean over any one realization. El Nino and La Nina years were identified in the HadCM3 member runs based on the NOAA Climate Prediction Center criterion of sea surface temperature anomalies in the Nino 3.4 area. The frequency of the El Nino and La Nina events in the studied period is underestimated by HadCM3. The precipitation and temperature anomalies typical of these events are reproduced by most of the Eta-CPTEC/HadCM3 ensemble, although small displacements of the positions of the anomalies occur. This experiment configuration is the first step on the

  16. Model confirmation in climate economics

    Science.gov (United States)

    Millner, Antony; McDermott, Thomas K. J.

    2016-01-01

    Benefit–cost integrated assessment models (BC-IAMs) inform climate policy debates by quantifying the trade-offs between alternative greenhouse gas abatement options. They achieve this by coupling simplified models of the climate system to models of the global economy and the costs and benefits of climate policy. Although these models have provided valuable qualitative insights into the sensitivity of policy trade-offs to different ethical and empirical assumptions, they are increasingly being used to inform the selection of policies in the real world. To the extent that BC-IAMs are used as inputs to policy selection, our confidence in their quantitative outputs must depend on the empirical validity of their modeling assumptions. We have a degree of confidence in climate models both because they have been tested on historical data in hindcasting experiments and because the physical principles they are based on have been empirically confirmed in closely related applications. By contrast, the economic components of BC-IAMs often rely on untestable scenarios, or on structural models that are comparatively untested on relevant time scales. Where possible, an approach to model confirmation similar to that used in climate science could help to build confidence in the economic components of BC-IAMs, or focus attention on which components might need refinement for policy applications. We illustrate the potential benefits of model confirmation exercises by performing a long-run hindcasting experiment with one of the leading BC-IAMs. We show that its model of long-run economic growth—one of its most important economic components—had questionable predictive power over the 20th century. PMID:27432964

  17. Development of regional future climate change scenarios in South America using the Eta CPTEC/HadCM3 climate change projections: climatology and regional analyses for the Amazon, Sao Francisco and the Parana River basins

    Energy Technology Data Exchange (ETDEWEB)

    Marengo, Jose A.; Chou, Sin Chan; Alves, Lincoln M.; Pesquero, Jose F.; Soares, Wagner R.; Santos, Daniel C.; Lyra, Andre A.; Sueiro, Gustavo; Chagas, Diego J.; Gomes, Jorge L.; Bustamante, Josiane F.; Tavares, Priscila [National Institute for Space Research (INPE) Cachoeira Paulista, Sao Paulo (Brazil); Kay, Gillian; Betts, Richard [UK Met Office Hadley Centre, Exeter, Devon (United Kingdom)

    2012-05-15

    The objective of this study is to assess the climate projections over South America using the Eta-CPTEC regional model driven by four members of an ensemble of the Met Office Hadley Centre Global Coupled climate model HadCM3. The global model ensemble was run over the twenty-first century according to the SRES A1B emissions scenario, but with each member having a different climate sensitivity. The four members selected to drive the Eta-CPTEC model span the sensitivity range in the global model ensemble. The Eta-CPTEC model nested in these lateral boundary conditions was configured with a 40-km grid size and was run over 1961-1990 to represent baseline climate, and 2011-2100 to simulate possible future changes. Results presented here focus on austral summer and winter climate of 2011-2040, 2041-2070 and 2071-2100 periods, for South America and for three major river basins in Brazil. Projections of changes in upper and low-level circulation and the mean sea level pressure (SLP) fields simulate a pattern of weakening of the tropical circulation and strengthening of the subtropical circulation, marked by intensification at the surface of the Chaco Low and the subtropical highs. Strong warming (4-6 C) of continental South America increases the temperature gradient between continental South America and the South Atlantic. This leads to stronger SLP gradients between continent and oceans, and to changes in moisture transport and rainfall. Large rainfall reductions are simulated in Amazonia and Northeast Brazil (reaching up to 40%), and rainfall increases around the northern coast of Peru and Ecuador and in southeastern South America, reaching up to 30% in northern Argentina. All changes are more intense after 2040. The Precipitation-Evaporation (P-E) difference in the A1B downscaled scenario suggest water deficits and river runoff reductions in the eastern Amazon and Sao Francisco Basin, making these regions susceptible to drier conditions and droughts in the future

  18. On the statistical comparison of climate model output and climate data

    International Nuclear Information System (INIS)

    Solow, A.R.

    1991-01-01

    Some broad issues arising in the statistical comparison of the output of climate models with the corresponding climate data are reviewed. Particular attention is paid to the question of detecting climate change. The purpose of this paper is to review some statistical approaches to the comparison of the output of climate models with climate data. There are many statistical issues arising in such a comparison. The author will focus on some of the broader issues, although some specific methodological questions will arise along the way. One important potential application of the approaches discussed in this paper is the detection of climate change. Although much of the discussion will be fairly general, he will try to point out the appropriate connections to the detection question. 9 refs

  19. On the statistical comparison of climate model output and climate data

    International Nuclear Information System (INIS)

    Solow, A.R.

    1990-01-01

    Some broad issues arising in the statistical comparison of the output of climate models with the corresponding climate data are reviewed. Particular attention is paid to the question of detecting climate change. The purpose of this paper is to review some statistical approaches to the comparison of the output of climate models with climate data. There are many statistical issues arising in such a comparison. The author will focus on some of the broader issues, although some specific methodological questions will arise along the way. One important potential application of the approaches discussed in this paper is the detection of climate change. Although much of the discussion will be fairly general, he will try to point out the appropriate connections to the detection question

  20. Analyses of Observed and Anticipated Changes in Extreme Climate Events in the Northwest Himalaya

    Directory of Open Access Journals (Sweden)

    Dharmaveer Singh

    2016-02-01

    Full Text Available In this study, past (1970-2005 as well as future long term (2011-2099 trends in various extreme events of temperature and precipitation have been investigated over selected hydro-meteorological stations in the Sutlej river basin. The ensembles of two Coupled Model Intercomparison Project (CMIP3 models: third generation Canadian Coupled Global Climate Model and Hadley Centre Coupled Model have been used for simulation of future daily time series of temperature (maximum and minimum and precipitation under A2 emission scenario. Large scale atmospheric variables of both models and National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis data sets have been downscaled using statistical downscaling technique at individual stations. A total number of 25 extreme indices of temperature (14 and precipitation (11 as specified by the Expert Team of the World Meteorological Organization and Climate Variability and Predictability are derived for the past and future periods. Trends in extreme indices are detected over time using the modified Mann-Kendall test method. The stations which have shown either decrease or no change in hot extreme events (i.e., maximum TMax, warm days, warm nights, maximum TMin, tropical nights, summer days and warm spell duration indicators for 1970–2005 and increase in cold extreme events (cool days, cool nights, frost days and cold spell duration indicators are predicted to increase and decrease respectively in the future. In addition, an increase in frequency and intensity of extreme precipitation events is also predicted.

  1. Regional climate projection of the Maritime Continent using the MIT Regional Climate Model

    Science.gov (United States)

    IM, E. S.; Eltahir, E. A. B.

    2014-12-01

    Given that warming of the climate system is unequivocal (IPCC AR5), accurate assessment of future climate is essential to understand the impact of climate change due to global warming. Modelling the climate change of the Maritime Continent is particularly challenge, showing a high degree of uncertainty. Compared to other regions, model agreement of future projections in response to anthropogenic emission forcings is much less. Furthermore, the spatial and temporal behaviors of climate projections seem to vary significantly due to a complex geographical condition and a wide range of scale interactions. For the fine-scale climate information (27 km) suitable for representing the complexity of climate change over the Maritime Continent, dynamical downscaling is performed using the MIT regional climate model (MRCM) during two thirty-year period for reference (1970-1999) and future (2070-2099) climate. Initial and boundary conditions are provided by Community Earth System Model (CESM) simulations under the emission scenarios projected by MIT Integrated Global System Model (IGSM). Changes in mean climate as well as the frequency and intensity of extreme climate events are investigated at various temporal and spatial scales. Our analysis is primarily centered on the different behavior of changes in convective and large-scale precipitation over land vs. ocean during dry vs. wet season. In addition, we attempt to find the added value to downscaled results over the Maritime Continent through the comparison between MRCM and CESM projection. Acknowledgements.This research was supported by the National Research Foundation Singapore through the Singapore MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling interdisciplinary research program.

  2. Separating climate change signals into thermodynamic, lapse-rate and circulation effects: theory and application to the European summer climate

    Science.gov (United States)

    Kröner, Nico; Kotlarski, Sven; Fischer, Erich; Lüthi, Daniel; Zubler, Elias; Schär, Christoph

    2017-05-01

    Climate models robustly project a strong overall summer warming across Europe showing a characteristic north-south gradient with enhanced warming and drying in southern Europe. However, the processes that are responsible for this pattern are not fully understood. We here employ an extended surrogate or pseudo-warming approach to disentangle the contribution of different mechanisms to this response pattern. The basic idea of the surrogate technique is to use a regional climate model and apply a large-scale warming to the lateral boundary conditions of a present-day reference simulation, while maintaining the relative humidity (and thus implicitly increasing the specific moisture content). In comparison to previous studies, our approach includes two important extensions: first, different vertical warming profiles are applied in order to separate the effects of a mean warming from lapse-rate effects. Second, a twin-design is used, in which the climate change signals are not only added to present-day conditions, but also subtracted from a scenario experiment. We demonstrate that these extensions provide an elegant way to separate the full climate change signal into contributions from large-scale thermodynamic (TD), lapse-rate (LR), and circulation and other remaining effects (CO). The latter in particular include changes in land-ocean contrast and spatial variations of the SST warming patterns. We find that the TD effect yields a large-scale warming across Europe with no distinct latitudinal gradient. The LR effect, which is quantified for the first time in our study, leads to a stronger warming and some drying in southern Europe. It explains about 50 % of the warming amplification over the Iberian Peninsula, thus demonstrating the important role of lapse-rate changes. The effect is linked to an extending Hadley circulation. The CO effect as inherited from the driving GCM is shown to further amplify the north-south temperature change gradient. In terms of mean summer

  3. Mediterranean climate modelling: variability and climate change scenarios

    International Nuclear Information System (INIS)

    Somot, S.

    2005-12-01

    Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)

  4. Paleoclimate validation of a numerical climate model

    International Nuclear Information System (INIS)

    Schelling, F.J.; Church, H.W.; Zak, B.D.; Thompson, S.L.

    1994-01-01

    An analysis planned to validate regional climate model results for a past climate state at Yucca Mountain, Nevada, against paleoclimate evidence for the period is described. This analysis, which will use the GENESIS model of global climate nested with the RegCM2 regional climate model, is part of a larger study for DOE's Yucca Mountain Site Characterization Project that is evaluating the impacts of long term future climate change on performance of the potential high level nuclear waste repository at Yucca Mountain. The planned analysis and anticipated results are presented

  5. Sensitivity of South American tropical climate to Last Glacial Maximum boundary conditions: focus on teleconnections with tropics and extratropics (Invited)

    Science.gov (United States)

    Khodri, M.; Kageyama, M.; Roche, D. M.

    2009-12-01

    Proxy data over tropical latitudes for the Last Glacial Maximum (LGM) has been interpreted as a southward shift of the Inter Tropical Convergence Zone (ITCZ) and so far linked to a mechanism analogous to the modern day “meridional-mode” in the Atlantic Ocean. Here we have explored alternative mechanisms, related to the direct impact of the LGM global changes in the dry static stability on tropical moist deep convection. We have used a coupled ocean-atmosphere model capable of capturing the thermodynamical structure of the atmosphere and the tropical component of the Hadley and Walker circulations. In each experiment, we have applied either all the LGM forcings, or the individual contributions of greenhouse gases (GHG) concentrations, ice sheet topography and/or albedo to explore the hydrological response over tropical latitudes with a focus on South America. The dominant forcing for the LGM tropical temperature and precipitation changes is found to be due to the reduced GHG, through the direct effect of reduced radiative heating (Clausius-Clapeyron relationship). The LGM GHG is also responsible for increased extra-tropical static stability which strengthens the Hadley Cell. Stronger subsidence over northern tropics then produces an amplification of the northern tropics drying initially due to the direct cooling effect. The land ice sheet is also able to promote the Hadley cell feedback mostly via the topographic effect on the extra-tropical dry static stability and on the position of the subtropical jets. Our results therefore suggest that the communication between the extratropics and the tropics is tighter during LGM and does not necessarily rely on the “meridional-mode” mechanism. The Hadley cell response is constrained by the requirement that diabatic heating in the tropics balances cooling in subtropics. We show that such extratropics-tropics dependence is stronger at the LGM because of the stronger perturbation of northern extra tropical thermal and

  6. Reconstructing Holocene climate using a climate model: Model strategy and preliminary results

    Science.gov (United States)

    Haberkorn, K.; Blender, R.; Lunkeit, F.; Fraedrich, K.

    2009-04-01

    An Earth system model of intermediate complexity (Planet Simulator; PlaSim) is used to reconstruct Holocene climate based on proxy data. The Planet Simulator is a user friendly general circulation model (GCM) suitable for palaeoclimate research. Its easy handling and the modular structure allow for fast and problem dependent simulations. The spectral model is based on the moist primitive equations conserving momentum, mass, energy and moisture. Besides the atmospheric part, a mixed layer-ocean with sea ice and a land surface with biosphere are included. The present-day climate of PlaSim, based on an AMIP II control-run (T21/10L resolution), shows reasonable agreement with ERA-40 reanalysis data. Combining PlaSim with a socio-technological model (GLUES; DFG priority project INTERDYNAMIK) provides improved knowledge on the shift from hunting-gathering to agropastoral subsistence societies. This is achieved by a data assimilation approach, incorporating proxy time series into PlaSim to initialize palaeoclimate simulations during the Holocene. For this, the following strategy is applied: The sensitivities of the terrestrial PlaSim climate are determined with respect to sea surface temperature (SST) anomalies. Here, the focus is the impact of regionally varying SST both in the tropics and the Northern Hemisphere mid-latitudes. The inverse of these sensitivities is used to determine the SST conditions necessary for the nudging of land and coastal proxy climates. Preliminary results indicate the potential, the uncertainty and the limitations of the method.

  7. The climate4impact platform: Providing, tailoring and facilitating climate model data access

    Science.gov (United States)

    Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael

    2017-04-01

    One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European

  8. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Auffhammer, M.; Hsiang, S. M.; Schlenker, W.; Sobel, A.

    2013-06-28

    Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

  9. Embedding complex hydrology in the climate system - towards fully coupled climate-hydrology models

    DEFF Research Database (Denmark)

    Butts, M.; Rasmussen, S.H.; Ridler, M.

    2013-01-01

    Motivated by the need to develop better tools to understand the impact of future management and climate change on water resources, we present a set of studies with the overall aim of developing a fully dynamic coupling between a comprehensive hydrological model, MIKE SHE, and a regional climate...... distributed parameters using satellite remote sensing. Secondly, field data are used to investigate the effects of model resolution and parameter scales for use in a coupled model. Finally, the development of the fully coupled climate-hydrology model is described and some of the challenges associated...... with coupling models for hydrological processes on sub-grid scales of the regional climate model are presented....

  10. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

    2015-12-01

    Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the

  11. Twenty first century climate change as simulated by European climate models

    International Nuclear Information System (INIS)

    Cubasch, Ulrich

    2007-01-01

    Full text: Climate change simulation results for seven European state-of-the-art climate models, participating in the European research project ENSEMBLES (ENSEMBLE-based Predictions of Climate Changes and their Impacts), will be presented. Models from Norway, France, Germany, Denmark, and Great Britain, representing a sub-ensemble of the models contributing to the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4), are included. Climate simulations are conducted with all the models for present-day climate and for future climate under the SRES A1B, A2, and B1 scenarios. The design of the simulations follows the guidelines of the IPCC AR4. The 21st century projections are compared to the corresponding present-day simulations. The ensemble mean global mean near surface temperature rise for the year 2099 compared to the 1961-1990 period amounts to 3.2Kforthe A1B scenario, to 4.1 K for the A2 scenario, and to 2.1 K for the B1 scenario. The spatial patterns of temperature change are robust among the contributing models with the largest temperature increase over the Arctic in boreal winter, stronger warming overland than over ocean, and little warming over the southern oceans. The ensemble mean globally averaged precipitation increases for the three scenarios (5.6%, 5.7%, and 3.8% for scenarios A1B, A2, and B1, respectively). The precipitation signals of the different models display a larger spread than the temperature signals. In general, precipitation increases in the Intertropical Convergence Zone and the mid- to high latitudes (most pronounced during the hemispheric winter) and decreases in the subtropics. Sea-level pressure decreases over the polar regions in all models and all scenarios, which is mainly compensated by a pressure increase in the subtropical highs. These changes imply an intensification of the Southern and Northern Annular Modes

  12. Modeling and assessing international climate financing

    Science.gov (United States)

    Wu, Jing; Tang, Lichun; Mohamed, Rayman; Zhu, Qianting; Wang, Zheng

    2016-06-01

    Climate financing is a key issue in current negotiations on climate protection. This study establishes a climate financing model based on a mechanism in which donor countries set up funds for climate financing and recipient countries use the funds exclusively for carbon emission reduction. The burden-sharing principles are based on GDP, historical emissions, and consumptionbased emissions. Using this model, we develop and analyze a series of scenario simulations, including a financing program negotiated at the Cancun Climate Change Conference (2010) and several subsequent programs. Results show that sustained climate financing can help to combat global climate change. However, the Cancun Agreements are projected to result in a reduction of only 0.01°C in global warming by 2100 compared to the scenario without climate financing. Longer-term climate financing programs should be established to achieve more significant benefits. Our model and simulations also show that climate financing has economic benefits for developing countries. Developed countries will suffer a slight GDP loss in the early stages of climate financing, but the longterm economic growth and the eventual benefits of climate mitigation will compensate for this slight loss. Different burden-sharing principles have very similar effects on global temperature change and economic growth of recipient countries, but they do result in differences in GDP changes for Japan and the FSU. The GDP-based principle results in a larger share of financial burden for Japan, while the historical emissions-based principle results in a larger share of financial burden for the FSU. A larger burden share leads to a greater GDP loss.

  13. Future directions in climate modeling: A climate impacts perspective

    International Nuclear Information System (INIS)

    Mearns, L.O.

    1990-01-01

    One of the most serious impediments to further progress on the determination of specific impacts of climate change on relevant earth systems is the lack of precise and accurate scenarios of regional change. Spatial resolution of models is generally coarse (5-10 degree, corresponding to 550-1,100 km), and the modeling of physical processes is quite crude. Three main areas in which improvements in the modeling of physical processes are being made are modeling of surface processes, modeling of oceans and coupling of oceans and atmospheric models, and modeling of clouds. Improvements are required in the modeling of surface hydrology and vegetative effects, which have significant impact on the albedo scheme used. Oceans are important in climate modeling for the following reasons: delay of warming due to oceanic heat absorption; effect of mean meridional circulation; control of regional patterns of sea surface temperatures and sea ice by wind driven currents; absorption of atmospheric carbon dioxide by the oceans; and determination of interannual climatic variability via variability in sea surface temperature. The effects of clouds on radiation balance is highly significant. Clouds both reflect shortwave radiation and trap longwave radiation. Most cloud properties are sub-grid scale and thus difficult to include explicitly in models. 25 refs., 1 tab

  14. The impacts of climate change on a Norwegian high-head hydropower plant

    Energy Technology Data Exchange (ETDEWEB)

    Chernet, Haregewoin Haile; Alfredsen, Knut; Killintveit, Aanund

    2010-07-01

    Full text: Norway relies on hydropower for 99 percent of the electricity production and thus Hydropower is important for Norway today and in the future energy system. The work presented in this paper shows how a high-head hydropower system in Norway will be affected in the future climate. The Aurland Hydropower system, operated by E-Co Vannkraft, Norway is the test case for the study. The Aurland hydropower system has many reservoirs and transfer systems and is considered to be one of the complex systems in Norway, but also a typical example of a Norwegian high head system. The nMAG Hydropower simulation model, which has been developed at the Norwegian Hydro technical Laboratory, is used to simulate the hydropower system. Historical and future inflow series were transposed from the neighbouring catchment Flaamselvi using scaling based on area and specific runoff, as there is no discharge station in Aurland catchment with long unregulated inflow series to set up the model and to be used for developing future climate scenarios. To generate the future inflow series for the analysis, the HBV hydrological model is calibrated for the Flaamselvi catchment. The model is then used to generate future inflow series of using the Hadley GCM (HADAm3) and A2, B2 climate scenarios. The operation of the hydropower system is then simulated for the period 2071 -2100 to see how future power production is affected by the change in the inflow conditions. The HBV model is also used to see how snow accumulation will be affected in the future as snow melt is important for Norwegian reservoir and hydropower systems. The Hydrologic scenarios under climate change imply an average increase in runoff for the system. Snow accumulation will decrease with sooner snow melt and more winter precipitation as rain. The hydropower simulation results show that associated with the increase in runoff there is an increase in energy generation with 10-20% under the current reservoir operation strategies

  15. Climate Ocean Modeling on Parallel Computers

    Science.gov (United States)

    Wang, P.; Cheng, B. N.; Chao, Y.

    1998-01-01

    Ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change. However, modeling the ocean circulation at various spatial and temporal scales is a very challenging computational task.

  16. Changes and Attribution of Extreme Precipitation in Climate Models: Subdaily and Daily Scales

    Science.gov (United States)

    Zhang, W.; Villarini, G.; Scoccimarro, E.; Vecchi, G. A.

    2017-12-01

    Extreme precipitation events are responsible for numerous hazards, including flooding, soil erosion, and landslides. Because of their significant socio-economic impacts, the attribution and projection of these events is of crucial importance to improve our response, mitigation and adaptation strategies. Here we present results from our ongoing work.In terms of attribution, we use idealized experiments [pre-industrial control experiment (PI) and 1% per year increase (1%CO2) in atmospheric CO2] from ten general circulation models produced under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the fraction of attributable risk to examine the CO2 effects on extreme precipitation at the sub-daily and daily scales. We find that the increased CO2 concentration substantially increases the odds of the occurrence of sub-daily precipitation extremes compared to the daily scale in most areas of the world, with the exception of some regions in the sub-tropics, likely in relation to the subsidence of the Hadley Cell. These results point to the large role that atmospheric CO2 plays in extreme precipitation under an idealized framework. Furthermore, we investigate the changes in extreme precipitation events with the Community Earth System Model (CESM) climate experiments using the scenarios consistent with the 1.5°C and 2°C temperature targets. We find that the frequency of annual extreme precipitation at a global scale increases in both 1.5°C and 2°C scenarios until around 2070, after which the magnitudes of the trend become much weaker or even negative. Overall, the frequency of global annual extreme precipitation is similar between 1.5°C and 2°C for the period 2006-2035, and the changes in extreme precipitation in individual seasons are consistent with those for the entire year. The frequency of extreme precipitation in the 2°C experiments is higher than for the 1.5°C experiment after the late 2030s, particularly for the period 2071-2100.

  17. An Exploration of Mechanisms for Mediating the Influence of Extratropical Glaciation on the Tropical Climate

    Science.gov (United States)

    Pierrehumbert, R. T.; Frierson, D. M.

    2006-05-01

    the NHWARM and NHCOLD cases, despite the substantial reduction in atmospheric water vapor in the cold case. The extremely strong midlatitude cooling produces a modest southward shift in the January ITCZ, and none at all in the July ITCZ, indicating that basic Hadley dynamics can make the ITCZ very resistant to moving; we find that the ITCZ position closely follows the tropical temperature maximum. The ITCZ shifts are discussed in terms of theoretical concepts applying to the Hadley circulation. Using an energy balance model (EBM) based on diffusion of moist static energy, Frierson and Held have shown that there is a compensation between changes in latent and sensible heat transport as climate warms, provided the meridional distribution of absorbed solar radiation remains fixed. We have extended this analysis to the case in which the solar forcing gradient is allowed to change, as is the case in our simulations owing to the change in surface albedo between the two simulations. In this case, the EBM does not require strict compensation, and in fact correctly reproduces the fact that tropical heat export increases in the NHCOLD case. However, the EBM over-estimates the penetration of the cooling past the Equator, owing to inadequacies in the diffusive treatment of the Hadley circulation. The EBM also misprepresents the magnitude of midlatitude heat flux changes, owing to the bottom-trapped nature of extratropical cooling seen in the GCM experiments, which is not reflected in the assumptions about the vertical profile of temperature built into the EBM. The implications of incorporating this effect will be discussed.

  18. Selection of climate change scenario data for impact modelling

    DEFF Research Database (Denmark)

    Sloth Madsen, M; Fox Maule, C; MacKellar, N

    2012-01-01

    Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study...... illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make...... the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented...

  19. Constraining Transient Climate Sensitivity Using Coupled Climate Model Simulations of Volcanic Eruptions

    KAUST Repository

    Merlis, Timothy M.; Held, Isaac M.; Stenchikov, Georgiy L.; Zeng, Fanrong; Horowitz, Larry W.

    2014-01-01

    Coupled climate model simulations of volcanic eruptions and abrupt changes in CO2 concentration are compared in multiple realizations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1). The change in global-mean surface temperature (GMST) is analyzed to determine whether a fast component of the climate sensitivity of relevance to the transient climate response (TCR; defined with the 1%yr-1 CO2-increase scenario) can be estimated from shorter-time-scale climate changes. The fast component of the climate sensitivity estimated from the response of the climate model to volcanic forcing is similar to that of the simulations forced by abrupt CO2 changes but is 5%-15% smaller than the TCR. In addition, the partition between the top-of-atmosphere radiative restoring and ocean heat uptake is similar across radiative forcing agents. The possible asymmetry between warming and cooling climate perturbations, which may affect the utility of volcanic eruptions for estimating the TCR, is assessed by comparing simulations of abrupt CO2 doubling to abrupt CO2 halving. There is slightly less (~5%) GMST change in 0.5 × CO2 simulations than in 2 × CO2 simulations on the short (~10 yr) time scales relevant to the fast component of the volcanic signal. However, inferring the TCR from volcanic eruptions is more sensitive to uncertainties from internal climate variability and the estimation procedure. The response of the GMST to volcanic eruptions is similar in GFDL CM2.1 and GFDL Climate Model, version 3 (CM3), even though the latter has a higher TCR associated with a multidecadal time scale in its response. This is consistent with the expectation that the fast component of the climate sensitivity inferred from volcanic eruptions is a lower bound for the TCR.

  20. Constraining Transient Climate Sensitivity Using Coupled Climate Model Simulations of Volcanic Eruptions

    KAUST Repository

    Merlis, Timothy M.

    2014-10-01

    Coupled climate model simulations of volcanic eruptions and abrupt changes in CO2 concentration are compared in multiple realizations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1). The change in global-mean surface temperature (GMST) is analyzed to determine whether a fast component of the climate sensitivity of relevance to the transient climate response (TCR; defined with the 1%yr-1 CO2-increase scenario) can be estimated from shorter-time-scale climate changes. The fast component of the climate sensitivity estimated from the response of the climate model to volcanic forcing is similar to that of the simulations forced by abrupt CO2 changes but is 5%-15% smaller than the TCR. In addition, the partition between the top-of-atmosphere radiative restoring and ocean heat uptake is similar across radiative forcing agents. The possible asymmetry between warming and cooling climate perturbations, which may affect the utility of volcanic eruptions for estimating the TCR, is assessed by comparing simulations of abrupt CO2 doubling to abrupt CO2 halving. There is slightly less (~5%) GMST change in 0.5 × CO2 simulations than in 2 × CO2 simulations on the short (~10 yr) time scales relevant to the fast component of the volcanic signal. However, inferring the TCR from volcanic eruptions is more sensitive to uncertainties from internal climate variability and the estimation procedure. The response of the GMST to volcanic eruptions is similar in GFDL CM2.1 and GFDL Climate Model, version 3 (CM3), even though the latter has a higher TCR associated with a multidecadal time scale in its response. This is consistent with the expectation that the fast component of the climate sensitivity inferred from volcanic eruptions is a lower bound for the TCR.

  1. Climate change analysis relevant to Jabiluka. Supervising Scientist report 141

    International Nuclear Information System (INIS)

    Jones, R.N.; Abbs, D.J.; Hennessy, K.J.

    1999-01-01

    The aim of the work presented here is to quantify the effects of climate change on rainfall and temperature, and its implications for parameters used in the design of water storage facilities to be used for the next 30 years at the Jabiluka Project, Northern Territory. Changes to average rainfall and temperature, and rainfall variability on decadal to scales of less than one day are investigated. Climate change scenarios have been constructed where projections of climate change can be quantified. Some submissions to the Draft Jabiluka Environmental Impact Statement (EIS) raised concerns about the impact of climate change on the design of hydrologic structures for the Jabiluka project (eg Supplement to the Draft EIS, Kinhill and ERAES 1997, p5-27; Wasson et al 1998). Six General Circulation Model (GCM) simulations were analysed to determine possible temperature and rainfall changes over the region surrounding the Jabiluka mine site: two simulations of the CSIRO GCM, one from the CSIRO limited area model, DARLAM, and single GCM simulations from the Deutsches Klimarechenzentrum (DKRZ), UK Meteorological Office (Hadley Centre) and Canadian Centre for Climate Modelling and Analysis. Due to uncertainties resulting from differing emission scenarios and climate sensitivities these climate models will give different answers. However, under climate change, the hydrological cycle is expected to become more intense (IPCC 1996) through higher evaporation, an increase in the water-holding capacity of the atmosphere and heavier rainfall. GCM output is required to show how this may change on the regional scale, so CSIRO has investigated the models listed above to create scenarios for seasonal rainfall. This involves deriving patterns of local change calculated from the models. The methods used are described in section 2.2. In addition to the enhanced greenhouse effect, natural climatic variability can also have implications for the design of water retention structures. Decadal

  2. MECCA coordinated research program: analysis of climate models uncertainties used for climatic changes study

    International Nuclear Information System (INIS)

    Caneill, J.Y.; Hakkarinen, C.

    1992-01-01

    An international consortium, called MECCA, (Model Evaluation Consortium for Climate Assessment) has been created in 1991 by different partners including electric utilities, government and academic groups to make available to the international scientific community, a super-computer facility for climate evolution studies. The first phase of the program consists to assess uncertainties of climate model simulations in the framework of global climate change studies. Fourteen scientific projects have been accepted on an international basis in this first phase. The second phase of the program will consist in the evaluation of a set of long climate simulations realized with coupled ocean/atmosphere models, in order to study the transient aspects of climate changes and the associated uncertainties. A particular attention will be devoted, on the consequences of these assessments on climate impact studies, and on the regional aspects of climate changes

  3. Simulating fire regimes in the Amazon in response to climate change and deforestation.

    Science.gov (United States)

    Silvestrini, Rafaella Almeida; Soares-Filho, Britaldo Silveira; Nepstad, Daniel; Coe, Michael; Rodrigues, Hermann; Assunção, Renato

    2011-07-01

    Fires in tropical forests release globally significant amounts of carbon to the atmosphere and may increase in importance as a result of climate change. Despite the striking impacts of fire on tropical ecosystems, the paucity of robust spatial models of forest fire still hampers our ability to simulate tropical forest fire regimes today and in the future. Here we present a probabilistic model of human-induced fire occurrence for the Amazon that integrates the effects of a series of anthropogenic factors with climatic conditions described by vapor pressure deficit. The model was calibrated using NOAA-12 night satellite hot pixels for 2003 and validated for the years 2002, 2004, and 2005. Assessment of the fire risk map yielded fitness values > 85% for all months from 2002 to 2005. Simulated fires exhibited high overlap with NOAA-12 hot pixels regarding both spatial and temporal distributions, showing a spatial fit of 50% within a radius of 11 km and a maximum yearly frequency deviation of 15%. We applied this model to simulate fire regimes in the Amazon until 2050 using IPCC's A2 scenario climate data from the Hadley Centre model and a business-as-usual (BAU) scenario of deforestation and road expansion from SimAmazonia. Results show that the combination of these scenarios may double forest fire occurrence outside protected areas (PAs) in years of extreme drought, expanding the risk of fire even to the northwestern Amazon by midcentury. In particular, forest fires may increase substantially across southern and southwestern Amazon, especially along the highways slated for paving and in agricultural zones. Committed emissions from Amazon forest fires and deforestation under a scenario of global warming and uncurbed deforestation may amount to 21 +/- 4 Pg of carbon by 2050. BAU deforestation may increase fires occurrence outside PAs by 19% over the next four decades, while climate change alone may account for a 12% increase. In turn, the combination of climate change

  4. Using a Global Climate Model in an On-line Climate Change Course

    Science.gov (United States)

    Randle, D. E.; Chandler, M. A.; Sohl, L. E.

    2012-12-01

    Seminars on Science: Climate Change is an on-line, graduate-level teacher professional development course offered by the American Museum of Natural History. It is an intensive 6-week course covering a broad range of global climate topics, from the fundamentals of the climate system, to the causes of climate change, the role of paleoclimate investigations, and a discussion of potential consequences and risks. The instructional method blends essays, videos, textbooks, and linked websites, with required participation in electronic discussion forums that are moderated by an experienced educator and a course scientist. Most weeks include additional assignments. Three of these assignments employ computer models, including two weeks spent working with a full-fledged 3D global climate model (GCM). The global climate modeling environment is supplied through a partnership with Columbia University's Educational Global Climate Modeling Project (EdGCM). The objective is to have participants gain hands-on experience with one of the most important, yet misunderstood, aspects of climate change research. Participants in the course are supplied with a USB drive that includes installers for the software and sample data. The EdGCM software includes a version of NASA's global climate model fitted with a graphical user interface and pre-loaded with several climate change simulations. Step-by-step assignments and video tutorials help walk people through these challenging exercises and the course incorporates a special assignment discussion forum to help with technical problems and questions about the NASA GCM. There are several takeaways from our first year and a half of offering this course, which has become one of the most popular out of the twelve courses offered by the Museum. Participants report a high level of satisfaction in using EdGCM. Some report frustration at the initial steps, but overwhelmingly claim that the assignments are worth the effort. Many of the difficulties that

  5. Modeling lakes and reservoirs in the climate system

    Science.gov (United States)

    MacKay, M.D.; Neale, P.J.; Arp, C.D.; De Senerpont Domis, L. N.; Fang, X.; Gal, G.; Jo, K.D.; Kirillin, G.; Lenters, J.D.; Litchman, E.; MacIntyre, S.; Marsh, P.; Melack, J.; Mooij, W.M.; Peeters, F.; Quesada, A.; Schladow, S.G.; Schmid, M.; Spence, C.; Stokes, S.L.

    2009-01-01

    Modeling studies examining the effect of lakes on regional and global climate, as well as studies on the influence of climate variability and change on aquatic ecosystems, are surveyed. Fully coupled atmosphere-land surface-lake climate models that could be used for both of these types of study simultaneously do not presently exist, though there are many applications that would benefit from such models. It is argued here that current understanding of physical and biogeochemical processes in freshwater systems is sufficient to begin to construct such models, and a path forward is proposed. The largest impediment to fully representing lakes in the climate system lies in the handling of lakes that are too small to be explicitly resolved by the climate model, and that make up the majority of the lake-covered area at the resolutions currently used by global and regional climate models. Ongoing development within the hydrological sciences community and continual improvements in model resolution should help ameliorate this issue.

  6. The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yuying [Lawrence Livermore National Laboratory, Livermore, California; Xie, Shaocheng [Lawrence Livermore National Laboratory, Livermore, California; Klein, Stephen A. [Lawrence Livermore National Laboratory, Livermore, California; Marchand, Roger [University of Washington, Seattle, Washington; Kollias, Pavlos [Stony Brook University, Stony Brook, New York; Clothiaux, Eugene E. [The Pennsylvania State University, University Park, Pennsylvania; Lin, Wuyin [Brookhaven National Laboratory, Upton, New York; Johnson, Karen [Brookhaven National Laboratory, Upton, New York; Swales, Dustin [CIRES and NOAA/Earth System Research Laboratory, Boulder, Colorado; Bodas-Salcedo, Alejandro [Met Office Hadley Centre, Exeter, United Kingdom; Tang, Shuaiqi [Lawrence Livermore National Laboratory, Livermore, California; Haynes, John M. [Cooperative Institute for Research in the Atmosphere/Colorado State University, Fort Collins, Colorado; Collis, Scott [Argonne National Laboratory, Argonne, Illinois; Jensen, Michael [Brookhaven National Laboratory, Upton, New York; Bharadwaj, Nitin [Pacific Northwest National Laboratory, Richland, Washington; Hardin, Joseph [Pacific Northwest National Laboratory, Richland, Washington; Isom, Bradley [Pacific Northwest National Laboratory, Richland, Washington

    2018-01-01

    Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are

  7. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

    A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs

  8. Abilities and limitations in the use of regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Koeltzov, Morten Andreas Oedegaard

    2012-11-01

    In order to say something about the effect of climate change at the regional level, one takes in use regional climate models. In these models the thesis introduce regional features, which are not included in the global climate models (which are basically in climate research). Regional models can provide good and useful climate projections that add more value than the global climate models, but also introduces an uncertainty in the calculations. How should this uncertainty affect the use of regional climate models?The most common methodology for calculating potential future climate developments are based on different scenarios of possible emissions of greenhouse gases. These scenarios operates as global climate models using physical laws and calculate possible future developments. This is considered mathematical complexed and processes with limited supercomputing capacity calculates the global models for the larger scale of the climate system. To study the effects of climate change are regional details required and the regional models used therefore in a limited area of the climate system. These regional models are driven by data from the global models and refines and improves these data. Impact studies can then use the data from the regional models or data which are further processed to provide more local details using geo-statistical methods. In the preparation of the climate projections is there a minimum of 4 sources of uncertainty. This uncertainty is related to the provision of emission scenarios of greenhouse gases, uncertainties related to the use of global climate models, uncertainty related to the use of regional climate models and the uncertainty of internal variability in the climate system. This thesis discusses the use of regional climate models, and illustrates how the regional climate model adds value to climate projections, and at the same time introduce uncertainty in the calculations. It discusses in particular the importance of the choice of

  9. The Climate-Agriculture-Modeling and Decision Tool (CAMDT) for Climate Risk Management in Agriculture

    Science.gov (United States)

    Ines, A. V. M.; Han, E.; Baethgen, W.

    2017-12-01

    Advances in seasonal climate forecasts (SCFs) during the past decades have brought great potential to improve agricultural climate risk managements associated with inter-annual climate variability. In spite of popular uses of crop simulation models in addressing climate risk problems, the models cannot readily take seasonal climate predictions issued in the format of tercile probabilities of most likely rainfall categories (i.e, below-, near- and above-normal). When a skillful SCF is linked with the crop simulation models, the informative climate information can be further translated into actionable agronomic terms and thus better support strategic and tactical decisions. In other words, crop modeling connected with a given SCF allows to simulate "what-if" scenarios with different crop choices or management practices and better inform the decision makers. In this paper, we present a decision support tool, called CAMDT (Climate Agriculture Modeling and Decision Tool), which seamlessly integrates probabilistic SCFs to DSSAT-CSM-Rice model to guide decision-makers in adopting appropriate crop and agricultural water management practices for given climatic conditions. The CAMDT has a functionality to disaggregate a probabilistic SCF into daily weather realizations (either a parametric or non-parametric disaggregation method) and to run DSSAT-CSM-Rice with the disaggregated weather realizations. The convenient graphical user-interface allows easy implementation of several "what-if" scenarios for non-technical users and visualize the results of the scenario runs. In addition, the CAMDT also translates crop model outputs to economic terms once the user provides expected crop price and cost. The CAMDT is a practical tool for real-world applications, specifically for agricultural climate risk management in the Bicol region, Philippines, having a great flexibility for being adapted to other crops or regions in the world. CAMDT GitHub: https://github.com/Agro-Climate/CAMDT

  10. Spatial scale separation in regional climate modelling

    Energy Technology Data Exchange (ETDEWEB)

    Feser, F.

    2005-07-01

    In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter

  11. Impact of climate change on agro-climatic zoning of Arabica coffee in the State of Espirito Santo, Brazil = Impactos das mudanças climáticas no zoneamento agroclimatológico do café arábica no Espírito Santo

    Directory of Open Access Journals (Sweden)

    Rosembergue Bragança

    2016-06-01

    Full Text Available The aim of this study was to define, using current agro-climatic zoning, and for the next 100 years, areas of different climatic suitability for the cultivation of Arabica coffee (Coffea arabica L. in the State of Espirito Santo, Brazil. Monthly and yearly data of average air temperature and rainfall were used, taken from historical series for the period of 1976 to 2006. It was necessary to simulate the effects of temperature increments of +1 ºC, +2 ºC, +3 ºC, +4 ºC and +5 ºC, using the mean result of six models, namely: GFDL-R30 (Geophysical Fluid Dynamics Laboratory, R-30 resolution, CCSR/NIES (Center for Climate Research Studies, CSIROMk2 (Commonwealth Scientific and Industrial Research Organization GCM mark 2, CGCM2 (Canadian Global Coupled Model v 2, ECHAM4 (European Centre Hamburg Model v 4 and HadCM3 (Hadley Centre Coupled Model v 3. The results showed that currently, areas which are completely suitable represent 19.49% of the area of Espirito Santo which, with an increase of 5 °C, would decrease to 0.02%; whereas completely unsuitable areas would increase from 33.47% to 95.63%, making the cultivation of Arabica coffee unsuited to the state if the genetic and physiological characteristics, which have a tolerance limit for the average annual temperature of between 23 °C and 24 °C, are maintained. = Objetivou-se com este trabalho definir, por meio do zoneamento agroclimatológico atual e para os próximos 100 anos, áreas com diferentes aptidões climáticas para a cultura do café arábica (Coffea arabica L., no estado do Espírito Santo. Para isso, foram utilizados dados de temperatura média do ar e precipitação pluviométrica, em escala mensal e anual, de séries históricas representativas do período de 1976 a 2006. Foi necessário simular o efeito do incremento de temperatura de +1 ºC, +2 ºC, +3 ºC, +4 ºC e +5 ºC, por meio da média obtida do resultado de seis modelos, a saber: GFDL-R30 (Geophysical Fluid Dynamics

  12. Estimating daily climatologies for climate indices derived from climate model data and observations

    Science.gov (United States)

    Mahlstein, Irina; Spirig, Christoph; Liniger, Mark A; Appenzeller, Christof

    2015-01-01

    Climate indices help to describe the past, present, and the future climate. They are usually closer related to possible impacts and are therefore more illustrative to users than simple climate means. Indices are often based on daily data series and thresholds. It is shown that the percentile-based thresholds are sensitive to the method of computation, and so are the climatological daily mean and the daily standard deviation, which are used for bias corrections of daily climate model data. Sample size issues of either the observed reference period or the model data lead to uncertainties in these estimations. A large number of past ensemble seasonal forecasts, called hindcasts, is used to explore these sampling uncertainties and to compare two different approaches. Based on a perfect model approach it is shown that a fitting approach can improve substantially the estimates of daily climatologies of percentile-based thresholds over land areas, as well as the mean and the variability. These improvements are relevant for bias removal in long-range forecasts or predictions of climate indices based on percentile thresholds. But also for climate change studies, the method shows potential for use. Key Points More robust estimates of daily climate characteristics Statistical fitting approach Based on a perfect model approach PMID:26042192

  13. Pleistocene climate, phylogeny, and climate envelope models: an integrative approach to better understand species' response to climate change.

    Directory of Open Access Journals (Sweden)

    A Michelle Lawing

    Full Text Available Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models, phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species, and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr than it has been on average for the past 320 ky (2.3 m/yr.

  14. Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data

    Science.gov (United States)

    Peel, M. C.; Srikanthan, R.; McMahon, T. A.; Karoly, D. J.

    2015-04-01

    Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between global climate models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) data sets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to present a proof-of-concept approximation of within-GCM uncertainty for monthly precipitation and temperature projections and to assess the impact of within-GCM uncertainty on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. We adopt stochastic replicates of available GCM runs to approximate within-GCM uncertainty because large ensembles, hundreds of runs, for a given GCM and scenario are unavailable, other than the Climateprediction.net data set for the Hadley Centre GCM. To date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2015) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from

  15. Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States Climate Dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; Kotamarthi, V. Rao

    2018-02-01

    This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 x 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmental Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation’s performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.

  16. The role of soil moisture in land surface-atmosphere coupling: climate model sensitivity experiments over India

    Science.gov (United States)

    Williams, Charles; Turner, Andrew

    2015-04-01

    It is generally acknowledged that anthropogenic land use changes, such as a shift from forested land into irrigated agriculture, may have an impact on regional climate and, in particular, rainfall patterns in both time and space. India provides an excellent example of a country in which widespread land use change has occurred during the last century, as the country tries to meet its growing demand for food. Of primary concern for agriculture is the Indian summer monsoon (ISM), which displays considerable seasonal and subseasonal variability. Although it is evident that changing rainfall variability will have a direct impact on land surface processes (such as soil moisture variability), the reverse impact is less well understood. However, the role of soil moisture in the coupling between the land surface and atmosphere needs to be properly explored before any potential impact of changing soil moisture variability on ISM rainfall can be understood. This paper attempts to address this issue, by conducting a number of sensitivity experiments using a state-of-the-art climate model from the UK Meteorological Office Hadley Centre: HadGEM2. Several experiments are undertaken, with the only difference between them being the extent to which soil moisture is coupled to the atmosphere. Firstly, the land surface is fully coupled to the atmosphere, globally (as in standard model configurations); secondly, the land surface is entirely uncoupled from the atmosphere, again globally, with soil moisture values being prescribed on a daily basis; thirdly, the land surface is uncoupled from the atmosphere over India but fully coupled elsewhere; and lastly, vice versa (i.e. the land surface is coupled to the atmosphere over India but uncoupled elsewhere). Early results from this study suggest certain 'hotspot' regions where the impact of soil moisture coupling/uncoupling may be important, and many of these regions coincide with previous studies. Focusing on the third experiment, i

  17. Evaluation of water vapor distribution in general circulation models using satellite observations

    Science.gov (United States)

    Soden, Brian J.; Bretherton, Francis P.

