Modelling the climate of the last millennium: what causes the differences between simulations?

NARCIS (Netherlands)

Goosse, H.; Crowley, T.J.; Zorita, E.; Ammann, C.M.; Renssen, H.; Driesschaert, E.

2005-01-01

An ensemble of simulations performed with a coarse resolution 3-D climate model driven by various combinations of external forcing is used to investigate possible causes for differences noticed in two recent simulations of the climate of the past millennium using General Circulation Models (GCMs).

Responses of the ocean carbon cycle to climate change: Results from an earth system climate model simulation

Institute of Scientific and Technical Information of China (English)

WANG Shuang-Jing; CAO Long; LI Na

2014-01-01

Based on simulations using the University of Victoria’s Earth System Climate Model, we analyzed the responses of the ocean carbon cycle to increasing atmospheric CO2 levels and climate change from 1800 to 2500 following the RCP 8.5 scenario and its extension. Compared to simulations without climate change, the simulation with a climate sensitivity of 3.0 K shows that in 2100, due to increased atmospheric CO2 concentrations, the simulated sea surface temperature increases by 2.7 K, the intensity of the North Atlantic deep water formation reduces by4.5 Sv, and the oceanic uptake of anthropogenic CO2 decreases by 0.8 Pg C. Climate change is also found to have a large effect on the North Atlantic’s ocean column inventory of anthropogenic CO2. Between the years 1800 and 2500, compared with the simulation with no climate change, the simulation with climate change causes a reduction in the total anthropogenic CO2 column inventory over the entire ocean and in North Atlantic by 23.1% and 32.0%, respectively. A set of simulations with climate sensitivity variations from 0.5 K to 4.5 K show that with greater climate sensitivity climate change would have a greater effect in reducing the ocean’s ability to absorb CO2 from the atmosphere.

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.

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.;

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.

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.

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.)

Can climate models be tuned to simulate the global mean absolute temperature correctly?

Science.gov (United States)

Duan, Q.; Shi, Y.; Gong, W.

2016-12-01

The Inter-government Panel on Climate Change (IPCC) has already issued five assessment reports (ARs), which include the simulation of the past climate and the projection of the future climate under various scenarios. The participating models can simulate reasonably well the trend in global mean temperature change, especially of the last 150 years. However, there is a large, constant discrepancy in terms of global mean absolute temperature simulations over this period. This discrepancy remained in the same range between IPCC-AR4 and IPCC-AR5, which amounts to about 3oC between the coldest model and the warmest model. This discrepancy has great implications to the land processes, particularly the processes related to the cryosphere, and casts doubts over if land-atmosphere-ocean interactions are correctly considered in those models. This presentation aims to explore if this discrepancy can be reduced through model tuning. We present an automatic model calibration strategy to tune the parameters of a climate model so the simulated global mean absolute temperature would match the observed data over the last 150 years. An intermediate complexity model known as LOVECLIM is used in the study. This presentation will show the preliminary results.

Simulating Climate Change in Ireland

Science.gov (United States)

Nolan, P.; Lynch, P.

2012-04-01

At the Meteorology & Climate Centre at University College Dublin, we are using the CLM-Community's COSMO-CLM Regional Climate Model (RCM) and the WRF RCM (developed at NCAR) to simulate the climate of Ireland at high spatial resolution. To address the issue of model uncertainty, a Multi-Model Ensemble (MME) approach is used. The ensemble method uses different RCMs, driven by several Global Climate Models (GCMs), to simulate climate change. Through the MME approach, the uncertainty in the RCM projections is quantified, enabling us to estimate the probability density function of predicted changes, and providing a measure of confidence in the predictions. The RCMs were validated by performing a 20-year simulation of the Irish climate (1981-2000), driven by ECMWF ERA-40 global re-analysis data, and comparing the output to observations. Results confirm that the output of the RCMs exhibit reasonable and realistic features as documented in the historical data record. Projections for the future Irish climate were generated by downscaling the Max Planck Institute's ECHAM5 GCM, the UK Met Office HadGEM2-ES GCM and the CGCM3.1 GCM from the Canadian Centre for Climate Modelling. Simulations were run for a reference period 1961-2000 and future period 2021-2060. The future climate was simulated using the A1B, A2, B1, RCP 4.5 & RCP 8.5 greenhouse gas emission scenarios. Results for the downscaled simulations show a substantial overall increase in precipitation and wind speed for the future winter months and a decrease during the summer months. The predicted annual change in temperature is approximately 1.1°C over Ireland. To date, all RCM projections are in general agreement, thus increasing our confidence in the robustness of the results.

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

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

Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium - Part 1: Theory

Science.gov (United States)

Sundberg, R.; Moberg, A.; Hind, A.

2012-08-01

A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations.

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.

Weather regimes in past climate atmospheric general circulation model simulations

Energy Technology Data Exchange (ETDEWEB)

Kageyama, M.; Ramstein, G. [CEA Saclay, Gif-sur-Yvette (France). Lab. des Sci. du Climat et de l' Environnement; D' Andrea, F.; Vautard, R. [Laboratoire de Meteorologie Dynamique, Ecole Normale Superieure, Paris (France); Valdes, P.J. [Department of Meteorology, University of Reading (United Kingdom)

1999-10-01