    1994-01-01

    This paper presents a comparison of the water vapor distribution obtained from two general circulation models, the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM), with satellite observations of total precipitable water (TPW) from Special Sensor Microwave/Imager (SSM/I) and upper tropospheric relative humidity (UTH) from GOES. Overall, both models are successful in capturing the primary features of the observed water vapor distribution and its seasonal variation. For the ECMWF model, however, a systematic moist bias in TPW is noted over well-known stratocumulus regions in the eastern subtropical oceans. Comparison with radiosonde profiles suggests that this problem is attributable to difficulties in modeling the shallowness of the boundary layer and large vertical water vapor gradients which characterize these regions. In comparison, the CCM is more successful in capturing the low values of TPW in the stratocumulus regions, although it tends to exhibit a dry bias over the eastern half of the subtropical oceans and a corresponding moist bias in the western half. The CCM also significantly overestimates the daily variability of the moisture fields in convective regions, suggesting a problem in simulating the temporal nature of moisture transport by deep convection. Comparison of the monthly mean UTH distribution indicates generally larger discrepancies than were noted for TPW owing to the greater influence of large-scale dynamical processes in determining the distribution of UTH. In particular, the ECMWF model exhibits a distinct dry bias along the Intertropical Convergence Zone (ITCZ) and a moist bias over the subtropical descending branches of the Hadley cell, suggesting an underprediction in the strength of the Hadley circulation. The CCM, on the other hand, demonstrates greater discrepancies in UTH than are observed for the ECMWF model, but none that are as

  18. Animating climate model data

    Science.gov (United States)

    DaPonte, John S.; Sadowski, Thomas; Thomas, Paul

    2006-05-01

    This paper describes a collaborative project conducted by the Computer Science Department at Southern Connecticut State University and NASA's Goddard Institute for Space Science (GISS). Animations of output from a climate simulation math model used at GISS to predict rainfall and circulation have been produced for West Africa from June to September 2002. These early results have assisted scientists at GISS in evaluating the accuracy of the RM3 climate model when compared to similar results obtained from satellite imagery. The results presented below will be refined to better meet the needs of GISS scientists and will be expanded to cover other geographic regions for a variety of time frames.

  19. Economy-Energy-Climate Interaction. The Model Wiagem

    International Nuclear Information System (INIS)

    Kemfert, C.

    2001-09-01

    This paper presents an integrated economy-energy-climate model WIAGEM (World Integrated Assessment General Equilibrium Model) which incorporates economic, energetic and climatic modules in an integrated assessment approach. In order to evaluate market and non-market costs and benefits of climate change WIAGEM combines an economic approach with a special focus on the international energy market and integrates climate interrelations by temperature changes and sea level variations. WIAGEM bases on 25 world regions which are aggregated to 11 trading regions and 14 sectors within each region. The representation of the economic relations is based on an intertemporal general equilibrium approach and contains the international markets for oil, coal and gas. The model incorporates all greenhouse gases (GHG) which influence the potential global temperature, the sea level variation and the assessed probable impacts in terms of costs and benefits of climate change. Market and non market damages are evaluated due to the damage costs approaches of Tol (2001). Additionally, this model includes net changes in GHG emissions from sources and removals by sinks resulting from land use change and forest activities. This paper describes the model structure in detail and outlines some general results, especially the impacts of climate change. As a result, climate change impacts do matter within the next 50 years, developing regions face high economic losses in terms of welfare and GDP losses. The inclusion of sinks and other GHG changes results significantly

  20. Assessing NARCCAP climate model effects using spatial confidence regions

    Directory of Open Access Journals (Sweden)

    J. P. French

    2017-07-01

    Full Text Available We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

  1. Climate model diversity in the Northern Hemisphere Polar vortex response to climate change.

    Science.gov (United States)

    Simpson, I.; Seager, R.; Hitchcock, P.; Cohen, N.

    2017-12-01

    Global climate models vary widely in their predictions of the future of the Northern Hemisphere stratospheric polar vortex, with some showing a significant strengthening of the vortex, some showing a significant weakening and others displaying a response that is not outside of the range expected from internal variability alone. This inter-model spread in stratospheric predictions may account for some inter-model spread in tropospheric predictions with important implications for the storm tracks and regional climate change, particularly for the North Atlantic sector. Here, our current state of understanding of this model spread and its tropospheric impacts will be reviewed. Previous studies have proposed relationships between a models polar vortex response to climate change and its present day vortex climatology while others have demonstrated links between a models polar vortex response and changing wave activity coming up from the troposphere below under a warming climate. The extent to which these mechanisms can account for the spread in polar vortex changes exhibited by the Coupled Model Intercomparison Project, phase 5 models will be assessed. In addition, preliminary results from a series of idealized experiments with the Community Atmosphere Model will be presented. In these experiments, nudging of the stratospheric zonal mean state has been imposed to mimic the inter-model spread in the polar vortex response to climate change so that the downward influence of the spread in zonal mean stratospheric responses on the tropospheric circulation can be assessed within one model.

  2. Study of the global and regional climatic impacts of ENSO magnitude using SPEEDY AGCM

    KAUST Repository

    Dogar, Muhammad Mubashar; Kucharski, Fred; Azharuddin, Syed

    2017-01-01

    ENSO is considered as a strong atmospheric teleconnection that has pronounced global and regional circulation effects. It modifies global monsoon system, especially, Asian and African monsoons. Previous studies suggest that both the frequency and magnitude of ENSO events have increased over the last few decades resulting in a need to study climatic impacts of ENSO magnitude both at global and regional scales. Hence, to better understand the impact of ENSO amplitude over the tropical and extratropical regions focussing on the Asian and African domains, ENSO sensitivity experiments are conducted using ICTPAGCM (‘SPEEDY’). It is anticipated that the tropical Pacific SST forcing will be enough to produce ENSO-induced teleconnection patterns; therefore, the model is forced using NINO3.4 regressed SST anomalies over the tropical Pacific only. SPEEDY reproduces the impact of ENSO over the Pacific, North and South America and African regions very well. However, it underestimates ENSO teleconnection patterns and associated changes over South Asia, particularly in the Indian region, which suggests that the tropical Pacific SST forcing is not sufficient to represent ENSO-induced teleconnection patterns over South Asia. Therefore, SST forcing over the tropical Indian Ocean together with air–sea coupling is also required for better representation of ENSO-induced changes in these regions. Moreover, results obtained by this pacemaker experiment show that ENSO impacts are relatively stronger over the Inter-Tropical Convergence Zone (ITCZ) compared to extratropics and high latitude regions. The positive phase of ENSO causes weakening in rainfall activity over African tropical rain belt, parts of South and Southeast Asia, whereas, the La Niña phase produces more rain over these regions during the summer season. Model results further reveal that ENSO magnitude has a stronger impact over African Sahel and South Asia, especially over the Indian region because of its significant

  3. Study of the global and regional climatic impacts of ENSO magnitude using SPEEDY AGCM

    KAUST Repository

    Dogar, Muhammad Mubashar

    2017-03-09

    ENSO is considered as a strong atmospheric teleconnection that has pronounced global and regional circulation effects. It modifies global monsoon system, especially, Asian and African monsoons. Previous studies suggest that both the frequency and magnitude of ENSO events have increased over the last few decades resulting in a need to study climatic impacts of ENSO magnitude both at global and regional scales. Hence, to better understand the impact of ENSO amplitude over the tropical and extratropical regions focussing on the Asian and African domains, ENSO sensitivity experiments are conducted using ICTPAGCM (‘SPEEDY’). It is anticipated that the tropical Pacific SST forcing will be enough to produce ENSO-induced teleconnection patterns; therefore, the model is forced using NINO3.4 regressed SST anomalies over the tropical Pacific only. SPEEDY reproduces the impact of ENSO over the Pacific, North and South America and African regions very well. However, it underestimates ENSO teleconnection patterns and associated changes over South Asia, particularly in the Indian region, which suggests that the tropical Pacific SST forcing is not sufficient to represent ENSO-induced teleconnection patterns over South Asia. Therefore, SST forcing over the tropical Indian Ocean together with air–sea coupling is also required for better representation of ENSO-induced changes in these regions. Moreover, results obtained by this pacemaker experiment show that ENSO impacts are relatively stronger over the Inter-Tropical Convergence Zone (ITCZ) compared to extratropics and high latitude regions. The positive phase of ENSO causes weakening in rainfall activity over African tropical rain belt, parts of South and Southeast Asia, whereas, the La Niña phase produces more rain over these regions during the summer season. Model results further reveal that ENSO magnitude has a stronger impact over African Sahel and South Asia, especially over the Indian region because of its significant

  4. Assessment of climate change scenarios for Saudi Arabia using data from global climate models

    International Nuclear Information System (INIS)

    Husain, T.; Chowdhury, S.

    2009-01-01

    This study assesses available scientific information and data to predict changes in the climatic parameters in Saudi Arabia for understanding the impacts for mitigation and/or adaptation. Meteorological data from 26 synoptic stations were analyzed in this study. Various climatic change scenarios were reviewed and A 2 and B 2 climatic scenario families were selected. In order to assess long-term global impact, global climatic models were used to simulate changes in temperature, precipitation, relative humidity, solar radiation, and wind circulation. Using global climate model (GCM), monthly time series data was retrieved for Longitude 15 o N to 35 o N and 32.5 o E to 60 o E covering the Kingdom of Saudi Arabia from 1970 to 2100 for all grids. Taking averages of 1970 to 2003 as baseline, change in temperature, relative humidity and precipitation were estimated for the base period. A comparative evaluation was performed for predictive capabilities of these models for temperature, precipitation and relative humidity. Available meteorological data from 1970 to 2003 was used to determine trends. This paper discusses the inconsistency in these parameters for decision-making and recommends future studies by linking global climate models with a suitable regional climate modeling tool. (author)

  5. Developing climatic scenarios for pesticide fate modelling in Europe

    International Nuclear Information System (INIS)

    Blenkinsop, S.; Fowler, H.J.; Dubus, I.G.; Nolan, B.T.; Hollis, J.M.

    2008-01-01

    A climatic classification for Europe suitable for pesticide fate modelling was constructed using a 3-stage process involving the identification of key climatic variables, the extraction of the dominant modes of spatial variability in those variables and the use of k-means clustering to identify regions with similar climates. The procedure identified 16 coherent zones that reflect the variability of climate across Europe whilst maintaining a manageable number of zones for subsequent modelling studies. An analysis of basic climatic parameters for each zone demonstrates the success of the scheme in identifying distinct climatic regions. Objective criteria were used to identify one representative 26-year daily meteorological series from a European dataset for each zone. The representativeness of each series was then verified against the zonal classifications. These new FOOTPRINT climate zones provide a state-of-the-art objective classification of European climate complete with representative daily data that are suitable for use in pesticide fate modelling. - The FOOTPRINT climatic zones provide an objective climatic classification and daily climate series that may be used for the modelling of pesticide fate across Europe

  6. Assessing climate change impact by integrated hydrological modelling

    Science.gov (United States)

    Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

    2013-04-01

    Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations

  7. Predicting Future Seed Sourcing of Platycladus orientalis (L. for Future Climates Using Climate Niche Models

    Directory of Open Access Journals (Sweden)

    Xian-Ge Hu

    2017-12-01

    Full Text Available Climate niche modeling has been widely used to assess the impact of climate change on forest trees at the species level. However, geographically divergent tree populations are expected to respond differently to climate change. Considering intraspecific local adaptation in modeling species responses to climate change will thus improve the credibility and usefulness of climate niche models, particularly for genetic resources management. In this study, we used five Platycladus orientalis (L. seed zones (Northwestern; Northern; Central; Southern; and Subtropical covering the entire species range in China. A climate niche model was developed and used to project the suitable climatic conditions for each of the five seed zones for current and various future climate scenarios (Representative Concentration Pathways: RCP2.6, RCP4.5, RCP6.0, and RCP8.5. Our results indicated that the Subtropical seed zone would show consistent reduction for all climate change scenarios. The remaining seed zones, however, would experience various degrees of expansion in suitable habitat relative to their current geographic distributions. Most of the seed zones would gain suitable habitats at their northern distribution margins and higher latitudes. Thus, we recommend adjusting the current forest management strategies to mitigate the negative impacts of climate change.

  8. Development of ALARO-Climate regional climate model for a very high resolution

    Science.gov (United States)

    Skalak, Petr; Farda, Ales; Brozkova, Radmila; Masek, Jan

    2014-05-01

    ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main results of the RCM ALARO-Climate model simulations in 25 and 6.25 km resolutions on the longer time-scale (1961-1990). The model was driven by the ERA-40 re-analyses and run on the integration domain of ~ 2500 x 2500 km size covering the central Europe. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version dataset 8. Other simulated parameters (e.g., cloudiness, radiation or components of water cycle) were compared to the ERA-40 re-analyses. The validation of the first ERA-40 simulation in both, 25 km and 6.25 km resolutions, revealed significant cold biases in all seasons and overestimation of precipitation in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The differences between these simulations were small and thus revealed a robustness of the model's physical parameterization on the resolution change. The series of 25 km resolution simulations with several model adaptations was carried out to study their effect on the simulated properties of climate variables and thus possibly identify a source of major errors in the simulated climate. The current investigation suggests the main reason for biases is related to the model physic. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1

  9. Conceptual Model of Climate Change Impacts at LANL

    Energy Technology Data Exchange (ETDEWEB)

    Dewart, Jean Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-17

    Goal 9 of the LANL FY15 Site Sustainability Plan (LANL 2014a) addresses Climate Change Adaptation. As part of Goal 9, the plan reviews many of the individual programs the Laboratory has initiated over the past 20 years to address climate change impacts to LANL (e.g. Wildland Fire Management Plan, Forest Management Plan, etc.). However, at that time, LANL did not yet have a comprehensive approach to climate change adaptation. To fill this gap, the FY15 Work Plan for the LANL Long Term Strategy for Environmental Stewardship and Sustainability (LANL 2015) included a goal of (1) establishing a comprehensive conceptual model of climate change impacts at LANL and (2) establishing specific climate change indices to measure climate change and impacts at Los Alamos. Establishing a conceptual model of climate change impacts will demonstrate that the Laboratory is addressing climate change impacts in a comprehensive manner. This paper fulfills the requirement of goal 1. The establishment of specific indices of climate change at Los Alamos (goal 2), will improve our ability to determine climate change vulnerabilities and assess risk. Future work will include prioritizing risks, evaluating options/technologies/costs, and where appropriate, taking actions. To develop a comprehensive conceptual model of climate change impacts, we selected the framework provided in the National Oceanic and Atmospheric Administration (NOAA) Climate Resilience Toolkit (http://toolkit.climate.gov/).

  10. Climate and climate change sensitivity to model configuration in the Canadian RCM over North America

    Energy Technology Data Exchange (ETDEWEB)

    De Elia, Ramon [Ouranos Consortium on Regional Climate and Adaptation to Climate Change, Montreal (Canada); Centre ESCER, Univ. du Quebec a Montreal (Canada); Cote, Helene [Ouranos Consortium on Regional Climate and Adaptation to Climate Change, Montreal (Canada)

    2010-06-15

    Climate simulations performed with Regional Climate Models (RCMs) have been found to show sensitivity to parameter settings. The origin, consequences and interpretations of this sensitivity are varied, but it is generally accepted that sensitivity studies are very important for a better understanding and a more cautious manipulation of RCM results. In this work we present sensitivity experiments performed on the simulated climate produced by the Canadian Regional Climate Model (CRCM). In addition to climate sensitivity to parameter variation, we analyse the impact of the sensitivity on the climate change signal simulated by the CRCM. These studies are performed on 30-year long simulated present and future seasonal climates, and we have analysed the effect of seven kinds of configuration modifications: CRCM initial conditions, lateral boundary condition (LBC), nesting update interval, driving Global Climate Model (GCM), driving GCM member, large-scale spectral nudging, CRCM version, and domain size. Results show that large changes in both the driving model and the CRCM physics seem to be the main sources of sensitivity for the simulated climate and the climate change. Their effects dominate those of configuration issues, such as the use or not of large-scale nudging, domain size, or LBC update interval. Results suggest that in most cases, differences between simulated climates for different CRCM configurations are not transferred to the estimated climate change signal: in general, these tend to cancel each other out. (orig.)

  11. The Swedish Regional Climate Modelling Programme, SWECLIM: a review.

    Science.gov (United States)

    Rummukainen, Markku; Bergström, Sten; Persson, Gunn; Rodhe, Johan; Tjernström, Michael

    2004-06-01

    The Swedish Regional Climate Modelling Programme, SWECLIM, was a 6.5-year national research network for regional climate modeling, regional climate change projections and hydrological impact assessment and information to a wide range of stakeholders. Most of the program activities focussed on the regional climate system of Northern Europe. This led to the establishment of an advanced, coupled atmosphere-ocean-hydrology regional climate model system, a suite of regional climate change projections and progress on relevant data and process studies. These were, in turn, used for information and educational purposes, as a starting point for impact analyses on different societal sectors and provided contributions also to international climate research.

  12. Multi-scale climate modelling over Southern Africa using a variable-resolution global model

    CSIR Research Space (South Africa)

    Engelbrecht, FA

    2011-12-01

    Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

  13. Improving the representation of radiation interception and photosynthesis for climate model applications

    International Nuclear Information System (INIS)

    Mercado, Lina M.; Huntingford, Chris; Gash, John H.C.; Cox, Peter M.; Jogireddy, Venkata

    2007-01-01

    The Joint UK Land Environment Simulator (JULES) (which is based on Met Office Surface Exchange Scheme MOSES), the land surface scheme of the Hadley Centre General Circulation Models (GCM) has been improved to contain an explicit description of light interception for different canopy levels, which consequently leads to a multilayer approach to scaling from leaf to canopy level photosynthesis. We test the improved JULES model at a site in the Amazonian rainforest by comparing against measurements of vertical profiles of radiation through the canopy, eddy covariance measurements of carbon and energy fluxes, and also measurements of carbon isotopic fractionation from top canopy leaves. Overall, the new light interception formulation improves modelled photosynthetic carbon uptake compared to the standard big leaf approach used in the original JULES formulation. Additional model improvement was not significant when incorporating more realistic vertical variation of photosynthetic capacity. Even with the improved representation of radiation interception, JULES simulations of net carbon uptake underestimate eddy covariance measurements by 14%. This discrepancy can be removed by either increasing the photosynthetic capacity throughout the canopy or by explicitly including light inhibition of leaf respiration. Along with published evidence of such inhibition of leaf respiration, our study suggests this effect should be considered for inclusion in other GCMs

  14. Understanding National Models for Climate Assessments

    Science.gov (United States)

    Dave, A.; Weingartner, K.

    2017-12-01

    National-level climate assessments have been produced or are underway in a number of countries. These efforts showcase a variety of approaches to mapping climate impacts onto human and natural systems, and involve a variety of development processes, organizational structures, and intended purposes. This presentation will provide a comparative overview of national `models' for climate assessments worldwide, drawing from a geographically diverse group of nations with varying capacities to conduct such assessments. Using an illustrative sampling of assessment models, the presentation will highlight the range of assessment mandates and requirements that drive this work, methodologies employed, focal areas, and the degree to which international dimensions are included for each nation's assessment. This not only allows the U.S. National Climate Assessment to be better understood within an international context, but provides the user with an entry point into other national climate assessments around the world, enabling a better understanding of the risks and vulnerabilities societies face.

  15. Climate change projections for Greek viticulture as simulated by a regional climate model

    Science.gov (United States)

    Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos

    2017-07-01

    Viticulture represents an important economic activity for Greek agriculture. Winegrapes are cultivated in many areas covering the whole Greek territory, due to the favorable soil and climatic conditions. Given the dependence of viticulture on climate, the vitivinicultural sector is expected to be affected by possible climatic changes. The present study is set out to investigate the impacts of climatic change in Greek viticulture, using nine bioclimatic indices for the period 1981-2100. For this purpose, reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the regional climatic model Regional Climate Model Version 3 (RegCM3) are used. It was found that the examined regional climate model estimates satisfactorily these bioclimatic indices. The results of the study show that the increasing trend of temperature and drought will affect all wine-producing regions in Greece. In vineyards in mountainous regions, the impact is positive, while in islands and coastal regions, it is negative. Overall, it should be highlighted that for the first time that Greece is classified into common climatic characteristic categories, according to the international Geoviticulture Multicriteria Climatic Classification System (MCC system). According to the proposed classification, Greek viticulture regions are estimated to have similar climatic characteristics with the warmer wine-producing regions of the world up to the end of twenty-first century. Wine growers and winemakers should take the findings of the study under consideration in order to take measures for Greek wine sector adaptation and the continuation of high-quality wine production.

  16. Precipitation projections under GCMs perspective and Turkish Water Foundation (TWF) statistical downscaling model procedures

    Science.gov (United States)

    Dabanlı, İsmail; Şen, Zekai

    2018-04-01

    The statistical climate downscaling model by the Turkish Water Foundation (TWF) is further developed and applied to a set of monthly precipitation records. The model is structured by two phases as spatial (regional) and temporal downscaling of global circulation model (GCM) scenarios. The TWF model takes into consideration the regional dependence function (RDF) for spatial structure and Markov whitening process (MWP) for temporal characteristics of the records to set projections. The impact of climate change on monthly precipitations is studied by downscaling Intergovernmental Panel on Climate Change-Special Report on Emission Scenarios (IPCC-SRES) A2 and B2 emission scenarios from Max Plank Institute (EH40PYC) and Hadley Center (HadCM3). The main purposes are to explain the TWF statistical climate downscaling model procedures and to expose the validation tests, which are rewarded in same specifications as "very good" for all stations except one (Suhut) station in the Akarcay basin that is in the west central part of Turkey. Eventhough, the validation score is just a bit lower at the Suhut station, the results are "satisfactory." It is, therefore, possible to say that the TWF model has reasonably acceptable skill for highly accurate estimation regarding standard deviation ratio (SDR), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS) criteria. Based on the validated model, precipitation predictions are generated from 2011 to 2100 by using 30-year reference observation period (1981-2010). Precipitation arithmetic average and standard deviation have less than 5% error for EH40PYC and HadCM3 SRES (A2 and B2) scenarios.

  17. The international coordination of climate model validation and intercomparison

    Energy Technology Data Exchange (ETDEWEB)

    Gates, W L [Lawrence Livermore National Lab. Livermore, CA (United States). Program for Climate Model Diagnosis and Intercomparison

    1996-12-31

    Climate modeling, whereby basic physical laws are used to integrate the physics and dynamics of climate into a consistent system, plays a key role in climate research and is the medium through. Depending upon the portion(s) of the climate system being considered, climate models range from those concerned only with the equilibrium globally-averaged surface temperature to those depicting the 3-dimensional time-dependent evolution of the coupled atmosphere, ocean, sea ice and land surface. Here only the latter class of models are considered, which are commonly known as general circulation models (or GCMs). (author)

  18. The international coordination of climate model validation and intercomparison

    Energy Technology Data Exchange (ETDEWEB)

    Gates, W.L. [Lawrence Livermore National Lab. Livermore, CA (United States). Program for Climate Model Diagnosis and Intercomparison

    1995-12-31

    Climate modeling, whereby basic physical laws are used to integrate the physics and dynamics of climate into a consistent system, plays a key role in climate research and is the medium through. Depending upon the portion(s) of the climate system being considered, climate models range from those concerned only with the equilibrium globally-averaged surface temperature to those depicting the 3-dimensional time-dependent evolution of the coupled atmosphere, ocean, sea ice and land surface. Here only the latter class of models are considered, which are commonly known as general circulation models (or GCMs). (author)

  19. Modeling U.S. water resources under climate change

    Science.gov (United States)

    Blanc, Elodie; Strzepek, Kenneth; Schlosser, Adam; Jacoby, Henry; Gueneau, Arthur; Fant, Charles; Rausch, Sebastian; Reilly, John

    2014-04-01

    Water is at the center of a complex and dynamic system involving climatic, biological, hydrological, physical, and human interactions. We demonstrate a new modeling system that integrates climatic and hydrological determinants of water supply with economic and biological drivers of sectoral and regional water requirement while taking into account constraints of engineered water storage and transport systems. This modeling system is an extension of the Massachusetts Institute of Technology (MIT) Integrated Global System Model framework and is unique in its consistent treatment of factors affecting water resources and water requirements. Irrigation demand, for example, is driven by the same climatic conditions that drive evapotranspiration in natural systems and runoff, and future scenarios of water demand for power plant cooling are consistent with energy scenarios driving climate change. To illustrate the modeling system we select "wet" and "dry" patterns of precipitation for the United States from general circulation models used in the Climate Model Intercomparison Project (CMIP3). Results suggest that population and economic growth alone would increase water stress in the United States through mid-century. Climate change generally increases water stress with the largest increases in the Southwest. By identifying areas of potential stress in the absence of specific adaptation responses, the modeling system can help direct attention to water planning that might then limit use or add storage in potentially stressed regions, while illustrating how avoiding climate change through mitigation could change likely outcomes.

  20. A dynamic, climate-driven model of Rift Valley fever

    Directory of Open Access Journals (Sweden)

    Joseph Leedale

    2016-03-01

    Full Text Available Outbreaks of Rift Valley fever (RVF in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

  1. Evolution of extreme temperature events in short term climate projection for Iberian Peninsula.

    Science.gov (United States)

    Rodriguez, Alfredo; Tarquis, Ana M.; Sanchez, Enrique; Dosio, Alessandro; Ruiz-Ramos, Margarita

    2014-05-01

    Extreme events of maximum and minimum temperatures are a main hazard for agricultural production in Iberian Peninsula. For this purpose, in this study we analyze projections of their evolution that could be valid for the next decade, represented in this study by the 30-year period 2004-2034 (target period). For this purpose two kinds of data were used in this study: 1) observations from the station network of AEMET (Spanish National Meteorological Agency) for five Spanish locations, and 2) simulated data at a resolution of 50 ×50 km horizontal grid derived from the outputs of twelve Regional Climate Models (RCMs) taken from project ENSEMBLES (van der Linden and Mitchell, 2009), with a bias correction (Dosio and Paruolo, 2011; Dosio et al., 2012) regarding the observational dataset Spain02 (Herrera et al., 2012). To validate the simulated climate, the available period of observations was compared to a baseline period (1964-1994) of simulated climate for all locations. Then, to analyze the changes for the present/very next future, probability of extreme temperature events for 2004-2034 were compared to that of the baseline period. Although only minor changes are expected, small variations in variability may have a significant impact in crop performance. The objective of the work is to evaluate the utility of these short term projections for potential users, as for instance insurance companies. References Dosio A. and Paruolo P., 2011. Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate. Journal of Geophysical Research, VOL. 116,D16106, doi:10.1029/2011JD015934 Dosio A., Paruolo P. and Rojas R., 2012. Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: Analysis of the climate change signal. Journal of Geophysical Research,Volume 117, D17, doi: 0.1029/2012JD017968 Herrera et. al. (2012) Development and Analysis of a 50 year high

  2. A prognostic pollen emissions model for climate models (PECM1.0

    Directory of Open Access Journals (Sweden)

    M. C. Wozniak

    2017-11-01

    Full Text Available We develop a prognostic model called Pollen Emissions for Climate Models (PECM for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus, evergreen needleleaf trees (Cupressaceae, Pinaceae, grasses (Poaceae; C3, C4, and ragweed (Ambrosia. This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4 over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1 a taxa-specific land cover database, phenology, and emission potential, and (2 a plant functional type (PFT land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions

  3. Offshore Wind Energy Climate Projection Using UPSCALE Climate Data under the RCP8.5 Emission Scenario.

    Science.gov (United States)

    Gross, Markus; Magar, Vanesa

    2016-01-01

    In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)-weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide

  4. Offshore Wind Energy Climate Projection Using UPSCALE Climate Data under the RCP8.5 Emission Scenario.

    Directory of Open Access Journals (Sweden)

    Markus Gross

    Full Text Available In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe-weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in

  5. Offshore Wind Energy Climate Projection Using UPSCALE Climate Data under the RCP8.5 Emission Scenario

    Science.gov (United States)

    Gross, Markus; Magar, Vanesa

    2016-01-01

    In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)—weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will

  6. Overview of climate information needs for ecological effects models

    Energy Technology Data Exchange (ETDEWEB)

    Peer, R.L.

    1990-01-01

    Atmospheric scientists engaged in climate change research require a basic understanding of how ecological effects models incorporate climate. The report provides an overview of existing ecological models that might be used to model climate change effects on vegetation. Some agricultural models and statistical methods are also discussed. The weather input data requirements, weather simulation methods, and other model characteristics relevant to climate change research are described for a selected number of models. The ecological models are classified as biome, ecosystem, or tree models; the ecosystem models are further subdivided into species dynamics or process models. In general, ecological modelers have had to rely on readily available meteorological data such as temperature and rainfall. Although models are becoming more sophisticated in their treatment of weather and require more kinds of data (such as wind, solar radiation, or potential evapotranspiration), modelers are still hampered by a lack of data for many applications. Future directions of ecological effects models and the climate variables that will be required by the models are discussed.

  7. Multi-wheat-model ensemble responses to interannual climatic variability

    DEFF Research Database (Denmark)

    Ruane, A C; Hudson, N I; Asseng, S

    2016-01-01

    We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we...... evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...

  8. Climate change impact on available water resources obtained using multiple global climate and hydrology models

    Directory of Open Access Journals (Sweden)

    S. Hagemann

    2013-05-01

    Full Text Available Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three and hydrological models (eight were used to systematically assess the hydrological response to climate change and project the future state of global water resources. This multi-model ensemble allows us to investigate how the hydrology models contribute to the uncertainty in projected hydrological changes compared to the climate models. Due to their systematic biases, GCM outputs cannot be used directly in hydrological impact studies, so a statistical bias correction has been applied. The results show a large spread in projected changes in water resources within the climate–hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change, and that the spread resulting from the choice of the hydrology model is larger than the spread originating from the climate models over many areas. But there are also areas showing a robust change signal, such as at high latitudes and in some midlatitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence in this ensemble mean signal. In many catchments an increase of available water resources is expected but there are some severe decreases in Central and Southern Europe, the Middle East, the Mississippi River basin, southern Africa, southern China and south-eastern Australia.

  9. Modeling key processes causing climate change and variability

    Energy Technology Data Exchange (ETDEWEB)

    Henriksson, S.

    2013-09-01

    Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are (1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, (2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, (3) identifying a power law shape S(f) {proportional_to} f-{alpha} for the spectrum of global mean temperature with {alpha} {approx} 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, (4) separating aerosol properties and climate effects in India by season and location (5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, (6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and (7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy

  10. The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

    Science.gov (United States)

    Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J

    2013-10-28

    Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.

  11. Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

    Science.gov (United States)

    Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

    2016-01-01

    We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

  12. Modelling interactions of carbon dioxide, forests, and climate

    International Nuclear Information System (INIS)

    Luxmoore, R.J.; Baldocchi, D.D.

    1994-01-01

    Atmospheric carbon dioxide is rising and forests and climate is changing exclamation point This combination of fact and premise may be evaluated at a range of temporal and spatial scales with the aid of computer simulators describing the interrelationships between forest vegetation, litter and soil characteristics, and appropriate meteorological variables. Some insights on the effects of climate on the transfers of carbon and the converse effect of carbon transfer on climate are discussed as a basis for assessing the significance of feedbacks between vegetation and climate under conditions of rising atmospheric carbon dioxide. Three main classes of forest models are reviewed. These are physiologically-based models, forest succession simulators based on the JABOWA model, and ecosystem-carbon budget models that use compartment transfer rates with empirically estimated coefficients. Some regression modeling approaches are also outlined. Energy budget models applied to forests and grasslands are also reviewed. This review presents examples of forest models; a comprehensive discussion of all available models is not undertaken

  13. Reconstructing Climate Change: The Model-Data Ping-Pong

    Science.gov (United States)

    Stocker, T. F.

    2017-12-01

    When Cesare Emiliani, the father of paleoceanography, made the first attempts at a quantitative reconstruction of Pleistocene climate change in the early 1950s, climate models were not yet conceived. The understanding of paleoceanographic records was therefore limited, and scientists had to resort to plausibility arguments to interpret their data. With the advent of coupled climate models in the early 1970s, for the first time hypotheses about climate processes and climate change could be tested in a dynamically consistent framework. However, only a model hierarchy can cope with the long time scales and the multi-component physical-biogeochemical Earth System. There are many examples how climate models have inspired the interpretation of paleoclimate data on the one hand, and conversely, how data have questioned long-held concepts and models. In this lecture I critically revisit a few examples of this model-data ping-pong, such as the bipolar seesaw, the mid-Holocene greenhouse gas increase, millennial and rapid CO2 changes reconstructed from polar ice cores, and the interpretation of novel paleoceanographic tracers. These examples also highlight many of the still unsolved questions and provide guidance for future research. The combination of high-resolution paleoceanographic data and modeling has never been more relevant than today. It will be the key for an appropriate risk assessment of impacts on the Earth System that are already underway in the Anthropocene.

  14. A climate robust integrated modelling framework for regional impact assessment of climate change

    Science.gov (United States)

    Janssen, Gijs; Bakker, Alexander; van Ek, Remco; Groot, Annemarie; Kroes, Joop; Kuiper, Marijn; Schipper, Peter; van Walsum, Paul; Wamelink, Wieger; Mol, Janet

    2013-04-01

    Decision making towards climate proofing the water management of regional catchments can benefit greatly from the availability of a climate robust integrated modelling framework, capable of a consistent assessment of climate change impacts on the various interests present in the catchments. In the Netherlands, much effort has been devoted to developing state-of-the-art regional dynamic groundwater models with a very high spatial resolution (25x25 m2). Still, these models are not completely satisfactory to decision makers because the modelling concepts do not take into account feedbacks between meteorology, vegetation/crop growth, and hydrology. This introduces uncertainties in forecasting the effects of climate change on groundwater, surface water, agricultural yields, and development of groundwater dependent terrestrial ecosystems. These uncertainties add to the uncertainties about the predictions on climate change itself. In order to create an integrated, climate robust modelling framework, we coupled existing model codes on hydrology, agriculture and nature that are currently in use at the different research institutes in the Netherlands. The modelling framework consists of the model codes MODFLOW (groundwater flow), MetaSWAP (vadose zone), WOFOST (crop growth), SMART2-SUMO2 (soil-vegetation) and NTM3 (nature valuation). MODFLOW, MetaSWAP and WOFOST are coupled online (i.e. exchange information on time step basis). Thus, changes in meteorology and CO2-concentrations affect crop growth and feedbacks between crop growth, vadose zone water movement and groundwater recharge are accounted for. The model chain WOFOST-MetaSWAP-MODFLOW generates hydrological input for the ecological prediction model combination SMART2-SUMO2-NTM3. The modelling framework was used to support the regional water management decision making process in the 267 km2 Baakse Beek-Veengoot catchment in the east of the Netherlands. Computations were performed for regionalized 30-year climate change

  15. Hydrological Modeling in Northern Tunisia with Regional Climate Model Outputs: Performance Evaluation and Bias-Correction in Present Climate Conditions

    Directory of Open Access Journals (Sweden)

    Asma Foughali

    2015-07-01

    Full Text Available This work aims to evaluate the performance of a hydrological balance model in a watershed located in northern Tunisia (wadi Sejnane, 378 km2 in present climate conditions using input variables provided by four regional climate models. A modified version (MBBH of the lumped and single layer surface model BBH (Bucket with Bottom Hole model, in which pedo-transfer parameters estimated using watershed physiographic characteristics are introduced is adopted to simulate the water balance components. Only two parameters representing respectively the water retention capacity of the soil and the vegetation resistance to evapotranspiration are calibrated using rainfall-runoff data. The evaluation criterions for the MBBH model calibration are: relative bias, mean square error and the ratio of mean actual evapotranspiration to mean potential evapotranspiration. Daily air temperature, rainfall and runoff observations are available from 1960 to 1984. The period 1960–1971 is selected for calibration while the period 1972–1984 is chosen for validation. Air temperature and precipitation series are provided by four regional climate models (DMI, ARP, SMH and ICT from the European program ENSEMBLES, forced by two global climate models (GCM: ECHAM and ARPEGE. The regional climate model outputs (precipitation and air temperature are compared to the observations in terms of statistical distribution. The analysis was performed at the seasonal scale for precipitation. We found out that RCM precipitation must be corrected before being introduced as MBBH inputs. Thus, a non-parametric quantile-quantile bias correction method together with a dry day correction is employed. Finally, simulated runoff generated using corrected precipitation from the regional climate model SMH is found the most acceptable by comparison with runoff simulated using observed precipitation data, to reproduce the temporal variability of mean monthly runoff. The SMH model is the most accurate to

  16. Using idealized snow forcing to test teleconnections with the Indian summer monsoon in the Hadley Centre GCM

    Energy Technology Data Exchange (ETDEWEB)

    Turner, A.G. [University of Reading, NCAS-Climate, Walker Institute for Climate System Research, Department of Meteorology, Reading (United Kingdom); Slingo, J.M. [University of Reading, NCAS-Climate, Walker Institute for Climate System Research, Department of Meteorology, Reading (United Kingdom); Met Office, Exeter (United Kingdom)

    2011-05-15

    Anomalous heavy snow during winter or spring has long been regarded as a possible precursor of deficient Indian monsoon rainfall during the subsequent summer. However previous work in this field is inconclusive, in terms of the mechanism that communicates snow anomalies to the monsoon summer, and even the region from which snow has the most impact. In this study we explore these issues in coupled and atmosphere-only versions of the Hadley Centre model. A 1050-year control integration of the HadCM3 coupled model, which well represents the seasonal cycle of snow cover over the Eurasian continent, is analysed and shows evidence for weakened monsoons being preceded by strong snow forcing (in the absence of ENSO) over either the Himalaya/Tibetan Plateau or north/west Eurasia regions. However, empirical orthogonal function (EOF) analysis of springtime interannual variability in snow depth shows the leading mode to have opposite signs between these two regions, suggesting that competing mechanisms may be possible. To determine the dominant region, ensemble integrations are carried out using HadAM3, the atmospheric component of HadCM3, and a variety of anomalous snow forcing initial conditions obtained from the control integration of the coupled model. Forcings are applied during spring in separate experiments over the Himalaya/Tibetan Plateau and north/west Eurasia regions, in conjunction with climatological SSTs in order to avoid the direct effects of ENSO. With the aid of idealized forcing conditions in sensitivity tests, we demonstrate that forcing from the Himalaya region is dominant in this model via a Blanford-type mechanism involving reduced surface sensible heat and longwave fluxes, reduced heating of the troposphere over the Tibetan Plateau and consequently a reduced meridional tropospheric temperature gradient which weakens the monsoon during early summer. Snow albedo is shown to be key to the mechanism, explaining around 50% of the perturbation in sensible

  17. GLOBAL CLIMATE MODEL:A COMPREHENSIVE TOOL IN CLIMATE CHANGE IMPACT STUDIES

    Directory of Open Access Journals (Sweden)

    Dharmaveer Singh

    2015-01-01

    Full Text Available There is growing concern, how and to what extent future changes in climate will affect human society and natural environments. Continuous emissions of Green House Gasses (GHGs at or above current rates will cause further warming. This, in turn, may modify global climate system during 21st century that very likely would have larger impacts than those observed during 20th century. At present, Global Climate Models (GCMs are only the most reliable tools available for studying behaviour of the climate system. This paper presents a comprehensive review of GCMs including their development and applications in climate change impacts studies. Following a discussion of the limitations of GCMs at regional and local scales, different approaches of downscaling are discussed in detail.

  18. The treatment of climate science in Integrated Assessment Modelling: integration of climate step function response in an energy system integrated assessment model.

    Science.gov (United States)

    Dessens, Olivier

    2016-04-01

    Integrated Assessment Models (IAMs) are used as crucial inputs to policy-making on climate change. These models simulate aspect of the economy and climate system to deliver future projections and to explore the impact of mitigation and adaptation policies. The IAMs' climate representation is extremely important as it can have great influence on future political action. The step-function-response is a simple climate model recently developed by the UK Met Office and is an alternate method of estimating the climate response to an emission trajectory directly from global climate model step simulations. Good et al., (2013) have formulated a method of reconstructing general circulation models (GCMs) climate response to emission trajectories through an idealized experiment. This method is called the "step-response approach" after and is based on an idealized abrupt CO2 step experiment results. TIAM-UCL is a technology-rich model that belongs to the family of, partial-equilibrium, bottom-up models, developed at University College London to represent a wide spectrum of energy systems in 16 regions of the globe (Anandarajah et al. 2011). The model uses optimisation functions to obtain cost-efficient solutions, in meeting an exogenously defined set of energy-service demands, given certain technological and environmental constraints. Furthermore, it employs linear programming techniques making the step function representation of the climate change response adapted to the model mathematical formulation. For the first time, we have introduced the "step-response approach" method developed at the UK Met Office in an IAM, the TIAM-UCL energy system, and we investigate the main consequences of this modification on the results of the model in term of climate and energy system responses. The main advantage of this approach (apart from the low computational cost it entails) is that its results are directly traceable to the GCM involved and closely connected to well-known methods of

  19. Increase of carbon cycle feedback with climate sensitivity: results from a coupled climate and carbon cycle model

    International Nuclear Information System (INIS)

    Govindasamy, B.; Thompson, S.; Mirin, A.; Wickett, M.; Caldeira, K.; Delire, C.

    2005-01-01

    Coupled climate and carbon cycle modelling studies have shown that the feedback between global warming and the carbon cycle, in particular the terrestrial carbon cycle, could accelerate climate change and result in greater warming. In this paper we investigate the sensitivity of this feedback for year 2100 global warming in the range of 0 to 8 K. Differing climate sensitivities to increased CO 2 content are imposed on the carbon cycle models for the same emissions. Emissions from the SRES A2 scenario are used. We use a fully coupled climate and carbon cycle model, the INtegrated Climate and CArbon model (INCCA), the NCAR/DOE Parallel Climate Model coupled to the IBIS terrestrial biosphere model and a modified OCMIP ocean biogeochemistry model. In our integrated model, for scenarios with year 2100 global warming increasing from 0 to 8 K, land uptake decreases from 47% to 29% of total CO 2 emissions. Due to competing effects, ocean uptake (16%) shows almost no change at all. Atmospheric CO 2 concentration increases are 48% higher in the run with 8 K global climate warming than in the case with no warming. Our results indicate that carbon cycle amplification of climate warming will be greater if there is higher climate sensitivity to increased atmospheric CO 2 content; the carbon cycle feedback factor increases from 1.13 to 1.48 when global warming increases from 3.2 to 8 K

  20. Application of CarboSOIL model to predict the effects of climate change on soil organic carbon stocks in agro-silvo-pastoral Mediterranean management systems

    Science.gov (United States)

    Muñoz-Rojas, Miriam; Doro, Luca; Ledda, Luigi; Francaviglia, Rosa

    2014-05-01

    ñoz-Rojas et al., 2012) or olive groves (Lozano-García and Parras-Alcántara, 2013). The local climate is warm temperate with dry and hot summers, with a mean annual rainfall of 623 mm (range 367-811 mm) and mean annual temperature of 15.0?C (13.8-16.4?C). Climate change scenarios were generated from the baseline climate with two Global Climate Models: GISS (Goddard Institute of Space Studies, USA), and HadCM3 (Met Office, Hadley Centre, UK), for two of the Intergovernmental Panel on Climate Change (IPCC) emission scenarios (A2 and B2). Three time horizons were chosen for climate change projections: 2020, mean climate change for the period 2010-2039; 2050 for the period 2040-2069; and 2080 for the period 2070-2099, providing respectively a very close, an intermediate, and a fully realized climate change scenario. The agreement of model predictions with the measured values of soil organic carbon stocks was tested using the correlation coefficient R2, the root mean square error RMSE and the modelling efficiency EF. For a good model performance, RMSE should have approximately the same order of magnitude of the standard deviation, while EF should be positive and close to 1. With reference to the three soil depths (0-25, 25-50, 50-75 cm), R2, RMSE and EF are in the range 0.76-0.99, 5.07-8.42, and 0.63-0.98 respectively. CarboSOIL predictions are fully acceptable since the linear regression coefficients are always significant at p

  1. The Effect of No Agricultural Productivity Growth on Future Land Use and Climate through Biogeophysical Mechanisms

    Science.gov (United States)

    Davies-Barnard, T.; Valdes, P. J.; Singarayer, J. S.; Jones, C.

    2012-12-01

    Future land use and the consequent land cover change will have a significant impact on future climate through biogeophysical (albedo, surface roughness and latent heat transfer, etc.) as well as biogeochemical (greenhouse gas emissions etc.) mechanisms. One of the major determinants of the extent of land use induced land cover change is the agricultural productivity growth within the socio-economic models used for developing the RCP scenarios. There are considerable uncertainties in the size of agricultural productivity under climate change, as yields are projected to vary spatially in signal and strength. Previous climate modeling work has considered the impacts to the carbon cycle of different levels of agricultural productivity growth, but has failed to consider the biogeophysical effects of the land use induced land cover change on climate. Here we examine the climate impacts of the assumption of agricultural productivity growth and business as usual land use. The effects are considered through the biogeophysical land use induced land cover change, using the Hadley Centre climate model HadGEM2. The model simulations use the set biogeochemical climate forcing of the RCP 4.5 scenario, but the biogeophysical land use change specification is altered over a 100 year simulation. Simulations are run with combinations of no land use change; standard RCP 4.5 land use change; business as usual land use change; and zero agricultural productivity growth. The key effect of no agricultural productivity growth is that more cropland is required to feed the same population, necessitating cropland expansion. The expansion of cropland and consequent deforestation increases the albedo and gives an extensive cooling effect in the northern hemisphere (up to 2°C). Differences in global mean temperature between the zero agricultural productivity growth with business as usual land use change specified run and the standard RCP 4.5 run are -0.2°C by 2040 and -0.7°C by 2100. There is

  2. Future Flows Climate: an ensemble of 1-km climate change projections for hydrological application in Great Britain

    Directory of Open Access Journals (Sweden)

    C. Prudhomme

    2012-11-01

    Full Text Available The dataset Future Flows Climate was developed as part of the project ''Future Flows and Groundwater Levels'' to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications, and to enable climate change uncertainty and climate variability to be accounted for in the assessment of their possible impacts on the environment.

    Future Flows Climate is derived from the Hadley Centre's ensemble projection HadRM3-PPE that is part of the basis of UKCP09 and includes projections in available precipitation (water available to hydrological processes after snow and ice storages have been accounted for and potential evapotranspiration. It corresponds to an 11-member ensemble of transient projections from January 1950 to December 2098, each a single realisation from a different variant of HadRM3. Data are provided on a 1-km grid over the HadRM3 land areas at a daily (available precipitation and monthly (PE time step as netCDF files.

    Because systematic biases in temperature and precipitation were found between HadRM3-PPE and gridded temperature and precipitation observations for the 1962–1991 period, a monthly bias correction procedure was undertaken, based on a linear correction for temperature and a quantile-mapping correction (using the gamma distribution for precipitation followed by a spatial downscaling. Available precipitation was derived from the bias-corrected precipitation and temperature time series using a simple elevation-dependant snow-melt model. Potential evapotranspiration time series were calculated for each month using the FAO-56 Penman-Monteith equations and bias-corrected temperature, cloud cover, relative humidity and wind speed from HadRM3-PPE along with latitude of the grid and the day of the year.

    Future Flows Climate is freely available for non-commercial use under certain licensing conditions. It is the

  3. Agricultural climate impacts assessment for economic modeling and decision support

    Science.gov (United States)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  4. Regional Impacts of Climate Change on the Amazon Rainforest: 2080-2100

    Science.gov (United States)

    Cook, K. H.; Vizy, E. K.

    2006-12-01

    A regional climate model with resolution of 60 km is coupled with a potential vegetation model to simulate future climate over South America. The following steps are taken to effectively communicate the results across disciplines and to make them useful to the policy and impacts communities: the simulation is aimed at a particular time period (2081-2100), the climate change results are translated into changes in vegetation distribution, and the results are reported on regional space scales relative to political boundaries. In addition, the model validation in clearly presented to provide perspective on uncertainty for the prognosis. The model reproduces today's climate and vegetation over tropical and subtropical South America accurately. In simulations of the future, the model is forced by the IPCC's A2 scenario of future emissions, which assumes that CO2 emissions continue to grow at essentially today's rate throughout the 21st century, reaching 757 ppmv averaged over 2081-2100. The model is constrained on its lateral boundaries by atmospheric conditions simulated by a global climate model, applied as anomalies to present day conditions, and predicted changes in sea surface temperatures. The extent of the Amazon rainforest is reduced by about 70 per cent in the simulation, and the shrubland (caatinga) vegetation of Brazil's Nordeste region spreads westward and southward well into the continental interior. Bolivia, Paraguay, and Argentina lose all of their rainforest vegetation, and Brazil and Peru lose most of it. The surviving rain forest is concentrated near the equator. Columbia's rainforest survives largely intact and, along the northern coast, Venezuela and French Guiana suffer relatively small reductions. The loss in Guyana and Surinam is 30-50 per cent. Much of the rainforest in the central Amazon north of about 15S is replaced by savanna vegetation, but in southern Bolivia, northern Paraguay, and southern Brazil, grasslands take the place of the

  5. Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

    Science.gov (United States)

    Delgado, Juan; Moreno-Navas, Juan; Pulido, Antoine; García-Lafuente, Juan; Calero Quesada, Maria C.; García, Rodrigo

    2017-04-01

    Extreme climatic events, such as heat waves and severe storms are predicted to increase in frequency and magnitude as a consequence of global warming but their socio-ecological effects are poorly understood, particularly in estuarine ecosystems. The Guadalquivir Estuary has been anthropologically modified several times, the original salt marshes have been transformed to grow rice and cotton and approximately one-fourth of the total surface of the estuary is now part of two protected areas, one of them is a UNESCO, MAB Biosphere Reserve. The climatic events are most likely to affect Europe in forthcoming decades and a further understanding how these climatic disturbances drive abrupt changes in the Guadalquivir estuary is needed. A barotropic model has been developed to study how severe storm events affects the estuary by conducting paired control and climate-events simulations. The changes in the local wind and atmospheric pressure conditions in the estuary have been studied in detail and several scenarios are obtained by running the model under control and real storm conditions. The model output has been validated with in situ water elevation and good agreement between modelled and real measurements have been obtained. Our preliminary results show that the model demonstrated the capability describe of the tide-surge levels in the estuary, opening the possibility to study the interaction between climatic events and the port operations and food production activities. The barotropic hydrodynamic model provide spatially explicit information on the key variables governing the tide dynamics of estuarine areas under severe climatic scenarios . The numerical model will be a powerful tool in future climate change mitigation and adaptation programs in a complex socio-ecological system.

  6. [Lake eutrophication modeling in considering climatic factors change: a review].

    Science.gov (United States)

    Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

    2012-11-01

    Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

  7. Evaluating the performance and utility of regional climate models

    DEFF Research Database (Denmark)

    Christensen, Jens H.; Carter, Timothy R.; Rummukainen, Markku

    2007-01-01

    This special issue of Climatic Change contains a series of research articles documenting co-ordinated work carried out within a 3-year European Union project 'Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects' (PRUDENCE). The main objective...... of the PRUDENCE project was to provide high resolution climate change scenarios for Europe at the end of the twenty-first century by means of dynamical downscaling (regional climate modelling) of global climate simulations. The first part of the issue comprises seven overarching PRUDENCE papers on: (1) the design...... of the model simulations and analyses of climate model performance, (2 and 3) evaluation and intercomparison of simulated climate changes, (4 and 5) specialised analyses of impacts on water resources and on other sectors including agriculture, ecosystems, energy, and transport, (6) investigation of extreme...

  8. A review on regional convection permitting climate modeling

    Science.gov (United States)

    van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin

    2016-04-01

    With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing climate model COSMO-CLM is frequently applied for CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using CPMs to study climate change it is necessary that these deficiencies

  9. Reconstructing the climate states of the Late Pleistocene with the MIROC climate model

    Science.gov (United States)

    Chan, Wing-Le; Abe-Ouchi, Ayako; O'ishi, Ryouta; Takahashi, Kunio

    2014-05-01

    The Late Pleistocene was a period which lasted from the Eemian interglacial period to the start of the warm Holocene and was characterized mostly by widespread glacial ice. It was also a period which saw modern humans spread throughout the world and other species of the same genus, like the Neanderthals, become extinct. Various hypotheses have been put forward to explain the extinction of Neanderthals, about 30,000 years ago. Among these is one which involves changes in past climate and the inability of Neanderthals to adapt to such changes. The last traces of Neanderthals coincide with the end of Marine Isotope Stage 3 (MIS3) which was marked by large fluctuations in temperature and so-called Heinrich events, as suggested by geochemical records from ice cores. It is thought that melting sea ice or icebergs originating from the Laurentide ice sheet led to a large discharge of freshwater into the North Atlantic Ocean during the Heinrich events and severely weakened the Atlantic meridional overturning circulation, with important environmental ramifications across parts of Europe such as sharp decreases in temperature and reduction in forest cover. In order to assess the effects of past climate change on past hominin migration and on the extinction of certain species, it is first important to have a good understanding of the past climate itself. In this study, we have used three variants of MIROC (The Model for Interdisciplinary Research on Climate), a global climate model, for a time slice experiment within the Late Pleistocene: two mid-resolution models (an atmosphere model and a coupled atmosphere-ocean model) and a high-resolution atmosphere model. To obtain a fuller picture, we also look at a cool stadial state as obtained from a 'freshwater hosing' coupled-model experiment, designed to mimic the effects of freshwater discharge in the North Atlantic. We next use the sea surface temperature response from this experiment to drive the atmosphere models. We discuss

  10. Climate Change Modelling and Its Roles to Chinese Crops Yield

    Institute of Scientific and Technical Information of China (English)

    JU Hui; LIN Er-da; Tim Wheeler; Andrew Challinor; JIANG Shuai

    2013-01-01

    Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation. Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability. Understanding the interactions between climate change and agricultural production is essential for society stable development of China. The first mission is to fully understand how to predict future climate and link it with agriculture production system. In this paper, recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches. The methods for climate change scenarios construction are introduced. The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized. The study found that simulated productions of grain crop inherit uncertainty from using different climate models, emission scenarios and the crops simulation models. Moreover, studies have different spatial resolutions, and methods for general circulation model (GCM) downscaling which increase the uncertainty for regional impacts assessment. However, the magnitude of change in crop production due to climate change (at 700 ppm CO2 eq correct) appears within ±10%for China in these assessments. In most literatures, the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase. Finally, the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops. The uncertainty for crop yield projection is associated with climate change scenarios, CO2 fertilization effects and adaptation options. Therefore, more studies on the fields such as free air CO2 enrichment experiment and practical adaptations implemented need to be carried out.

  11. Practice and philosophy of climate model tuning across six US modeling centers

    Directory of Open Access Journals (Sweden)

    G. A. Schmidt

    2017-09-01

    Full Text Available Model calibration (or tuning is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.

  12. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Overview and Description of Models, Simulations and Climate Diagnostics

    Science.gov (United States)

    Lamarque, J.-F.; Shindell, D. T.; Naik, V.; Plummer, D.; Josse, B.; Righi, M.; Rumbold, S. T.; Schulz, M.; Skeie, R. B.; Strode, S.; hide

    2013-01-01

    The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.

  13. Climate change decision-making: Model & parameter uncertainties explored

    Energy Technology Data Exchange (ETDEWEB)

    Dowlatabadi, H.; Kandlikar, M.; Linville, C.

    1995-12-31

    A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.

  14. Improved Analysis of Earth System Models and Observations using Simple Climate Models

    Science.gov (United States)

    Nadiga, B. T.; Urban, N. M.

    2016-12-01

    Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using

  15. A Practical Philosophy of Complex Climate Modelling

    Science.gov (United States)

    Schmidt, Gavin A.; Sherwood, Steven

    2014-01-01

    We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.

  16. Future Projections of Air Temperature and Precipitation for the CORDEX-MENA Domain by Using RegCM4.3.5

    Science.gov (United States)

    Ozturk, Tugba; Turp, M. Tufan; Türkeş, Murat; Kurnaz, M. Levent

    2015-04-01

    In this study, the projected changes for the periods of 2016 - 2035, 2046 - 2065, and 2081 - 2100 in the seasonal averages of air temperature and precipitation variables with respect to the reference period of 1981 - 2000 were examined for the Middle East and North Africa region. In this context, Regional Climate Model (RegCM4.3.5) of ICTP (International Centre for Theoretical Physics) was run by using two different global climate models. MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology and HadGEM2 of the Met Office Hadley Centre were dynamically downscaled to 50 km for the CORDEX-MENA domain. The projections were realized according to the RCP4.5 and the RCP8.5 emission scenarios of the IPCC (Intergovernmental Panel of Climate Change).

  17. Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

    Science.gov (United States)

    Tselioudis, G.; Bauer, M.; Rossow, W.

    2009-04-01

    Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

  18. Effect of model resolution on a regional climate model simulation over southeast Australia

    KAUST Repository

    Evans, J. P.; McCabe, Matthew

    2013-01-01

    Dynamically downscaling climate projections from global climate models (GCMs) for use in impacts and adaptation research has become a common practice in recent years. In this study, the CSIRO Mk3.5 GCM is downscaled using the Weather Research and Forecasting (WRF) regional climate model (RCM) to medium (50 km) and high (10 km) resolution over southeast Australia. The influence of model resolution on the present-day (1985 to 2009) modelled regional climate and projected future (2075 to 2099) changes are examined for both mean climate and extreme precipitation characteristics. Increasing model resolution tended to improve the simulation of present day climate, with larger improvements in areas affected by mountains and coastlines. Examination of circumstances under which increasing the resolution decreased performance revealed an error in the GCM circulation, the effects of which had been masked by the coarse GCM topography. Resolution modifications to projected changes were largest in regions with strong topographic and coastline influences, and can be large enough to change the sign of the climate change projected by the GCM. Known physical mechanisms for these changes included orographic uplift and low-level blocking of air-masses caused by mountains. In terms of precipitation extremes, the GCM projects increases in extremes even when the projected change in the mean was a decrease: but this was not always true for the higher resolution models. Thus, while the higher resolution RCM climate projections often concur with the GCM projections, there are times and places where they differ significantly due to their better representation of physical processes. It should also be noted that the model resolution can modify precipitation characteristics beyond just its mean value.

  19. Effect of model resolution on a regional climate model simulation over southeast Australia

    KAUST Repository

    Evans, J. P.

    2013-03-26

    Dynamically downscaling climate projections from global climate models (GCMs) for use in impacts and adaptation research has become a common practice in recent years. In this study, the CSIRO Mk3.5 GCM is downscaled using the Weather Research and Forecasting (WRF) regional climate model (RCM) to medium (50 km) and high (10 km) resolution over southeast Australia. The influence of model resolution on the present-day (1985 to 2009) modelled regional climate and projected future (2075 to 2099) changes are examined for both mean climate and extreme precipitation characteristics. Increasing model resolution tended to improve the simulation of present day climate, with larger improvements in areas affected by mountains and coastlines. Examination of circumstances under which increasing the resolution decreased performance revealed an error in the GCM circulation, the effects of which had been masked by the coarse GCM topography. Resolution modifications to projected changes were largest in regions with strong topographic and coastline influences, and can be large enough to change the sign of the climate change projected by the GCM. Known physical mechanisms for these changes included orographic uplift and low-level blocking of air-masses caused by mountains. In terms of precipitation extremes, the GCM projects increases in extremes even when the projected change in the mean was a decrease: but this was not always true for the higher resolution models. Thus, while the higher resolution RCM climate projections often concur with the GCM projections, there are times and places where they differ significantly due to their better representation of physical processes. It should also be noted that the model resolution can modify precipitation characteristics beyond just its mean value.

  20. Global climate change model natural climate variation: Paleoclimate data base, probabilities and astronomic predictors

    Energy Technology Data Exchange (ETDEWEB)

    Kukla, G.; Gavin, J. [Columbia Univ., Palisades, NY (United States). Lamont-Doherty Geological Observatory

    1994-05-01

    This report was prepared at the Lamont-Doherty Geological Observatory of Columbia University at Palisades, New York, under subcontract to Pacific Northwest Laboratory it is a part of a larger project of global climate studies which supports site characterization work required for the selection of a potential high-level nuclear waste repository and forms part of the Performance Assessment Scientific Support (PASS) Program at PNL. The work under the PASS Program is currently focusing on the proposed site at Yucca Mountain, Nevada, and is under the overall direction of the Yucca Mountain Project Office US Department of Energy, Las Vegas, Nevada. The final results of the PNL project will provide input to global atmospheric models designed to test specific climate scenarios which will be used in the site specific modeling work of others. The primary purpose of the data bases compiled and of the astronomic predictive models is to aid in the estimation of the probabilities of future climate states. The results will be used by two other teams working on the global climate study under contract to PNL. They are located at and the University of Maine in Orono, Maine, and the Applied Research Corporation in College Station, Texas. This report presents the results of the third year`s work on the global climate change models and the data bases describing past climates.

  1. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    To ensure optimal management and sustainable strategies for water resources, infrastructures, food production and ecosystems there is a need for an improved understanding of feedback and interaction mechanisms between the atmosphere and the land surface. This is especially true in light of expected...... global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate...... and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface...

  2. A characteristics of East Asian climate using high-resolution regional climate model

    Science.gov (United States)

    Yhang, Y.

    2013-12-01

    Climate research, particularly application studies for water, agriculture, forestry, fishery and energy management require fine scale multi-decadal information of meteorological, oceanographic and land states. Unfortunately, spatially and temporally homogeneous multi-decadal observations of these variables in high horizontal resolution are non-existent. Some long term surface records of temperature and precipitation exist, but the number of observation is very limited and the measurements are often contaminated by changes in instrumentation over time. Some climatologically important variables, such as soil moisture, surface evaporation, and radiation are not even measured over most of East Asia. Reanalysis is one approach to obtaining long term homogeneous analysis of needed variables. However, the horizontal resolution of global reanalysis is of the order of 100 to 200 km, too coarse for many application studies. Regional climate models (RCMs) are able to provide valuable regional finescale information, especially in regions where the climate variables are strongly regulated by the underlying topography and the surface heterogeneity. In this study, we will provide accurately downscaled regional climate over East Asia using the Global/Regional Integrated Model system [GRIMs; Hong et al. 2013]. A mixed layer model is embedded within the GRIMs in order to improve air-sea interaction. A detailed description of the characteristics of the East Asian summer and winter climate will be presented through the high-resolution numerical simulations. The increase in horizontal resolution is expected to provide the high-quality data that can be used in various application areas such as hydrology or environmental model forcing.

  3. OpenClimateGIS - A Web Service Providing Climate Model Data in Commonly Used Geospatial Formats

    Science.gov (United States)

    Erickson, T. A.; Koziol, B. W.; Rood, R. B.

    2011-12-01

    The goal of the OpenClimateGIS project is to make climate model datasets readily available in commonly used, modern geospatial formats used by GIS software, browser-based mapping tools, and virtual globes.The climate modeling community typically stores climate data in multidimensional gridded formats capable of efficiently storing large volumes of data (such as netCDF, grib) while the geospatial community typically uses flexible vector and raster formats that are capable of storing small volumes of data (relative to the multidimensional gridded formats). OpenClimateGIS seeks to address this difference in data formats by clipping climate data to user-specified vector geometries (i.e. areas of interest) and translating the gridded data on-the-fly into multiple vector formats. The OpenClimateGIS system does not store climate data archives locally, but rather works in conjunction with external climate archives that expose climate data via the OPeNDAP protocol. OpenClimateGIS provides a RESTful API web service for accessing climate data resources via HTTP, allowing a wide range of applications to access the climate data.The OpenClimateGIS system has been developed using open source development practices and the source code is publicly available. The project integrates libraries from several other open source projects (including Django, PostGIS, numpy, Shapely, and netcdf4-python).OpenClimateGIS development is supported by a grant from NOAA's Climate Program Office.

  4. Terrestrial biogeochemistry in the community climate system model (CCSM)

    International Nuclear Information System (INIS)

    Hoffman, Forrest; Fung, Inez; Randerson, Jim; Thornton, Peter; Foley, Jon; Covey, Curtis; John, Jasmin; Levis, Samuel; Post, W Mac; Vertenstein, Mariana; Stoeckli, Reto; Running, Steve; Heinsch, Faith Ann; Erickson, David; Drake, John

    2006-01-01

    Described here is the formulation of the CASA ' biogeochemistry model of Fung, et al., which has recently been coupled to the Community Land Model Version 3 (CLM3) and the Community Climate System Model Version 3 (CCSM3). This model is presently being used for Coupled Climate/Carbon Cycle Model Intercomparison Project (C 4 MIP) Phase 1 experiments. In addition, CASA ' is one of three models - in addition to CN (Thornton, et al.) and IBIS (Thompson, et al.) - that are being run within CCSM to investigate their suitability for use in climate change predictions in a future version of CCSM. All of these biogeochemistry experiments are being performed on the Computational Climate Science End Station (Dr. Warren Washington, Principle Investigator) at the National Center for Computational Sciences at Oak Ridge National Laboratory

  5. The Urgent Need for Improved Climate Models and Predictions

    Science.gov (United States)

    Goddard, Lisa; Baethgen, Walter; Kirtman, Ben; Meehl, Gerald

    2009-09-01

    An investment over the next 10 years of the order of US$2 billion for developing improved climate models was recommended in a report (http://wcrp.wmo.int/documents/WCRP_WorldModellingSummit_Jan2009.pdf) from the May 2008 World Modelling Summit for Climate Prediction, held in Reading, United Kingdom, and presented by the World Climate Research Programme. The report indicated that “climate models will, as in the past, play an important, and perhaps central, role in guiding the trillion dollar decisions that the peoples, governments and industries of the world will be making to cope with the consequences of changing climate.” If trillions of dollars are going to be invested in making decisions related to climate impacts, an investment of $2 billion, which is less than 0.1% of that amount, to provide better climate information seems prudent. One example of investment in adaptation is the World Bank's Climate Investment Fund, which has drawn contributions of more than $6 billion for work on clean technologies and adaptation efforts in nine pilot countries and two pilot regions. This is just the beginning of expenditures on adaptation efforts by the World Bank and other mechanisms, focusing on only a small fraction of the nations of the world and primarily aimed at anticipated anthropogenic climate change. Moreover, decisions are being made now, all around the world—by individuals, companies, and governments—that affect people and their livelihoods today, not just 50 or more years in the future. Climate risk management, whether related to projects of the scope of the World Bank's or to the planning and decisions of municipalities, will be best guided by meaningful climate information derived from observations of the past and model predictions of the future.

  6. Simulated pre-industrial climate in Bergen Climate Model (version 2: model description and large-scale circulation features

    Directory of Open Access Journals (Sweden)

    O. H. Otterå

    2009-11-01

    Full Text Available The Bergen Climate Model (BCM is a fully-coupled atmosphere-ocean-sea-ice model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate. Here, a pre-industrial multi-century simulation with an updated version of BCM is described and compared to observational data. The model is run without any form of flux adjustments and is stable for several centuries. The simulated climate reproduces the general large-scale circulation in the atmosphere reasonably well, except for a positive bias in the high latitude sea level pressure distribution. Also, by introducing an updated turbulence scheme in the atmosphere model a persistent cold bias has been eliminated. For the ocean part, the model drifts in sea surface temperatures and salinities are considerably reduced compared to earlier versions of BCM. Improved conservation properties in the ocean model have contributed to this. Furthermore, by choosing a reference pressure at 2000 m and including thermobaric effects in the ocean model, a more realistic meridional overturning circulation is simulated in the Atlantic Ocean. The simulated sea-ice extent in the Northern Hemisphere is in general agreement with observational data except for summer where the extent is somewhat underestimated. In the Southern Hemisphere, large negative biases are found in the simulated sea-ice extent. This is partly related to problems with the mixed layer parametrization, causing the mixed layer in the Southern Ocean to be too deep, which in turn makes it hard to maintain a realistic sea-ice cover here. However, despite some problematic issues, the pre-industrial control simulation presented here should still be appropriate for climate change studies requiring multi-century simulations.

  7. Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

    Science.gov (United States)

    Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

    2018-04-01

    This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent

  8. Flexible global ocean-atmosphere-land system model. A modeling tool for the climate change research community

    International Nuclear Information System (INIS)

    Zhou, Tianjun; Yu, Yongqiang; Liu, Yimin; Wang, Bin

    2014-01-01

    First book available on systematic evaluations of the performance of the global climate model FGOALS. Covers the whole field, ranging from the development to the applications of this climate system model. Provide an outlook for the future development of the FGOALS model system. Offers brief introduction about how to run FGOALS. Coupled climate system models are of central importance for climate studies. A new model known as FGOALS (the Flexible Global Ocean-Atmosphere-Land System model), has been developed by the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP, CAS), a first-tier national geophysical laboratory. It serves as a powerful tool, both for deepening our understanding of fundamental mechanisms of the climate system and for making decadal prediction and scenario projections of future climate change. ''Flexible Global Ocean-Atmosphere-Land System Model: A Modeling Tool for the Climate Change Research Community'' is the first book to offer systematic evaluations of this model's performance. It is comprehensive in scope, covering both developmental and application-oriented aspects of this climate system model. It also provides an outlook of future development of FGOALS and offers an overview of how to employ the model. It represents a valuable reference work for researchers and professionals working within the related areas of climate variability and change.

  9. Three-pattern decomposition of global atmospheric circulation: part I—decomposition model and theorems

    Science.gov (United States)

    Hu, Shujuan; Chou, Jifan; Cheng, Jianbo

    2018-04-01

    In order to study the interactions between the atmospheric circulations at the middle-high and low latitudes from the global perspective, the authors proposed the mathematical definition of three-pattern circulations, i.e., horizontal, meridional and zonal circulations with which the actual atmospheric circulation is expanded. This novel decomposition method is proved to accurately describe the actual atmospheric circulation dynamics. The authors used the NCEP/NCAR reanalysis data to calculate the climate characteristics of those three-pattern circulations, and found that the decomposition model agreed with the observed results. Further dynamical analysis indicates that the decomposition model is more accurate to capture the major features of global three dimensional atmospheric motions, compared to the traditional definitions of Rossby wave, Hadley circulation and Walker circulation. The decomposition model for the first time realized the decomposition of global atmospheric circulation using three orthogonal circulations within the horizontal, meridional and zonal planes, offering new opportunities to study the large-scale interactions between the middle-high latitudes and low latitudes circulations.

  10. Integrated climate and hydrology modelling - Coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model

    Energy Technology Data Exchange (ETDEWEB)

    Dahl Larsen, M.A. [Technical Univ. of Denmark. DTU Management Engineering, DTU Risoe Campus, Roskilde (Denmark)

    2013-10-15

    To ensure optimal management and sustainable strategies for water resources, infrastructures, food production and ecosystems there is a need for an improved understanding of feedback and interaction mechanisms between the atmosphere and the land surface. This is especially true in light of expected global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate and hydrology have used each model component in an offline mode where the models are run in sequential steps and one model serves as a boundary condition or data input source to the other. Within recent years a new field of research has emerged where efforts have been made to dynamically couple existing climate and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface. The modelling tool consists of a fully dynamic two-way coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model. The expected gain is twofold. Firstly, HIRHAM utilizes the land surface component of the combined MIKE SHE/SWET hydrology and land surface model (LSM), which is superior to the LSM in HIRHAM. A wider range of processes are included at the land surface, subsurface flow is distributed in three dimensions and the temporal and spatial resolution is higher. Secondly, the feedback mechanisms of e.g. soil moisture and precipitation between the two models are included. The preparation of the HIRHAM and MIKE SHE models for the coupled study revealed several findings. The performance of HIRHAM was highly affected by the domain size, domain

  11. Stress testing hydrologic models using bottom-up climate change assessment

    Science.gov (United States)

    Stephens, C.; Johnson, F.; Marshall, L. A.

    2017-12-01

    Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.

  12. Terrestrial biogeochemistry in the community climate system model (CCSM)

    Energy Technology Data Exchange (ETDEWEB)

    Hoffman, Forrest [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6016 (United States); Fung, Inez [University of California at Berkeley, Berkeley, California (United States); Randerson, Jim [University of California at Irvine, Irvine, California (United States); Thornton, Peter [National Center for Atmospheric Research, Boulder, Colorado (United States); Foley, Jon [University of Wisconsin at Madison, Madison, Wisconsin (United States); Covey, Curtis [Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, California (United States); John, Jasmin [University of California at Berkeley, Berkeley, California (United States); Levis, Samuel [National Center for Atmospheric Research, Boulder, Colorado (United States); Post, W Mac [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6016 (United States); Vertenstein, Mariana [National Center for Atmospheric Research, Boulder, Colorado (United States); Stoeckli, Reto [Colorado State University, Ft. Collins, Colorado (United States); Running, Steve [University of Montana, Missoula, Montana (United States); Heinsch, Faith Ann [University of Montana, Missoula, Montana (United States); Erickson, David [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6016 (United States); Drake, John [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6016 (United States)

    2006-09-15

    Described here is the formulation of the CASA{sup '} biogeochemistry model of Fung, et al., which has recently been coupled to the Community Land Model Version 3 (CLM3) and the Community Climate System Model Version 3 (CCSM3). This model is presently being used for Coupled Climate/Carbon Cycle Model Intercomparison Project (C{sup 4}MIP) Phase 1 experiments. In addition, CASA{sup '} is one of three models - in addition to CN (Thornton, et al.) and IBIS (Thompson, et al.) - that are being run within CCSM to investigate their suitability for use in climate change predictions in a future version of CCSM. All of these biogeochemistry experiments are being performed on the Computational Climate Science End Station (Dr. Warren Washington, Principle Investigator) at the National Center for Computational Sciences at Oak Ridge National Laboratory.

  13. Improving poverty and inequality modelling in climate research

    Science.gov (United States)

    Rao, Narasimha D.; van Ruijven, Bas J.; Riahi, Keywan; Bosetti, Valentina

    2017-12-01

    As climate change progresses, the risk of adverse impacts on vulnerable populations is growing. As governments seek increased and drastic action, policymakers are likely to seek quantification of climate-change impacts and the consequences of mitigation policies on these populations. Current models used in climate research have a limited ability to represent the poor and vulnerable, or the different dimensions along which they face these risks. Best practices need to be adopted more widely, and new model features that incorporate social heterogeneity and different policy mechanisms need to be developed. Increased collaboration between modellers, economists, and other social scientists could aid these developments.

  14. Quercus pollen season dynamics in the Iberian peninsula: response to meteorological parameters and possible consequences of climate change.

    Science.gov (United States)

    Garcia-Mozo, Herminia; Galan, Carmen; Jato, Victoria; Belmonte, Jordina; de la Guardia, Consuelo; Fernandez, Delia; Gutierrez, Montserrat; Aira, M; Roure, Joan; Ruiz, Luis; Trigo, Mar; Dominguez-Vilches, Eugenio

    2006-01-01

    The main characteristics of the Quercus pollination season were studied in 14 different localities of the Iberian Peninsula from 1992-2004. Results show that Quercus flowering season has tended to start earlier in recent years, probably due to the increased temperatures in the pre-flowering period, detected at study sites over the second half of the 20th century. A Growing Degree Days forecasting model was used, together with future meteorological data forecast using the Regional Climate Model developed by the Hadley Meteorological Centre, in order to determine the expected advance in the start of Quercus pollination in future years. At each study site, airborne pollen curves presented a similar pattern in all study years, with different peaks over the season attributable in many cases to the presence of several species. High pollen concentrations were recorded, particularly at Mediterranean sites. This study also proposes forecasting models to predict both daily pollen values and annual pollen emission. All models were externally validated using data for 2001 and 2004, with acceptable results. Finally, the impact of the highly-likely climate change on Iberian Quercus pollen concentration values was studied by applying RCM meteorological data for different future years, 2025, 2050, 2075 and 2099. Results indicate that under a doubled CO(2) scenario at the end of the 21st century Quercus pollination season could start on average one month earlier and airborne pollen concentrations will increase by 50 % with respect to current levels, with higher values in Mediterranean inland areas.

  15. The Software Architecture of Global Climate Models

    Science.gov (United States)

    Alexander, K. A.; Easterbrook, S. M.

    2011-12-01

    It has become common to compare and contrast the output of multiple global climate models (GCMs), such as in the Climate Model Intercomparison Project Phase 5 (CMIP5). However, intercomparisons of the software architecture of GCMs are almost nonexistent. In this qualitative study of seven GCMs from Canada, the United States, and Europe, we attempt to fill this gap in research. We describe the various representations of the climate system as computer programs, and account for architectural differences between models. Most GCMs now practice component-based software engineering, where Earth system components (such as the atmosphere or land surface) are present as highly encapsulated sub-models. This architecture facilitates a mix-and-match approach to climate modelling that allows for convenient sharing of model components between institutions, but it also leads to difficulty when choosing where to draw the lines between systems that are not encapsulated in the real world, such as sea ice. We also examine different styles of couplers in GCMs, which manage interaction and data flow between components. Finally, we pay particular attention to the varying levels of complexity in GCMs, both between and within models. Many GCMs have some components that are significantly more complex than others, a phenomenon which can be explained by the respective institution's research goals as well as the origin of the model components. In conclusion, although some features of software architecture have been adopted by every GCM we examined, other features show a wide range of different design choices and strategies. These architectural differences may provide new insights into variability and spread between models.

  16. Modeling maize response to climate modification in Hungary

    OpenAIRE

    Angela Anda

    2006-01-01

    Modeling provides a tool for a better understanding of the modified plant behaviour that results from various climatic differences. The present study provides new information about the physiological processes in maize (Zea mays L.) in response to climatic changes. The aim was to help local farmers adapt to climate modifications in Hungary and mitigate the future consequences of these changes. A simulation model was applied to estimate the possible feedback on crop properties and elevated CO2....

  17. A probabilistic model of ecosystem response to climate change

    International Nuclear Information System (INIS)

    Shevliakova, E.; Dowlatabadi, H.

    1994-01-01

    Anthropogenic activities are leading to rapid changes in land cover and emissions of greenhouse gases into the atmosphere. These changes can bring about climate change typified by average global temperatures rising by 1--5 C over the next century. Climate change of this magnitude is likely to alter the distribution of terrestrial ecosystems on a large scale. Options available for dealing with such change are abatement of emissions, adaptation, and geoengineering. The integrated assessment of climate change demands that frameworks be developed where all the elements of the climate problem are present (from economic activity to climate change and its impacts on market and non-market goods and services). Integrated climate assessment requires multiple impact metrics and multi-attribute utility functions to simulate the response of different key actors/decision-makers to the actual physical impacts (rather than a dollar value) of the climate-damage vs. policy-cost debate. This necessitates direct modeling of ecosystem impacts of climate change. The authors have developed a probabilistic model of ecosystem response to global change. This model differs from previous efforts in that it is statistically estimated using actual ecosystem and climate data yielding a joint multivariate probability of prevalence for each ecosystem, given climatic conditions. The authors expect this approach to permit simulation of inertia and competition which have, so far, been absent in transfer models of continental-scale ecosystem response to global change. Thus, although the probability of one ecotype will dominate others at a given point, others would have the possibility of establishing an early foothold

  18. Oscillations in a simple climate-vegetation model

    Science.gov (United States)

    Rombouts, J.; Ghil, M.

    2015-05-01

    We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation off the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various timescales is discussed.

  19. Flexible global ocean-atmosphere-land system model. A modeling tool for the climate change research community

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Tianjun; Yu, Yongqiang; Liu, Yimin; Wang, Bin (eds.) [Chinese Academy of Sciences, Beijing, (China). Inst. of Atmospheric Physics

    2014-04-01

    First book available on systematic evaluations of the performance of the global climate model FGOALS. Covers the whole field, ranging from the development to the applications of this climate system model. Provide an outlook for the future development of the FGOALS model system. Offers brief introduction about how to run FGOALS. Coupled climate system models are of central importance for climate studies. A new model known as FGOALS (the Flexible Global Ocean-Atmosphere-Land System model), has been developed by the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP, CAS), a first-tier national geophysical laboratory. It serves as a powerful tool, both for deepening our understanding of fundamental mechanisms of the climate system and for making decadal prediction and scenario projections of future climate change. ''Flexible Global Ocean-Atmosphere-Land System Model: A Modeling Tool for the Climate Change Research Community'' is the first book to offer systematic evaluations of this model's performance. It is comprehensive in scope, covering both developmental and application-oriented aspects of this climate system model. It also provides an outlook of future development of FGOALS and offers an overview of how to employ the model. It represents a valuable reference work for researchers and professionals working within the related areas of climate variability and change.

  20. Modelling rainfall erosion resulting from climate change

    Science.gov (United States)

    Kinnell, Peter

    2016-04-01

    It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

  1. Reduced connection between the East Asian Summer Monsoon and Southern Hemisphere Circulation on interannual timescales under intense global warming

    Science.gov (United States)

    Yu, Tianlei; Guo, Pinwen; Cheng, Jun; Hu, Aixue; Lin, Pengfei; Yu, Yongqiang

    2018-03-01

    Previous studies show a close relationship between the East Asian Summer Monsoon (EASM) and Southern Hemisphere (SH) circulation on interannual timescales. In this study, we investigate whether this close relationship will change under intensive greenhouse-gas effect by analyzing simulations under two different climate background states: preindustrial era and Representative Concentration Pathway (RCP) 8.5 stabilization from the Community Climate System Model Version 4 (CCSM4). Results show a significantly reduced relationship under stabilized RCP8.5 climate state, such a less correlated EASM with the sea level pressure in the southern Indian Ocean and the SH branch of local Hadley Cell. Further analysis suggests that the collapse of the Atlantic Meridional Overturning Circulation (AMOC) due to this warming leads to a less vigorous northward meridional heat transport, a decreased intertropical temperature contrast in boreal summer, which produces a weaker cross-equatorial Hadley Cell in the monsoonal region and a reduced Interhemispheric Mass Exchange (IME). Since the monsoonal IME acts as a bridge connecting EASM and SH circulation, the reduced IME weakens this connection. By performing freshwater hosing experiment using the Flexible Global Ocean—Atmosphere—Land System model, Grid-point Version 2 (FGOALS-g2), we show a weakened relationship between the EASM and SH circulation as in CCSM4 when AMOC collapses. Our results suggest that a substantially weakened AMOC is the main driver leading to the EASM, which is less affected by SH circulation in the future warmer climate.

  2. Regionalization of climate model results for the North Sea

    Energy Technology Data Exchange (ETDEWEB)

    Kauker, F.

    1999-07-01

    A dynamical downscaling is presented that allows an estimation of potential effects of climate change on the North Sea. Therefore, the ocean general circulation model OPYC is adapted for application on a shelf by adding a lateral boundary formulation and a tide model. In this set-up the model is forced, first, with data from the ECMWF reanalysis for model validation and the study of the natural variability, and, second, with data from climate change experiments to estimate the effects of climate change on the North Sea. (orig.)

  3. Towards a regional climate model coupled to a comprehensive hydrological model

    Science.gov (United States)

    Rasmussen, S. H.; Drews, M.; Christensen, J. H.; Butts, M. B.; Jensen, K. H.; Refsgaard, J.; Hydrological ModellingAssessing Climate Change Impacts At Different Scales (Hyacints)

    2010-12-01

    When planing new ground water abstractions wells, building areas, roads or other land use activities information about expected future groundwater table location for the lifetime of the construction may be critical. The life time of an abstraction well can be expected to be more than 50 years, while if for buildings may be up to 100 years or more. The construction of an abstraction well is expensive and it is important to know if clean groundwater is available for its expected life time. The future groundwater table is depending on the future climate. With climate change the hydrology is expected to change as well. Traditionally, this assessment has been done by driving hydrological models with output from a climate model. In this way feedback between the groundwater hydrology and the climate is neglected. Neglecting this feedback can lead to imprecise or wrong results. The goal of this work is to couple the regional climate model HIRHAM (Christensen et al. 2006) to the hydrological model MIKE SHE (Graham and Butts, 2006). The coupling exploits the new OpenMI technology that provides a standardized interface to define, describe and transfer data on a time step basis between software components that run simultaneously (Gregersen et al., 2007). HIRHAM runs on a UNIX platform whereas MIKE SHE and OpenMI are under WINDOWS. Therefore the first critical task has been to develop an effective communication link between the platforms. The first step towards assessing the coupled models performance are addressed by looking at simulated land-surface atmosphere feedback through variables such as evapotranspiration, sensible heat flux and soil moisture content. Christensen, O.B., Drews, M., Christensen, J.H., Dethloff, K., Ketelsen, K., Hebestadt, I. and Rinke, A. (2006) The HIRHAM Regional Climate Model. Version 5; DMI Scientific Report 0617. Danish Meteorological Institute. Graham, D.N. and Butts, M.B. (2005) Flexible, integrated watershed modelling with MIKE SHE, In

  4. A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus).

    Science.gov (United States)

    Shabani, Farzin; Shafapour Tehrany, Mahyat; Solhjouy-Fard, Samaneh; Kumar, Lalit

    2018-01-01

    Aedes albopictus , the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus ? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according

  5. A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus

    Directory of Open Access Journals (Sweden)

    Farzin Shabani

    2018-03-01

    Full Text Available Aedes albopictus, the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus? Our study used current Ae. albopictus distribution data to develop two independent models: (i regions with suitable non-climatic factors, and (ii regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF, together with six geographical conditioning factors (raster data layers, to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs, Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically

  6. Mechanism of ENSO influence on the South Asian monsoon rainfall in global model simulations

    Science.gov (United States)

    Joshi, Sneh; Kar, Sarat C.

    2018-02-01

    Coupled ocean atmosphere global climate models are increasingly being used for seasonal scale simulation of the South Asian monsoon. In these models, sea surface temperatures (SSTs) evolve as coupled air-sea interaction process. However, sensitivity experiments with various SST forcing can only be done in an atmosphere-only model. In this study, the Global Forecast System (GFS) model at T126 horizontal resolution has been used to examine the mechanism of El Niño-Southern Oscillation (ENSO) forcing on the monsoon circulation and rainfall. The model has been integrated (ensemble) with observed, climatological and ENSO SST forcing to document the mechanism on how the South Asian monsoon responds to basin-wide SST variations in the Indian and Pacific Oceans. The model simulations indicate that the internal variability gets modulated by the SSTs with warming in the Pacific enhancing the ensemble spread over the monsoon region as compared to cooling conditions. Anomalous easterly wind anomalies cover the Indian region both at 850 and 200 hPa levels during El Niño years. The locations and intensity of Walker and Hadley circulations are altered due to ENSO SST forcing. These lead to reduction of monsoon rainfall over most parts of India during El Niño events compared to La Niña conditions. However, internally generated variability is a major source of uncertainty in the model-simulated climate.

  7. Production functions for climate policy modeling. An empirical analysis

    International Nuclear Information System (INIS)

    Van der Werf, Edwin

    2008-01-01

    Quantitative models for climate policy modeling differ in the production structure used and in the sizes of the elasticities of substitution. The empirical foundation for both is generally lacking. This paper estimates the parameters of 2-level CES production functions with capital, labour and energy as inputs, and is the first to systematically compare all nesting structures. Using industry-level data from 12 OECD countries, we find that the nesting structure where capital and labour are combined first, fits the data best, but for most countries and industries we cannot reject that all three inputs can be put into one single nest. These two nesting structures are used by most climate models. However, while several climate policy models use a Cobb-Douglas function for (part of the) production function, we reject elasticities equal to one, in favour of considerably smaller values. Finally we find evidence for factor-specific technological change. With lower elasticities and with factor-specific technological change, some climate policy models may find a bigger effect of endogenous technological change on mitigating the costs of climate policy. (author)

  8. Climate models with delay differential equations.

    Science.gov (United States)

    Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M

    2017-11-01

    A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

  9. Climate models with delay differential equations

    Science.gov (United States)

    Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M.

    2017-11-01

    A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

  10. Computer experiments with a coarse-grid hydrodynamic climate model

    International Nuclear Information System (INIS)

    Stenchikov, G.L.

    1990-01-01

    A climate model is developed on the basis of the two-level Mintz-Arakawa general circulation model of the atmosphere and a bulk model of the upper layer of the ocean. A detailed model of the spectral transport of shortwave and longwave radiation is used to investigate the radiative effects of greenhouse gases. The radiative fluxes are calculated at the boundaries of five layers, each with a pressure thickness of about 200 mb. The results of the climate sensitivity calculations for mean-annual and perpetual seasonal regimes are discussed. The CCAS (Computer Center of the Academy of Sciences) climate model is used to investigate the climatic effects of anthropogenic changes of the optical properties of the atmosphere due to increasing CO 2 content and aerosol pollution, and to calculate the sensitivity to changes of land surface albedo and humidity

  11. Current climate and climate change over India as simulated by the Canadian Regional Climate Model

    Science.gov (United States)

    Alexandru, Adelina; Sushama, Laxmi

    2015-08-01

    The performance of the fifth generation of the Canadian Regional Climate Model (CRCM5) in reproducing the main climatic characteristics over India during the southwest (SW)-, post- and pre-monsoon seasons are presented in this article. To assess the performance of CRCM5, European Centre for Medium- Range Weather Forecasts (ECMWF) Re- Analysis (ERA- 40) and Interim re-analysis (ERA-Interim) driven CRCM5 simulation is compared against independent observations and reanalysis data for the 1971-2000 period. Projected changes for two future periods, 2041-2070 and 2071-2100, with respect to the 1971-2000 current period are assessed based on two transient climate change simulations of CRCM5 spanning the 1950-2100 period. These two simulations are driven by the Canadian Earth System Model version 2 (CanESM2) and the Max Planck Institute for Meteorology's Earth System Low Resolution Model (MPI-ESM-LR), respectively. The boundary forcing errors associated with errors in the driving global climate models are also studied by comparing the 1971-2000 period of the CanESM2 and MPI-ESM-LR driven simulations with that of the CRCM5 simulation driven by ERA-40/ERA-Interim. Results show that CRCM5 driven by ERA-40/ERA-Interim is in general able to capture well the temporal and spatial patterns of 2 m-temperature, precipitation, wind, sea level pressure, total runoff and soil moisture over India in comparison with available reanalysis and observations. However, some noticeable differences between the model and observational data were found during the SW-monsoon season within the domain of integration. CRCM5 driven by ERA-40/ERA-Interim is 1-2 °C colder than CRU observations and generates more precipitation over the Western Ghats and central regions of India, and not enough in the northern and north-eastern parts of India and along the Konkan west coast in comparison with the observed precipitation. The monsoon onset seems to be relatively well captured over the southwestern coast of

  12. Comparative Climates of the Trappist-1 Planetary System: Results from a Simple Climate-vegetation Model

    Energy Technology Data Exchange (ETDEWEB)

    Alberti, Tommaso; Carbone, Vincenzo; Lepreti, Fabio [Dipartimento di Fisica, Università della Calabria, Ponte P. Bucci, Cubo 31C, I-87036, Rende (CS) (Italy); Vecchio, Antonio, E-mail: tommaso.alberti@unical.it, E-mail: tommasoalberti89@gmail.com [LESIA—Observatoire de Paris, PSL Research University, 5 place Jules Janssen, F-92190, Meudon (France)

    2017-07-20

    The recent discovery of the planetary system hosted by the ultracool dwarf star TRAPPIST-1 could open new paths for investigations of the planetary climates of Earth-sized exoplanets, their atmospheres, and their possible habitability. In this paper, we use a simple climate-vegetation energy-balance model to study the climate of the seven TRAPPIST-1 planets and the climate dependence on various factors: the global albedo, the fraction of vegetation that could cover their surfaces, and the different greenhouse conditions. The model allows us to investigate whether liquid water could be maintained on the planetary surfaces (i.e., by defining a “surface water zone (SWZ)”) in different planetary conditions, with or without the presence of a greenhouse effect. It is shown that planet TRAPPIST-1d seems to be the most stable from an Earth-like perspective, since it resides in the SWZ for a wide range of reasonable values of the model parameters. Moreover, according to the model, outer planets (f, g, and h) cannot host liquid water on their surfaces, even with Earth-like conditions, entering a snowball state. Although very simple, the model allows us to extract the main features of the TRAPPIST-1 planetary climates.

  13. Comparative Climates of the Trappist-1 Planetary System: Results from a Simple Climate-vegetation Model

    International Nuclear Information System (INIS)

    Alberti, Tommaso; Carbone, Vincenzo; Lepreti, Fabio; Vecchio, Antonio

    2017-01-01

    The recent discovery of the planetary system hosted by the ultracool dwarf star TRAPPIST-1 could open new paths for investigations of the planetary climates of Earth-sized exoplanets, their atmospheres, and their possible habitability. In this paper, we use a simple climate-vegetation energy-balance model to study the climate of the seven TRAPPIST-1 planets and the climate dependence on various factors: the global albedo, the fraction of vegetation that could cover their surfaces, and the different greenhouse conditions. The model allows us to investigate whether liquid water could be maintained on the planetary surfaces (i.e., by defining a “surface water zone (SWZ)”) in different planetary conditions, with or without the presence of a greenhouse effect. It is shown that planet TRAPPIST-1d seems to be the most stable from an Earth-like perspective, since it resides in the SWZ for a wide range of reasonable values of the model parameters. Moreover, according to the model, outer planets (f, g, and h) cannot host liquid water on their surfaces, even with Earth-like conditions, entering a snowball state. Although very simple, the model allows us to extract the main features of the TRAPPIST-1 planetary climates.

  14. Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

    Science.gov (United States)

    Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

    2002-12-01

    The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).

  15. Identifying misbehaving models using baseline climate variance

    Science.gov (United States)

    Schultz, Colin

    2011-06-01

    The majority of projections made using general circulation models (GCMs) are conducted to help tease out the effects on a region, or on the climate system as a whole, of changing climate dynamics. Sun et al., however, used model runs from 20 different coupled atmosphere-ocean GCMs to try to understand a different aspect of climate projections: how bias correction, model selection, and other statistical techniques might affect the estimated outcomes. As a case study, the authors focused on predicting the potential change in precipitation for the Murray-Darling Basin (MDB), a 1-million- square- kilometer area in southeastern Australia that suffered a recent decade of drought that left many wondering about the potential impacts of climate change on this important agricultural region. The authors first compared the precipitation predictions made by the models with 107 years of observations, and they then made bias corrections to adjust the model projections to have the same statistical properties as the observations. They found that while the spread of the projected values was reduced, the average precipitation projection for the end of the 21st century barely changed. Further, the authors determined that interannual variations in precipitation for the MDB could be explained by random chance, where the precipitation in a given year was independent of that in previous years.

  16. Climate change hotspots in the CMIP5 global climate model ensemble.

    Science.gov (United States)

    Diffenbaugh, Noah S; Giorgi, Filippo

    2012-01-10

    We use a statistical metric of multi-dimensional climate change to quantify the emergence of global climate change hotspots in the CMIP5 climate model ensemble. Our hotspot metric extends previous work through the inclusion of extreme seasonal temperature and precipitation, which exert critical influence on climate change impacts. The results identify areas of the Amazon, the Sahel and tropical West Africa, Indonesia, and the Tibetan Plateau as persistent regional climate change hotspots throughout the 21 st century of the RCP8.5 and RCP4.5 forcing pathways. In addition, areas of southern Africa, the Mediterranean, the Arctic, and Central America/western North America also emerge as prominent regional climate change hotspots in response to intermediate and high levels of forcing. Comparisons of different periods of the two forcing pathways suggest that the pattern of aggregate change is fairly robust to the level of global warming below approximately 2°C of global warming (relative to the late-20 th -century baseline), but not at the higher levels of global warming that occur in the late-21 st -century period of the RCP8.5 pathway, with areas of southern Africa, the Mediterranean, and the Arctic exhibiting particular intensification of relative aggregate climate change in response to high levels of forcing. Although specific impacts will clearly be shaped by the interaction of climate change with human and biological vulnerabilities, our identification of climate change hotspots can help to inform mitigation and adaptation decisions by quantifying the rate, magnitude and causes of the aggregate climate response in different parts of the world.

  17. Ecological Assimilation of Land and Climate Observations - the EALCO model

    Science.gov (United States)

    Wang, S.; Zhang, Y.; Trishchenko, A.

    2004-05-01

    Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net

  18. Simulated climate change during the last 1,000 years: comparing the ECHO-G general circulation model with the MAGICC simple climate model

    Energy Technology Data Exchange (ETDEWEB)

    Osborn, Timothy J.; Briffa, Keith R. [University of East Anglia, Climatic Research Unit, School of Environmental Sciences, Norwich (United Kingdom); Raper, Sarah C.B. [University of East Anglia, Climatic Research Unit, School of Environmental Sciences, Norwich (United Kingdom); Manchester Metropolitan University, Dalton Research Institute, Manchester (United Kingdom)

    2006-08-15

    An intercomparison of eight climate simulations, each driven with estimated natural and anthropogenic forcings for the last millennium, indicates that the so-called ''Erik'' simulation of the ECHO-G coupled ocean-atmosphere climate model exhibits atypical behaviour. The ECHO-G simulation has a much stronger cooling trend from 1000 to 1700 and a higher rate of warming since 1800 than the other simulations, with the result that the overall amplitude of millennial-scale temperature variations in the ECHO-G simulation is much greater than in the other models. The MAGICC (Model for the Assessment of Greenhouse-gas-Induced Climate Change) simple climate model is used to investigate possible causes of this atypical behaviour. It is shown that disequilibrium in the initial conditions probably contributes spuriously to the cooling trend in the early centuries of the simulation, and that the omission of tropospheric sulphate aerosol forcing is the likely explanation for the anomalously large recent warming. The simple climate model results are used to adjust the ECHO-G Erik simulation to mitigate these effects, which brings the simulation into better agreement with the other seven models considered here and greatly reduces the overall range of temperature variations during the last millennium simulated by ECHO-G. Smaller inter-model differences remain which can probably be explained by a combination of the particular forcing histories and model sensitivities of each experiment. These have not been investigated here, though we have diagnosed the effective climate sensitivity of ECHO-G to be 2.39{+-}0.11 K for a doubling of CO{sub 2}. (orig.)

  19. Modeling climatic effects of anthropogenic CO2 emissions: Unknowns and uncertainties

    Science.gov (United States)

    Soon, W.; Baliunas, S.; Idso, S.; Kondratyev, K. Ya.; Posmentier, E. S.

    2001-12-01

    A likelihood of disastrous global environmental consequences has been surmised as a result of projected increases in anthropogenic greenhouse gas emissions. These estimates are based on computer climate modeling, a branch of science still in its infancy despite recent, substantial strides in knowledge. Because the expected anthropogenic climate forcings are relatively small compared to other background and forcing factors (internal and external), the credibility of the modeled global and regional responses rests on the validity of the models. We focus on this important question of climate model validation. Specifically, we review common deficiencies in general circulation model calculations of atmospheric temperature, surface temperature, precipitation and their spatial and temporal variability. These deficiencies arise from complex problems associated with parameterization of multiply-interacting climate components, forcings and feedbacks, involving especially clouds and oceans. We also review examples of expected climatic impacts from anthropogenic CO2 forcing. Given the host of uncertainties and unknowns in the difficult but important task of climate modeling, the unique attribution of observed current climate change to increased atmospheric CO2 concentration, including the relatively well-observed latest 20 years, is not possible. We further conclude that the incautious use of GCMs to make future climate projections from incomplete or unknown forcing scenarios is antithetical to the intrinsically heuristic value of models. Such uncritical application of climate models has led to the commonly-held but erroneous impression that modeling has proven or substantiated the hypothesis that CO2 added to the air has caused or will cause significant global warming. An assessment of the positive skills of GCMs and their use in suggesting a discernible human influence on global climate can be found in the joint World Meteorological Organisation and United Nations

  20. Climate Forcing of Ripple Migration and Crest Alignment in the Last 400 kyr in Meridiani Planum, Mars

    Science.gov (United States)

    Fenton, Lori K.; Carson, Helen C.; Michaels, Timothy I.

    2018-04-01

    The plains ripples of Meridiani Planum are the first paleo-aeolian bedforms on Mars to have had their last migration episode constrained in time (to 50-200 ka). Here we test how variations in orbital configuration, air pressure, and atmospheric dust loading over the past 400 kyr affect bedform mobility and crest alignment. Using the National Aeronautics and Space Administration Ames Mars Global Climate Model, we ran a series of sensitivity tests under a number of different conditions, seeking changes in wind patterns relative to those modeled for present-day conditions. Results indicate that enhanced sand drift potential in Meridiani Planum correlates with (1) high axial obliquity, (2) a longitude of perihelion (Lp) near southern summer solstice, and (3) a greater air pressure. The last pulse of westward plains ripple migration likely occurred during the most recent obliquity (relative) maximum, from 111 to 86 ka. At Lp coinciding with southern summer solstice, the Mars Global Climate Model produced a westward resultant drift direction, consistent with the observed north-south plains ripple crest alignment. However, smaller superposed ripples, aligned NNE-SSW, are consistent with a strengthened northern summer Hadley return flow, occurring when Lp coincided with northern summer solstice. The superposed NNE-SSW ripples likely formed as the axial obliquity decreased during the last relative maximum and Lp swung toward northern summer, from 86 to 72 ka. The timeline of bedform activity supports the proposed sequence of CO2 sequestration in the south polar residual cap over the past 400 kyr.

  1. Climate change web picker. A tool bridging daily climate needs in process based modelling in forestry and agriculture

    Energy Technology Data Exchange (ETDEWEB)

    Palma, J.H.N.

    2017-11-01

    Aim of study: Climate data is a need for different types of modeling assessments, especially those involving process based modeling focusing on climate change impacts. However, there is a scarcity of tools delivering easy access to climate datasets to use in biological related modeling. This study aimed at the development of a tool that could provide an user-friendly interface to facilitate access to climate datasets, that are used to supply climate scenarios for the International Panel on Climate Change. Area of study: The tool provides daily datasets across Europe, and also parts of northern Africa Material and Methods: The tool uses climatic datasets generated from third party sources (IPCC related) while a web based interface was developed in JavaScript to ease the access to the datasets Main Results: The interface delivers daily (or monthly) climate data from a user-defined location in Europe for 7 climate variables: minimum and maximum temperature, precipitation, radiation, minimum and maximum relative humidity and wind speed). The time frame ranges from 1951 to 2100, providing the basis to use the data for climate change impact assessments. The tool is free and publicly available at http://www.isa.ulisboa.pt/proj/clipick/. Research Highlights: A new and easy-to-use tool is suggested that will promote the use of climate change scenarios across Europe, especially when daily time steps are needed. CliPick eases the communication between climatic and modelling communities such as agriculture and forestry.

  2. Climate change web picker. A tool bridging daily climate needs in process based modelling in forestry and agriculture

    International Nuclear Information System (INIS)

    Palma, J.H.N.

    2017-01-01

    Aim of study: Climate data is a need for different types of modeling assessments, especially those involving process based modeling focusing on climate change impacts. However, there is a scarcity of tools delivering easy access to climate datasets to use in biological related modeling. This study aimed at the development of a tool that could provide an user-friendly interface to facilitate access to climate datasets, that are used to supply climate scenarios for the International Panel on Climate Change. Area of study: The tool provides daily datasets across Europe, and also parts of northern Africa Material and Methods: The tool uses climatic datasets generated from third party sources (IPCC related) while a web based interface was developed in JavaScript to ease the access to the datasets Main Results: The interface delivers daily (or monthly) climate data from a user-defined location in Europe for 7 climate variables: minimum and maximum temperature, precipitation, radiation, minimum and maximum relative humidity and wind speed). The time frame ranges from 1951 to 2100, providing the basis to use the data for climate change impact assessments. The tool is free and publicly available at http://www.isa.ulisboa.pt/proj/clipick/. Research Highlights: A new and easy-to-use tool is suggested that will promote the use of climate change scenarios across Europe, especially when daily time steps are needed. CliPick eases the communication between climatic and modelling communities such as agriculture and forestry.

  3. Modeling of climate change impacts on agriculture, forestry and fishery

    International Nuclear Information System (INIS)

    Bala, B.K.; Munnaf, M.A.

    2014-01-01

    Changes in climate affect agriculture, forest and fisheries. This paper examines the climate change impact on crop production, fishery and forestry using state - of - the - art modeling technique. Crop growth model InfoCrop was used to predict the climate change impacts on the yields of rice, wheat and maize in Bangladesh. Historical climate change scenario has little or no negative impacts on rice and wheat yields in Mymensingh and Dinajpur but IPCC climate change scenario has higher negative impacts. There is almost no change in the yields of maize for the historical climate change scenario in the Chittagong, Hill Tracts of but there is a small decrease in the yields of rice and maize for IPCC climate change scenario. A new statistical model to forecast climate change impacts on fishery in the world oceans has been developed. Total climate change impact on fishery in the Indian Ocean is negative and the predictor power is 94.14% for eastern part and 98.59% for the western part. Two models are presented for the mangrove forests of the Sundarbans. To bole volumes of the pioneer, intermediate and climax are simulated for three different logging strategies and the results have been discussed in this paper. (author)

  4. Tropical-extratropical climate interaction as revealed in idealized coupled climate model experiments

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Haijun [Peking University, Department of Atmospheric Science and Laboratory for Severe Storm and Flood Disasters, School of Physics, Beijing (China); Liu, Zhengyu [University of Wisconsin-Madison, Center for Climatic Research and Department of the Atmospheric and Oceanic Sciences, Madison, WI (United States)

    2005-06-01

    Tropical-extratropical climate interactions are studied by idealized experiments with a prescribed 2 C SST anomaly at different latitude bands in a coupled climate model. Instead of focusing on intrinsic climate variability, this work investigates the mean climate adjustment to remote external forcing. The extratropical impact on tropical climate can be as strong as the tropical impact on extratropical climate, with the remote sea surface temperature (SST) response being about half the magnitude of the imposed SST change in the forcing region. The equatorward impact of extratropical climate is accomplished by both the atmospheric bridge and the oceanic tunnel. About two-thirds of the tropical SST change comes from the atmospheric bridge, while the remaining one-third comes from the oceanic tunnel. The equatorial SST increase is first driven by the reduced latent heat flux and the weakened poleward surface Ekman transport, and then enhanced by the decrease in subtropical cells' strength and the equatorward subduction of warm anomalies. In contrast, the poleward impact of tropical climate is accomplished mainly by the atmospheric bridge, which is responsible for extratropical temperature changes in both the surface and subsurface. Sensitivity experiments also show the dominant role of the Southern Hemisphere oceans in the tropical climate change. (orig.)

  5. Improved Regional Climate Model Simulation of Precipitation by a Dynamical Coupling to a Hydrology Model

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Drews, Martin; Hesselbjerg Christensen, Jens

    convective precipitation systems. As a result climate model simulations let alone future projections of precipitation often exhibit substantial biases. Here we show that the dynamical coupling of a regional climate model to a detailed fully distributed hydrological model - including groundwater-, overland...... of local precipitation dynamics are seen for time scales of app. Seasonal duration and longer. We show that these results can be attributed to a more complete treatment of land surface feedbacks. The local scale effect on the atmosphere suggests that coupled high-resolution climate-hydrology models...... including a detailed 3D redistribution of sub- and land surface water have a significant potential for improving climate projections even diminishing the need for bias correction in climate-hydrology studies....

  6. Supercomputing for weather and climate modelling: convenience or necessity

    CSIR Research Space (South Africa)

    Landman, WA

    2009-12-01

    Full Text Available Weather and climate modelling require dedicated computer infrastructure in order to generate high-resolution, large ensemble, various models with different configurations, etc. in order to optimise operational forecasts and climate projections. High...

  7. Solar radiation modelling using ANNs for different climates in China

    International Nuclear Information System (INIS)

    Lam, Joseph C.; Wan, Kevin K.W.; Yang, Liu

    2008-01-01

    Artificial neural networks (ANNs) were used to develop prediction models for daily global solar radiation using measured sunshine duration for 40 cities covering nine major thermal climatic zones and sub-zones in China. Coefficients of determination (R 2 ) for all the 40 cities and nine climatic zones/sub-zones are 0.82 or higher, indicating reasonably strong correlation between daily solar radiation and the corresponding sunshine hours. Mean bias error (MBE) varies from -3.3 MJ/m 2 in Ruoqiang (cold climates) to 2.19 MJ/m 2 in Anyang (cold climates). Root mean square error (RMSE) ranges from 1.4 MJ/m 2 in Altay (severe cold climates) to 4.01 MJ/m 2 in Ruoqiang. The three principal statistics (i.e., R 2 , MBE and RMSE) of the climatic zone/sub-zone ANN models are very close to the corresponding zone/sub-zone averages of the individual city ANN models, suggesting that climatic zone ANN models could be used to estimate global solar radiation for locations within the respective zones/sub-zones where only measured sunshine duration data are available. (author)

  8. Cross-validation of an employee safety climate model in Malaysia.

    Science.gov (United States)

    Bahari, Siti Fatimah; Clarke, Sharon

    2013-06-01

    Whilst substantial research has investigated the nature of safety climate, and its importance as a leading indicator of organisational safety, much of this research has been conducted with Western industrial samples. The current study focuses on the cross-validation of a safety climate model in the non-Western industrial context of Malaysian manufacturing. The first-order factorial validity of Cheyne et al.'s (1998) [Cheyne, A., Cox, S., Oliver, A., Tomas, J.M., 1998. Modelling safety climate in the prediction of levels of safety activity. Work and Stress, 12(3), 255-271] model was tested, using confirmatory factor analysis, in a Malaysian sample. Results showed that the model fit indices were below accepted levels, indicating that the original Cheyne et al. (1998) safety climate model was not supported. An alternative three-factor model was developed using exploratory factor analysis. Although these findings are not consistent with previously reported cross-validation studies, we argue that previous studies have focused on validation across Western samples, and that the current study demonstrates the need to take account of cultural factors in the development of safety climate models intended for use in non-Western contexts. The results have important implications for the transferability of existing safety climate models across cultures (for example, in global organisations) and highlight the need for future research to examine cross-cultural issues in relation to safety climate. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

  9. A potato model intercomparison across varying climates and productivity levels

    DEFF Research Database (Denmark)

    H. Fleisher, David; Condori, Bruno; Quiroz, Roberto

    2017-01-01

    A potato crop multi-model assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low- (Chinoli, Bolivia and Gisozi, Burundi) and high- (Jyndevad, Denmark and Washington, United States.......01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be improved using an ensemble approach....

  10. Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

    Science.gov (United States)

    Parsons, Luke Alexander

    Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall

  11. Downscaling GISS ModelE Boreal Summer Climate over Africa

    Science.gov (United States)

    Druyan, Leonard M.; Fulakeza, Matthew

    2015-01-01

    The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June- September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2deg latitude by 2.5deg longitude and the RM3 grid spacing is 0.44deg. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

  12. Regional-Scale Climate Change: Observations and Model Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, Raymond S; Diaz, Henry F

    2010-12-14

    This collaborative proposal addressed key issues in understanding the Earth's climate system, as highlighted by the U.S. Climate Science Program. The research focused on documenting past climatic changes and on assessing future climatic changes based on suites of global and regional climate models. Geographically, our emphasis was on the mountainous regions of the world, with a particular focus on the Neotropics of Central America and the Hawaiian Islands. Mountain regions are zones where large variations in ecosystems occur due to the strong climate zonation forced by the topography. These areas are particularly susceptible to changes in critical ecological thresholds, and we conducted studies of changes in phonological indicators based on various climatic thresholds.

  13. Global warming and livestock husbandry in Kenya. Impacts and adaptations

    International Nuclear Information System (INIS)

    Kabubo-Mariara, Jane

    2009-01-01

    This paper examines the economic impact of climate change on livestock production in Kenya. We estimate a Ricardian model of net livestock incomes and further estimate the marginal impacts of climate change. We also simulate the impact of different climate scenarios on livestock incomes. The Ricardian results show that livestock production in Kenya is highly sensitive to climate change and that there is a non-linear relationship between climate change and livestock productivity. The estimated marginal impacts suggest modest gains from rising temperatures and losses from increased precipitation. The predictions from atmospheric ocean general circulation models suggest that livestock farmers in Kenya are likely to incur heavy losses from global warming. The highest and lowest losses are predicted from the Hadley Centre Coupled model (HADCM) and Parallel Climate Model (PCM) respectively, based on the Intergovernmental Panel on Climate Change A2 Special Report on Emissions Scenarios. The paper concludes that in the long term, climate change is likely to lead to increased poverty, vulnerability and loss of livelihoods. Several policy interventions are recommended to counter this impact. (author)

  14. Global warming and livestock husbandry in Kenya. Impacts and adaptations

    Energy Technology Data Exchange (ETDEWEB)

    Kabubo-Mariara, Jane [School of Economics, University of Nairobi, P.O. Box 30197, 00100, Nairobi (Kenya)

    2009-05-15

    This paper examines the economic impact of climate change on livestock production in Kenya. We estimate a Ricardian model of net livestock incomes and further estimate the marginal impacts of climate change. We also simulate the impact of different climate scenarios on livestock incomes. The Ricardian results show that livestock production in Kenya is highly sensitive to climate change and that there is a non-linear relationship between climate change and livestock productivity. The estimated marginal impacts suggest modest gains from rising temperatures and losses from increased precipitation. The predictions from atmospheric ocean general circulation models suggest that livestock farmers in Kenya are likely to incur heavy losses from global warming. The highest and lowest losses are predicted from the Hadley Centre Coupled model (HADCM) and Parallel Climate Model (PCM) respectively, based on the Intergovernmental Panel on Climate Change A2 Special Report on Emissions Scenarios. The paper concludes that in the long term, climate change is likely to lead to increased poverty, vulnerability and loss of livelihoods. Several policy interventions are recommended to counter this impact. (author)

  15. Assessment of the Impact of Climate Change on the Water Balances and Flooding Conditions of Peninsular Malaysia watersheds by a Coupled Numerical Climate Model - Watershed Hydrology Model

    Science.gov (United States)

    Ercan, A.; Kavvas, M. L.; Ishida, K.; Chen, Z. Q.; Amin, M. Z. M.; Shaaban, A. J.

    2017-12-01

    Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over various watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model that utilized an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century were dynamically downscaled to 6 km resolution over Peninsular Malaysia by a regional numerical climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over the selected watersheds of Peninsular Malaysia. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions at the selected watersheds during the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90 years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant at the selected watersheds. Furthermore, the flood frequency analyses for the selected watersheds indicate an overall increasing trend in the second half of the 21st century.

  16. Modelling of anthropogenic and natural climate changes

    Energy Technology Data Exchange (ETDEWEB)

    Grassl, H; Mikolajewicz, U; Bakan, S [Max Planck Institute of Meteorology, Hamburg (Germany)

    1993-06-01

    The delay of anthropogenic climate change caused by oceans and other slowly reacting climate system components forces us to numerical modeling as the basis of decisions. For three three-dimensional numerical examples, namely transient coupled ocean-atmosphere models for the additional greenhouse effect, internal ocean-atmosphere variability, and disturbance by soot particles from burning oil wells, the present-day status is described. From all anthropogenic impacts on the radiative balance, the contribution from trace gases is the most important.

  17. Impact of climate change estimated through statistical downscaling on crop productivity and soil water balance in Southern Italy

    Science.gov (United States)

    Ventrella, D.; Giglio, L.; Charfeddine, M.; Palatella, L.; Pizzigalli, C.; Vitale, D.; Paradisi, P.; Miglietta, M. M.; Rana, G.

    2010-09-01

    The climatic change induced by the global warming is expected to modify the agricultural activity and consequently the other social and economical sectors. In this context, an efficient management of the water resources is considered very important for Italy and in particular for Southern areas characterized by a typical Mediterranean climate in order to improve the economical and environmental sustainability of the agricultural activity. Climate warming could have a substantial impact on some agronomical practices as the choice of the crops to be included in the rotations, the sowing time and the irrigation scheduling. For a particular zone, the impact of climatic change on agricultural activity will depend also on the continuum "soil-plant-climate" and this continuum has to be included in the analysis for forecasting purposes. The Project CLIMESCO is structured in four workpackages (WP): (1) Identification of homogeneous areas, (2) Climatic change, (3) Optimization of water resources and (4) Scenarios analysis. In this study we applied a statistical downscaling method, Canonical Correlation Analysis after Principal Component Analysis filtering, to two sub-regions of agricultural interest in Sicily and Apulia (respectively, Delia basin and Capitanata). We adopt, as large scale predictors, the sea level pressure from the the EMULATE project dataset and the 1000 hPa temperature obtained from the NCEP reanalyses, while the predictands are monthly time series of maximum and minimum temperature and precipitation. As the crop growth models need daily datasets, a stochastic weather generator (the LARS-WG model) has been applied for this purpose. LARS-WG needs a preliminary calibration with daily time series of meteorological fields, that are available in the framework of CLIMESCO project. Then, the statistical relationships have been applied to two climate change scenarios (SRES A2 and B2), provided by three different GCM's: the Hadley Centre Coupled Model version 3 (Had

  18. Climate: Policy, Modeling, and Federal Priorities (Invited)

    Science.gov (United States)

    Koonin, S.; Department Of Energy Office Of The Under SecretaryScience

    2010-12-01

    The Administration has set ambitious national goals to reduce our dependence on fossil fuels and reduce anthropogenic greenhouse gas (GHG) emissions. The US and other countries involved in the U.N. Framework Convention on Climate Change continue to work toward a goal of establishing a viable treaty that would encompass limits on emissions and codify actions that nations would take to reduce emissions. These negotiations are informed by the science of climate change and by our understanding of how changes in technology and the economy might affect the overall climate in the future. I will describe the present efforts within the U.S. Department of Energy, and the federal government more generally, to address issues related to climate change. These include state-of-the-art climate modeling and uncertainty assessment, economic and climate scenario planning based on best estimates of different technology trajectories, adaption strategies for climate change, and monitoring and reporting for treaty verification.

  19. Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

    Czech Academy of Sciences Publication Activity Database

    Gaál, Ľ.; Beranová, R.; Hlavčová, K.; Kyselý, Jan

    2014-01-01

    Roč. 2014, č. 943487 (2014), s. 1-14 ISSN 1687-9309 Institutional support: RVO:67179843 ; RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: EH - Ecology, Behaviour Impact factor: 0.946, year: 2014

  20. Climate effects of anthropogenic sulfate: Simulations from a coupled chemistry/climate model

    International Nuclear Information System (INIS)

    Chuang, C.C.; Penner, J.E.; Taylor, K.E.; Walton, J.J.

    1993-09-01

    In this paper, we use a more comprehensive approach by coupling a climate model with a 3-D global chemistry model to investigate the forcing by anthropogenic aerosol sulfate. The chemistry model treats the global-scale transport, transformation, and removal of SO 2 , DMS and H 2 SO 4 species in the atmosphere. The mass concentration of anthropogenic sulfate from fossil fuel combustion and biomass burning is calculated in the chemistry model and provided to the climate model where it affects the shortwave radiation. We also investigate the effect, with cloud nucleation parameterized in terms of local aerosol number, sulfate mass concentration and updraft velocity. Our simulations indicate that anthropogenic sulfate may result in important increases in reflected solar radiation, which would mask locally the radiative forcing from increased greenhouse gases. Uncertainties in these results will be discussed

  1. Ensemble catchment hydrological modelling for climate change impact analysis

    Science.gov (United States)

    Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

    2014-05-01

    It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions

  2. Ensemble of regional climate model projections for Ireland

    Science.gov (United States)

    Nolan, Paul; McGrath, Ray

    2016-04-01

    The method of Regional Climate Modelling (RCM) was employed to assess the impacts of a warming climate on the mid-21st-century climate of Ireland. The RCM simulations were run at high spatial resolution, up to 4 km, thus allowing a better evaluation of the local effects of climate change. Simulations were run for a reference period 1981-2000 and future period 2041-2060. Differences between the two periods provide a measure of climate change. To address the issue of uncertainty, a multi-model ensemble approach was employed. Specifically, the future climate of Ireland was simulated using three different RCMs, driven by four Global Climate Models (GCMs). To account for the uncertainty in future emissions, a number of SRES (B1, A1B, A2) and RCP (4.5, 8.5) emission scenarios were used to simulate the future climate. Through the ensemble approach, the uncertainty in the RCM projections can be partially quantified, thus providing a measure of confidence in the predictions. In addition, likelihood values can be assigned to the projections. The RCMs used in this work are the COnsortium for Small-scale MOdeling-Climate Limited-area Modelling (COSMO-CLM, versions 3 and 4) model and the Weather Research and Forecasting (WRF) model. The GCMs used are the Max Planck Institute's ECHAM5, the UK Met Office's HadGEM2-ES, the CGCM3.1 model from the Canadian Centre for Climate Modelling and the EC-Earth consortium GCM. The projections for mid-century indicate an increase of 1-1.6°C in mean annual temperatures, with the largest increases seen in the east of the country. Warming is enhanced for the extremes (i.e. hot or cold days), with the warmest 5% of daily maximum summer temperatures projected to increase by 0.7-2.6°C. The coldest 5% of night-time temperatures in winter are projected to rise by 1.1-3.1°C. Averaged over the whole country, the number of frost days is projected to decrease by over 50%. The projections indicate an average increase in the length of the growing season

  3. Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models

    Science.gov (United States)

    Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby

    2018-06-01

    The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices.

  4. Storm Water Management Model Climate Adjustment Tool (SWMM-CAT)

    Science.gov (United States)

    The US EPA’s newest tool, the Stormwater Management Model (SWMM) – Climate Adjustment Tool (CAT) is meant to help municipal stormwater utilities better address potential climate change impacts affecting their operations. SWMM, first released in 1971, models hydrology and hydrauli...

  5. Evaluation of global climate models for Indian monsoon climatology

    International Nuclear Information System (INIS)

    Kodra, Evan; Ganguly, Auroop R; Ghosh, Subimal

    2012-01-01

    The viability of global climate models for forecasting the Indian monsoon is explored. Evaluation and intercomparison of model skills are employed to assess the reliability of individual models and to guide model selection strategies. Two dominant and unique patterns of Indian monsoon climatology are trends in maximum temperature and periodicity in total rainfall observed after 30 yr averaging over India. An examination of seven models and their ensembles reveals that no single model or model selection strategy outperforms the rest. The single-best model for the periodicity of Indian monsoon rainfall is the only model that captures a low-frequency natural climate oscillator thought to dictate the periodicity. The trend in maximum temperature, which most models are thought to handle relatively better, is best captured through a multimodel average compared to individual models. The results suggest a need to carefully evaluate individual models and model combinations, in addition to physical drivers where possible, for regional projections from global climate models. (letter)

  6. Multi-model approach to assess the impact of climate change on runoff

    Science.gov (United States)

    Dams, J.; Nossent, J.; Senbeta, T. B.; Willems, P.; Batelaan, O.

    2015-10-01

    The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a

  7. Bringing a Realistic Global Climate Modeling Experience to a Broader Audience

    Science.gov (United States)

    Sohl, L. E.; Chandler, M. A.; Zhou, J.

    2010-12-01

    EdGCM, the Educational Global Climate Model, was developed with the goal of helping students learn about climate change and climate modeling by giving them the ability to run a genuine NASA global climate model (GCM) on a desktop computer. Since EdGCM was first publicly released in January 2005, tens of thousands of users on seven continents have downloaded the software. EdGCM has been utilized by climate science educators from middle school through graduate school levels, and on occasion even by researchers who otherwise do not have ready access to climate model at national labs in the U.S. and elsewhere. The EdGCM software is designed to walk users through the same process a climate scientist would use in designing and running simulations, and analyzing and visualizing GCM output. Although the current interface design gives users a clear view of some of the complexities involved in using a climate model, it can be daunting for users whose main focus is on climate science rather than modeling per se. As part of the work funded by NASA’s Global Climate Change Education (GCCE) program, we will begin modifications to the user interface that will improve the accessibility of EdGCM to a wider array of users, especially at the middle school and high school levels, by: 1) Developing an automated approach (a “wizard”) to simplify the user experience in setting up new climate simulations; 2) Produce a catalog of “rediscovery experiments” that allow users to reproduce published climate model results, and in some cases compare model projections to real world data; and 3) Enhance distance learning and online learning opportunities through the development of a web-based interface. The prototypes for these modifications will then be presented to educators belonging to an EdGCM Users Group for feedback, so that we can further refine the EdGCM software, and thus deliver the tools and materials educators want and need across a wider range of learning environments.

  8. Model Interpretation of Climate Signals: Application to the Asian Monsoon Climate

    Science.gov (United States)

    Lau, William K. M.

    2002-01-01

    This is an invited review paper intended to be published as a Chapter in a book entitled "The Global Climate System: Patterns, Processes and Teleconnections" Cambridge University Press. The author begins with an introduction followed by a primer of climate models, including a description of various modeling strategies and methodologies used for climate diagnostics and predictability studies. Results from the CLIVAR Monsoon Model Intercomparison Project (MMIP) were used to illustrate the application of the strategies to modeling the Asian monsoon. It is shown that state-of-the art atmospheric GCMs have reasonable capability in simulating the seasonal mean large scale monsoon circulation, and response to El Nino. However, most models fail to capture the climatological as well as interannual anomalies of regional scale features of the Asian monsoon. These include in general over-estimating the intensity and/or misplacing the locations of the monsoon convection over the Bay of Bengal, and the zones of heavy rainfall near steep topography of the Indian subcontinent, Indonesia, and Indo-China and the Philippines. The intensity of convection in the equatorial Indian Ocean is generally weaker in models compared to observations. Most important, an endemic problem in all models is the weakness and the lack of definition of the Mei-yu rainbelt of the East Asia, in particular the part of the Mei-yu rainbelt over the East China Sea and southern Japan are under-represented. All models seem to possess certain amount of intraseasonal variability, but the monsoon transitions, such as the onset and breaks are less defined compared with the observed. Evidences are provided that a better simulation of the annual cycle and intraseasonal variability is a pre-requisite for better simulation and better prediction of interannual anomalies.

  9. Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

    Science.gov (United States)

    Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

    2018-05-01

    Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

  10. Regional and Global Climate Response to Anthropogenic SO2 Emissions from China in Three Climate Models

    Science.gov (United States)

    Kasoar, M.; Voulgarakis, Apostolos; Lamarque, Jean-Francois; Shindell, Drew T.; Bellouin, Nicholas; Collins, William J.; Faluvegi, Greg; Tsigaridis, Kostas

    2016-01-01

    We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against

  11. Lake Representations in Global Climate Models: An End-User Perspective

    Science.gov (United States)

    Rood, R. B.; Briley, L.; Steiner, A.; Wells, K.

    2017-12-01

    The weather and climate in the Great Lakes region of the United States and Canada are strongly influenced by the lakes. Within global climate models, lakes are incorporated in many ways. If one is interested in quantitative climate information for the Great Lakes, then it is a first principle requirement that end-users of climate model simulation data, whether scientists or practitioners, need to know if and how lakes are incorporated into models. We pose the basic question, how are lakes represented in CMIP models? Despite significant efforts by the climate community to document and publish basic information about climate models, it is unclear how to answer the question about lake representations? With significant knowledge of the practice of the field, then a reasonable starting point is to use the ES-DOC Comparator (https://compare.es-doc.org/ ). Once at this interface to model information, the end-user is faced with the need for more knowledge about the practice and culture of the discipline. For example, lakes are often categorized as a type of land, a counterintuitive concept. In some models, though, lakes are specified in ocean models. There is little evidence and little confidence that the information obtained through this process is complete or accurate. In fact, it is verifiably not accurate. This experience, then, motivates identifying and finding either human experts or technical documentation for each model. The conclusion from this exercise is that it can take months or longer to provide a defensible answer to if and how lakes are represented in climate models. Our experience with lake finding is that this is not a unique experience. This talk documents our experience and explores barriers we have identified and strategies for reducing those barriers.

  12. Climate change and high-resolution whole-building numerical modelling

    NARCIS (Netherlands)

    Blocken, B.J.E.; Briggen, P.M.; Schellen, H.L.; Hensen, J.L.M.

    2010-01-01

    This paper briefly discusses the need of high-resolution whole-building numerical modelling in the context of climate change. High-resolution whole-building numerical modelling can be used for detailed analysis of the potential consequences of climate change on buildings and to evaluate remedial

  13. Historical and idealized climate model experiments: an EMIC intercomparison

    DEFF Research Database (Denmark)

    Eby, M.; Weaver, A. J.; Alexander, K.

    2012-01-01

    Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE......, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows considerable synergy between land-use change and CO2... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures...

  14. Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment

    Science.gov (United States)

    Taner, M. U.; Wi, S.; Brown, C.

    2017-12-01

    The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.

  15. Future extreme events in European climate: An exploration of regional climate model projections

    DEFF Research Database (Denmark)

    Beniston, M.; Stephenson, D.B.; Christensen, O.B.

    2007-01-01

    -90) and future (2071-2 100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves - Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first...

  16. Climate Model Diagnostic and Evaluation: With a Focus on Satellite Observations

    Science.gov (United States)

    Waliser, Duane

    2011-01-01

    Each year, we host a summer school that brings together the next generation of climate scientists - about 30 graduate students and postdocs from around the world - to engage with premier climate scientists from the Jet Propulsion Laboratory and elsewhere. Our yearly summer school focuses on topics on the leading edge of climate science research. Our inaugural summer school, held in 2011, was on the topic of "Using Satellite Observations to Advance Climate Models," and enabled students to explore how satellite observations can be used to evaluate and improve climate models. Speakers included climate experts from both NASA and the National Oceanic and Atmospheric Administration (NOAA), who provided updates on climate model diagnostics and evaluation and remote sensing of the planet. Details of the next summer school will be posted here in due course.

  17. The Co-evolution of Climate Models and the Intergovernmental Panel on Climate Change

    Science.gov (United States)

    Somerville, R. C.

    2010-12-01

    As recently as the 1950s, global climate models, or GCMs, did not exist, and the notion that man-made carbon dioxide might lead to significant climate change was not regarded as a serious possibility by most experts. Today, of course, the prospect or threat of exactly this type of climate change dominates the science and ranks among the most pressing issues confronting all mankind. Indeed, the prevailing scientific view throughout the first half of the twentieth century was that adding carbon dioxide to the atmosphere would have only a negligible effect on climate. The science of climate change caused by atmospheric carbon dioxide changes has thus undergone a genuine revolution. An extraordinarily rapid development of global climate models has also characterized this period, especially in the three decades since about 1980. In these three decades, the number of GCMs has greatly increased, and their physical and computational aspects have both markedly improved. Modeling progress has been enabled by many scientific advances, of course, but especially by a massive increase in available computer power, with supercomputer speeds increasing by roughly a factor of a million in the three decades from about 1980 to 2010. This technological advance has permitted a rapid increase in the physical comprehensiveness of GCMs as well as in spatial computational resolution. In short, GCMs have dramatically evolved over time, in exactly the same recent period as popular interest and scientific concern about anthropogenic climate change have markedly increased. In parallel, a unique international organization, the Intergovernmental Panel on Climate Change, or IPCC, has also recently come into being and also evolved rapidly. Today, the IPCC has become widely respected and globally influential. The IPCC was founded in 1988, and its history is thus even shorter than that of GCMs. Yet, its stature today is such that a series of IPCC reports assessing climate change science has already

  18. The transferability of hydrological models under nonstationary climatic conditions

    Directory of Open Access Journals (Sweden)

    C. Z. Li

    2012-04-01

    Full Text Available This paper investigates issues involved in calibrating hydrological models against observed data when the aim of the modelling is to predict future runoff under different climatic conditions. To achieve this objective, we tested two hydrological models, DWBM and SIMHYD, using data from 30 unimpaired catchments in Australia which had at least 60 yr of daily precipitation, potential evapotranspiration (PET, and streamflow data. Nash-Sutcliffe efficiency (NSE, modified index of agreement (d1 and water balance error (WBE were used as performance criteria. We used a differential split-sample test to split up the data into 120 sub-periods and 4 different climatic sub-periods in order to assess how well the calibrated model could be transferred different periods. For each catchment, the models were calibrated for one sub-period and validated on the other three. Monte Carlo simulation was used to explore parameter stability compared to historic climatic variability. The chi-square test was used to measure the relationship between the distribution of the parameters and hydroclimatic variability. The results showed that the performance of the two hydrological models differed and depended on the model calibration. We found that if a hydrological model is set up to simulate runoff for a wet climate scenario then it should be calibrated on a wet segment of the historic record, and similarly a dry segment should be used for a dry climate scenario. The Monte Carlo simulation provides an effective and pragmatic approach to explore uncertainty and equifinality in hydrological model parameters. Some parameters of the hydrological models are shown to be significantly more sensitive to the choice of calibration periods. Our findings support the idea that when using conceptual hydrological models to assess future climate change impacts, a differential split-sample test and Monte Carlo simulation should be used to quantify uncertainties due to

  19. Regional model simulations of New Zealand climate

    Science.gov (United States)

    Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

    1998-03-01

    Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

  20. Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

    Science.gov (United States)

    Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

    2017-11-01

    Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

  1. The regional aerosol-climate model REMO-HAM

    Directory of Open Access Journals (Sweden)

    J.-P. Pietikäinen

    2012-11-01

    Full Text Available REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes most of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM is coupled with a two-moment stratiform cloud scheme. On the other hand, REMO-HAM does not include an online coupled aerosol-radiation nor a secondary organic aerosol module. In this work, we evaluate the model and compare the results against ECHAM5-HAM and measurements. Four different measurement sites were chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50 × 50 km2 and 10 × 10 km2. Based on our simulations, REMO-HAM is in reasonable agreement with the measured values. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. Since we did not use activation nor kinetic nucleation for the boundary layer, the total number concentrations are somewhat underestimated. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we show that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.

  2. Coupling a global climatic model with insurance impact models for flood and drought: an estimation of the financial impact of climate change

    Directory of Open Access Journals (Sweden)

    Tinard Pierre

    2016-01-01

    Full Text Available CCR, a French reinsurance company mostly involved in natural disasters coverage in France, has been developing tools for the estimation of its exposure to climatic risks for many years. Both a flood and a drought models were developed and calibrated on a large policies and claims database supplied every year with insurers’ data. More recently, CCR has been developing a stochastic approach in order to evaluate its financial exposure to extreme events. A large and realistic event set has been generated by applying extreme value statistic tools to simulate hazard and to estimate, using our impact models, the average annual losses and losses related to different return periods. These event sets have been simulated separately for flood and drought, with a hypothesis of independence, consistent with recent annual damage data. The newest development presented here consists in the use of the ARPEGE–Climat model performed by Météo-France to simulate two 200-years sets of hourly atmospheric time series reflecting both the current climate and the RCP 4.5 climate conditions circa year 2050. These climatic data constitute the input data for the flood and drought impact models to detect events and simulate the associated hazard and damages. Our two main goals are (1 to simulate simultaneously flood and drought events for the same simulated years and (2 to evaluate the financial impact of climate change.

  3. Modeling Past Abrupt Climate Changes

    DEFF Research Database (Denmark)

    Marchionne, Arianna

    of the orbital variations on Earth's climate; however, the knowledge and tools needed to complete a unied theory for ice ages have not been developed yet. Here, we focus on the climatic variations that have occurred over the last few million years. Paleoclimatic records show that the glacial cycles are linked...... to those present in the astronomical forcing. We shall do this in terms of a general framework of conceptual dynamical models, which may or may not exhibit internal self-sustained oscillations. We introduce and discuss two distinct mechanisms for a periodic response at a dierent period to a periodic...

  4. Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

    Science.gov (United States)

    Erfanian, A.; Fomenko, L.; Wang, G.

    2016-12-01

    Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

  5. The origins of computer weather prediction and climate modeling

    International Nuclear Information System (INIS)

    Lynch, Peter

    2008-01-01

    Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed

  6. Model based climate information on drought risk in Africa

    Science.gov (United States)

    Calmanti, S.; Syroka, J.; Jones, C.; Carfagna, F.; Dell'Aquila, A.; Hoefsloot, P.; Kaffaf, S.; Nikulin, G.

    2012-04-01

    The United Nations World Food Programme (WFP) has embarked upon the endeavor of creating a sustainable Africa-wide natural disaster risk management system. A fundamental building block of this initiative is the setup of a drought impact modeling platform called Africa Risk-View that aims to quantify and monitor weather-related food security risk in Africa. The modeling approach is based the Water Requirement Satisfaction Index (WRSI), as the fundamental indicator of the performances of agriculture and uses historical records of food assistance operation to project future potential needs for livelihood protection. By using climate change scenarios as an input to Africa Risk-View it is possible, in principles, to evaluate the future impact of climate variability on critical issues such as food security and the overall performance of the envisaged risk management system. A necessary preliminary step to this challenging task is the exploration of the sources of uncertainties affecting the assessment based on modeled climate change scenarios. For this purpose, a limited set of climate models have been selected in order verify the relevance of using climate model output data with Africa Risk-View and to explore a minimal range of possible sources of uncertainty. This first evaluation exercise started before the setup of the CORDEX framework and has relied on model output available at the time. In particular only one regional downscaling was available for the entire African continent from the ENSEMBLES project. The analysis shows that current coarse resolution global climate models can not directly feed into the Africa RiskView risk-analysis tool. However, regional downscaling may help correcting the inherent biases observed in the datasets. Further analysis is performed by using the first data available under the CORDEX framework. In particular, we consider a set of simulation driven with boundary conditions from the reanalysis ERA-Interim to evaluate the skill drought

  7. What’s Needed from Climate Modeling to Advance Actionable Science for Water Utilities?

    Science.gov (United States)

    Barsugli, J. J.; Anderson, C. J.; Smith, J. B.; Vogel, J. M.

    2009-12-01

    “…perfect information on climate change is neither available today nor likely to be available in the future, but … over time, as the threats climate change poses to our systems grow more real, predicting those effects with greater certainty is non-discretionary. We’re not yet at a level at which climate change projections can drive climate change adaptation.” (Testimony of WUCA Staff Chair David Behar to the House Committee on Science and Technology, May 5, 2009) To respond to this challenge, the Water Utility Climate Alliance (WUCA) has sponsored a white paper titled “Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. ” This report concerns how investments in the science of climate change, and in particular climate modeling and downscaling, can best be directed to help make climate projections more actionable. The meaning of “model improvement” can be very different depending on whether one is talking to a climate model developer or to a water manager trying to incorporate climate projections in to planning. We first surveyed the WUCA members on present and potential uses of climate model projections and on climate inputs to their various system models. Based on those surveys and on subsequent discussions, we identified four dimensions along which improvement in modeling would make the science more “actionable”: improved model agreement on change in key parameters; narrowing the range of model projections; providing projections at spatial and temporal scales that match water utilities system models; providing projections that water utility planning horizons. With these goals in mind we developed four options for improving global-scale climate modeling and three options for improving downscaling that will be discussed. However, there does not seem to be a single investment - the proverbial “magic bullet” -- which will substantially reduce the range of model projections at the scales at which utility

  8. Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

    Energy Technology Data Exchange (ETDEWEB)

    Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

    2015-07-14

    The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project

  9. What Can Human Geography Offer Climate Change Modelling?

    DEFF Research Database (Denmark)

    Grindsted, Thomas Skou

    2014-01-01

    behaviour to economic rationality when construed in sophisticated climate models and sometimes in nongeographical representations. The need to comprehensively take into consideration methodological approaches concerning the interface of society-environment interactions seems highly relevant to contemporary...... regularities, rationalities, and pre-analytic assumptions. Lastly we discuss challenges of constructing nature(s) and how we better understand the (geo) politics of climate change modeling.......The discipline of Geography may be one of the most prominent and oldest disciplines in the conceptualization of human–environment interactions that integrates elements from both natural and social sciences. Yet, much research on society–environment interactions on climate change reduces human...

  10. IIASA's climate-vegetation-biogeochemical cycle module as a part of an integrated model for climate change

    International Nuclear Information System (INIS)

    Ganopolski, A.V.; Jonas, M.; Krabec, J.; Olendrzynski, K.; Petoukhov, V.K.; Venevsky, S.V.

    1994-01-01

    The main objective of this study is the development of a hierarchy of coupled climate biosphere models with a full description of the global biogeochemical cycles. These models are planned for use as the core of a set of integrated models of climate change and they will incorporate the main elements of the Earth system (atmosphere, hydrosphere, pedosphere and biosphere) linked with each other (and eventually with the antroposphere) through the fluxes of heat, momentum, water and through the global biogeochemical cycles of carbon and nitrogen. This set of integrated models can be considered to fill the gap between highly simplified integrated models of climate change and very sophisticated and computationally expensive coupled models, developed on the basis of general circulation models (GCMs). It is anticipated that this range of integrated models will be an effective tool for investigating the broad spectrum of problems connected with the coexistence of human society and biosphere

  11. Learning About Climate and Atmospheric Models Through Machine Learning

    Science.gov (United States)

    Lucas, D. D.

    2017-12-01

    From the analysis of ensemble variability to improving simulation performance, machine learning algorithms can play a powerful role in understanding the behavior of atmospheric and climate models. To learn about model behavior, we create training and testing data sets through ensemble techniques that sample different model configurations and values of input parameters, and then use supervised machine learning to map the relationships between the inputs and outputs. Following this procedure, we have used support vector machines, random forests, gradient boosting and other methods to investigate a variety of atmospheric and climate model phenomena. We have used machine learning to predict simulation crashes, estimate the probability density function of climate sensitivity, optimize simulations of the Madden Julian oscillation, assess the impacts of weather and emissions uncertainty on atmospheric dispersion, and quantify the effects of model resolution changes on precipitation. This presentation highlights recent examples of our applications of machine learning to improve the understanding of climate and atmospheric models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  12. Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs*

    KAUST Repository

    Castruccio, Stefano

    2014-03-01

    The authors describe a new approach for emulating the output of a fully coupled climate model under arbitrary forcing scenarios that is based on a small set of precomputed runs from the model. Temperature and precipitation are expressed as simple functions of the past trajectory of atmospheric CO2 concentrations, and a statistical model is fit using a limited set of training runs. The approach is demonstrated to be a useful and computationally efficient alternative to pattern scaling and captures the nonlinear evolution of spatial patterns of climate anomalies inherent in transient climates. The approach does as well as pattern scaling in all circumstances and substantially better in many; it is not computationally demanding; and, once the statistical model is fit, it produces emulated climate output effectively instantaneously. It may therefore find wide application in climate impacts assessments and other policy analyses requiring rapid climate projections.

  13. Statistical surrogate models for prediction of high-consequence climate change.

    Energy Technology Data Exchange (ETDEWEB)

    Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

    2011-09-01

    In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.

  14. Adjustment of regional climate model output for modeling the climatic mass balance of all glaciers on Svalbard.

    NARCIS (Netherlands)

    Möller, M.; Obleitner, F.; Reijmer, C.H.; Pohjola, V.A.; Glowacki, P.; Kohler, J.

    2016-01-01

    Large-scale modeling of glacier mass balance relies often on the output from regional climate models (RCMs). However, the limited accuracy and spatial resolution of RCM output pose limitations on mass balance simulations at subregional or local scales. Moreover, RCM output is still rarely available

  15. A Regional Climate Model Evaluation System

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop a packaged data management infrastructure for the comparison of generated climate model output to existing observational datasets that includes capabilities...

  16. Cluster-based analysis of multi-model climate ensembles

    Science.gov (United States)

    Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

    2018-06-01

    Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and

  17. Local control on precipitation in a fully coupled climate-hydrology model.

    Science.gov (United States)

    Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

    2016-03-10

    The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

  18. A Reusable Framework for Regional Climate Model Evaluation

    Science.gov (United States)

    Hart, A. F.; Goodale, C. E.; Mattmann, C. A.; Lean, P.; Kim, J.; Zimdars, P.; Waliser, D. E.; Crichton, D. J.

    2011-12-01

    Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and

  19. Scale dependency of regional climate modeling of current and future climate extremes in Germany

    Science.gov (United States)

    Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

    2017-11-01

    A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

  20. Uncertainty and endogenous technical change in climate policy models

    International Nuclear Information System (INIS)

    Baker, Erin; Shittu, Ekundayo

    2008-01-01

    Until recently endogenous technical change and uncertainty have been modeled separately in climate policy models. In this paper, we review the emerging literature that considers both these elements together. Taken as a whole the literature indicates that explicitly including uncertainty has important quantitative and qualitative impacts on optimal climate change technology policy. (author)

  1. Visualizing projected Climate Changes - the CMIP5 Multi-Model Ensemble

    Science.gov (United States)

    Böttinger, Michael; Eyring, Veronika; Lauer, Axel; Meier-Fleischer, Karin

    2017-04-01

    Large ensembles add an additional dimension to climate model simulations. Internal variability of the climate system can be assessed for example by multiple climate model simulations with small variations in the initial conditions or by analyzing the spread in large ensembles made by multiple climate models under common protocols. This spread is often used as a measure of uncertainty in climate projections. In the context of the fifth phase of the WCRP's Coupled Model Intercomparison Project (CMIP5), more than 40 different coupled climate models were employed to carry out a coordinated set of experiments. Time series of the development of integral quantities such as the global mean temperature change for all models visualize the spread in the multi-model ensemble. A similar approach can be applied to 2D-visualizations of projected climate changes such as latitude-longitude maps showing the multi-model mean of the ensemble by adding a graphical representation of the uncertainty information. This has been demonstrated for example with static figures in chapter 12 of the last IPCC report (AR5) using different so-called stippling and hatching techniques. In this work, we focus on animated visualizations of multi-model ensemble climate projections carried out within CMIP5 as a way of communicating climate change results to the scientific community as well as to the public. We take a closer look at measures of robustness or uncertainty used in recent publications suitable for animated visualizations. Specifically, we use the ESMValTool [1] to process and prepare the CMIP5 multi-model data in combination with standard visualization tools such as NCL and the commercial 3D visualization software Avizo to create the animations. We compare different visualization techniques such as height fields or shading with transparency for creating animated visualization of ensemble mean changes in temperature and precipitation including corresponding robustness measures. [1] Eyring, V

  2. Development and application of an interactive climate-ecosystem model system

    Institute of Scientific and Technical Information of China (English)

    CHEN Ming; D. Pollard

    2003-01-01

    A regional climate-ecosystem model system is developed in this study. It overcomes the weakness in traditional one-way coupling models and enables detailed description of interactive process between climate and natural ecosystem. It is applied to interaction study between monsoon climate and ecosystem in East Asia, with emphasis on future climate and ecosystem change scenario forced by doubled CO2. The climate tends to be warmer and wetter under doubled CO2 in Jianghuai and the Yangzi River valley, but it becomes warmer and drier in inland areas of northern and northwestern China. The largest changes and feedbacks between vegetation and climate occur in northern China. Northern inland ecosystems experience considerable degradation and desertification, indicating a marked sensitivity and vulnerability to climatic change. The strongest vegetation response to climate change occurs in northern China and the weakest in southern China. Vegetation feedbacks intensify warming and reduce drying due to increased CO2 during summer in northern China. Generally, vegetation-climate interactions are much stronger in northern China than in southern China.

  3. Modeling climate change impacts on water trading.

    Science.gov (United States)

    Luo, Bin; Maqsood, Imran; Gong, Yazhen

    2010-04-01

    This paper presents a new method of evaluating the impacts of climate change on the long-term performance of water trading programs, through designing an indicator to measure the mean of periodic water volume that can be released by trading through a water-use system. The indicator is computed with a stochastic optimization model which can reflect the random uncertainty of water availability. The developed method was demonstrated in the Swift Current Creek watershed of Prairie Canada under two future scenarios simulated by a Canadian Regional Climate Model, in which total water availabilities under future scenarios were estimated using a monthly water balance model. Frequency analysis was performed to obtain the best probability distributions for both observed and simulated water quantity data. Results from the case study indicate that the performance of a trading system is highly scenario-dependent in future climate, with trading effectiveness highly optimistic or undesirable under different future scenarios. Trading effectiveness also largely depends on trading costs, with high costs resulting in failure of the trading program. (c) 2010 Elsevier B.V. All rights reserved.

  4. Isotopes as validation tools for global climate models

    International Nuclear Information System (INIS)

    Henderson-Sellers, A.

    2001-01-01

    Global Climate Models (GCMs) are the predominant tool with which we predict the future climate. In order that people can have confidence in such predictions, GCMs require validation. As almost every available item of meteorological data has been exploited in the construction and tuning of GCMs to date, independent validation is very difficult. This paper explores the use of isotopes as a novel and fully independent means of evaluating GCMs. The focus is the Amazon Basin which has a long history of isotope collection and analysis and also of climate modelling: both having been reported for over thirty years. Careful consideration of the results of GCM simulations of Amazonian deforestation and climate change suggests that the recent stable isotope record is more consistent with the predicted effects of greenhouse warming, possibly combined with forest removal, than with GCM predictions of the effects of deforestation alone

  5. Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

    Science.gov (United States)

    Hanson, D. A.; Kotamarthi, V. R.; Foster, I. T.; Franklin, M.; Zhu, E.; Patel, D. M.

    2008-12-01

    Here, we compare two scenarios based on Stanford University's Energy Modeling Forum Study 22 on global cooperative and non-cooperative climate policies. In the former, efficient transition paths are implemented including technology Research and Development effort, energy conservation programs, and price signals for greenhouse gas (GHG) emissions. In the non-cooperative case, some countries try to relax their regulations and be free riders. Total emissions and costs are higher in the non-cooperative scenario. The simulations, including climate impacts, run to the year 2100. We use the Argonne AMIGA-MARS economic-energy systems model, the Texas AM University's Forest and Agricultural Sector Optimization Model (FASOM), and the University of Illinois's Integrated Science Assessment Model (ISAM), with offline coupling between the FASOM and AMIGA-MARS and an online coupling between AMIGA-MARS and ISAM. This set of models captures the interaction of terrestrial systems, land use, crops and forests, climate change, human activity, and energy systems. Our scenario simulations represent dynamic paths over which all the climate, terrestrial, economic, and energy technology equations are solved simultaneously Special attention is paid to biofuels and how they interact with conventional gasoline/diesel fuel markets. Possible low-carbon penetration paths are based on estimated costs for new technologies, including cellulosic biomass, coal-to-liquids, plug-in electric vehicles, solar and nuclear energy. We explicitly explore key uncertainties that affect mitigation and adaptation scenarios.

  6. The Milankovitch theory and climate sensitivity. I - Equilibrium climate model solutions for the present surface conditions. II - Interaction between the Northern Hemisphere ice sheets and the climate system

    Science.gov (United States)

    Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

    1988-01-01

    A seasonal climate model was developed to test the climate sensitivity and, in particular, the Milankovitch (1941) theory. Four climate model versions were implemented to investigate the range of uncertainty in the parameterizations of three basic feedback mechanisms: the ice albedo-temperature, the outgoing long-wave radiation-temperature, and the eddy transport-meridional temperature gradient. It was found that the differences between the simulation of the present climate by the four versions were generally small, especially for annually averaged results. The climate model was also used to study the effect of growing/shrinking of a continental ice sheet, bedrock sinking/uplifting, and sea level changes on the climate system, taking also into account the feedback effects on the climate of the building of the ice caps.

  7. Parameterization of clouds and radiation in climate models

    Energy Technology Data Exchange (ETDEWEB)

    Roeckner, E. [Max Planck Institute for Meterology, Hamburg (Germany)

    1995-09-01

    Clouds are a very important, yet poorly modeled element in the climate system. There are many potential cloud feedbacks, including those related to cloud cover, height, water content, phase change, and droplet concentration and size distribution. As a prerequisite to studying the cloud feedback issue, this research reports on the simulation and validation of cloud radiative forcing under present climate conditions using the ECHAM general circulation model and ERBE top-of-atmosphere radiative fluxes.

  8. A commentary on the Atlantic meridional overturning circulation stability in climate models

    Science.gov (United States)

    Gent, Peter R.

    2018-02-01

    The stability of the Atlantic meridional overturning circulation (AMOC) in ocean models depends quite strongly on the model formulation, especially the vertical mixing, and whether it is coupled to an atmosphere model. A hysteresis loop in AMOC strength with respect to freshwater forcing has been found in several intermediate complexity climate models and in one fully coupled climate model that has very coarse resolution. Over 40% of modern climate models are in a bistable AMOC state according to the very frequently used simple stability criterion which is based solely on the sign of the AMOC freshwater transport across 33° S. In a recent freshwater hosing experiment in a climate model with an eddy-permitting ocean component, the change in the gyre freshwater transport across 33° S is larger than the AMOC freshwater transport change. This casts very strong doubt on the usefulness of this simple AMOC stability criterion. If a climate model uses large surface flux adjustments, then these adjustments can interfere with the atmosphere-ocean feedbacks, and strongly change the AMOC stability properties. AMOC can be shut off for many hundreds of years in modern fully coupled climate models if the hosing or carbon dioxide forcing is strong enough. However, in one climate model the AMOC recovers after between 1000 and 1400 years. Recent 1% increasing carbon dioxide runs and RCP8.5 future scenario runs have shown that the AMOC reduction is smaller using an eddy-resolving ocean component than in the comparable standard 1° ocean climate models.

  9. Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

    Energy Technology Data Exchange (ETDEWEB)

    Bhatt, Uma S. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Atmospheric Sciences; Wackerbauer, Renate [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Physics; Polyakov, Igor V. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Atmospheric Sciences; Newman, David E. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Physics; Sanchez, Raul E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Fusion Energy Division; Univ. Carlos III de Madrid (Spain)

    2015-11-13

    The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were applied to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.

  10. Chapter 7: Developing climate-informed state-and-transition models

    Science.gov (United States)

    Miles A. Hemstrom; Jessica E. Halofsky; David R. Conklin; Joshua S. Halofsky; Dominique Bachelet; Becky K. Kerns

    2014-01-01

    Land managers and others need ways to understand the potential effects of climate change on local vegetation types and how management activities might be impacted by climate change. To date, climate change impact models have not included localized vegetation communities or the integrated effects of vegetation development dynamics, natural disturbances, and management...

  11. Climate Modeling and Causal Identification for Sea Ice Predictability

    Energy Technology Data Exchange (ETDEWEB)

    Hunke, Elizabeth Clare [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urrego Blanco, Jorge Rolando [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urban, Nathan Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-02-12

    This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments in which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.

  12. Historical and idealized climate model experiments: an EMIC intercomparison

    DEFF Research Database (Denmark)

    Eby, M.; Weaver, A. J.; Alexander, K.

    2012-01-01

    Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE...... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures...... the Medieval Climate Anomaly and the Little Ice Age estimated from paleoclimate reconstructions. This in turn could be a result of errors in the reconstructions of volcanic and/or solar radiative forcing used to drive the models or the incomplete representation of certain processes or variability within...

  13. Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

    Science.gov (United States)

    Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard

    2013-01-01

    Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

  14. Climate simulations for the last interglacial period by means of climate models of different complexity

    Energy Technology Data Exchange (ETDEWEB)

    Montoya, M L [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

    1999-07-01

    Climatic conditions during the lst interglacial (125,000 years before present) are investigated with two climate models of different complexity: The atmosphere-ocean general circulation model ECHAM-1/LSG and the climate system model of intermediate complexity CLIMBER-2. In particular the role of vegetation at the last interglacial maximum, and its importance for a consistent simulation of the Mid-Holocene climate, has been investigated (EU project ASPEN: Air-Sea Wave Processes in Climate Change Models). Comparison of the results of the two models reveals a broad agreement in most large-scale features. Nevertheless, discrepancies are also detected. Essentially, the models differ in their ocean circulation responses. Profiting of the fast turnaround time of CLIMBER-2, a number of sensitivity experiments have been performed to try to explain the possible reasons for these differences, and to analyze additional effects not included in the previous simulations. In particular, the role of vegetation at the last interglacial maximum has been investigated. Comparison of the simulated responses against CLIMAP reconstructed SSTs for Marine Isotope Stage 5e shows a satisfactory agreement within the data uncertainties. (orig.) [German] Die klimatischen Bedingungen waehrend der letzten interglazialen Periode (vor 125 000 Jahren) werden anhand zweier Klimamodelle unterschiedlicher Komplexitaet untersucht: Dem Ozean-Atmosphaere gekoppelten allgemeinen Zirkulationsmodell ECHAM-1/LSG und dem Klimasystemmodell mittlerer Komplexitaet CLIMBER-2. Inbesondere wurde die Rolle der Vegetation in der letzten interglazialen Periode und ihre Bedeutung fuer eine konsistente Simulation des mittelholozaenischen Klimas untersucht (EU-Projekt ASPEN: Air-Sea Wave Processes in Climate Change Models - 'Klimavariationen in historischen Zeiten'). Der Vergleich der Ergebnisse beider Modelle zeigt eine gute Uebereinstimmung der meisten der grossskaligen Eigenschaften, allerdings zeigen sich auch

  15. Climate simulations for the last interglacial period by means of climate models of different complexity

    Energy Technology Data Exchange (ETDEWEB)

    Montoya, M.L. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

    1999-07-01

    Climatic conditions during the lst interglacial (125,000 years before present) are investigated with two climate models of different complexity: The atmosphere-ocean general circulation model ECHAM-1/LSG and the climate system model of intermediate complexity CLIMBER-2. In particular the role of vegetation at the last interglacial maximum, and its importance for a consistent simulation of the Mid-Holocene climate, has been investigated (EU project ASPEN: Air-Sea Wave Processes in Climate Change Models). Comparison of the results of the two models reveals a broad agreement in most large-scale features. Nevertheless, discrepancies are also detected. Essentially, the models differ in their ocean circulation responses. Profiting of the fast turnaround time of CLIMBER-2, a number of sensitivity experiments have been performed to try to explain the possible reasons for these differences, and to analyze additional effects not included in the previous simulations. In particular, the role of vegetation at the last interglacial maximum has been investigated. Comparison of the simulated responses against CLIMAP reconstructed SSTs for Marine Isotope Stage 5e shows a satisfactory agreement within the data uncertainties. (orig.) [German] Die klimatischen Bedingungen waehrend der letzten interglazialen Periode (vor 125 000 Jahren) werden anhand zweier Klimamodelle unterschiedlicher Komplexitaet untersucht: Dem Ozean-Atmosphaere gekoppelten allgemeinen Zirkulationsmodell ECHAM-1/LSG und dem Klimasystemmodell mittlerer Komplexitaet CLIMBER-2. Inbesondere wurde die Rolle der Vegetation in der letzten interglazialen Periode und ihre Bedeutung fuer eine konsistente Simulation des mittelholozaenischen Klimas untersucht (EU-Projekt ASPEN: Air-Sea Wave Processes in Climate Change Models - 'Klimavariationen in historischen Zeiten'). Der Vergleich der Ergebnisse beider Modelle zeigt eine gute Uebereinstimmung der meisten der grossskaligen Eigenschaften, allerdings zeigen sich

  16. Modeling Impacts of Climate Change on Giant Panda Habitat

    Directory of Open Access Journals (Sweden)

    Melissa Songer

    2012-01-01

    Full Text Available Giant pandas (Ailuropoda melanoleuca are one of the most widely recognized endangered species globally. Habitat loss and fragmentation are the main threats, and climate change could significantly impact giant panda survival. We integrated giant panda habitat information with general climate models (GCMs to predict future geographic distribution and fragmentation of giant panda habitat. Results support a major general prediction of climate change—a shift of habitats towards higher elevation and higher latitudes. Our models predict climate change could reduce giant panda habitat by nearly 60% over 70 years. New areas may become suitable outside the current geographic range but much of these areas is far from the current giant panda range and only 15% fall within the current protected area system. Long-term survival of giant pandas will require the creation of new protected areas that are likely to support suitable habitat even if the climate changes.

  17. A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

    Directory of Open Access Journals (Sweden)

    Rachel D. Cavanagh

    2017-09-01

    Full Text Available Increasing concern about the impacts of climate change on ecosystems is prompting ecologists and ecosystem managers to seek reliable projections of physical drivers of change. The use of global climate models in ecology is growing, although drawing ecologically meaningful conclusions can be problematic. The expertise required to access and interpret output from climate and earth system models is hampering progress in utilizing them most effectively to determine the wider implications of climate change. To address this issue, we present a joint approach between climate scientists and ecologists that explores key challenges and opportunities for progress. As an exemplar, our focus is the Southern Ocean, notable for significant change with global implications, and on sea ice, given its crucial role in this dynamic ecosystem. We combined perspectives to evaluate the representation of sea ice in global climate models. With an emphasis on ecologically-relevant criteria (sea ice extent and seasonality we selected a subset of eight models that reliably reproduce extant sea ice distributions. While the model subset shows a similar mean change to the full ensemble in sea ice extent (approximately 50% decline in winter and 30% decline in summer, there is a marked reduction in the range. This improved the precision of projected future sea ice distributions by approximately one third, and means they are more amenable to ecological interpretation. We conclude that careful multidisciplinary evaluation of climate models, in conjunction with ongoing modeling advances, should form an integral part of utilizing model output.

  18. Investigations of the Climate System Response to Climate Engineering in a Hierarchy of Models

    Science.gov (United States)

    McCusker, Kelly E.

    Global warming due to anthropogenic emissions of greenhouse gases is causing negative impacts on diverse ecological and human systems around the globe, and these impacts are projected to worsen as climate continues to warm. In the absence of meaningful greenhouse gas emissions reductions, new strategies have been proposed to engineer the climate, with the aim of preventing further warming and avoiding associated climate impacts. We investigate one such strategy here, falling under the umbrella of `solar radiation management', in which sulfate aerosols are injected into the stratosphere. We use a global climate model with a coupled mixed-layer depth ocean and with a fully-coupled ocean general circulation model to simulate the stabilization of climate by balancing increasing carbon dioxide with increasing stratospheric sulfate concentrations. We evaluate whether or not severe climate impacts, such as melting Arctic sea ice, tropical crop failure, or destabilization of the West Antarctic ice sheet, could be avoided. We find that while tropical climate emergencies might be avoided by use of stratospheric aerosol injections, avoiding polar emergencies cannot be guaranteed due to large residual climate changes in those regions, which are in part due to residual atmospheric circulation anomalies. We also find that the inclusion of a fully-coupled ocean is important for determining the regional climate response because of its dynamical feedbacks. The efficacy of stratospheric sulfate aerosol injections, and solar radiation management more generally, depends on its ability to be maintained indefinitely, without interruption from a variety of possible sources, such as technological failure, a breakdown in global cooperation, lack of funding, or negative unintended consequences. We next consider the scenario in which stratospheric sulfate injections are abruptly terminated after a multi- decadal period of implementation while greenhouse gas emissions have continued unabated

  19. Global climate model performance over Alaska and Greenland

    DEFF Research Database (Denmark)

    Walsh, John E.; Chapman, William L.; Romanovsky, Vladimir

    2008-01-01

    The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958...... to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic....... of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic...

  20. A report on workshops: General circulation model study of climate- chemistry interaction

    International Nuclear Information System (INIS)

    Wei-Chyung, Wang; Isaksen, I.S.A.

    1993-01-01

    This report summarizes the discussion on General Circulation Model Study of Climate-Chemistry Interaction from two workshops, the first held 19--21 August 1992 at Oslo, Norway and the second 26--27 May 1993 at Albany, New York, USA. The workshops are the IAMAP activities under the Trace Constituent Working Group. The main objective of the two workshops was to recommend specific general circulation model (GCM) studies of the ozone distribution and the climatic effect of its changes. The workshops also discussed the climatic implications of increasing sulfate aerosols because of its importance to regional climate. The workshops were organized into four working groups: observation of atmospheric O 3 ; modeling of atmospheric chemical composition; modeling of sulfate aerosols; and aspects of climate modeling

  1. Educational and Scientific Applications of Climate Model Diagnostic Analyzer

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Zhang, J.; Bao, Q.

    2016-12-01

    Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA infrastructure and technology have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences for three years since 2014. In the summer school, the students work on group research projects where CMDA provide datasets and analysis tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. A provenance management system for CMDA is developed to keep track of students' usages of CMDA, and to recommend datasets and analysis tools for their research topic. The provenance system also allows students to revisit their analysis results and share them with their group. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each use case developed is described and listed in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered from the use case, an analysis result such as output plots and data files, and a link to the exact analysis service call with all the input arguments filled. For example, one science use case is the evaluation of NCAR CAM5 model with MODIS total cloud fraction. The analysis service used is Difference Plot Service of

  2. Daily precipitation statistics in regional climate models

    DEFF Research Database (Denmark)

    Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel

    2003-01-01

    An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...

  3. Physical-Socio-Economic Modeling of Climate Change

    Science.gov (United States)

    Chamberlain, R. G.; Vatan, F.

    2008-12-01

    Because of the global nature of climate change, any assessment of the effects of plans, policies, and response to climate change demands a model that encompasses the entire Earth System, including socio- economic factors. Physics-based climate models of the factors that drive global temperatures, rainfall patterns, and sea level are necessary but not sufficient to guide decision making. Actions taken by farmers, industrialists, environmentalists, politicians, and other policy makers may result in large changes to economic factors, international relations, food production, disease vectors, and beyond. These consequences will not be felt uniformly around the globe or even across a given region. Policy models must comprehend all of these considerations. Combining physics-based models of the Earth's climate and biosphere with societal models of population dynamics, economics, and politics is a grand challenge with high stakes. We propose to leverage our recent advances in modeling and simulation of military stability and reconstruction operations to models that address all these areas of concern. Following over twenty years' experience of successful combat simulation, JPL has started developing Minerva, which will add demographic, economic, political, and media/information models to capabilities that already exist. With these new models, for which we have design concepts, it will be possible to address a very wide range of potential national and international problems that were previously inaccessible. Our climate change model builds on Minerva and expands the geographical horizon from playboxes containing regions and neighborhoods to the entire globe. This system consists of a collection of interacting simulation models that specialize in different aspects of the global situation. They will each contribute to and draw from a pool of shared data. The basic models are: the physical model; the demographic model; the political model; the economic model; and the media

  4. Intervention model in organizational climate

    OpenAIRE

    Cárdenas Niño, Lucila; Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias de la Salud, Escuela de Psicología, Hospital Antiguo, Carrera 10 No 16ª05; Arciniegas Rodríguez, Yuly Cristina; Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias de la Salud, Escuela de Psicología, Hospital Antiguo, Carrera 10 No 16ª05; Barrera Cárdenas, Mónica; Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias de la Salud, Escuela de Psicología, Hospital Antiguo, Carrera 10 No 16ª05

    2015-01-01

    The aim of this study was to assess whether the intervention model in organizational climate PMCO, was effective in the Hospital of Yopal, Colombia. The following five phases, proposed by the model, were implemented: 1) problem analysis, 2) awareness, 3) strategies design and planning, at the individual, intergroup, and organizational levels, 4) implementation of the strategy, and 5) process evaluation. A design composed of two groups, experimental and control, was chosen, analyzing whether t...

  5. Documenting Climate Models and Simulations: the ES-DOC Ecosystem in Support of CMIP

    Science.gov (United States)

    Pascoe, C. L.; Guilyardi, E.

    2017-12-01

    The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now non-specialists such as government officials, policy-makers, and the general public, all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. Here we describe the ES-DOC community-govern project to collect and make available documentation of climate models and their simulations for the internationally coordinated modeling activity CMIP6 (Coupled Model Intercomparison Project, Phase 6). An overview of the underlying standards, key properties and features, the evolution from CMIP5, the underlying tools and workflows as well as what modelling groups should expect and how they should engage with the documentation of their contribution to CMIP6 is also presented.

  6. High Resolution Modeling of Hurricanes in a Climate Context

    Science.gov (United States)

    Knutson, T. R.

    2007-12-01

    Modeling of tropical cyclone activity in a climate context initially focused on simulation of relatively weak tropical storm-like disturbances as resolved by coarse grid (200 km) global models. As computing power has increased, multi-year simulations with global models of grid spacing 20-30 km have become feasible. Increased resolution also allowed for simulation storms of increasing intensity, and some global models generate storms of hurricane strength, depending on their resolution and other factors, although detailed hurricane structure is not simulated realistically. Results from some recent high resolution global model studies are reviewed. An alternative for hurricane simulation is regional downscaling. An early approach was to embed an operational (GFDL) hurricane prediction model within a global model solution, either for 5-day case studies of particular model storm cases, or for "idealized experiments" where an initial vortex is inserted into an idealized environments derived from global model statistics. Using this approach, hurricanes up to category five intensity can be simulated, owing to the model's relatively high resolution (9 km grid) and refined physics. Variants on this approach have been used to provide modeling support for theoretical predictions that greenhouse warming will increase the maximum intensities of hurricanes. These modeling studies also simulate increased hurricane rainfall rates in a warmer climate. The studies do not address hurricane frequency issues, and vertical shear is neglected in the idealized studies. A recent development is the use of regional model dynamical downscaling for extended (e.g., season-length) integrations of hurricane activity. In a study for the Atlantic basin, a non-hydrostatic model with grid spacing of 18km is run without convective parameterization, but with internal spectral nudging toward observed large-scale (basin wavenumbers 0-2) atmospheric conditions from reanalyses. Using this approach, our

  7. Introducing an integrated climate change perspective in POPs modelling, monitoring and regulation

    International Nuclear Information System (INIS)

    Lamon, L.; Dalla Valle, M.; Critto, A.; Marcomini, A.

    2009-01-01

    This paper presents a review on the implications of climate change on the monitoring, modelling and regulation of persistent organic pollutants (POPs). Current research gaps are also identified and discussed. Long-term data sets are essential to identify relationships between climate fluctuations and changes in chemical species distribution. Reconstructing the influence of climatic changes on POPs environmental behaviour is very challenging in some local studies, and some insights can be obtained by the few available dated sediment cores or by studying POPs response to inter-annual climate fluctuations. Knowledge gaps and future projections can be studied by developing and applying various modelling tools, identifying compounds susceptibility to climate change, local and global effects, orienting international policies. Long-term monitoring strategies and modelling exercises taking into account climate change should be considered when devising new regulatory plans in chemicals management. - Climate change implications on POPs are addressed here with special attention to monitoring, modelling and regulation issues.

  8. Modelling coffee leaf rust risk in Colombia with climate reanalysis data.

    Science.gov (United States)

    Bebber, Daniel P; Castillo, Ángela Delgado; Gurr, Sarah J

    2016-12-05

    Many fungal plant diseases are strongly controlled by weather, and global climate change is thus likely to have affected fungal pathogen distributions and impacts. Modelling the response of plant diseases to climate change is hampered by the difficulty of estimating pathogen-relevant microclimatic variables from standard meteorological data. The availability of increasingly sophisticated high-resolution climate reanalyses may help overcome this challenge. We illustrate the use of climate reanalyses by testing the hypothesis that climate change increased the likelihood of the 2008-2011 outbreak of Coffee Leaf Rust (CLR, Hemileia vastatrix) in Colombia. We develop a model of germination and infection risk, and drive this model using estimates of leaf wetness duration and canopy temperature from the Japanese 55-Year Reanalysis (JRA-55). We model germination and infection as Weibull functions with different temperature optima, based upon existing experimental data. We find no evidence for an overall trend in disease risk in coffee-growing regions of Colombia from 1990 to 2015, therefore, we reject the climate change hypothesis. There was a significant elevation in predicted CLR infection risk from 2008 to 2011 compared with other years. JRA-55 data suggest a decrease in canopy surface water after 2008, which may have helped terminate the outbreak. The spatial resolution and accuracy of climate reanalyses are continually improving, increasing their utility for biological modelling. Confronting disease models with data requires not only accurate climate data, but also disease observations at high spatio-temporal resolution. Investment in monitoring, storage and accessibility of plant disease observation data are needed to match the quality of the climate data now available.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Authors.

  9. How Does a Regional Climate Model Modify the Projected Climate Change Signal of the Driving GCM: A Study over Different CORDEX Regions Using REMO

    Directory of Open Access Journals (Sweden)

    Claas Teichmann

    2013-06-01

    Full Text Available Global and regional climate model simulations are frequently used for regional climate change assessments and in climate impact modeling studies. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations from different global and regional climate model combinations. To interpret the spread of simulated results, it is useful to understand how the climate change signal is modified in the GCM-RCM modelmodelgeneral circulation model-regional climate model (GCM-RCM chain. This kind of information can also be useful for impact modelers; for the process of experiment design and when interpreting model results. In this study, we investigate how the simulated historical and future climate of the Max-Planck-Institute earth system model (MPI-ESM is modified by dynamic downscaling with the regional model REMO in different world regions. The historical climate simulations for 1950–2005 are driven by observed anthropogenic forcing. The climate projections are driven by projected anthropogenic forcing according to different Representative Concentration Pathways (RCPs. The global simulations are downscaled with REMO over the Coordinated Regional Climate Downscaling Experiment (CORDEX domains Africa, Europe, South America and West Asia from 2006–2100. This unique set of simulations allows for climate type specific analysis across multiple world regions and for multi-scenarios. We used a classification of climate types by Köppen-Trewartha to define evaluation regions with certain climate conditions. A systematic comparison of near-surface temperature and precipitation simulated by the regional and the global model is done. In general, the historical time period is well represented by the GCM and the RCM. Some different biases occur in the RCM compared to the GCM as in the Amazon Basin, northern Africa and the West Asian domain. Both models project similar warming

  10. Impacts of climate change and socio-economic scenarios on flow and water quality of the Ganges, Brahmaputra and Meghna (GBM) river systems: low flow and flood statistics.

    Science.gov (United States)

    Whitehead, P G; Barbour, E; Futter, M N; Sarkar, S; Rodda, H; Caesar, J; Butterfield, D; Jin, L; Sinha, R; Nicholls, R; Salehin, M

    2015-06-01

    The potential impacts of climate change and socio-economic change on flow and water quality in rivers worldwide is a key area of interest. The Ganges-Brahmaputra-Meghna (GBM) is one of the largest river basins in the world serving a population of over 650 million, and is of vital concern to India and Bangladesh as it provides fresh water for people, agriculture, industry, conservation and for the delta system downstream. This paper seeks to assess future changes in flow and water quality utilising a modelling approach as a means of assessment in a very complex system. The INCA-N model has been applied to the Ganges, Brahmaputra and Meghna river systems to simulate flow and water quality along the rivers under a range of future climate conditions. Three model realisations of the Met Office Hadley Centre global and regional climate models were selected from 17 perturbed model runs to evaluate a range of potential futures in climate. In addition, the models have also been evaluated using socio-economic scenarios, comprising (1) a business as usual future, (2) a more sustainable future, and (3) a less sustainable future. Model results for the 2050s and the 2090s indicate a significant increase in monsoon flows under the future climates, with enhanced flood potential. Low flows are predicted to fall with extended drought periods, which could have impacts on water and sediment supply, irrigated agriculture and saline intrusion. In contrast, the socio-economic changes had relatively little impact on flows, except under the low flow regimes where increased irrigation could further reduce water availability. However, should large scale water transfers upstream of Bangladesh be constructed, these have the potential to reduce flows and divert water away from the delta region depending on the volume and timing of the transfers. This could have significant implications for the delta in terms of saline intrusion, water supply, agriculture and maintaining crucial ecosystems such

  11. Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

    Science.gov (United States)

    Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

    2013-12-01

    Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

  12. Impact of the choice of the precipitation reference data set on climate model selection and the resulting climate change signal

    Science.gov (United States)

    Gampe, D.; Ludwig, R.

    2017-12-01

    Regional Climate Models (RCMs) that downscale General Circulation Models (GCMs) are the primary tool to project future climate and serve as input to many impact models to assess the related changes and impacts under such climate conditions. Such RCMs are made available through the Coordinated Regional climate Downscaling Experiment (CORDEX). The ensemble of models provides a range of possible future climate changes around the ensemble mean climate change signal. The model outputs however are prone to biases compared to regional observations. A bias correction of these deviations is a crucial step in the impact modelling chain to allow the reproduction of historic conditions of i.e. river discharge. However, the detection and quantification of model biases are highly dependent on the selected regional reference data set. Additionally, in practice due to computational constraints it is usually not feasible to consider the entire ensembles of climate simulations with all members as input for impact models which provide information to support decision-making. Although more and more studies focus on model selection based on the preservation of the climate model spread, a selection based on validity, i.e. the representation of the historic conditions is still a widely applied approach. In this study, several available reference data sets for precipitation are selected to detect the model bias for the reference period 1989 - 2008 over the alpine catchment of the Adige River located in Northern Italy. The reference data sets originate from various sources, such as station data or reanalysis. These data sets are remapped to the common RCM grid at 0.11° resolution and several indicators, such as dry and wet spells, extreme precipitation and general climatology, are calculate to evaluate the capability of the RCMs to produce the historical conditions. The resulting RCM spread is compared against the spread of the reference data set to determine the related uncertainties and

  13. "On Clocks and Clouds:" Confirming and Interpreting Climate Models as Scientific Hypotheses (Invited)

    Science.gov (United States)

    Donner, L.

    2009-12-01

    The certainty of climate change projected under various scenarios of emissions using general circulation models is an issue of vast societal importance. Unlike numerical weather prediction, a problem to which general circulation models are also applied, projected climate changes usually lie outside of the range of external forcings for which the models generating these changes have been directly evaluated. This presentation views climate models as complex scientific hypotheses and thereby frames these models within a well-defined process of both advancing scientific knowledge and recognizing its limitations. Karl Popper's Logik der Forschung (The Logic of Scientific Discovery, 1934) and 1965 essay “On Clocks and Clouds” capture well the methodologies and challenges associated with constructing climate models. Indeed, the process of a problem situation generating tentative theories, refined by error elimination, characterizes aptly the routine of general circulation model development. Limitations on certainty arise from the distinction Popper perceived in types of natural processes, which he exemplified by clocks, capable of exact measurement, and clouds, subject only to statistical approximation. Remarkably, the representation of clouds in general circulation models remains the key uncertainty in understanding atmospheric aspects of climate change. The asymmetry of hypothesis falsification by negation and much vaguer development of confidence in hypotheses consistent with some of their implications is an important practical challenge to confirming climate models. The presentation will discuss the ways in which predictions made by climate models for observable aspects of the present and past climate can be regarded as falsifiable hypotheses. The presentation will also include reasons why “passing” these tests does not provide complete confidence in predictions about the future by climate models. Finally, I will suggest that a “reductionist” view, in

  14. Predicting climate-induced range shifts: model differences and model reliability.

    Science.gov (United States)

    Joshua J. Lawler; Denis White; Ronald P. Neilson; Andrew R. Blaustein

    2006-01-01

    Predicted changes in the global climate are likely to cause large shifts in the geographic ranges of many plant and animal species. To date, predictions of future range shifts have relied on a variety of modeling approaches with different levels of model accuracy. Using a common data set, we investigated the potential implications of alternative modeling approaches for...

  15. Do projections from bioclimatic envelope models and climate change metrics match?

    DEFF Research Database (Denmark)

    Garcia, Raquel A.; Cabeza, Mar; Altwegg, Res

    2016-01-01

    as indicators of the exposure of species to climate change. Here, we investigate whether these two approaches provide qualitatively similar indications about where biodiversity is potentially most exposed to climate change. Location: Sub-Saharan Africa. Methods: We compared a range of climate change metrics...... for sub-Saharan Africa with ensembles of bioclimatic envelope models for 2723 species of amphibians, snakes, mammals and birds. For each taxonomic group, we performed three comparisons between the two approaches: (1) is projected change in local climatic suitability (models) greater in grid cells...... between the two approaches was found for all taxonomic groups, although it was stronger for species with a narrower climatic envelope breadth. Main conclusions: For sub-Saharan African vertebrates, projected patterns of exposure to climate change given by climate change metrics alone were qualitatively...

  16. Modelling Interglacial Climate

    DEFF Research Database (Denmark)

    Pedersen, Rasmus Anker

    the impact of a changing sea ice cover. The first part focusses on the last interglacial climate (125,000 years before present) which was characterized by substantial warming at high northern latitudes due to an increased insolation during summer. The simulations reveal that the oceanic changes dominate......Past warm climate states could potentially provide information on future global warming. The past warming was driven by changed insolation rather than an increased greenhouse effect, and thus the warm climate states are expected to be different. Nonetheless, the response of the climate system......, with maximum warming occurring in winter. The three scenarios all affect the climate beyond the Arctic, especially the mid-latitude circulation which is sensitive to the location of the ice loss. Together, the results presented in this thesis illustrate that the changes in the Arctic sea ice cover...

  17. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models

    Science.gov (United States)

    Ramírez-Albores, Jorge E.; Bustamante, Ramiro O.

    2016-01-01

    Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of

  18. A Bayesian posterior predictive framework for weighting ensemble regional climate models

    Directory of Open Access Journals (Sweden)

    Y. Fan

    2017-06-01

    Full Text Available We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.

  19. Future bloom and blossom frost risk for Malus domestica considering climate model and impact model uncertainties.

    Science.gov (United States)

    Hoffmann, Holger; Rath, Thomas

    2013-01-01

    The future bloom and risk of blossom frosts for Malus domestica were projected using regional climate realizations and phenological ( = impact) models. As climate impact projections are susceptible to uncertainties of climate and impact models and model concatenation, the significant horizon of the climate impact signal was analyzed by applying 7 impact models, including two new developments, on 13 climate realizations of the IPCC emission scenario A1B. Advancement of phenophases and a decrease in blossom frost risk for Lower Saxony (Germany) for early and late ripeners was determined by six out of seven phenological models. Single model/single grid point time series of bloom showed significant trends by 2021-2050 compared to 1971-2000, whereas the joint signal of all climate and impact models did not stabilize until 2043. Regarding blossom frost risk, joint projection variability exceeded the projected signal. Thus, blossom frost risk cannot be stated to be lower by the end of the 21st century despite a negative trend. As a consequence it is however unlikely to increase. Uncertainty of temperature, blooming date and blossom frost risk projection reached a minimum at 2078-2087. The projected phenophases advanced by 5.5 d K(-1), showing partial compensation of delayed fulfillment of the winter chill requirement and faster completion of the following forcing phase in spring. Finally, phenological model performance was improved by considering the length of day.

  20. High-resolution climate modelling of Antarctica and the Antarctic Peninsula

    NARCIS (Netherlands)

    van Wessem, J.M.|info:eu-repo/dai/nl/413533085

    2016-01-01

    In this thesis we have used a high-resolution regional atmospheric climate model (RACMO2.3) to simulate the present-day climate (1979-2014) of Antarctica and the Antarctic Peninsula. We have evaluated the model results with several observations, such as in situ surface energy balance (SEB)

  1. Climate change, crop yields, and undernutrition: development of a model to quantify the impact of climate scenarios on child undernutrition.

    Science.gov (United States)

    Lloyd, Simon J; Kovats, R Sari; Chalabi, Zaid

    2011-12-01

    Global climate change is anticipated to reduce future cereal yields and threaten food security, thus potentially increasing the risk of undernutrition. The causation of undernutrition is complex, and there is a need to develop models that better quantify the potential impacts of climate change on population health. We developed a model for estimating future undernutrition that accounts for food and nonfood (socioeconomic) causes and can be linked to available regional scenario data. We estimated child stunting attributable to climate change in five regions in South Asia and sub-Saharan Africa (SSA) in 2050. We used current national food availability and undernutrition data to parameterize and validate a global model, using a process-driven approach based on estimations of the physiological relationship between a lack of food and stunting. We estimated stunting in 2050 using published modeled national calorie availability under two climate scenarios and a reference scenario (no climate change). We estimated that climate change will lead to a relative increase in moderate stunting of 1-29% in 2050 compared with a future without climate change. Climate change will have a greater impact on rates of severe stunting, which we estimated will increase by 23% (central SSA) to 62% (South Asia). Climate change is likely to impair future efforts to reduce child malnutrition in South Asia and SSA, even when economic growth is taken into account. Our model suggests that to reduce and prevent future undernutrition, it is necessary to both increase food access and improve socioeconomic conditions, as well as reduce greenhouse gas emissions.

  2. Misleading prioritizations from modelling range shifts under climate change

    Science.gov (United States)

    Sofaer, Helen R.; Jarnevich, Catherine S.; Flather, Curtis H.

    2018-01-01

    AimConservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change.LocationConterminous U.S.A.Time period1977–2014.Major taxa studiedPasserine birds.MethodsWe estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c. 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size.ResultsSpecies distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species.Main conclusionsModels failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and

  3. Can we trust climate models to realistically represent severe European windstorms?

    Science.gov (United States)

    Trzeciak, Tomasz M.; Knippertz, Peter; Owen, Jennifer S. R.

    2014-05-01

    Despite the enormous advances made in climate change research, robust projections of the position and the strength of the North Atlantic stormtrack are not yet possible. In particular with respect to damaging windstorms, this incertitude bears enormous risks to European societies and the (re)insurance industry. Previous studies have addressed the problem of climate model uncertainty through statistical comparisons of simulations of the current climate with (re-)analysis data and found that there is large disagreement between different climate models, different ensemble members of the same model and observed climatologies of intense cyclones. One weakness of such statistical evaluations lies in the difficulty to separate influences of the climate model's basic state from the influence of fast processes on the development of the most intense storms. Compensating effects between the two might conceal errors and suggest higher reliability than there really is. A possible way to separate influences of fast and slow processes in climate projections is through a "seamless" approach of hindcasting historical, severe storms with climate models started from predefined initial conditions and run in a numerical weather prediction mode on the time scale of several days. Such a cost-effective case-study approach, which draws from and expands on the concepts from the Transpose-AMIP initiative, has recently been undertaken in the SEAMSEW project at the University of Leeds funded by the AXA Research Fund. Key results from this work focusing on 20 historical storms and using different lead times and horizontal and vertical resolutions include: (a) Tracks are represented reasonably well by most hindcasts. (b) Sensitivity to vertical resolution is low. (c) There is a systematic underprediction of cyclone depth for a coarse resolution of T63, but surprisingly no systematic bias is found for higher-resolution runs using T127, showing that climate models are in fact able to represent the

  4. Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific

    Science.gov (United States)

    Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B.

    2015-12-01

    Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study.

  5. Biodiversity and Climate Modeling Workshop Series: Identifying gaps and needs for improving large-scale biodiversity models

    Science.gov (United States)

    Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.

    2017-12-01

    At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.

  6. THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE.

    Science.gov (United States)

    Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

    2015-10-01

    The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran's universities. This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran's public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran's libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries.

  7. Integration of climatic indices in an objective probabilistic model for establishing and mapping viticultural climatic zones in a region

    Science.gov (United States)

    Moral, Francisco J.; Rebollo, Francisco J.; Paniagua, Luis L.; García, Abelardo; Honorio, Fulgencio

    2016-05-01

    Different climatic indices have been proposed to determine the wine suitability in a region. Some of them are related to the air temperature, but the hydric component of climate should also be considered which, in turn, is influenced by the precipitation during the different stages of the grapevine growing and ripening periods. In this study, we propose using the information obtained from ten climatic indices [heliothermal index (HI), cool night index (CI), dryness index (DI), growing season temperature (GST), the Winkler index (WI), September mean thermal amplitude (MTA), annual precipitation (AP), precipitation during flowering (PDF), precipitation before flowering (PBF), and summer precipitation (SP)] as inputs in an objective and probabilistic model, the Rasch model, with the aim of integrating the individual effects of them, obtaining the climate data that summarize all main climatic indices, which could influence on wine suitability from a climate viewpoint, and utilizing the Rasch measures to generate homogeneous climatic zones. The use of the Rasch model to estimate viticultural climatic suitability constitutes a new application of great practical importance, enabling to rationally determine locations in a region where high viticultural potential exists and establishing a ranking of the climatic indices which exerts an important influence on wine suitability in a region. Furthermore, from the measures of viticultural climatic suitability at some locations, estimates can be computed using a geostatistical algorithm, and these estimates can be utilized to map viticultural climatic zones in a region. To illustrate the process, an application to Extremadura, southwestern Spain, is shown.

  8. An Examination of the Hadley Sea-Surface Temperature Time Series for the Nino 3.4 Region

    Science.gov (United States)

    Wilson, Robert M.

    2010-01-01

    The Hadley sea-surface temperature (HadSST) dataset is investigated for the interval 1871-2008. The purpose of this investigation is to determine the degree of success in identifying and characterizing El Nino (EN) southern (ENSO) extreme events, both EN and La Nina (LN) events. Comparisons are made against both the Southern Oscillation Index for the same time interval and with published values of the Oceanic Nino Index for the interval since 1950. Some 60 ENSO extreme events are identified in the HadSST dataset, consisting of 33 EN and 27 LN events. Also, preferential associations are found to exist between the duration of ENSO extreme events and their maximum anomalous excursion temperatures and between the recurrence rate for an EN event and the duration of the last known EN event. Because the present ongoing EN is a strong event, it should persist 11 months or longer, inferring that the next EN event should not be expected until June 2012 or later. Furthermore, the decadal sum of EN-related months is found to have increased somewhat steadily since the decade of 1920-1929, suggesting that the present decade (2010-2019) possibly will see about 3-4 EN events, totaling about 37 +/- 3 EN-related months (i.e., months that meet the definition for the occurrence of an EN event).

  9. Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

    Science.gov (United States)

    Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

    2012-01-01

    Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

  10. Is the climate right for pleistocene rewilding? Using species distribution models to extrapolate climatic suitability for mammals across continents.

    Directory of Open Access Journals (Sweden)

    Orien M W Richmond

    Full Text Available Species distribution models (SDMs are increasingly used for extrapolation, or predicting suitable regions for species under new geographic or temporal scenarios. However, SDM predictions may be prone to errors if species are not at equilibrium with climatic conditions in the current range and if training samples are not representative. Here the controversial "Pleistocene rewilding" proposal was used as a novel example to address some of the challenges of extrapolating modeled species-climate relationships outside of current ranges. Climatic suitability for three proposed proxy species (Asian elephant, African cheetah and African lion was extrapolated to the American southwest and Great Plains using Maxent, a machine-learning species distribution model. Similar models were fit for Oryx gazella, a species native to Africa that has naturalized in North America, to test model predictions. To overcome biases introduced by contracted modern ranges and limited occurrence data, random pseudo-presence points generated from modern and historical ranges were used for model training. For all species except the oryx, models of climatic suitability fit to training data from historical ranges produced larger areas of predicted suitability in North America than models fit to training data from modern ranges. Four naturalized oryx populations in the American southwest were correctly predicted with a generous model threshold, but none of these locations were predicted with a more stringent threshold. In general, the northern Great Plains had low climatic suitability for all focal species and scenarios considered, while portions of the southern Great Plains and American southwest had low to intermediate suitability for some species in some scenarios. The results suggest that the use of historical, in addition to modern, range information and randomly sampled pseudo-presence points may improve model accuracy. This has implications for modeling range shifts of

  11. Simulation of recent and future climates using CNRM and IPSL models

    International Nuclear Information System (INIS)

    Dufresne, J.L.; Bony, S.; Fairhead, L.; Grandpeix, J.Y.; Hourdin, F.; Idelkadi, A.; Musat, I.; Salas y Melia, D.; Tyteca, S.; Chauvin, F.; Deque, M.; Douville, H.; Gueremy, J.F.; Marquet, P.; Planton, S.; Royer, J.F.; Voldoire, A.; Denvil, S.; Cadule, P.; Foujols, M.A.; Arzel, O.; Fichefet, T.; Krinner, G.; Levy, C.; Madec, G.

    2006-01-01

    In support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) that should appear in early 2007, modelling groups world-wide have performed a huge coordinated exercise of climate change runs for the 20. and 21. centuries. In this paper we present the results of the two French climate models, CNRM and IPSL. In particular we emphasize the progress made since the previous IPCC report and we identify which results are comparable among models and which strongly differ. (authors)

  12. A discrete-continuous choice model of climate change impacts on energy

    International Nuclear Information System (INIS)

    Morrison, W.N.; Mendelsohn, R.

    1998-01-01

    This paper estimates a discrete-continuous fuel choice model in order to explore climate impacts on the energy sector. The model is estimated on a national data set of firms and households. The results reveal that actors switch from oil in cold climates to electricity and natural gas in warm climates and that fuel-specific expenditures follow a U-shaped relationship with respect to temperature. The model implies that warming will increase American energy expenditures, reflecting a sizable welfare damage

  13. Bayesian hierarchical models for regional climate reconstructions of the last glacial maximum

    Science.gov (United States)

    Weitzel, Nils; Hense, Andreas; Ohlwein, Christian

    2017-04-01

    Spatio-temporal reconstructions of past climate are important for the understanding of the long term behavior of the climate system and the sensitivity to forcing changes. Unfortunately, they are subject to large uncertainties, have to deal with a complex proxy-climate structure, and a physically reasonable interpolation between the sparse proxy observations is difficult. Bayesian Hierarchical Models (BHMs) are a class of statistical models that is well suited for spatio-temporal reconstructions of past climate because they permit the inclusion of multiple sources of information (e.g. records from different proxy types, uncertain age information, output from climate simulations) and quantify uncertainties in a statistically rigorous way. BHMs in paleoclimatology typically consist of three stages which are modeled individually and are combined using Bayesian inference techniques. The data stage models the proxy-climate relation (often named transfer function), the process stage models the spatio-temporal distribution of the climate variables of interest, and the prior stage consists of prior distributions of the model parameters. For our BHMs, we translate well-known proxy-climate transfer functions for pollen to a Bayesian framework. In addition, we can include Gaussian distributed local climate information from preprocessed proxy records. The process stage combines physically reasonable spatial structures from prior distributions with proxy records which leads to a multivariate posterior probability distribution for the reconstructed climate variables. The prior distributions that constrain the possible spatial structure of the climate variables are calculated from climate simulation output. We present results from pseudoproxy tests as well as new regional reconstructions of temperatures for the last glacial maximum (LGM, ˜ 21,000 years BP). These reconstructions combine proxy data syntheses with information from climate simulations for the LGM that were

  14. Modelling the regional effects of climate change on air quality

    International Nuclear Information System (INIS)

    Giorgi, F.; Meleux, F.

    2007-01-01

    The life cycle of pollutants is affected by chemical as well as meteorological factors, such as wind, temperature, precipitation, solar radiation. Therefore, climatic changes induced by anthropogenic emissions of greenhouse gases may be expected to have significant effects on air quality. Because of the spatial variability of the pollutant emissions and climate-change signals, these effects are particularly relevant at the regional to local scales. This paper first briefly reviews modelling tools and methodologies used to study regional climate-change impacts on air quality. Patterns of regional precipitation, temperature, and sea-level changes emerging from the latest set of general circulation model projections are then discussed. Finally, the specific case of climate-change effects on summer ozone concentrations over Europe is presented to illustrate the potential impacts of climate change on pollutant amounts. It is concluded that climate change is an important factor that needs to be taken into account when designing future pollution-reduction policies. (authors)

  15. High-resolution regional climate model evaluation using variable-resolution CESM over California

    Science.gov (United States)

    Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

    2015-12-01

    Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine

  16. Land use allocation model considering climate change impact

    Science.gov (United States)

    Lee, D. K.; Yoon, E. J.; Song, Y. I.

    2017-12-01

    In Korea, climate change adaptation plans are being developed for each administrative district based on impact assessments constructed in various fields. This climate change impact assessments are superimposed on the actual space, which causes problems in land use allocation because the spatial distribution of individual impacts may be different each other. This implies that trade-offs between climate change impacts can occur depending on the composition of land use. Moreover, the actual space is complexly intertwined with various factors such as required area, legal regulations, and socioeconomic values, so land use allocation in consideration of climate change can be very difficult problem to solve (Liu et al. 2012; Porta et al. 2013).Optimization techniques can generate a sufficiently good alternatives for land use allocation at the strategic level if only the fitness function of relationship between impact and land use composition are derived. It has also been noted that land use optimization model is more effective than the scenario-based prediction model in achieving the objectives for problem solving (Zhang et al. 2014). Therefore in this study, we developed a quantitative tool, MOGA (Multi Objective Genetic Algorithm), which can generate a comprehensive land use allocations considering various climate change impacts, and apply it to the Gangwon-do in Korea. Genetic Algorithms (GAs) are the most popular optimization technique to address multi-objective in land use allocation. Also, it allows for immediate feedback to stake holders because it can run a number of experiments with different parameter values. And it is expected that land use decision makers and planners can formulate a detailed spatial plan or perform additional analysis based on the result of optimization model. Acknowledgments: This work was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program (Project number: 2014001310006)"

  17. Toward a consistent modeling framework to assess multi-sectoral climate impacts.

    Science.gov (United States)

    Monier, Erwan; Paltsev, Sergey; Sokolov, Andrei; Chen, Y-H Henry; Gao, Xiang; Ejaz, Qudsia; Couzo, Evan; Schlosser, C Adam; Dutkiewicz, Stephanie; Fant, Charles; Scott, Jeffery; Kicklighter, David; Morris, Jennifer; Jacoby, Henry; Prinn, Ronald; Haigh, Martin

    2018-02-13

    Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.

  18. Cpl6: The New Extensible, High-Performance Parallel Coupler forthe Community Climate System Model

    Energy Technology Data Exchange (ETDEWEB)

    Craig, Anthony P.; Jacob, Robert L.; Kauffman, Brain; Bettge,Tom; Larson, Jay; Ong, Everest; Ding, Chris; He, Yun

    2005-03-24

    Coupled climate models are large, multiphysics applications designed to simulate the Earth's climate and predict the response of the climate to any changes in the forcing or boundary conditions. The Community Climate System Model (CCSM) is a widely used state-of-art climate model that has released several versions to the climate community over the past ten years. Like many climate models, CCSM employs a coupler, a functional unit that coordinates the exchange of data between parts of climate system such as the atmosphere and ocean. This paper describes the new coupler, cpl6, contained in the latest version of CCSM,CCSM3. Cpl6 introduces distributed-memory parallelism to the coupler, a class library for important coupler functions, and a standardized interface for component models. Cpl6 is implemented entirely in Fortran90 and uses Model Coupling Toolkit as the base for most of its classes. Cpl6 gives improved performance over previous versions and scales well on multiple platforms.

  19. ESCAPE: an integrated climate model for the EC

    International Nuclear Information System (INIS)

    Rotmans, J.

    1992-01-01

    A framework has been developed for the evaluation of policy options for climate change, called ESCAPE (Evaluation of Strategies to address Climate change by Adapting to and Preventing Emissions). ESCAPE consists of a suite of linked models which enables scenarios of greenhouse gas emissions to be constructed and their impact on global and regional climate and sea level and sectors of the European economy to be assessed. Conclusions resulting from simulations with the ESCAPE 1.1 model include: the major problem of a climate change for the EC is a sea level rise; Greece, Italy, Portugal and Spain will be faced with higher costs in the agricultural sector; worldwide implementation of an EC carbon tax leads to about 12% lower worldwide CO 2 emissions; to stabilize CO 2 emissions an Ecotax of 18 dollars per barrel would be required; and in all cases the rate of global temperature increase will be above the rate of 0.1 degree C per decade for the coming 40 years. 2 figs

  20. Decomposing the uncertainty in climate impact projections of Dynamic Vegetation Models: a test with the forest models LANDCLIM and FORCLIM

    Science.gov (United States)

    Cailleret, Maxime; Snell, Rebecca; von Waldow, Harald; Kotlarski, Sven; Bugmann, Harald

    2015-04-01

    Different levels of uncertainty should be considered in climate impact projections by Dynamic Vegetation Models (DVMs), particularly when it comes to managing climate risks. Such information is useful to detect the key processes and uncertainties in the climate model - impact model chain and may be used to support recommendations for future improvements in the simulation of both climate and biological systems. In addition, determining which uncertainty source is dominant is an important aspect to recognize the limitations of climate impact projections by a multi-model ensemble mean approach. However, to date, few studies have clarified how each uncertainty source (baseline climate data, greenhouse gas emission scenario, climate model, and DVM) affects the projection of ecosystem properties. Focusing on one greenhouse gas emission scenario, we assessed the uncertainty in the projections of a forest landscape model (LANDCLIM) and a stand-scale forest gap model (FORCLIM) that is caused by linking climate data with an impact model. LANDCLIM was used to assess the uncertainty in future landscape properties of the Visp valley in Switzerland that is due to (i) the use of different 'baseline' climate data (gridded data vs. data from weather stations), and (ii) differences in climate projections among 10 GCM-RCM chains. This latter point was also considered for the projections of future forest properties by FORCLIM at several sites along an environmental gradient in Switzerland (14 GCM-RCM chains), for which we also quantified the uncertainty caused by (iii) the model chain specific statistical properties of the climate time-series, and (iv) the stochasticity of the demographic processes included in the model, e.g., the annual number of saplings that establish, or tree mortality. Using methods of variance decomposition analysis, we found that (i) The use of different baseline climate data strongly impacts the prediction of forest properties at the lowest and highest, but

  1. The Bern Simple Climate Model (BernSCM) v1.0: an extensible and fully documented open-source re-implementation of the Bern reduced-form model for global carbon cycle-climate simulations

    Science.gov (United States)

    Strassmann, Kuno M.; Joos, Fortunat

    2018-05-01

    The Bern Simple Climate Model (BernSCM) is a free open-source re-implementation of a reduced-form carbon cycle-climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRFs). The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near-linear behavior. Illustrative simulations of scenarios from previous multimodel studies show that BernSCM is broadly representative of the range of the climate-carbon cycle response simulated by more complex and detailed models. Model code (in Fortran) was written from scratch with transparency and extensibility in mind, and is provided open source. BernSCM makes scientifically sound carbon cycle-climate modeling available for many applications. Supporting up to decadal time steps with high accuracy, it is suitable for studies with high computational load and for coupling with integrated assessment models (IAMs), for example. Further applications include climate risk assessment in a business, public, or educational context and the estimation of CO2 and climate benefits of emission mitigation options.

  2. Climate change and watershed mercury export: a multiple projection and model analysis.

    Science.gov (United States)

    Golden, Heather E; Knightes, Christopher D; Conrads, Paul A; Feaster, Toby D; Davis, Gary M; Benedict, Stephen T; Bradley, Paul M

    2013-09-01

    Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling. Copyright © 2013 SETAC.

  3. Climate change and watershed mercury export: a multiple projection and model analysis

    Science.gov (United States)

    Golden, Heather E.; Knightes, Christopher D.; Conrads, Paul; Feaster, Toby D.; Davis, Gary M.; Benedict, Stephen T.; Bradley, Paul M.

    2013-01-01

    Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

  4. European Climate - Energy Security Nexus. A model based scenario analysis

    International Nuclear Information System (INIS)

    Criqui, Patrick; Mima, Silvana

    2011-01-01

    In this research, we have provided an overview of the climate-security nexus in the European sector through a model based scenario analysis with POLES model. The analysis underline that under stringent climate policies, Europe take advantage of a double dividend in its capacity to develop a new cleaner energy model and in lower vulnerability to potential shocks on the international energy markets. (authors)

  5. AMOC decadal variability in Earth system models: Mechanisms and climate impacts

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, Alexey [Yale Univ., New Haven, CT (United States)

    2017-09-06

    This is the final report for the project titled "AMOC decadal variability in Earth system models: Mechanisms and climate impacts". The central goal of this one-year research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) within a hierarchy of climate models ranging from realistic ocean GCMs to Earth system models. The AMOC is a key element of ocean circulation responsible for oceanic transport of heat from low to high latitudes and controlling, to a large extent, climate variations in the North Atlantic. The questions of the AMOC stability, variability and predictability, directly relevant to the questions of climate predictability, were at the center of the research work.

  6. Simulation of recent and future climates using CNRM and IPSL models; Simulation du climat recent et futur par les modeles du CNRM et de l'IPSL

    Energy Technology Data Exchange (ETDEWEB)

    Dufresne, J.L.; Bony, S.; Fairhead, L.; Grandpeix, J.Y.; Hourdin, F.; Idelkadi, A.; Musat, I. [Universite Pierre et Marie Curie, Lab. de Meteorologie Dynamique (LMD-IPSL), CNRS, 75 - Paris (France); Salas y Melia, D.; Tyteca, S.; Chauvin, F.; Deque, M.; Douville, H.; Gueremy, J.F.; Marquet, P.; Planton, S.; Royer, J.F.; Voldoire, A. [Meteo France Centre National de Recherches Meteorologiques, 31 - Toulouse (France); Denvil, S.; Cadule, P.; Foujols, M.A. [Universite Pierre et Marie Curie, Institut Pierre-Simon Laplace, CNRS, 75 - Paris (France); Arzel, O.; Fichefet, T. [Universite Catholique de Louvain (UCL), Louvain-la-Neuve (Belgium). Inst. d' Astronomie et de Geophysique G. Lemaitre; Braconnot, P.; Brockmann, P.; Caubel, A.; Friedlingstein, P.; Marti, O.; Swingedouw, D. [Laboratoire des Sciences du Climat et de l' Environnement, Domaine du CNRS, 91 - Gif Sur Yvette (France); Krinner, G. [Universite Joseph-Fourier, Grenoble I, Lab. de Glaciologie et Geophysique de l' Environnement (LGGE), CNRS, 38 - Saint Martin d' Heres (France); Levy, C.; Madec, G. [Universite Pierre et Marie Curie, Lab. d' Oceanographie et Climat (Locean-IPLS), CNRS, 75 - Paris (France)

    2006-11-15

    In support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) that should appear in early 2007, modelling groups world-wide have performed a huge coordinated exercise of climate change runs for the 20. and 21. centuries. In this paper we present the results of the two French climate models, CNRM and IPSL. In particular we emphasize the progress made since the previous IPCC report and we identify which results are comparable among models and which strongly differ. (authors)

  7. Updating known distribution models for forecasting climate change impact on endangered species.

    Science.gov (United States)

    Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo

    2013-01-01

    To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only.

  8. On the Baltic Sea Response to Climate Change: Model Implications

    International Nuclear Information System (INIS)

    Omstedt, Anders; Leppaeranta, Matti

    1999-01-01

    The sensitivity of the Baltic Sea to climate change is reviewed on the basis of recent model studies. In general, the presently available models indicate that the Baltic Sea is a most sensitive system to climate change, particularly in air temperature, wind, fresh water inflow and the barotropic forcing in the entrance area. Available scenarios for ice conditions and climate warming around year 2100 show 2-3 months' shortening of the ice season in the Bothnian Bay and about 0.4 m decrease in the maximum annual ice thickness. Corresponding scenarios for climate cooling show 1-2 months' longer ice season in the Bothnian Bay and 0.2 - 0.5 m increase in the maximum annual ice thickness

  9. Agent Model Development for Assessing Climate-Induced Geopolitical Instability.

    Energy Technology Data Exchange (ETDEWEB)

    Boslough, Mark B.; Backus, George A.

    2005-12-01

    We present the initial stages of development of new agent-based computational methods to generate and test hypotheses about linkages between environmental change and international instability. This report summarizes the first year's effort of an originally proposed three-year Laboratory Directed Research and Development (LDRD) project. The preliminary work focused on a set of simple agent-based models and benefited from lessons learned in previous related projects and case studies of human response to climate change and environmental scarcity. Our approach was to define a qualitative model using extremely simple cellular agent models akin to Lovelock's Daisyworld and Schelling's segregation model. Such models do not require significant computing resources, and users can modify behavior rules to gain insights. One of the difficulties in agent-based modeling is finding the right balance between model simplicity and real-world representation. Our approach was to keep agent behaviors as simple as possible during the development stage (described herein) and to ground them with a realistic geospatial Earth system model in subsequent years. This work is directed toward incorporating projected climate data--including various C02 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report--and ultimately toward coupling a useful agent-based model to a general circulation model.3

  10. High-resolution integration of water, energy, and climate models to assess electricity grid vulnerabilities to climate change

    Science.gov (United States)

    Meng, M.; Macknick, J.; Tidwell, V. C.; Zagona, E. A.; Magee, T. M.; Bennett, K.; Middleton, R. S.

    2017-12-01

    The U.S. electricity sector depends on large amounts of water for hydropower generation and cooling thermoelectric power plants. Variability in water quantity and temperature due to climate change could reduce the performance and reliability of individual power plants and of the electric grid as a system. While studies have modeled water usage in power systems planning, few have linked grid operations with physical water constraints or with climate-induced changes in water resources to capture the role of the energy-water nexus in power systems flexibility and adequacy. In addition, many hydrologic and hydropower models have a limited representation of power sector water demands and grid interaction opportunities of demand response and ancillary services. A multi-model framework was developed to integrate and harmonize electricity, water, and climate models, allowing for high-resolution simulation of the spatial, temporal, and physical dynamics of these interacting systems. The San Juan River basin in the Southwestern U.S., which contains thermoelectric power plants, hydropower facilities, and multiple non-energy water demands, was chosen as a case study. Downscaled data from three global climate models and predicted regional water demand changes were implemented in the simulations. The Variable Infiltration Capacity hydrologic model was used to project inflows, ambient air temperature, and humidity in the San Juan River Basin. Resulting river operations, water deliveries, water shortage sharing agreements, new water demands, and hydroelectricity generation at the basin-scale were estimated with RiverWare. The impacts of water availability and temperature on electric grid dispatch, curtailment, cooling water usage, and electricity generation cost were modeled in PLEXOS. Lack of water availability resulting from climate, new water demands, and shortage sharing agreements will require thermoelectric generators to drastically decrease power production, as much as 50

  11. Paladin Enterprises: Monolithic particle physics models global climate.

    CERN Multimedia

    2002-01-01

    Paladin Enterprises presents a monolithic particle model of the universe which will be used by them to build an economical fusion energy system. The model is an extension of the work done by James Clerk Maxwell. Essentially, gravity is unified with electro-magnetic forces and shown to be a product of a closed loop current system, i.e. a particle - monolithic or sub atomic. This discovery explains rapid global climate changes which are evident in the geological record and also provides an explanation for recent changes in the global climate.

  12. Evaluating the impacts of climate change on diurnal wind power cycles using multiple regional climate models

    KAUST Repository

    Goddard, Scott D.

    2015-05-01

    Electrical utility system operators must plan resources so that electricity supply matches demand throughout the day. As the proportion of wind-generated electricity in the US grows, changes in daily wind patterns have the potential either to disrupt the utility or increase the value of wind to the system over time. Wind power projects are designed to last many years, so at this timescale, climate change may become an influential factor on wind patterns. We examine the potential effects of climate change on the average diurnal power production cycles at 12 locations in North America by analyzing averaged and individual output from nine high-resolution regional climate models comprising historical (1971–1999) and future (2041–2069) periods. A semi-parametric mixed model is fit using cubic B-splines, and model diagnostics are checked. Then, a likelihood ratio test is applied to test for differences between the time periods in the seasonal daily averaged cycles, and agreement among the individual regional climate models is assessed. We investigate the significant changes by combining boxplots with a differencing approach and identify broad categories of changes in the amplitude, shape, and position of the average daily cycles. We then discuss the potential impact of these changes on wind power production.

  13. Use of System Thinking Software for Determining Climate Change Impacts in Water Balance for the Rio Yaqui Basin, Sonora, Mexico

    Science.gov (United States)

    Tapia, E. M.; Minjarez, J. I.; Espinoza, I. G.; Sosa, C. M.

    2013-05-01

    Climate change in Northwestern Mexico and its hydrological impact on water balance, water scarcity and flooding events, has become a matter of increasing concern over the past several decades due to the region's semiarid conditions. Changes in temperature, precipitation, and sea level will affect agriculture, farming, and aquaculture, in addition to compromising the quality of water resources for human consumption. According to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2007), Global Circulation Models (GCMs) can provide reliable estimations of future climate conditions in addition to atmospheric processes that cause them, based on different input scenarios such as A2 (higher emission of greenhouse gases) and B1 (lower emission of GHG), among others. However, GCM`s resolution results to coarse in regions which have high space and time climate variability. To remediate this, several methods based on dynamical, statistical and empirical analysis have been proposed for downcaling. In this study, we evaluate possible changes in precipitation and temperature for the "Rio Yaqui Basin" in Sonora, Mexico and assess the impact of such changes on runoff, evapotranspiration and aquifer recharge for the 2010-2099 period of time. For this purpose, we analyzed the results of a Bias Corrected and Downscaled Climate Projection from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset: UKMO-HADCM3 from the Hadley Centre for Climate Prediction. Northwest Mexico is under the influence of the North American Monsoon (NAM), a system affecting the states of Sinaloa and Sonora where the precipitation regimes change drastically during the summer months of June, July and August. It is associated to the sharp variations of topography, precipitation and temperature regimes in the region, so the importance of analyzing the downscaled climate projections. The Rio Yaqui Basin is one of

  14. Software Testing and Verification in Climate Model Development

    Science.gov (United States)

    Clune, Thomas L.; Rood, RIchard B.

    2011-01-01

    Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

  15. Modeling forest dynamics along climate gradients in Bolivia

    Science.gov (United States)

    Seiler, C.; Hutjes, R. W. A.; Kruijt, B.; Quispe, J.; Añez, S.; Arora, V. K.; Melton, J. R.; Hickler, T.; Kabat, P.

    2014-05-01

    Dynamic vegetation models have been used to assess the resilience of tropical forests to climate change, but the global application of these modeling experiments often misrepresents carbon dynamics at a regional level, limiting the validity of future projections. Here a dynamic vegetation model (Lund Potsdam Jena General Ecosystem Simulator) was adapted to simulate present-day potential vegetation as a baseline for climate change impact assessments in the evergreen and deciduous forests of Bolivia. Results were compared to biomass measurements (819 plots) and remote sensing data. Using regional parameter values for allometric relations, specific leaf area, wood density, and disturbance interval, a realistic transition from the evergreen Amazon to the deciduous dry forest was simulated. This transition coincided with threshold values for precipitation (1400 mm yr-1) and water deficit (i.e., potential evapotranspiration minus precipitation) (-830 mm yr-1), beyond which leaf abscission became a competitive advantage. Significant correlations were found between modeled and observed values of seasonal leaf abscission (R2 = 0.6, p days. Decreasing rainfall trends were simulated to reduce GPP in the Amazon. The current model setup provides a baseline for assessing the potential impacts of climate change in the transition zone from wet to dry tropical forests in Bolivia.

  16. Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models.

    Science.gov (United States)

    Beauregard, Frieda; de Blois, Sylvie

    2014-01-01

    Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential

  17. Basis of a formal language for facilitating communication among climate modelers

    Energy Technology Data Exchange (ETDEWEB)

    Elia, Ramon de [Climate Analysis Team, Consortium Ouranos, Montreal, QC (Canada); Universite du Quebec a Montreal, Centre ESCER, Montreal, QC (Canada)

    2012-08-15

    The objective of this work is to present the basis for a formal language that aims to express in a concise way some fundamental beliefs held within the climate research community. The expression of this set of beliefs takes the form of relations, conjectures or propositions that describe characteristics of different aspects of climate modeling. Examples are constructed using topics that are much discussed within the climate modeling community. The article first introduces, as elements of this formal language, models considered a priori (the model as a code or algorithm) or a posteriori (the model as output), and then presents different relations between these elements. The most important relation is that of dominance, which helps to define the superiority of one model over another based on which model a rational agent will choose. Various kinds of dominance are considered. Also presented in a formal language are propositions and conjectures relating to model development, model calibration and climate change ensemble projections, each of which are held with diverse levels of acceptance within the climate modeling community. In addition, the relevance of defining elements - models - whose existence is improbable, such as bug-free model versions, is discussed. Although the potential value of this language is shown, there remains a need to improve the definitions presented here, as some of them remain unsatisfying. Still, we believe that this attempt may help us not only communicate more clearly but also to better distinguish different schools of thought that currently exist within the community. (orig.)

  18. Assessment of spatiotemporal variations in the fluvial wash-load component in the 21st century with regard to GCM climate change scenarios.

    Science.gov (United States)

    Mouri, Goro

    2015-11-15

    For stream water, in which a relationship exists between wash-load concentration and discharge, an estimate of fine-sediment delivery may be obtained from a traditional fluvial wash-load rating curve. Here, we demonstrate that the remaining wash-load material load can be estimated from a traditional empirical principle on a nationwide scale. The traditional technique was applied to stream water for the whole of Japan. Four typical GCMs were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields for the following regional climate models to assess the wash-load component based on rating curves: the Model for Interdisciplinary Research on Climate (MIROC), the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), the Hadley Centre Global Environment Model (HadGEM) and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model. The simulations consisted of an ensemble, including multiple physics configurations and different Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5), which was used to produce monthly datasets for the whole country of Japan. The impacts of future climate changes on fluvial wash load in Japanese stream water were based on the balance of changes in hydrological factors. The annual and seasonal variations of the fluvial wash load were assessed from the result of the ensemble analysis in consideration of the Greenhouse Gas (GHG) emission scenarios. The determined results for the amount of wash load increase range from approximately 20 to 110% in the 2040s, especially along part of the Pacific Ocean and the Sea of Japan regions. In the 2090s, the amount of wash load is projected to increase by more than 50% over the whole of Japan. The assessment indicates that seasonal variation is particularly important because the rainy and typhoon seasons, which include extreme events, are the dominant seasons. Because fluvial wash-load-component turbidity

  19. A model of the responses of ecotones to climate change

    Energy Technology Data Exchange (ETDEWEB)

    Noble, I.R. (Australian National University, Canberra, ACT (Australia). Research School of Biological Sciences, Ecosystem Dynamics Group)

    1993-08-01

    It has been suggested that global climatic change may be detected by monitoring the positions of ecotones. The author built a model of the dynamics of ecotones similar to those found in altitudinal or latitudinal treelines, where a slow tendency for the ecotone to advance is counterbalanced by disturbances such as fire or landslides. The model showed that the response of such ecotones to a wide range of simulated climate changes was slow and that the ecotone front was dissected. It would appear that such ecotones would not make suitable sites for monitoring climate change.

  20. Mid-late Holocene changes in the El Niño Southern Oscillation and Hadley Cell intensity; their effect on sea-surface conditions in the mid-latitude southeast Pacific Ocean (41°S)

    OpenAIRE

    Verleye, T.

    2010-01-01

    The study focuses on the observed effects of changes in the El Niño Southern Oscillation (ENSO) and Hadley Cell intensity on sea-surface water conditions in the SE Pacific (41°S; Site ODP1233) during the last 8.000 years. Recent studies suggest that periods characterised by a negative Southern Oscillation Index (SOI; El Niño) cause positive precipitation anomalies during austral winter (and annually) in Mid-South Chile, while austral summer periods are rather drier. This because El Niño weake...

  1. Generating synthetic wave climates for coastal modelling: a linear mixed modelling approach

    Science.gov (United States)

    Thomas, C.; Lark, R. M.

    2013-12-01

    Numerical coastline morphological evolution models require wave climate properties to drive morphological change through time. Wave climate properties (typically wave height, period and direction) may be temporally fixed, culled from real wave buoy data, or allowed to vary in some way defined by a Gaussian or other pdf. However, to examine sensitivity of coastline morphologies to wave climate change, it seems desirable to be able to modify wave climate time series from a current to some new state along a trajectory, but in a way consistent with, or initially conditioned by, the properties of existing data, or to generate fully synthetic data sets with realistic time series properties. For example, mean or significant wave height time series may have underlying periodicities, as revealed in numerous analyses of wave data. Our motivation is to develop a simple methodology to generate synthetic wave climate time series that can change in some stochastic way through time. We wish to use such time series in a coastline evolution model to test sensitivities of coastal landforms to changes in wave climate over decadal and centennial scales. We have worked initially on time series of significant wave height, based on data from a Waverider III buoy located off the coast of Yorkshire, England. The statistical framework for the simulation is the linear mixed model. The target variable, perhaps after transformation (Box-Cox), is modelled as a multivariate Gaussian, the mean modelled as a function of a fixed effect, and two random components, one of which is independently and identically distributed (iid) and the second of which is temporally correlated. The model was fitted to the data by likelihood methods. We considered the option of a periodic mean, the period either fixed (e.g. at 12 months) or estimated from the data. We considered two possible correlation structures for the second random effect. In one the correlation decays exponentially with time. In the second

  2. Modelling forest dynamics along climate gradients in Bolivia

    NARCIS (Netherlands)

    Seiler, C.; Hutjes, R.W.A.; Kruijt, B.; Quispe, J.; Añez, S.; Arora, V.K.; Melton, J.R.; Hickler, T.; Kabat, P.

    2014-01-01

    Dynamic vegetation models have been used to assess the resilience of tropical forests to climate change, but the global application of these modeling experiments often misrepresents carbon dynamics at a regional level, limiting the validity of future projections. Here a dynamic vegetation model

  3. pyhector: A Python interface for the simple climate model Hector

    Energy Technology Data Exchange (ETDEWEB)

    N Willner, Sven; Hartin, Corinne; Gieseke, Robert

    2017-04-01

    Pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary production and respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system (Hartin et al. 2016). The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2. These were developed to cover the range of baseline and mitigation emissions scenarios and are widely used in climate change research and model intercomparison projects. Using DataFrames from the Python library Pandas (McKinney 2010) as a data structure for the scenarios simplifies generating and adapting scenarios. Other parameters of the Hector model can easily be modified when running the model. Pyhector can be installed using pip from the Python Package Index.3 Source code and issue tracker are available in Pyhector's GitHub repository4. Documentation is provided through Readthedocs5. Usage examples are also contained in the repository as a Jupyter Notebook (Pérez and Granger 2007; Kluyver et al. 2016). Courtesy of the Mybinder project6, the example Notebook can also be executed and modified without installing Pyhector locally.

  4. Potential impact of the global climate changes on the spatial distribution of areas of risk for the occurrence of eucalyptus rust in Brazil

    Directory of Open Access Journals (Sweden)

    Willian Bucker Moraes

    2014-06-01

    Full Text Available Rust, caused by Puccinia psidii, is one of the most important diseases affecting eucalyptus in Brazil. This pathogen causes disease in mini-clonal garden and in young plants in the field, especially in leaves and juvenile shoots. Favorable climate conditions for infection by this pathogen in eucalyptus include temperature between 18 and 25 ºC, together with at least 6-hour leaf wetness periods, for 5 to 7 consecutive days. Considering the interaction between the environment and the pathogen, this study aimed to evaluate the potential impact of global climate changes on the spatial distribution of areas of risk for the occurrence of eucalyptus rust in Brazil. Thus, monthly maps of the areas of risk for the occurrence of this disease were elaborated, considering the current climate conditions, based on a historic series between 1961 and 1990, and the future scenarios A2 and B2, predicted by IPCC. The climate conditions were classified into three categories, according to the potential risk for the disease occurrence, considering temperature (T and air relative humidity (RH: i high risk (18 90%; ii medium risk (18 25 ºC and RH > 90%; and iii low risk (T 25 ºC and RH < 90%. Data about the future climate scenarios were supplied by GCM Change Fields. In this study, the simulation model Hadley Centers for Climate Prediction and Research (HadCm3 was adopted, using the software Idrisi 32. The obtained results led to the conclusion that there will be a reduction in the area favorable to eucalyptus rust occurrence, and such a reduction will be gradual for the decades of 2020, 2050 and 2080 but more marked in scenario A2 than in B2. However, it is important to point out that extensive areas will still be favorable to the disease development, especially in the coldest months of the year, i.e., June and July. Therefore, the zoning of areas and periods of higher occurrence risk, considering the global climate changes, becomes important knowledge for the

  5. Assessment of spatiotemporal variations in the fluvial wash-load component in the 21st century with regard to GCM climate change scenarios

    International Nuclear Information System (INIS)

    Mouri, Goro

    2015-01-01

    For stream water, in which a relationship exists between wash-load concentration and discharge, an estimate of fine-sediment delivery may be obtained from a traditional fluvial wash-load rating curve. Here, we demonstrate that the remaining wash-load material load can be estimated from a traditional empirical principle on a nationwide scale. The traditional technique was applied to stream water for the whole of Japan. Four typical GCMs were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields for the following regional climate models to assess the wash-load component based on rating curves: the Model for Interdisciplinary Research on Climate (MIROC), the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), the Hadley Centre Global Environment Model (HadGEM) and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model. The simulations consisted of an ensemble, including multiple physics configurations and different Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5), which was used to produce monthly datasets for the whole country of Japan. The impacts of future climate changes on fluvial wash load in Japanese stream water were based on the balance of changes in hydrological factors. The annual and seasonal variations of the fluvial wash load were assessed from the result of the ensemble analysis in consideration of the Greenhouse Gas (GHG) emission scenarios. The determined results for the amount of wash load increase range from approximately 20 to 110% in the 2040s, especially along part of the Pacific Ocean and the Sea of Japan regions. In the 2090s, the amount of wash load is projected to increase by more than 50% over the whole of Japan. The assessment indicates that seasonal variation is particularly important because the rainy and typhoon seasons, which include extreme events, are the dominant seasons. Because fluvial wash-load-component turbidity

  6. Assessment of spatiotemporal variations in the fluvial wash-load component in the 21st century with regard to GCM climate change scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Mouri, Goro, E-mail: mouri@rainbow.iis.u-tokyo.ac.jp

    2015-11-15

    For stream water, in which a relationship exists between wash-load concentration and discharge, an estimate of fine-sediment delivery may be obtained from a traditional fluvial wash-load rating curve. Here, we demonstrate that the remaining wash-load material load can be estimated from a traditional empirical principle on a nationwide scale. The traditional technique was applied to stream water for the whole of Japan. Four typical GCMs were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields for the following regional climate models to assess the wash-load component based on rating curves: the Model for Interdisciplinary Research on Climate (MIROC), the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), the Hadley Centre Global Environment Model (HadGEM) and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model. The simulations consisted of an ensemble, including multiple physics configurations and different Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5), which was used to produce monthly datasets for the whole country of Japan. The impacts of future climate changes on fluvial wash load in Japanese stream water were based on the balance of changes in hydrological factors. The annual and seasonal variations of the fluvial wash load were assessed from the result of the ensemble analysis in consideration of the Greenhouse Gas (GHG) emission scenarios. The determined results for the amount of wash load increase range from approximately 20 to 110% in the 2040s, especially along part of the Pacific Ocean and the Sea of Japan regions. In the 2090s, the amount of wash load is projected to increase by more than 50% over the whole of Japan. The assessment indicates that seasonal variation is particularly important because the rainy and typhoon seasons, which include extreme events, are the dominant seasons. Because fluvial wash-load-component turbidity

  7. Modeled impact of anthropogenic land cover change on climate

    Science.gov (United States)

    Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J.

    2007-01-01

    Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.

  8. Evaluating meteo marine climatic model inputs for the investigation of coastal hydrodynamics

    Science.gov (United States)

    Bellafiore, D.; Bucchignani, E.; Umgiesser, G.

    2010-09-01

    One of the major aspects discussed in the recent works on climate change is how to provide information from the global scale to the local one. In fact the influence of sea level rise and changes in the meteorological conditions due to climate change in strategic areas like the coastal zone is at the base of the well known mitigation and risk assessment plans. The investigation of the coastal zone hydrodynamics, from a modeling point of view, has been the field for the connection between hydraulic models and ocean models and, in terms of process studies, finite element models have demonstrated their suitability in the reproduction of complex coastal morphology and in the capability to reproduce different spatial scale hydrodynamic processes. In this work the connection between two different model families, the climate models and the hydrodynamic models usually implemented for process studies, is tested. Together, they can be the most suitable tool for the investigation of climate change on coastal systems. A finite element model, SHYFEM (Shallow water Hydrodynamic Finite Element Model), is implemented on the Adriatic Sea, to investigate the effect of wind forcing datasets produced by different downscaling from global climate models in terms of surge and its coastal effects. The wind datasets are produced by the regional climate model COSMO-CLM (CIRA), and by EBU-POM model (Belgrade University), both downscaling from ECHAM4. As a first step the downscaled wind datasets, that have different spatial resolutions, has been analyzed for the period 1960-1990 to compare what is their capability to reproduce the measured wind statistics in the coastal zone in front of the Venice Lagoon. The particularity of the Adriatic Sea meteo climate is connected with the influence of the orography in the strengthening of winds like Bora, from North-East. The increase in spatial resolution permits the more resolved wind dataset to better reproduce meteorology and to provide a more

  9. A comparison of metrics for assessing state-of-the-art climate models and implications for probabilistic projections of climate change

    Science.gov (United States)

    Ring, Christoph; Pollinger, Felix; Kaspar-Ott, Irena; Hertig, Elke; Jacobeit, Jucundus; Paeth, Heiko

    2018-03-01

    A major task of climate science are reliable projections of climate change for the future. To enable more solid statements and to decrease the range of uncertainty, global general circulation models and regional climate models are evaluated based on a 2 × 2 contingency table approach to generate model weights. These weights are compared among different methodologies and their impact on probabilistic projections of temperature and precipitation changes is investigated. Simulated seasonal precipitation and temperature for both 50-year trends and climatological means are assessed at two spatial scales: in seven study regions around the globe and in eight sub-regions of the Mediterranean area. Overall, 24 models of phase 3 and 38 models of phase 5 of the Coupled Model Intercomparison Project altogether 159 transient simulations of precipitation and 119 of temperature from four emissions scenarios are evaluated against the ERA-20C reanalysis over the 20th century. The results show high conformity with previous model evaluation studies. The metrics reveal that mean of precipitation and both temperature mean and trend agree well with the reference dataset and indicate improvement for the more recent ensemble mean, especially for temperature. The method is highly transferrable to a variety of further applications in climate science. Overall, there are regional differences of simulation quality, however, these are less pronounced than those between the results for 50-year mean and trend. The trend results are suitable for assigning weighting factors to climate models. Yet, the implications for probabilistic climate projections is strictly dependent on the region and season.

  10. Holocene glacier variability: three case studies using an intermediate-complexity climate model

    NARCIS (Netherlands)

    Weber, S.L.; Oerlemans, J.

    2003-01-01

    Synthetic glacier length records are generated for the Holocene epoch using a process-based glacier model coupled to the intermediate-complexity climate model ECBilt. The glacier model consists of a massbalance component and an ice-flow component. The climate model is forced by the insolation change

  11. An Interactive Multi-Model for Consensus on Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Kocarev, Ljupco [University of California, San Diego

    2014-07-02

    This project purports to develop a new scheme for forming consensus among alternative climate models, that give widely divergent projections as to the details of climate change, that is more intelligent than simply averaging the model outputs, or averaging with ex post facto weighting factors. The method under development effectively allows models to assimilate data from one another in run time with weights that are chosen in an adaptive training phase using 20th century data, so that the models synchronize with one another as well as with reality. An alternate approach that is being explored in parallel is the automated combination of equations from different models in an expert-system-like framework.

  12. Development of climate data storage and processing model

    Science.gov (United States)

    Okladnikov, I. G.; Gordov, E. P.; Titov, A. G.

    2016-11-01

    We present a storage and processing model for climate datasets elaborated in the framework of a virtual research environment (VRE) for climate and environmental monitoring and analysis of the impact of climate change on the socio-economic processes on local and regional scales. The model is based on a «shared nothings» distributed computing architecture and assumes using a computing network where each computing node is independent and selfsufficient. Each node holds a dedicated software for the processing and visualization of geospatial data providing programming interfaces to communicate with the other nodes. The nodes are interconnected by a local network or the Internet and exchange data and control instructions via SSH connections and web services. Geospatial data is represented by collections of netCDF files stored in a hierarchy of directories in the framework of a file system. To speed up data reading and processing, three approaches are proposed: a precalculation of intermediate products, a distribution of data across multiple storage systems (with or without redundancy), and caching and reuse of the previously obtained products. For a fast search and retrieval of the required data, according to the data storage and processing model, a metadata database is developed. It contains descriptions of the space-time features of the datasets available for processing, their locations, as well as descriptions and run options of the software components for data analysis and visualization. The model and the metadata database together will provide a reliable technological basis for development of a high- performance virtual research environment for climatic and environmental monitoring.

  13. What climate changes could be observed by two generations of Poles?

    Science.gov (United States)

    Szwed, M.

    2010-09-01

    analyzed. The analysis of moving averages will help to find potential longer-term trends or cycles in the test time series. Trends will be detected based on parametric and nonparametric tests, such as linear regression and Mann-Kendall test. Finally, the current temperature and precipitation will be compared to the climate projections at the end of the 21st century. To this end, the climate models from the ENSEMBLES research project will be used. In the case of temperature, these will be C41RCA3 from Rossby Centre (Norrköping, Sweden); CLM from ETH (Zurich, Switzerland), KNMI-RACMO2 from the Royal National Meteorological Institute (De Bilt, the Netherlands), MPI-M-REMO from the Max Planck Institute (Hamburg, Germany); METO-HC from the Met Office's Hadley Centre (Exeter, UK), and RCA from the SMHI Swedish Meteorological and Hydrological Institute (Norrköping, Sweden). In the case of precipitation, only the MPI-M-REMO model will be used. The reason is the outcome of the validation of models for the territory of Poland (previously made by the author) which indicated that this model was the best fit for the Polish precipitation conditions.

  14. Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

    Directory of Open Access Journals (Sweden)

    B. Schneider

    2008-04-01

    Full Text Available Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP and export production (EP of particulate organic carbon (POC. Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation. Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006 with stronger stratification (higher sea surface temperature; SST being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL also reproduces the inverse relationship between stratification (SST and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

  15. Intercomparison of four regional climate models for the German State of Saxonia

    Science.gov (United States)

    Kreienkamp, F.; Spekat, A.; Enke, W.

    2009-09-01

    Results from four regional climate models which focus on Central Europe are presented: CCLM, the climate version of the German Weather Service's Local Model - REMO, the regional dynamic model from the Max Planck Institute for Meteorology in Hamburg - STAR, the statistical model developed at the PIK Potsdam Institute and WETTREG, the statistic-dynamic model developed by the company CEC Potsdam. For the area of the German State of Saxonia a host of properties and indicators were analyzed aiming to show the models' abilities to reconstruct the current climate and compare climate model scenarios. These include a group of thermal indicators, such as the number of ice, frost, summer and hot days, the number of tropical nights; then there are hydrometeorological indicators such as the exceedance of low and high precipitation thresholds; humidity, cloudiness and wind indicators complement the array. A selection of them showing similarities and differences of the models investigated will be presented.

  16. A piecewise modeling approach for climate sensitivity studies: Tests with a shallow-water model

    Science.gov (United States)

    Shao, Aimei; Qiu, Chongjian; Niu, Guo-Yue

    2015-10-01

    In model-based climate sensitivity studies, model errors may grow during continuous long-term integrations in both the "reference" and "perturbed" states and hence the climate sensitivity (defined as the difference between the two states). To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.

  17. Secular trends and climate drift in coupled ocean-atmosphere general circulation models

    Science.gov (United States)

    Covey, Curt; Gleckler, Peter J.; Phillips, Thomas J.; Bader, David C.

    2006-02-01

    Coupled ocean-atmosphere general circulation models (coupled GCMs) with interactive sea ice are the primary tool for investigating possible future global warming and numerous other issues in climate science. A long-standing problem with such models is that when different components of the physical climate system are linked together, the simulated climate can drift away from observation unless constrained by ad hoc adjustments to interface fluxes. However, 11 modern coupled GCMs, including three that do not employ flux adjustments, behave much better in this respect than the older generation of models. Surface temperature trends in control run simulations (with external climate forcing such as solar brightness and atmospheric carbon dioxide held constant) are small compared with observed trends, which include 20th century climate change due to both anthropogenic and natural factors. Sea ice changes in the models are dominated by interannual variations. Deep ocean temperature and salinity trends are small enough for model control runs to extend over 1000 simulated years or more, but trends in some regions, most notably the Arctic, differ substantially among the models and may be problematic. Methods used to initialize coupled GCMs can mitigate climate drift but cannot eliminate it. Lengthy "spin-ups" of models, made possible by increasing computer power, are one reason for the improvements this paper documents.

  18. Modelling the Impacts of Climate Change on Tropospheric Ozone over three Centuries

    Science.gov (United States)

    Brandt Hedegaard, Gitte; Brandt, Jørgen; Christensen, Jesper H.; Gross, Allan; May, Wihelm; Hansen, Kaj M.; Skjøth, Carsten A.

    2010-05-01

    So far reduction of the anthropogenic emissions of chemical species to the atmosphere has been profoundly investigated. However, new research indicates that climate change on its own also has a significant impact on the future air pollution levels. Climate Change and its impact on air pollution levels are currently studied by a number of research groups using, global, hemispherical and regional modelling systems. In the Department of Atmospheric Environment, National Environmental Research Institute (NERI), Aarhus University, in Denmark, we have developed a hemispherical model system which is based on the DEHM model (Christensen, 1997; Frohn et al., 2002a; Frohn et al., 2002b). In the DEHM modelling system an option for modelling the impacts of climate change has been included by using meteorological input from global climate models. Here we present results by using climate data that are provided by the ECHAM5/MPI-OM Atmosphere-Ocean General Circulation Model (May, 2008; Roeckner et al., 2003). In the current experiment the anthropogenic emissions in the chemistry model DEHM are kept constant on a 2000 level to separate out the signal of climate change on air pollutants while the meteorological drivers simulated by the ECHAM5/MPI-OM climate model is based on the IPCC SRES A1B Scenario. To save computing time the experiment is carried out in time-slices representing four centuries (1890s, 1990s, 2090s and the 2190s). The results show that the dominating impacts from climate change on a large number of the chemical species are related to the predicted temperature increase. This temperature affects chemistry as well as emissions from nature. The largest changes in both meteorology and air quality is found to happen in the 21st century. However, significant changes are also found in some parameters including tropospheric ozone in the following century. In general the background ozone concentrations is predicted to decrease at surface level however in the densely

  19. Time to refine key climate policy models

    Science.gov (United States)

    Barron, Alexander R.

    2018-05-01

    Ambition regarding climate change at the national level is critical but is often calibrated with the projected costs — as estimated by a small suite of energy-economic models. Weaknesses in several key areas in these models will continue to distort policy design unless collectively addressed by a diversity of researchers.

  20. The dynamical core of the Aeolus 1.0 statistical-dynamical atmosphere model: validation and parameter optimization

    Science.gov (United States)

    Totz, Sonja; Eliseev, Alexey V.; Petri, Stefan; Flechsig, Michael; Caesar, Levke; Petoukhov, Vladimir; Coumou, Dim

    2018-02-01

    We present and validate a set of equations for representing the atmosphere's large-scale general circulation in an Earth system model of intermediate complexity (EMIC). These dynamical equations have been implemented in Aeolus 1.0, which is a statistical-dynamical atmosphere model (SDAM) and includes radiative transfer and cloud modules (Coumou et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is computationally efficient and thus enables us to perform climate simulations at multimillennia timescales, which is a prime aim of our model development. Further, this computational efficiency enables us to scan large and high-dimensional parameter space to tune the model parameters, e.g., for sensitivity studies.Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0.We optimize the dynamical core parameter values by tuning all relevant dynamical fields to ERA-Interim reanalysis data (1983-2009) forcing the dynamical core with prescribed surface temperature, surface humidity and cumulus cloud fraction. We test the model's performance in reproducing the seasonal cycle and the influence of the El Niño-Southern Oscillation (ENSO). We use a simulated annealing optimization algorithm, which approximates the global minimum of a high-dimensional function.With non-tuned parameter values, the model performs reasonably in terms of its representation of zonal-mean circulation, planetary waves and storm tracks. The simulated annealing optimization improves in particular the model's representation of the Northern Hemisphere jet stream and storm tracks as well as the Hadley circulation.The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower

  1. Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models.

    Directory of Open Access Journals (Sweden)

    Frieda Beauregard

    Full Text Available Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839 covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study

  2. Decision- rather than scenario-centred downscaling: Towards smarter use of climate model outputs

    Science.gov (United States)

    Wilby, Robert L.

    2013-04-01

    Climate model output has been used for hydrological impact assessments for at least 25 years. Scenario-led methods raise awareness about risks posed by climate variability and change to the security of supplies, performance of water infrastructure, and health of freshwater ecosystems. However, it is less clear how these analyses translate into actionable information for adaptation. One reason is that scenario-led methods typically yield very large uncertainty bounds in projected impacts at regional and river catchment scales. Consequently, there is growing interest in vulnerability-based frameworks and strategies for employing climate model output in decision-making contexts. This talk begins by summarising contrasting perspectives on climate models and principles for testing their utility for water sector applications. Using selected examples it is then shown how water resource systems may be adapted with varying levels of reliance on climate model information. These approaches include the conventional scenario-led risk assessment, scenario-neutral strategies, safety margins and sensitivity testing, and adaptive management of water systems. The strengths and weaknesses of each approach are outlined and linked to selected water management activities. These cases show that much progress can be made in managing water systems without dependence on climate models. Low-regret measures such as improved forecasting, better inter-agency co-operation, and contingency planning, yield benefits regardless of the climate outlook. Nonetheless, climate model scenarios are useful for evaluating adaptation portfolios, identifying system thresholds and fixing weak links, exploring the timing of investments, improving operating rules, or developing smarter licensing regimes. The most problematic application remains the climate change safety margin because of the very low confidence in extreme precipitation and river flows generated by climate models. In such cases, it is necessary to

  3. Formulation of an ocean model for global climate simulations

    Directory of Open Access Journals (Sweden)

    S. M. Griffies

    2005-01-01

    Full Text Available This paper summarizes the formulation of the ocean component to the Geophysical Fluid Dynamics Laboratory's (GFDL climate model used for the 4th IPCC Assessment (AR4 of global climate change. In particular, it reviews the numerical schemes and physical parameterizations that make up an ocean climate model and how these schemes are pieced together for use in a state-of-the-art climate model. Features of the model described here include the following: (1 tripolar grid to resolve the Arctic Ocean without polar filtering, (2 partial bottom step representation of topography to better represent topographically influenced advective and wave processes, (3 more accurate equation of state, (4 three-dimensional flux limited tracer advection to reduce overshoots and undershoots, (5 incorporation of regional climatological variability in shortwave penetration, (6 neutral physics parameterization for representation of the pathways of tracer transport, (7 staggered time stepping for tracer conservation and numerical efficiency, (8 anisotropic horizontal viscosities for representation of equatorial currents, (9 parameterization of exchange with marginal seas, (10 incorporation of a free surface that accomodates a dynamic ice model and wave propagation, (11 transport of water across the ocean free surface to eliminate unphysical ``virtual tracer flux' methods, (12 parameterization of tidal mixing on continental shelves. We also present preliminary analyses of two particularly important sensitivities isolated during the development process, namely the details of how parameterized subgridscale eddies transport momentum and tracers.

  4. Implications of regional improvement in global climate models for agricultural impact research

    International Nuclear Information System (INIS)

    Ramirez-Villegas, Julian; Thornton, Philip K; Jarvis, Andy; Challinor, Andrew J

    2013-01-01

    Global climate models (GCMs) have become increasingly important for climate change science and provide the basis for most impact studies. Since impact models are highly sensitive to input climate data, GCM skill is crucial for getting better short-, medium- and long-term outlooks for agricultural production and food security. The Coupled Model Intercomparison Project (CMIP) phase 5 ensemble is likely to underpin the majority of climate impact assessments over the next few years. We assess 24 CMIP3 and 26 CMIP5 simulations of present climate against climate observations for five tropical regions, as well as regional improvements in model skill and, through literature review, the sensitivities of impact estimates to model error. Climatological means of seasonal mean temperatures depict mean errors between 1 and 18 ° C (2–130% with respect to mean), whereas seasonal precipitation and wet-day frequency depict larger errors, often offsetting observed means and variability beyond 100%. Simulated interannual climate variability in GCMs warrants particular attention, given that no single GCM matches observations in more than 30% of the areas for monthly precipitation and wet-day frequency, 50% for diurnal range and 70% for mean temperatures. We report improvements in mean climate skill of 5–15% for climatological mean temperatures, 3–5% for diurnal range and 1–2% in precipitation. At these improvement rates, we estimate that at least 5–30 years of CMIP work is required to improve regional temperature simulations and at least 30–50 years for precipitation simulations, for these to be directly input into impact models. We conclude with some recommendations for the use of CMIP5 in agricultural impact studies. (letter)

  5. Modeling Bird Migration under Climate Change: A Mechanistic Approach

    Science.gov (United States)

    Smith, James A.

    2009-01-01

    How will migrating birds respond to changes in the environment under climate change? What are the implications for migratory success under the various accelerated climate change scenarios as forecast by the Intergovernmental Panel on Climate Change? How will reductions or increased variability in the number or quality of wetland stop-over sites affect migratory bird species? The answers to these questions have important ramifications for conservation biology and wildlife management. Here, we describe the use of continental scale simulation modeling to explore how spatio-temporal changes along migratory flyways affect en-route migration success. We use an individually based, biophysical, mechanistic, bird migration model to simulate the movement of shorebirds in North America as a tool to study how such factors as drought and wetland loss may impact migratory success and modify migration patterns. Our model is driven by remote sensing and climate data and incorporates important landscape variables. The energy budget components of the model include resting, foraging, and flight, but presently predation is ignored. Results/Conclusions We illustrate our model by studying the spring migration of sandpipers through the Great Plains to their Arctic breeding grounds. Why many species of shorebirds have shown significant declines remains a puzzle. Shorebirds are sensitive to stop-over quality and spacing because of their need for frequent refueling stops and their opportunistic feeding patterns. We predict bird "hydrographs that is, stop-over frequency with latitude, that are in agreement with the literature. Mean stop-over durations predicted from our model for nominal cases also are consistent with the limited, but available data. For the shorebird species simulated, our model predicts that shorebirds exhibit significant plasticity and are able to shift their migration patterns in response to changing drought conditions. However, the question remains as to whether this

  6. Meeting the Next Generation Science Standards Through "Rediscovered" Climate Model Experiments

    Science.gov (United States)

    Sohl, L. E.; Chandler, M. A.; Zhou, J.

    2013-12-01

    Since the Educational Global Climate Model (EdGCM) Project made its debut in January 2005, over 150 institutions have employed EdGCM software for a variety of uses ranging from short lab exercises to semester-long and year-long thesis projects. The vast majority of these EdGCM adoptees have been at the undergraduate and graduate levels, with few users at the K-12 level. The K-12 instructors who have worked with EdGCM in professional development settings have commented that, although EdGCM can be used to illustrate a number of the Disciplinary Core Ideas and connects to many of the Common Core State Standards across subjects and grade levels, significant hurdles preclude easy integration of EdGCM into their curricula. Time constraints, a scarcity of curriculum materials, and classroom technology are often mentioned as obstacles in providing experiences to younger grade levels in realistic climate modeling research. Given that the NGSS incorporates student performance expectations relating to Earth System Science, and to climate science and the human dimension in particular, we feel that a streamlined version of EdGCM -- one that eliminates the need to run the climate model on limited computing resources, and provides a more guided climate modeling experience -- would be highly beneficial for the K-12 community. This new tool currently under development, called EzGCM, functions through a browser interface, and presents "rediscovery experiments" that allow students to do their own exploration of model output from published climate experiments, or from sensitivity experiments designed to illustrate how climate models as well as the climate system work. The experiments include background information and sample questions, with more extensive notes for instructors so that the instructors can design their own reflection questions or follow-on activities relating to physical or human impacts, as they choose. An added benefit of the EzGCM tool is that, like EdGCM, it helps

  7. REGIONAL CLIMATE MODELING STUDY FOR THE CARPATHIAN REGION USING REGCM4 EXPERIMENTS

    Directory of Open Access Journals (Sweden)

    PIECZKA I.

    2015-03-01

    Full Text Available The newest model version of RegCM is adapted with the ultimate aim of providing climate projection for the Carpathian region with 10 km horizontal resolution. For this purpose, first, coarse resolution reanalysis data and global climate model outputs are used to drive 50 km resolution model experiments, from which the outputs are used to provide necessary boundary conditions for the fine scale model runs. Besides the historical runs (for the period 1981-2010, RCP4.5 scenario is also analyzed in this paper for the 21st century. These experiments are essential since they form the basis of national climate and adaptation strategies by providing detailed regional scale climatic projections and enabling specific impact studies for various sectors.

  8. Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method.

    Science.gov (United States)

    Kara, Fatih; Yucel, Ismail

    2015-09-01

    This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.

  9. Contrasting model complexity under a changing climate in a headwaters catchment.

    Science.gov (United States)

    Foster, L.; Williams, K. H.; Maxwell, R. M.

    2017-12-01

    Alpine, snowmelt-dominated catchments are the source of water for more than 1/6th of the world's population. These catchments are topographically complex, leading to steep weather gradients and nonlinear relationships between water and energy fluxes. Recent evidence suggests that alpine systems are more sensitive to climate warming, but these regions are vastly simplified in climate models and operational water management tools due to computational limitations. Simultaneously, point-scale observations are often extrapolated to larger regions where feedbacks can both exacerbate or mitigate locally observed changes. It is critical to determine whether projected climate impacts are robust to different methodologies, including model complexity. Using high performance computing and an integrated model of a representative headwater catchment we determined the hydrologic response from 30 projected climate changes to precipitation, temperature and vegetation for the Rocky Mountains. Simulations were run with 100m and 1km resolution, and with and without lateral subsurface flow in order to vary model complexity. We found that model complexity alters nonlinear relationships between water and energy fluxes. Higher-resolution models predicted larger changes per degree of temperature increase than lower resolution models, suggesting that reductions to snowpack, surface water, and groundwater due to warming may be underestimated in simple models. Increases in temperature were found to have a larger impact on water fluxes and stores than changes in precipitation, corroborating previous research showing that mountain systems are significantly more sensitive to temperature changes than to precipitation changes and that increases in winter precipitation are unlikely to compensate for increased evapotranspiration in a higher energy environment. These numerical experiments help to (1) bracket the range of uncertainty in published literature of climate change impacts on headwater

  10. Climate change impacts utilizing regional models for agriculture, hydrology and natural ecosystems

    Science.gov (United States)

    Kafatos, M.; Asrar, G. R.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Medvigy, D.; Prasad, A. K.; Smith, E.; Stack, D. H.; Tremback, C.; Walko, R. L.

    2012-12-01

    Climate change impacts the entire Earth but with crucial and often catastrophic impacts at local and regional levels. Extreme phenomena such as fires, dust storms, droughts and other natural hazards present immediate risks and challenges. Such phenomena will become more extreme as climate change and anthropogenic activities accelerate in the future. We describe a major project funded by NIFA (Grant # 2011-67004-30224), under the joint NSF-DOE-USDA Earth System Models (EaSM) program, to investigate the impacts of climate variability and change on the agricultural and natural (i.e. rangeland) ecosystems in the Southwest USA using a combination of historical and present observations together with climate, and ecosystem models, both in hind-cast and forecast modes. The applicability of the methodology to other regions is relevant (for similar geographic regions as well as other parts of the world with different agriculture and ecosystems) and should advance the state of knowledge for regional impacts of climate change. A combination of multi-model global climate projections from the decadal predictability simulations, to downscale dynamically these projections using three regional climate models, combined with remote sensing MODIS and other data, in order to obtain high-resolution climate data that can be used with hydrological and ecosystem models for impacts analysis, is described in this presentation. Such analysis is needed to assess the future risks and potential impacts of projected changes on these natural and managed ecosystems. The results from our analysis can be used by scientists to assist extended communities to determine agricultural coping strategies, and is, therefore, of interest to wide communities of stakeholders. In future work we will be including surface hydrologic modeling and water resources, extend modeling to higher resolutions and include significantly more crops and geographical regions with different weather and climate conditions

  11. Peformance Tuning and Evaluation of a Parallel Community Climate Model

    Energy Technology Data Exchange (ETDEWEB)

    Drake, J.B.; Worley, P.H.; Hammond, S.

    1999-11-13

    The Parallel Community Climate Model (PCCM) is a message-passing parallelization of version 2.1 of the Community Climate Model (CCM) developed by researchers at Argonne and Oak Ridge National Laboratories and at the National Center for Atmospheric Research in the early to mid 1990s. In preparation for use in the Department of Energy's Parallel Climate Model (PCM), PCCM has recently been updated with new physics routines from version 3.2 of the CCM, improvements to the parallel implementation, and ports to the SGIKray Research T3E and Origin 2000. We describe our experience in porting and tuning PCCM on these new platforms, evaluating the performance of different parallel algorithm options and comparing performance between the T3E and Origin 2000.

  12. An intercomparison of regional climate model data for hydrological impact studies in Denmark

    DEFF Research Database (Denmark)

    Van Roosmalen, Lieke Petronella G; Christensen, Jens Hesselbjerg; Butts, Michael

    2010-01-01

    The use of high-resolution regional climate models (RCM) to examine the hydrological impacts of climate change has grown significantly in recent years due to the improved representation of the local climate. However, the application is not straightforward because most RCMs are subject to consider......The use of high-resolution regional climate models (RCM) to examine the hydrological impacts of climate change has grown significantly in recent years due to the improved representation of the local climate. However, the application is not straightforward because most RCMs are subject...... to considerable systematic errors. In this study, projected climate change data from the RCM HIRHAM4 are used to generate climate scenario time series of precipitation, temperature, and reference evapotranspiration for the period 2071-2100 for hydrological impact assessments in Denmark. RCM output for the present......-day period (1961-1990) are compared to an observational data set, with precipitation corrected for undercatch and wetting losses, to quantify systematic model errors. A delta change method is applied to cope with these biases. A question arises as to how variable the climate change signals are...

  13. Uncertainties in modelling CH4 emissions from northern wetlands in glacial climates: effect of hydrological model and CH4 model structure

    Directory of Open Access Journals (Sweden)

    J. van Huissteden

    2009-07-01

    Full Text Available Methane (CH4 fluxes from northern wetlands may have influenced atmospheric CH4 concentrations at climate warming phases during the last 800 000 years and during the present global warming. Including these CH4 fluxes in earth system models is essential to understand feedbacks between climate and atmospheric composition. Attempts to model CH4 fluxes from wetlands have previously been undertaken using various approaches. Here, we test a process-based wetland CH4 flux model (PEATLAND-VU which includes details of soil-atmosphere CH4 transport. The model has been used to simulate CH4 emissions from continental Europe in previous glacial climates and the current climate. This paper presents results regarding the sensitivity of modeling glacial terrestrial CH4 fluxes to (a basic tuning parameters of the model, (b different approaches in modeling of the water table, and (c model structure. In order to test the model structure, PEATLAND-VU was compared to a simpler modeling approach based on wetland primary production estimated from a vegetation model (BIOME 3.5. The tuning parameters are the CH4 production rate from labile organic carbon and its temperature sensitivity. The modelled fluxes prove comparatively insensitive to hydrology representation, while sensitive to microbial parameters and model structure. Glacial climate emissions are also highly sensitive to assumptions about the extent of ice cover and exposed seafloor. Wetland expansion over low relief exposed seafloor areas have compensated for a decrease of wetland area due to continental ice cover.

  14. Possible impact of climate change on meningitis in northwest Nigeria: an assessment using CMIP5 climate model simulations

    Science.gov (United States)

    Abdussalam, Auwal; Monaghan, Andrew; Steinhoff, Daniel; Dukic, Vanja; Hayden, Mary; Hopson, Thomas; Thornes, John; Leckebusch, Gregor

    2014-05-01

    Meningitis remains a major health burden throughout Sahelian Africa, especially in heavily-populated northwest Nigeria. Cases exhibit strong sensitivity to intra- and inter-annual climate variability, peaking during the hot and dry boreal spring months, raising concern that future climate change may increase the incidence of meningitis in the region. The impact of future climate change on meningitis risk in northwest Nigeria is assessed by forcing an empirical model of meningitis with monthly simulations from an ensemble of thirteen statistically downscaled global climate model projections from the Coupled Model Intercomparison Experiment Phase 5 (CMIP5) for RCPs 2.6, 6.0 and 8.5 scenarios. The results suggest future temperature increases due to climate change has the potential to significantly increase meningitis cases in both the early and late 21st century, and to increase the length of the meningitis season in the late century. March cases may increase from 23 per 100,000 people for present day (1990-2005), to 29-30 per 100,000 (p<0.01) in the early century (2020-2035) and 31-42 per 100,000 (p<0.01) in the late century (2060-2075), the range being dependent on the emissions scenario. It is noteworthy that these results represent the climatological potential for increased cases due to climate change, as we assume current prevention and treatment strategies remain similar in the future.

  15. High resolution climate scenarios for snowmelt modelling in small alpine catchments

    Science.gov (United States)

    Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.

    2017-12-01

    Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire

  16. Long term modelling in a second rank world: application to climate policies

    International Nuclear Information System (INIS)

    Crassous, R.

    2008-11-01

    This research aims at the identification of the dissatisfaction reasons with respect to the existing climate models, at the design of an innovating modelling architecture which would respond to these dissatisfactions, and at proposing climate policy assessment pathways. The authors gives a critique assessment of the modelling activity within the field of climate policies, outlines the fact that the large number and the scattering of existing long term scenarios hides a weak control of uncertainties and of the inner consistency of the produced paths, as well as the very low number of modelling paradigms. After a deepened analysis of modelling practices, the author presents the IMACLIM-R modelling architecture which is presented on a world scale and includes 12 areas and 12 sectors, and allows the simulation of evolutions by 2050, and even 2100, with a one-year time step. The author describes a scenario without any climate policy, highlights reassessment possibilities for economical trajectories which would allow greenhouse gas concentration stabilisation on a long term basis through the application of IMACLIM-R innovations. He outlines adjustment and refinement possibilities for climate policies which would robustly limit the transition cost risks

  17. Modeling the impact of climate change in Germany with biosphere models for long-term safety assessment of nuclear waste repositories

    International Nuclear Information System (INIS)

    Staudt, C.; Semiochkina, N.; Kaiser, J.C.; Pröhl, G.

    2013-01-01

    Biosphere models are used to evaluate the exposure of populations to radionuclides from a deep geological repository. Since the time frame for assessments of long-time disposal safety is 1 million years, potential future climate changes need to be accounted for. Potential future climate conditions were defined for northern Germany according to model results from the BIOCLIM project. Nine present day reference climate regions were defined to cover those future climate conditions. A biosphere model was developed according to the BIOMASS methodology of the IAEA and model parameters were adjusted to the conditions at the reference climate regions. The model includes exposure pathways common to those reference climate regions in a stylized biosphere and relevant to the exposure of a hypothetical self-sustaining population at the site of potential radionuclide contamination from a deep geological repository. The end points of the model are Biosphere Dose Conversion factors (BDCF) for a range of radionuclides and scenarios normalized for a constant radionuclide concentration in near-surface groundwater. Model results suggest an increased exposure of in dry climate regions with a high impact of drinking water consumption rates and the amount of irrigation water used for agriculture. - Highlights: ► We model Biosphere Dose Conversion Factors for a representative group exposed to radionuclides from a waste repository. ► The BDCF are modeled for different soil types. ► One model is used for the assessment of the influence of climate change during the disposal time frame.

  18. Asymmetric variations in the tropical ascending branches of Hadley circulations and the associated mechanisms and effects

    Science.gov (United States)

    Sun, Bo

    2018-03-01

    This study investigates the variations in the tropical ascending branches (TABs) of Hadley circulations (HCs) during past decades, using a variety of reanalysis datasets. The northern tropical ascending branch (NTAB) and the southern tropical ascending branch (STAB), which are defined as the ascending branches of the Northern Hemisphere HC and Southern Hemisphere HC, respectively, are identified and analyzed regarding their trends and variability. The reanalysis datasets consistently show a persistent increase in STAB during past decades, whereas they show less consistency in NTAB regarding its decadalto multidecadal variability, which generally features a decreasing trend. These asymmetric trends in STAB and NTAB are attributed to asymmetric trends in the tropical SSTs. The relationship between STAB/NTAB and tropical SSTs is further examined regarding their interannual and decadal- to multidecadal variability. On the interannual time scale, the STAB and NTAB are essentially modulated by the eastern-Pacific type of ENSO, with a strengthened (weakened) STAB (NTAB) under an El Niño condition. On the decadal- to multidecadal time scale, the variability of STAB and NTAB is closely related to the southern tropical SSTs and the meridional asymmetry of global tropical SSTs, respectively. The tropical eastern Pacific SSTs (southern tropical SSTs) dominate the tropical SST-NTAB/STAB relationship on the interannual (decadal- to multidecadal) scale, whereas the NTAB is a passive factor in this relationship. Moreover, a cross-hemispheric relationship between the NTAB/STAB and the HC upper-level meridional winds is revealed.

  19. Modeling current climate conditions for forest pest risk assessment

    Science.gov (United States)

    Frank H. Koch; John W. Coulston

    2010-01-01

    Current information on broad-scale climatic conditions is essential for assessing potential distribution of forest pests. At present, sophisticated spatial interpolation approaches such as the Parameter-elevation Regressions on Independent Slopes Model (PRISM) are used to create high-resolution climatic data sets. Unfortunately, these data sets are based on 30-year...

  20. The Bern Simple Climate Model (BernSCM v1.0: an extensible and fully documented open-source re-implementation of the Bern reduced-form model for global carbon cycle–climate simulations

    Directory of Open Access Journals (Sweden)

    K. M. Strassmann

    2018-05-01

    Full Text Available The Bern Simple Climate Model (BernSCM is a free open-source re-implementation of a reduced-form carbon cycle–climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRFs. The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near-linear behavior. Illustrative simulations of scenarios from previous multimodel studies show that BernSCM is broadly representative of the range of the climate–carbon cycle response simulated by more complex and detailed models. Model code (in Fortran was written from scratch with transparency and extensibility in mind, and is provided open source. BernSCM makes scientifically sound carbon cycle–climate modeling available for many applications. Supporting up to decadal time steps with high accuracy, it is suitable for studies with high computational load and for coupling with integrated assessment models (IAMs, for example. Further applications include climate risk assessment in a business, public, or educational context and the estimation of CO2 and climate benefits of emission mitigation options.

  1. A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence

    Directory of Open Access Journals (Sweden)

    Edlund Stefan

    2012-09-01

    Full Text Available Abstract Background The role of the Anopheles vector in malaria transmission and the effect of climate on Anopheles populations are well established. Models of the impact of climate change on the global malaria burden now have access to high-resolution climate data, but malaria surveillance data tends to be less precise, making model calibration problematic. Measurement of malaria response to fluctuations in climate variables offers a way to address these difficulties. Given the demonstrated sensitivity of malaria transmission to vector capacity, this work tests response functions to fluctuations in land surface temperature and precipitation. Methods This study of regional sensitivity of malaria incidence to year-to-year climate variations used an extended Macdonald Ross compartmental disease model (to compute malaria incidence built on top of a global Anopheles vector capacity model (based on 10 years of satellite climate data. The predicted incidence was compared with estimates from the World Health Organization and the Malaria Atlas. The models and denominator data used are freely available through the Eclipse Foundation’s Spatiotemporal Epidemiological Modeller (STEM. Results Although the absolute scale factor relating reported malaria to absolute incidence is uncertain, there is a positive correlation between predicted and reported year-to-year variation in malaria burden with an averaged root mean square (RMS error of 25% comparing normalized incidence across 86 countries. Based on this, the proposed measure of sensitivity of malaria to variations in climate variables indicates locations where malaria is most likely to increase or decrease in response to specific climate factors. Bootstrapping measures the increased uncertainty in predicting malaria sensitivity when reporting is restricted to national level and an annual basis. Results indicate a potential 20x improvement in accuracy if data were available at the level ISO 3166–2

  2. Modelling and observing urban climate in the Netherlands

    International Nuclear Information System (INIS)

    Van Hove, B.; Steeneveld, G.J.; Heusinkveld, B.; Holtslag, B.; Jacobs, C.; Ter Maat, H.; Elbers, J.; Moors, E.

    2011-06-01

    The main aims of the present study are: (1) to evaluate the performance of two well-known mesoscale NWP (numerical weather prediction) models coupled to a UCM (Urban Canopy Models), and (2) to develop a proper measurement strategy for obtaining meteorological data that can be used in model evaluation studies. We choose the mesoscale models WRF (Weather Research and Forecasting Model) and RAMS (Regional Atmospheric Modeling System), respectively, because the partners in the present project have a large expertise with respect to these models. In addition WRF and RAMS have been successfully used in the meteorology and climate research communities for various purposes, including weather prediction and land-atmosphere interaction research. Recently, state-of-the-art UCM's were embedded within the land surface scheme of the respective models, in order to better represent the exchange of heat, momentum, and water vapour in the urban environment. Key questions addressed here are: What is the general model performance with respect to the urban environment?; How can useful and observational data be obtained that allow sensible validation and further parameterization of the models?; and Can the models be easily modified to simulate the urban climate under Dutch climatic conditions, urban configuration and morphology? Chapter 2 reviews the available Urban Canopy Models; we discuss their theoretical basis, the different representations of the urban environment, the required input and the output. Much of the information was obtained from the Urban Surface Energy Balance: Land Surface Scheme Comparison project (PILPS URBAN, PILPS stands for Project for Inter-comparison of Land-Surface Parameterization Schemes). This project started in March 2008 and was coordinated by the Department of Geography, King's College London. In order to test the performance of our models we participated in this project. Chapter 3 discusses the main results of the first phase of PILPS URBAN. A first

  3. Multilevel model of safety climate for furniture industries.

    Science.gov (United States)

    Rodrigues, Matilde A; Arezes, Pedro M; Leão, Celina P

    2015-01-01

    Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies' safety conditions were also analyzed. Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies' safety conditions; the organizational scale is the one that best reflects the actual safety conditions. The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups' safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.

  4. A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

    Science.gov (United States)

    Rummukainen, M.; Räisänen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willén, U.; Hansson, U.; Jones, C.

    This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results.

  5. A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

    Energy Technology Data Exchange (ETDEWEB)

    Rummukainen, M.; Raeisaenen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willen, U.; Hansson, U.; Jones, C. [Rossby Centre, Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden)

    2001-03-01

    This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results. (orig.)

  6. ARCAS (ACACIA Regional Climate-data Access System) -- a Web Access System for Climate Model Data Access, Visualization and Comparison

    Science.gov (United States)

    Hakkarinen, C.; Brown, D.; Callahan, J.; hankin, S.; de Koningh, M.; Middleton-Link, D.; Wigley, T.

    2001-05-01

    A Web-based access system to climate model output data sets for intercomparison and analysis has been produced, using the NOAA-PMEL developed Live Access Server software as host server and Ferret as the data serving and visualization engine. Called ARCAS ("ACACIA Regional Climate-data Access System"), and publicly accessible at http://dataserver.ucar.edu/arcas, the site currently serves climate model outputs from runs of the NCAR Climate System Model for the 21st century, for Business as Usual and Stabilization of Greenhouse Gas Emission scenarios. Users can select, download, and graphically display single variables or comparisons of two variables from either or both of the CSM model runs, averaged for monthly, seasonal, or annual time resolutions. The time length of the averaging period, and the geographical domain for download and display, are fully selectable by the user. A variety of arithmetic operations on the data variables can be computed "on-the-fly", as defined by the user. Expansions of the user-selectable options for defining analysis options, and for accessing other DOD-compatible ("Distributed Ocean Data System-compatible") data sets, residing at locations other than the NCAR hardware server on which ARCAS operates, are planned for this year. These expansions are designed to allow users quick and easy-to-operate web-based access to the largest possible selection of climate model output data sets available throughout the world.

  7. A model for evaluating stream temperature response to climate change in Wisconsin

    Science.gov (United States)

    Stewart, Jana S.; Westenbroek, Stephen M.; Mitro, Matthew G.; Lyons, John D.; Kammel, Leah E.; Buchwald, Cheryl A.

    2015-01-01

    Expected climatic changes in air temperature and precipitation patterns across the State of Wisconsin may alter future stream temperature and flow regimes. As a consequence of flow and temperature changes, the composition and distribution of fish species assemblages are expected to change. In an effort to gain a better understanding of how climatic changes may affect stream temperature, an approach was developed to predict and project daily summertime stream temperature under current and future climate conditions for 94,341 stream kilometers across Wisconsin. The approach uses a combination of static landscape characteristics and dynamic time-series climatic variables as input for an Artificial Neural Network (ANN) Model integrated with a Soil-Water-Balance (SWB) Model. Future climate scenarios are based on output from downscaled General Circulation Models (GCMs). The SWB model provided a means to estimate the temporal variability in groundwater recharge and provided a mechanism to evaluate the effect of changing air temperature and precipitation on groundwater recharge and soil moisture. The Integrated Soil-Water-Balance and Artificial Neural Network version 1 (SWB-ANNv1) Model was used to simulate daily summertime stream temperature under current (1990–2008) climate and explained 76 percent of the variation in the daily mean based on validation at 67 independent sites. Results were summarized as July mean water temperature, and individual stream segments were classified by thermal class (cold, cold transition, warm transition, and warm) for comparison of current (1990–2008) with future climate conditions.

  8. New Gravity Wave Treatments for GISS Climate Models

    Science.gov (United States)

    Geller, Marvin A.; Zhou, Tiehan; Ruedy, Reto; Aleinov, Igor; Nazarenko, Larissa; Tausnev, Nikolai L.; Sun, Shan; Kelley, Maxwell; Cheng, Ye

    2011-01-01

    Previous versions of GISS climate models have either used formulations of Rayleigh drag to represent unresolved gravity wave interactions with the model-resolved flow or have included a rather complicated treatment of unresolved gravity waves that, while being climate interactive, involved the specification of a relatively large number of parameters that were not well constrained by observations and also was computationally very expensive. Here, the authors introduce a relatively simple and computationally efficient specification of unresolved orographic and nonorographic gravity waves and their interaction with the resolved flow. Comparisons of the GISS model winds and temperatures with no gravity wave parameterization; with only orographic gravity wave parameterization; and with both orographic and nonorographic gravity wave parameterizations are shown to illustrate how the zonal mean winds and temperatures converge toward observations. The authors also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. Then results are presented where the nonorographic gravity wave sources are specified to represent sources from convection in the intertropical convergence zone and spontaneous emission from jet imbalances. Finally, a strategy to include these effects in a climate-dependent manner is suggested.

  9. Assessing Impacts of Climate Change on Forests: The State of Biological Modeling

    Science.gov (United States)

    Dale, V. H.; Rauscher, H. M.

    1993-04-06

    Models that address the impacts to forests of climate change are reviewed by four levels of biological organization: global, regional or landscape, community, and tree. The models are compared as to their ability to assess changes in greenhouse gas flux, land use, maps of forest type or species composition, forest resource productivity, forest health, biodiversity, and wildlife habitat. No one model can address all of these impacts, but landscape transition models and regional vegetation and land-use models consider the largest number of impacts. Developing landscape vegetation dynamics models of functional groups is suggested as a means to integrate the theory of both landscape ecology and individual tree responses to climate change. Risk assessment methodologies can be adapted to deal with the impacts of climate change at various spatial and temporal scales. Four areas of research development are identified: (1) linking socioeconomic and ecologic models, (2) interfacing forest models at different scales, (3) obtaining data on susceptibility of trees and forest to changes in climate and disturbance regimes, and (4) relating information from different scales.

  10. Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality.

    Science.gov (United States)

    Gosling, Simon N; Hondula, David M; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

    2017-08-16

    Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. This study had three aims: a ) Compare the range in projected impacts that arises from using different adaptation modeling methods; b ) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c ) recommend modeling method(s) to use in future impact assessments. We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.

  11. Soil carbon model alternatives for ECHAM5/JSBACH climate model: Evaluation and impacts on global carbon cycle estimates

    DEFF Research Database (Denmark)

    Thum, T.; Raisanen, P.; Sevanto, S.

    2011-01-01

    The response of soil organic carbon to climate change might lead to significant feedbacks affecting global warming. This response can be studied by coupled climate-carbon cycle models but so far the description of soil organic carbon cycle in these models has been quite simple. In this work we used...... the coupled climate-carbon cycle model ECHAM5/JSBACH (European Center/Hamburg Model 5/Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg) with two different soil carbon modules, namely (1) the original soil carbon model of JSBACH called CBALANCE and (2) a new soil carbon model Yasso07, to study...... the interaction between climate variability and soil organic carbon. Equivalent ECHAM5/JSBACH simulations were conducted using both soil carbon models, with freely varying atmospheric CO2 for the last 30 years (1977-2006). In this study, anthropogenic CO2 emissions and ocean carbon cycle were excluded. The new...

  12. Performance of ALADIN-Climate/CZ over the area of the Czech Republic in comparison with ENSEMBLES regional climate models

    Czech Academy of Sciences Publication Activity Database

    Crhová, L.; Holtanova, E.; Kalvová, J.; Farda, Aleš

    2014-01-01

    Roč. 58, č. 1 (2014), s. 148-169 ISSN 0039-3169 R&D Projects: GA MŽP(CZ) SP/1A6/108/07 Institutional support: RVO:67179843 Keywords : regional climate model * climate model performance * Taylor diagram * skill score Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.806, year: 2014

  13. Integrating geological archives and climate models for the mid-Pliocene warm period.

    Science.gov (United States)

    Haywood, Alan M; Dowsett, Harry J; Dolan, Aisling M

    2016-02-16

    The mid-Pliocene Warm Period (mPWP) offers an opportunity to understand a warmer-than-present world and assess the predictive ability of numerical climate models. Environmental reconstruction and climate modelling are crucial for understanding the mPWP, and the synergy of these two, often disparate, fields has proven essential in confirming features of the past and in turn building confidence in projections of the future. The continual development of methodologies to better facilitate environmental synthesis and data/model comparison is essential, with recent work demonstrating that time-specific (time-slice) syntheses represent the next logical step in exploring climate change during the mPWP and realizing its potential as a test bed for understanding future climate change.

  14. Climate change due to greenhouse effects in China as simulated by a regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Gao, X.J.; Zhao, Z.C.; Ding, Y.H.; Huang, R.H.; Giorgi, F. [National Climate Centre, Beijing (China)

    2001-07-01

    Impacts of greenhouse effects (2 x CO{sub 2}) upon climate change over China as simulated by a regional climate model over China (RegCM / China) have been investigated. The model was based on RegCM2 and was nested to a global coupled ocean-atmosphere model (CSIRO R21L9 AOGCM model). Results of the control run (1 x CO{sub 2}) indicated that simulations of surface air temperature and precipitation in China by RegCM are much better than that by the global coupled model because of a higher resolution. Results of sensitive experiment by RegCM with 2 x CO{sub 2} showed that the surface air temperature over China might increase remarkably due to greenhouse effect, especially in winter season and in North China. Precipitation might also increase in most parts of China due to the CO{sub 2} doubling.

  15. A flexible climate model for use in integrated assessments

    Science.gov (United States)

    Sokolov, A. P.; Stone, P. H.

    Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model's sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO2 are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM

  16. Recursive inter-generational utility in global climate risk modeling

    Energy Technology Data Exchange (ETDEWEB)

    Minh, Ha-Duong [Centre International de Recherche sur l' Environnement et le Developpement (CIRED-CNRS), 75 - Paris (France); Treich, N. [Institut National de Recherches Agronomiques (INRA-LEERNA), 31 - Toulouse (France)

    2003-07-01

    This paper distinguishes relative risk aversion and resistance to inter-temporal substitution in climate risk modeling. Stochastic recursive preferences are introduced in a stylized numeric climate-economy model using preliminary IPCC 1998 scenarios. It shows that higher risk aversion increases the optimal carbon tax. Higher resistance to inter-temporal substitution alone has the same effect as increasing the discount rate, provided that the risk is not too large. We discuss implications of these findings for the debate upon discounting and sustainability under uncertainty. (author)

  17. Evaluation of the ACCESS – chemistry–climate model for the Southern Hemisphere

    Directory of Open Access Journals (Sweden)

    K. A. Stone

    2016-02-01

    Full Text Available Chemistry–climate models are important tools for addressing interactions of composition and climate in the Earth system. In particular, they are used to assess the combined roles of greenhouse gases and ozone in Southern Hemisphere climate and weather. Here we present an evaluation of the Australian Community Climate and Earth System Simulator – chemistry–climate model (ACCESS-CCM, focusing on the Southern Hemisphere and the Australian region. This model is used for the Australian contribution to the international Chemistry–Climate Model Initiative, which is soliciting hindcast, future projection and sensitivity simulations. The model simulates global total column ozone (TCO distributions accurately, with a slight delay in the onset and recovery of springtime Antarctic ozone depletion, and consistently higher ozone values. However, October-averaged Antarctic TCO from 1960 to 2010 shows a similar amount of depletion compared to observations. Comparison with model precursors shows large improvements in the representation of the Southern Hemisphere stratosphere, especially in TCO concentrations. A significant innovation is seen in the evaluation of simulated vertical profiles of ozone and temperature with ozonesonde data from Australia, New Zealand and Antarctica from 38 to 90° S. Excess ozone concentrations (greater than 26 % at Davis and the South Pole during winter and stratospheric cold biases (up to 10 K at the South Pole during summer and autumn outside the period of perturbed springtime ozone depletion are seen during all seasons compared to ozonesondes. A disparity in the vertical location of ozone depletion is seen: centred around 100 hPa in ozonesonde data compared to above 50 hPa in the model. Analysis of vertical chlorine monoxide profiles indicates that colder Antarctic stratospheric temperatures (possibly due to reduced mid-latitude heat flux are artificially enhancing polar stratospheric cloud formation at high altitudes

  18. Modeling European ruminant production systems: facing the challenges of climate change

    DEFF Research Database (Denmark)

    Kipling, Richard Philip; Bannink, Andre; Bellocchi, Gianni

    2016-01-01

    Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute significantly to climate change through greenhouse...... gas (GHG) emissions, while intensification of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance...... of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulfil this role. Many grassland models can predict plant growth...

  19. Study of tropical clouds feedback to a climate warming as simulated by climate models

    International Nuclear Information System (INIS)

    Brient, Florent

    2012-01-01

    The last IPCC report affirms the predominant role of low cloud-radiative feedbacks in the inter-model spread of climate sensitivity. Understanding the mechanisms that control the behavior of low-level clouds is thus crucial. However, the complexity of coupled ocean-atmosphere models and the large number of processes potentially involved make the analysis of this response difficult. To simplify the analysis and to identify the most critical controls of cloud feedbacks, we analyze the cloud response to climate change simulated by the IPSL-CM5A model in a hierarchy of configurations. A comparison between three model configurations (coupled, atmospheric and aqua-planet) using the same physical parametrizations shows that the cloud response to global warming is dominated by a decrease of low clouds in regimes of moderate subsidence. Using a Single Column Model, forced by weak subsidence large-scale forcing, allows us to reproduce the vertical cloud profile predicted in the 3D model, as well as its response to climate change (if a stochastic forcing is added on vertical velocity). We analyze the sensitivity of this low-cloud response to external forcing and also to uncertain parameters of physical parameterizations involved on the atmospheric model. Through a moist static energy (MSE) budget, we highlight several mechanisms: (1) Robust: Over weak subsidence regimes, the Clausius-Clapeyron relationship predicts that a warmer atmosphere leads to a increase of the vertical MSE gradient, resulting on a strengthening of the import of low-MSE from the free atmosphere into the cloudy boundary layer. The MSE budget links changes of vertical advection and cloud radiative effects. (2) Physics Model Dependent: The coupling between shallow convection, turbulence and cloud schemes allows the intensification of low-MSE transport so that cloud radiative cooling becomes 'less necessary' to balance the energy budget (Robust positive low cloud-radiative feedback for the model). The

  20. Streamflow in the upper Mississippi river basin as simulated by SWAT driven by 20{sup th} century contemporary results of global climate models and NARCCAP regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Takle, Eugene S.; Jha, Manoj; Lu, Er; Arritt, Raymond W.; Gutowski, William J. [Iowa State Univ. Ames, IA (United States)

    2010-06-15

    We use Soil and Water Assessment Tool (SWAT) when driven by observations and results of climate models to evaluate hydrological quantities, including streamflow, in the Upper Mississippi River Basin (UMRB) for 1981-2003 in comparison to observed streamflow. Daily meteorological conditions used as input to SWAT are taken from (1) observations at weather stations in the basin, (2) daily meteorological conditions simulated by a collection of regional climate models (RCMs) driven by reanalysis boundary conditions, and (3) daily meteorological conditions simulated by a collection of global climate models (GCMs). Regional models used are those whose data are archived by the North American Regional Climate Change Assessment Program (NARCCAP). Results show that regional models correctly simulate the seasonal cycle of precipitation, temperature, and streamflow within the basin. Regional models also capture interannual extremes represented by the flood of 1993 and the dry conditions of 2000. The ensemble means of both the GCM-driven and RCM-driven simulations by SWAT capture both the timing and amplitude of the seasonal cycle of streamflow with neither demonstrating significant superiority at the basin level. (orig.)

  1. Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

    Science.gov (United States)

    Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

    2015-01-01

    Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

  2. The effects of climate downscaling technique and observational data set on modeled ecological responses

    Science.gov (United States)

    Afshin Pourmokhtarian; Charles T. Driscoll; John L. Campbell; Katharine Hayhoe; Anne M. K. Stoner

    2016-01-01

    Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training...

  3. A modelling methodology for assessing the impact of climate variability and climatic change on hydroelectric generation

    International Nuclear Information System (INIS)

    Munoz, J.R.; Sailor, D.J.

    1998-01-01

    A new methodology relating basic climatic variables to hydroelectric generation was developed. The methodology can be implemented in large or small basins with any number of hydro plants. The method was applied to the Sacramento, Eel and Russian river basins in northern California where more than 100 hydroelectric plants are located. The final model predicts the availability of hydroelectric generation for the entire basin provided present and near past climate conditions, with about 90% accuracy. The results can be used for water management purposes or for analyzing the effect of climate variability on hydrogeneration availability in the basin. A wide range of results can be obtained depending on the climate change scenario used. (Author)

  4. Validation and quantification of uncertainty in coupled climate models using network analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bracco, Annalisa [Georgia Inst. of Technology, Atlanta, GA (United States)

    2015-08-10

    We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies. At the first layer, gridded climate data are used to identify ‘‘areas’’, i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956–2005 have been constrained towards observations or reanalysis data sets

  5. Global Climate Models for the Classroom: The Educational Impact of Student Work with a Key Tool of Climate Scientists

    Science.gov (United States)

    Bush, D. F.; Sieber, R.; Seiler, G.; Chandler, M. A.; Chmura, G. L.

    2017-12-01

    Efforts to address climate change require public understanding of Earth and climate science. To meet this need, educators require instructional approaches and scientific technologies that overcome cultural barriers to impart conceptual understanding of the work of climate scientists. We compared student inquiry learning with now ubiquitous climate education toy models, data and tools against that which took place using a computational global climate model (GCM) from the National Aeronautics and Space Administration (NASA). Our study at McGill University and John Abbott College in Montreal, QC sheds light on how best to teach the research processes important to Earth and climate scientists studying atmospheric and Earth system processes but ill-understood by those outside the scientific community. We followed a pre/post, control/treatment experimental design that enabled detailed analysis and statistically significant results. Our research found more students succeed at understanding climate change when exposed to actual climate research processes and instruments. Inquiry-based education with a GCM resulted in significantly higher scores pre to post on diagnostic exams (quantitatively) and more complete conceptual understandings (qualitatively). We recognize the difficulty in planning and teaching inquiry with complex technology and we also found evidence that lectures support learning geared toward assessment exams.

  6. Mixed precipitation occurrences over southern Québec, Canada, under warmer climate conditions using a regional climate model

    Science.gov (United States)

    Matte, Dominic; Thériault, Julie M.; Laprise, René

    2018-05-01

    Winter weather events with temperatures near 0°C are often associated with freezing rain. They can have major impacts on the society by causing power outages and disruptions to the transportation networks. Despite the catastrophic consequences of freezing rain, very few studies have investigated how their occurrences could evolve under climate change. This study aims to investigate the change of freezing rain and ice pellets over southern Québec using regional climate modeling at high resolution. The fifth-generation Canadian Regional Climate Model with climate scenario RCP 8.5 at 0.11° grid mesh was used. The precipitation types such as freezing rain, ice pellets or their combination are diagnosed using five methods (Cantin and Bachand, Bourgouin, Ramer, Czys and, Baldwin). The occurrences of the diagnosed precipitation types for the recent past (1980-2009) are found to be comparable to observations. The projections for the future scenario (2070-2099) suggested a general decrease in the occurrences of mixed precipitation over southern Québec from October to April. This is mainly due to a decrease in long-duration events (≥6 h ). Overall, this study contributes to better understand how the distribution of freezing rain and ice pellets might change in the future using high-resolution regional climate model.

  7. Storm track response to climate change: Insights from simulations using an idealized dry GCM.

    Science.gov (United States)

    Mbengue, Cheikh; Schneider, Tapio

    2013-04-01

    The midlatitude storm tracks, where the most intense extratropical cyclones are found, are an important fixture in the general circulation. They are instrumental in balancing the Earth's heat, momentum, and moisture budgets and are responsible for the weather and climatic patterns over large regions of the Earth's surface. As a result, the midlatitude storm tracks are the subject of a considerable amount of scientific research to understand their response to global warming. This has produced the robust result showing that the storm tracks migrate poleward with global warming. However, the dynamical mechanisms responsible for this migration remain unclear. Our work seeks to broaden understanding of the dynamical mechanisms responsible for storm track migration. Competing mechanisms present in the comprehensive climate models often used to study storm track dynamics make it difficult to determine the primary mechanisms responsible for storm track migration. We are thus prompted to study storm track dynamics from a simplified and idealized framework, which enables the decoupling of mean temperature effects from the effects of static stability and of tropical from extratropical effects. Using a statistically zonally symmetric, dry general circulation model (GCM), we conduct a series of numerical simulations to help understand the storm track response to global mean temperatures and to the tropical convective static stability, which we can vary independently. We define storm tracks as regions of zonally and temporally averaged maxima of barotropic eddy kinetic energy (EKE). This storm track definition also allows us to use previously found scalings between the magnitude of bulk measures of mean available potential energy (MAPE) and EKE, to decompose MAPE, and to obtain some mechanistic understanding of the storm track response in our simulations. These simulations provide several insights, which enable us to extend upon existing theories on the mechanisms driving the

  8. Future climate scenarios and rainfall-runoff modelling in the Upper Gallego catchment (Spain)

    International Nuclear Information System (INIS)

    Buerger, C.M.; Kolditz, O.; Fowler, H.J.; Blenkinsop, S.

    2007-01-01

    Global climate change may have large impacts on water supplies, drought or flood frequencies and magnitudes in local and regional hydrologic systems. Water authorities therefore rely on computer models for quantitative impact prediction. In this study we present kernel-based learning machine river flow models for the Upper Gallego catchment of the Ebro basin. Different learning machines were calibrated using daily gauge data. The models posed two major challenges: (1) estimation of the rainfall-runoff transfer function from the available time series is complicated by anthropogenic regulation and mountainous terrain and (2) the river flow model is weak when only climate data are used, but additional antecedent flow data seemed to lead to delayed peak flow estimation. These types of models, together with the presented downscaled climate scenarios, can be used for climate change impact assessment in the Gallego, which is important for the future management of the system. - Future climate change and data-based rainfall-runoff predictions are presented for the Upper Gallego

  9. Drivers of stability of climate coalitions in the STACO model

    NARCIS (Netherlands)

    Dellink, R.B.

    2011-01-01

    This paper investigates which drivers affect the formation and stability of international climate agreements (ICAs). The applied model STACO is used to project costs and benefits of an international agreement on climate change mitigation activities. The simulation results show that an

  10. Analyzing the Response of Climate Perturbations to (Tropical) Cyclones using the WRF Model

    Science.gov (United States)

    Tewari, M.; Mittal, R.; Radhakrishnan, C.; Cipriani, J.; Watson, C.

    2015-12-01

    An analysis of global climate models shows considerable changes in the intensity and characteristics of future, warm climate cyclones. At regional scales, deviations in cyclone characteristics are often derived using idealized perturbations in the humidity, temperature and surface conditions. In this work, a more realistic approach is adopted by applying climate perturbations from the Community Climate System Model (CCSM4) to ERA-interim data to generate the initial and boundary conditions for future climate simulations. The climate signal perturbations are generated from the differences in 21 years of mean data from CCSM4 with representative concentration pathways (RCP8.5) for the periods: (a) 2070-2090 (future climate), (b) 2025-2045 (near-future climate) and (c) 1985-2005 (current climate). Four individual cyclone cases are simulated with and without climate perturbations using the Weather Research and Forecasting model with a nested configuration. Each cyclone is characterized by variations in intensity, landfall location, precipitation and societal damage. To calculate societal damage, we use the recently introduced Cyclone Damage Potential (CDP) index evolved from the Willis Hurricane Index (WHI). As CDP has been developed for general societal applications, this work should provide useful insights for resilience analyses and industry (e.g., re-insurance).

  11. CORDEX - a treasure trove of open climate data for hydrological modelling

    Science.gov (United States)

    O'Rourke, Eleanor; Nikulin, Grigory; Kjellström, Erik

    2015-04-01

    The Coordinated Regional Downscaling Experiment (CORDEX) was initiated by the World Climate Research Programme (WCRP) to coordinate high-resolution Regional Climate Modelling and provide a set of regional climate projections for the majority of global land regions. Additionally making this data available, and importantly useable, to impact and adaptation communities was a fundamental goal. Phase I of CORDEX, which came to a close in November 2013, was successful in developing a framework in which scientists around the world adopted a common protocol to guide the development of high-resolution Regional Climate Model (RCM) and empirical statistical downscaling (ESD) projections, and the intercomparison of these projections, on each continent, with a particular focus on the African region. As a result of these intensive activities by groups across the globe more than 47000 quality checked open datasets are now freely available to users through the searchable Earth System Grid Federation (ESGF). The integration of this data into large scale hydrological modelling is in action within the Swedish Meteorological & Hydrological Institute (SMHI) exemplifying the great potential use of this resource to the hydrological community. The aim of CORDEX Phase II is to enhance the dialogue with end-users so as to meet the growing demand for tailored regional climate information. Here, greater interaction between the CORDEX and hydrological modelling community can only prove hugely beneficial leading to greater protection for those vulnerable to the impacts of a changing climate.

  12. Last Interglacial climate and sea-level evolution from a coupled ice sheet-climate model

    Science.gov (United States)

    Goelzer, Heiko; Huybrechts, Philippe; Loutre, Marie-France; Fichefet, Thierry

    2016-12-01

    As the most recent warm period in Earth's history with a sea-level stand higher than present, the Last Interglacial (LIG, ˜ 130 to 115 kyr BP) is often considered a prime example to study the impact of a warmer climate on the two polar ice sheets remaining today. Here we simulate the Last Interglacial climate, ice sheet, and sea-level evolution with the Earth system model of intermediate complexity LOVECLIM v.1.3, which includes dynamic and fully coupled components representing the atmosphere, the ocean and sea ice, the terrestrial biosphere, and the Greenland and Antarctic ice sheets. In this setup, sea-level evolution and climate-ice sheet interactions are modelled in a consistent framework.Surface mass balance change governed by changes in surface meltwater runoff is the dominant forcing for the Greenland ice sheet, which shows a peak sea-level contribution of 1.4 m at 123 kyr BP in the reference experiment. Our results indicate that ice sheet-climate feedbacks play an important role to amplify climate and sea-level changes in the Northern Hemisphere. The sensitivity of the Greenland ice sheet to surface temperature changes considerably increases when interactive albedo changes are considered. Southern Hemisphere polar and sub-polar ocean warming is limited throughout the Last Interglacial, and surface and sub-shelf melting exerts only a minor control on the Antarctic sea-level contribution with a peak of 4.4 m at 125 kyr BP. Retreat of the Antarctic ice sheet at the onset of the LIG is mainly forced by rising sea level and to a lesser extent by reduced ice shelf viscosity as the surface temperature increases. Global sea level shows a peak of 5.3 m at 124.5 kyr BP, which includes a minor contribution of 0.35 m from oceanic thermal expansion. Neither the individual contributions nor the total modelled sea-level stand show fast multi-millennial timescale variations as indicated by some reconstructions.

  13. The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

    Science.gov (United States)

    Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

    2013-10-01

    Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

  14. Failure analysis of parameter-induced simulation crashes in climate models

    Science.gov (United States)

    Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

    2013-08-01

    Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

  15. Modeling the impact of climate change in Germany with biosphere models for long-term safety assessment of nuclear waste repositories.

    Science.gov (United States)

    Staudt, C; Semiochkina, N; Kaiser, J C; Pröhl, G

    2013-01-01

    Biosphere models are used to evaluate the exposure of populations to radionuclides from a deep geological repository. Since the time frame for assessments of long-time disposal safety is 1 million years, potential future climate changes need to be accounted for. Potential future climate conditions were defined for northern Germany according to model results from the BIOCLIM project. Nine present day reference climate regions were defined to cover those future climate conditions. A biosphere model was developed according to the BIOMASS methodology of the IAEA and model parameters were adjusted to the conditions at the reference climate regions. The model includes exposure pathways common to those reference climate regions in a stylized biosphere and relevant to the exposure of a hypothetical self-sustaining population at the site of potential radionuclide contamination from a deep geological repository. The end points of the model are Biosphere Dose Conversion factors (BDCF) for a range of radionuclides and scenarios normalized for a constant radionuclide concentration in near-surface groundwater. Model results suggest an increased exposure of in dry climate regions with a high impact of drinking water consumption rates and the amount of irrigation water used for agriculture. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Integrating geological archives and climate models for the mid-Pliocene warm period

    Science.gov (United States)

    Haywood, Alan M.; Dowsett, Harry J.; Dolan, Aisling M.

    2016-01-01

    The mid-Pliocene Warm Period (mPWP) offers an opportunity to understand a warmer-than-present world and assess the predictive ability of numerical climate models. Environmental reconstruction and climate modelling are crucial for understanding the mPWP, and the synergy of these two, often disparate, fields has proven essential in confirming features of the past and in turn building confidence in projections of the future. The continual development of methodologies to better facilitate environmental synthesis and data/model comparison is essential, with recent work demonstrating that time-specific (time-slice) syntheses represent the next logical step in exploring climate change during the mPWP and realizing its potential as a test bed for understanding future climate change. PMID:26879640

  17. Modeling Two Types of Adaptation to Climate Change

    Science.gov (United States)

    Mitigation and adaptation are the two key responses available to policymakers to reduce the risks of climate change. We model these two policies together in a new DICE-based integrated assessment model that characterizes adaptation as either short-lived flow spending or long-live...

  18. Towards Measures to Establish the Relevance of Climate Model Output for Decision Support

    Science.gov (United States)

    Clarke, L.; Smith, L. A.

    2007-12-01

    How exactly can decision-support and policy making benefit from the use of multiple climate model experiments in terms of coping with the uncertainties on climate change projections? Climate modelling faces challenges beyond those of weather forecasting or even seasonal forecasting, as with climate we are now (and will probably always be) required to extrapolate to regimes in which we have no relevant forecast-verification archive. This suggests a very different approach from traditional methods of mixing models and skill based weighting to gain profitable probabilistic information when a large forecast-verification archive is in hand. In the case of climate, it may prove more rational to search for agreement between our models (in distribution), the aim being to determine the space and timescales on which, given our current understanding, the details of the simulation models are unimportant. This suggestion and others from Smith (2002, Proc. National Acad. Sci. USA 4 (99): 2487-2492) are interpreted in the light of recent advances. Climate models are large nonlinear dynamical systems which insightfully but imperfectly reflect the evolving weather patterns of the Earth. Their use in policy making and decision support assumes both that they contain sufficient information regarding reality to inform the decision, and that this information can be effectively communicated to the decision makers. There is nothing unique about climate modeling and these constraints, they apply in all cases where scientific modeling is applied to real-word actions (other than, perhaps, the action of improving our models). Starting with the issue of communication, figures from the 2007 IPCC Summary for Policy Makers will be constructively criticized from the perspective of decision makers, specifically those of the energy sector and the insurance/reinsurance sector. More information on basic questions of reliability and robustness would be of significant value when determining how heavily

  19. Utilising temperature differences as constraints for estimating parameters in a simple climate model

    International Nuclear Information System (INIS)

    Bodman, Roger W; Karoly, David J; Enting, Ian G

    2010-01-01

    Simple climate models can be used to estimate the global temperature response to increasing greenhouse gases. Changes in the energy balance of the global climate system are represented by equations that necessitate the use of uncertain parameters. The values of these parameters can be estimated from historical observations, model testing, and tuning to more complex models. Efforts have been made at estimating the possible ranges for these parameters. This study continues this process, but demonstrates two new constraints. Previous studies have shown that land-ocean temperature differences are only weakly correlated with global mean temperature for natural internal climate variations. Hence, these temperature differences provide additional information that can be used to help constrain model parameters. In addition, an ocean heat content ratio can also provide a further constraint. A pulse response technique was used to identify relative parameter sensitivity which confirmed the importance of climate sensitivity and ocean vertical diffusivity, but the land-ocean warming ratio and the land-ocean heat exchange coefficient were also found to be important. Experiments demonstrate the utility of the land-ocean temperature difference and ocean heat content ratio for setting parameter values. This work is based on investigations with MAGICC (Model for the Assessment of Greenhouse-gas Induced Climate Change) as the simple climate model.

  20. Climate modelling, uncertainty and responses to predictions of change

    International Nuclear Information System (INIS)

    Henderson-Sellers, A.

    1996-01-01

    Article 4.1(F) of the Framework Convention on Climate Change commits all parties to take climate change considerations into account, to the extent feasible, in relevant social, economic and environmental policies and actions and to employ methods such as impact assessments to minimize adverse effects of climate change. This could be achieved by, inter alia, incorporating climate change risk assessment into development planning processes, i.e. relating climatic change to issues of habitability and sustainability. Adaptation is an ubiquitous and beneficial natural and human strategy. Future adaptation (adjustment) to climate is inevitable at the least to decrease the vulnerability to current climatic impacts. An urgent issue is the mismatch between the predictions of global climatic change and the need for information on local to regional change in order to develop adaptation strategies. Mitigation efforts are essential since the more successful mitigation activities are, the less need there will be for adaptation responses. And, mitigation responses can be global (e.g. a uniform percentage reduction in greenhouse gas emissions) while adaptation responses will be local to regional in character and therefore depend upon confident predictions of regional climatic change. The dilemma facing policymakers is that scientists have considerable confidence in likely global climatic changes but virtually zero confidence in regional changes. Mitigation and adaptation strategies relevant to climatic change can most usefully be developed in the context of sound understanding of climate, especially the near-surface continental climate, permitting discussion of societally relevant issues. But, climate models can't yet deliver this type of regionally and locationally specific prediction and some aspects of current research even seem to indicate increased uncertainty. These topics are explored in this paper using the specific example of the prediction of land-surface climate changes

  1. Impact of ocean model resolution on CCSM climate simulations

    Energy Technology Data Exchange (ETDEWEB)

    Kirtman, Ben P.; Rousset, Clement; Siqueira, Leo [University of Miami, Rosenstiel School for Marine and Atmospheric Science, Coral Gables, FL (United States); Bitz, Cecilia [University of Washington, Department of Atmospheric Science, Seattle, WA (United States); Bryan, Frank; Dennis, John; Hearn, Nathan; Loft, Richard; Tomas, Robert; Vertenstein, Mariana [National Center for Atmospheric Research, Boulder, CO (United States); Collins, William [University of California, Berkeley, Berkeley, CA (United States); Kinter, James L.; Stan, Cristiana [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); George Mason University, Fairfax, VA (United States)

    2012-09-15

    The current literature provides compelling evidence suggesting that an eddy-resolving (as opposed to eddy-permitting or eddy-parameterized) ocean component model will significantly impact the simulation of the large-scale climate, although this has not been fully tested to date in multi-decadal global coupled climate simulations. The purpose of this paper is to examine how resolved ocean fronts and eddies impact the simulation of large-scale climate. The model used for this study is the NCAR Community Climate System Model version 3.5 (CCSM3.5) - the forerunner to CCSM4. Two experiments are reported here. The control experiment is a 155-year present-day climate simulation using a 0.5 atmosphere component (zonal resolution 0.625 meridional resolution 0.5 ; land surface component at the same resolution) coupled to ocean and sea-ice components with zonal resolution of 1.2 and meridional resolution varying from 0.27 at the equator to 0.54 in the mid-latitudes. The second simulation uses the same atmospheric and land-surface models coupled to eddy-resolving 0.1 ocean and sea-ice component models. The simulations are compared in terms of how the representation of smaller scale features in the time mean ocean circulation and ocean eddies impact the mean and variable climate. In terms of the global mean surface temperature, the enhanced ocean resolution leads to a ubiquitous surface warming with a global mean surface temperature increase of about 0.2 C relative to the control. The warming is largest in the Arctic and regions of strong ocean fronts and ocean eddy activity (i.e., Southern Ocean, western boundary currents). The Arctic warming is associated with significant losses of sea-ice in the high-resolution simulation. The sea surface temperature gradients in the North Atlantic, in particular, are better resolved in the high-resolution model leading to significantly sharper temperature gradients and associated large-scale shifts in the rainfall. In the extra-tropics, the

  2. Modelling Bambara Groundnut Yield in Southern Africa: Towards a Climate-Resilient Future

    Science.gov (United States)

    Karunaratne, A. S.; Walker, S.; Ruane, A. C.

    2015-01-01

    Current agriculture depends on a few major species grown as monocultures that are supported by global research underpinning current productivity. However, many hundreds of alternative crops have the potential to meet real world challenges by sustaining humanity, diversifying agricultural systems for food and nutritional security, and especially responding to climate change through their resilience to certain climate conditions. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilised African legume, is an exemplar crop for climate resilience. Predicted yield performances of Bambara groundnut by AquaCrop (a crop-water productivity model) were evaluated for baseline (1980-2009) and mid-century climates (2040-2069) under 20 downscaled Global Climate Models (CMIP5-RCP8.5), as well as for climate sensitivities (AgMIPC3MP) across 3 locations in Southern Africa (Botswana, South Africa, Namibia). Different land - races of Bambara groundnut originating from various semi-arid African locations showed diverse yield performances with diverse sensitivities to climate. S19 originating from hot-dry conditions in Namibia has greater future yield potential compared to the Swaziland landrace Uniswa Red-UN across study sites. South Africa has the lowest yield under the current climate, indicating positive future yield trends. Namibia reported the highest baseline yield at optimum current temperatures, indicating less yield potential in future climates. Bambara groundnut shows positive yield potential at temperatures of up to 31degC, with further warming pushing yields down. Thus, many regions in Southern Africa can utilize Bambara groundnut successfully in the coming decades. This modelling exercise supports decisions on genotypic suitability for present and future climates at specific locations.

  3. Can model weighting improve probabilistic projections of climate change?

    Energy Technology Data Exchange (ETDEWEB)

    Raeisaenen, Jouni; Ylhaeisi, Jussi S. [Department of Physics, P.O. Box 48, University of Helsinki (Finland)

    2012-10-15

    Recently, Raeisaenen and co-authors proposed a weighting scheme in which the relationship between observable climate and climate change within a multi-model ensemble determines to what extent agreement with observations affects model weights in climate change projection. Within the Third Coupled Model Intercomparison Project (CMIP3) dataset, this scheme slightly improved the cross-validated accuracy of deterministic projections of temperature change. Here the same scheme is applied to probabilistic temperature change projection, under the strong limiting assumption that the CMIP3 ensemble spans the actual modeling uncertainty. Cross-validation suggests that probabilistic temperature change projections may also be improved by this weighting scheme. However, the improvement relative to uniform weighting is smaller in the tail-sensitive logarithmic score than in the continuous ranked probability score. The impact of the weighting on projection of real-world twenty-first century temperature change is modest in most parts of the world. However, in some areas mainly over the high-latitude oceans, the mean of the distribution is substantially changed and/or the distribution is considerably narrowed. The weights of individual models vary strongly with location, so that a model that receives nearly zero weight in some area may still get a large weight elsewhere. Although the details of this variation are method-specific, it suggests that the relative strengths of different models may be difficult to harness by weighting schemes that use spatially uniform model weights. (orig.)

  4. Modelling Impacts of Climate Change: Case Studies using the New Generation of Erosion Models

    Science.gov (United States)

    Climate change is expected to impact upon a number of soil erosion drivers and processes, which should be taken into account when designing a modelling strategy. The fourth assessment report of the Intergovernmental Panel for Climate Change (IPCC) (Parry et al., 2007; Solomon et al., 2007) reviews a...

  5. Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

    Science.gov (United States)

    Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

    2018-04-01

    The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

  6. Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Jaroslav Solc

    2009-06-01

    The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.

  7. A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

    Directory of Open Access Journals (Sweden)

    M Irfan Ashraf

    Full Text Available Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model. Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2 5-year(-1 and volume: 0.0008 m(3 5-year(-1. Model variability described by root mean squared error (RMSE in basal area prediction was 40.53 cm(2 5-year(-1 and 0.0393 m(3 5-year(-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence

  8. Numerical Modeling of Climate-Chemistry Connections: Recent Developments and Future Challenges

    Directory of Open Access Journals (Sweden)

    Patrick Jöckel

    2013-05-01

    Full Text Available This paper reviews the current state and development of different numerical model classes that are used to simulate the global atmospheric system, particularly Earth’s climate and climate-chemistry connections. The focus is on Chemistry-Climate Models. In general, these serve to examine dynamical and chemical processes in the Earth atmosphere, their feedback, and interaction with climate. Such models have been established as helpful tools in addition to analyses of observational data. Definitions of the global model classes are given and their capabilities as well as weaknesses are discussed. Examples of scientific studies indicate how numerical exercises contribute to an improved understanding of atmospheric behavior. There, the focus is on synergistic investigations combining observations and model results. The possible future developments and challenges are presented, not only from the scientific point of view but also regarding the computer technology and respective consequences for numerical modeling of atmospheric processes. In the future, a stronger cross-linkage of subject-specific scientists is necessary, to tackle the looming challenges. It should link the specialist discipline and applied computer science.

  9. Automated parameter tuning applied to sea ice in a global climate model

    Science.gov (United States)

    Roach, Lettie A.; Tett, Simon F. B.; Mineter, Michael J.; Yamazaki, Kuniko; Rae, Cameron D.

    2018-01-01

    This study investigates the hypothesis that a significant portion of spread in climate model projections of sea ice is due to poorly-constrained model parameters. New automated methods for optimization are applied to historical sea ice in a global coupled climate model (HadCM3) in order to calculate the combination of parameters required to reduce the difference between simulation and observations to within the range of model noise. The optimized parameters result in a simulated sea-ice time series which is more consistent with Arctic observations throughout the satellite record (1980-present), particularly in the September minimum, than the standard configuration of HadCM3. Divergence from observed Antarctic trends and mean regional sea ice distribution reflects broader structural uncertainty in the climate model. We also find that the optimized parameters do not cause adverse effects on the model climatology. This simple approach provides evidence for the contribution of parameter uncertainty to spread in sea ice extent trends and could be customized to investigate uncertainties in other climate variables.

  10. Estimating uncertainty and its temporal variation related to global climate models in quantifying climate change impacts on hydrology

    Science.gov (United States)

    Shen, Mingxi; Chen, Jie; Zhuan, Meijia; Chen, Hua; Xu, Chong-Yu; Xiong, Lihua

    2018-01-01

    Uncertainty estimation of climate change impacts on hydrology has received much attention in the research community. The choice of a global climate model (GCM) is usually considered as the largest contributor to the uncertainty of climate change impacts. The temporal variation of GCM uncertainty needs to be investigated for making long-term decisions to deal with climate change. Accordingly, this study investigated the temporal variation (mainly long-term) of uncertainty related to the choice of a GCM in predicting climate change impacts on hydrology by using multi-GCMs over multiple continuous future periods. Specifically, twenty CMIP5 GCMs under RCP4.5 and RCP8.5 emission scenarios were adapted to adequately represent this uncertainty envelope, fifty-one 30-year future periods moving from 2021 to 2100 with 1-year interval were produced to express the temporal variation. Future climatic and hydrological regimes over all future periods were compared to those in the reference period (1971-2000) using a set of metrics, including mean and extremes. The periodicity of climatic and hydrological changes and their uncertainty were analyzed using wavelet analysis, while the trend was analyzed using Mann-Kendall trend test and regression analysis. The results showed that both future climate change (precipitation and temperature) and hydrological response predicted by the twenty GCMs were highly uncertain, and the uncertainty increased significantly over time. For example, the change of mean annual precipitation increased from 1.4% in 2021-2050 to 6.5% in 2071-2100 for RCP4.5 in terms of the median value of multi-models, but the projected uncertainty reached 21.7% in 2021-2050 and 25.1% in 2071-2100 for RCP4.5. The uncertainty under a high emission scenario (RCP8.5) was much larger than that under a relatively low emission scenario (RCP4.5). Almost all climatic and hydrological regimes and their uncertainty did not show significant periodicity at the P = .05 significance

  11. Modelling the influence of climate on malaria occurrence in Chimoio Municipality, Mozambique.

    Science.gov (United States)

    Ferrão, João Luís; Mendes, Jorge M; Painho, Marco

    2017-05-25

    Mozambique was recently ranked fifth in the African continent for the number of cases of malaria. In Chimoio municipality cases of malaria are increasing annually, contrary to the decreasing trend in Africa. As malaria transmission is influenced to a large extent by climatic conditions, modelling this relationship can provide useful insights for designing precision health measures for malaria control. There is a scarcity of information on the association between climatic variability and malaria transmission risk in Mozambique in general, and in Chimoio in particular. Therefore, the aim of this study is to model the association between climatic variables and malaria cases on a weekly basis, to help policy makers find adequate measures for malaria control and eradication. Time series analysis was conducted using data on weekly climatic variables and weekly malaria cases (counts) in Chimoio municipality, from 2006 to 2014. All data were analysed using SPSS-20, R 3.3.2 and BioEstat 5.0. Cross-correlation analysis, linear processes, namely ARIMA models and regression modelling, were used to develop the final model. Between 2006 and 2014, 490,561 cases of malaria were recorded in Chimoio. Both malaria and climatic data exhibit weekly and yearly systematic fluctuations. Cross-correlation analysis showed that mean temperature and precipitation present significantly lagged correlations with malaria cases. An ARIMA model (2,1,0) (2,1,1) 52 , and a regression model for a Box-Cox transformed number of malaria cases with lags 1, 2 and 3 of weekly malaria cases and lags 6 and 7 of weekly mean temperature and lags 12 of precipitation were fitted. Although, both produced similar widths for prediction intervals, the last was able to anticipate malaria outbreak more accurately. The Chimoio climate seems ideal for malaria occurrence. Malaria occurrence peaks during January to March in Chimoio. As the lag effect between climatic events and malaria occurrence is important for the

  12. Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods

    Science.gov (United States)

    Hakala, Kirsti; Addor, Nans; Seibert, Jan

    2017-04-01

    Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of

  13. Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

    Science.gov (United States)

    Wanders, N.; Van Lanen, H. A. J.

    2015-03-01

    Hydrological drought characteristics (drought in groundwater and streamflow) likely will change in the 21st century as a result of climate change. The magnitude and directionality of these changes and their dependency on climatology and catchment characteristics, however, is uncertain. In this study a conceptual hydrological model was forced by downscaled and bias-corrected outcome from three general circulation models for the SRES A2 emission scenario (GCM forced models), and the WATCH Forcing Data set (reference model). The threshold level method was applied to investigate drought occurrence, duration and severity. Results for the control period (1971-2000) show that the drought characteristics of each GCM forced model reasonably agree with the reference model for most of the climate types, suggesting that the climate models' results after post-processing produce realistic outcomes for global drought analyses. For the near future (2021-2050) and far future (2071-2100) the GCM forced models show a decrease in drought occurrence for all major climates around the world and increase of both average drought duration and deficit volume of the remaining drought events. The largest decrease in hydrological drought occurrence is expected in cold (D) climates where global warming results in a decreased length of the snow season and an increased precipitation. In the dry (B) climates the smallest decrease in drought occurrence is expected to occur, which probably will lead to even more severe water scarcity. However, in the extreme climate regions (desert and polar), the drought analysis for the control period showed that projections of hydrological drought characteristics are most uncertain. On a global scale the increase in hydrological drought duration and severity in multiple regions will lead to a higher impact of drought events, which should motivate water resource managers to timely anticipate the increased risk of more severe drought in groundwater and streamflow

  14. Toward an ultra-high resolution community climate system model for the BlueGene platform

    International Nuclear Information System (INIS)

    Dennis, John M; Jacob, Robert; Vertenstein, Mariana; Craig, Tony; Loy, Raymond

    2007-01-01

    Global climate models need to simulate several small, regional-scale processes which affect the global circulation in order to accurately simulate the climate. This is particularly important in the ocean where small scale features such as oceanic eddies are currently represented with adhoc parameterizations. There is also a need for higher resolution to provide climate predictions at small, regional scales. New high-performance computing platforms such as the IBM BlueGene can provide the necessary computational power to perform ultra-high resolution climate model integrations. We have begun to investigate the scaling of the individual components of the Community Climate System Model to prepare it for integrations on BlueGene and similar platforms. Our investigations show that it is possible to successfully utilize O(32K) processors. We describe the scalability of five models: the Parallel Ocean Program (POP), the Community Ice CodE (CICE), the Community Land Model (CLM), and the new CCSM sequential coupler (CPL7) which are components of the next generation Community Climate System Model (CCSM); as well as the High-Order Method Modeling Environment (HOMME) which is a dynamical core currently being evaluated within the Community Atmospheric Model. For our studies we concentrate on 1/10 0 resolution for CICE, POP, and CLM models and 1/4 0 resolution for HOMME. The ability to simulate high resolutions on the massively parallel petascale systems that will dominate high-performance computing for the foreseeable future is essential to the advancement of climate science

  15. A continuous latitudinal energy balance model to explore non-uniform climate engineering strategies

    Science.gov (United States)

    Bonetti, F.; McInnes, C. R.

    2016-12-01

    Current concentrations of atmospheric CO2 exceed measured historical levels in modern times, largely attributed to anthropogenic forcing since the industrial revolution. The required decline in emissions rates has never been achieved leading to recent interest in climate engineering for future risk-mitigation strategies. Climate engineering aims to offset human-driven climate change. It involves techniques developed both to reduce the concentration of CO2 in the atmosphere (Carbon Dioxide Removal (CDR) methods) and to counteract the radiative forcing that it generates (Solar Radiation Management (SRM) methods). In order to investigate effects of SRM technologies for climate engineering, an analytical model describing the main dynamics of the Earth's climate has been developed. The model is a time-dependent Energy Balance Model (EBM) with latitudinal resolution and allows for the evaluation of non-uniform climate engineering strategies. A significant disadvantage of climate engineering techniques involving the management of solar radiation is regional disparities in cooling. This model offers an analytical approach to design multi-objective strategies that counteract climate change on a regional basis: for example, to cool the Artic and restrict undesired impacts at mid-latitudes, or to control the equator-to-pole temperature gradient. Using the Green's function approach the resulting partial differential equation allows for the computation of the surface temperature as a function of time and latitude when a 1% per year increase in the CO2 concentration is considered. After the validation of the model through comparisons with high fidelity numerical models, it will be used to explore strategies for the injection of the aerosol precursors in the stratosphere. In particular, the model involves detailed description of the optical properties of the particles, the wash-out dynamics and the estimation of the radiative cooling they can generate.

  16. THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE

    OpenAIRE

    Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

    2015-01-01

    Background: The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran?s universities. Methods: This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran?s public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For pr...

  17. Expected utility and catastrophic risk in a stochastic economy-climate model

    Energy Technology Data Exchange (ETDEWEB)

    Ikefuji, M. [Institute of Social and Economic Research, Osaka University, Osaka (Japan); Laeven, R.J.A.; Magnus, J.R. [Department of Econometrics and Operations Research, Tilburg University, Tilburg (Netherlands); Muris, C. [CentER, Tilburg University, Tilburg (Netherlands)

    2010-11-15

    In the context of extreme climate change, we ask how to conduct expected utility analysis in the presence of catastrophic risks. Economists typically model decision making under risk and uncertainty by expected utility with constant relative risk aversion (power utility); statisticians typically model economic catastrophes by probability distributions with heavy tails. Unfortunately, the expected utility framework is fragile with respect to heavy-tailed distributional assumptions. We specify a stochastic economy-climate model with power utility and explicitly demonstrate this fragility. We derive necessary and sufficient compatibility conditions on the utility function to avoid fragility and solve our stochastic economy-climate model for two examples of such compatible utility functions. We further develop and implement a procedure to learn the input parameters of our model and show that the model thus specified produces quite robust optimal policies. The numerical results indicate that higher levels of uncertainty (heavier tails) lead to less abatement and consumption, and to more investment, but this effect is not unlimited.

  18. CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

    Science.gov (United States)

    Rose, B. E. J.

    2015-12-01

    Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

  19. Evaluating Impacts of climate and land use changes on streamflow using SWAT and land use models based CESM1-CAM5 Climate scenarios

    Science.gov (United States)

    Lin, Tzu Ping; Lin, Yu Pin; Lien, Wan Yu

    2015-04-01

    Climate change projects have various levels of impacts on hydrological cycles around the world. The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from the Coupled Model Intercomparison Project (CMIP5) which has been just be released in Taiwan, 2014. Since the streamflow run into ocean directly due to the steep terrain and the rainfall difference between wet and dry seasons is apparent; as a result, the allocation water resource reasonable is very challenge in Taiwan, particularly under climate change. The purpose of this study was to evaluate the impacts of climate and land use changes on a small watershed in Taiwan. The AR5 General Circulation Models(GCM) output data was adopted in this study and was downscaled from the monthly to the daily weather data as the input data of hydrological model such as Soil and Water Assessment Tool (SWAT) model in this study. The spatially explicit land uses change model, the Conservation of Land Use and its Effects at Small regional extent (CLUE-s), was applied to simulate land use scenarios in 2020-2039. Combined climate and land use change scenarios were adopted as input data of the hydrological model, the SWAT model, to estimate the future streamflows. With the increasing precipitation, increasing urban area and decreasing agricultural and grass land, the annual streamflow in the most of twenty-three subbasins were also increased. Besides, due to the increasing rainfall in wet season and decreasing rainfall in dry season, the difference of streamflow between wet season and dry season are also increased. This result indicates a more stringent challenge on the water resource management in future. Therefore, impacts on water resource caused by climate change and land use change should be considered in water resource planning for the Datuan river watershed. Keywords: SWAT, GCM, CLUE-s, streamflow, climate change, land use change

  20. Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

    DEFF Research Database (Denmark)

    Eby, M.; Weaver, A. J.; Alexander, K.

    2013-01-01

    Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE...... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20...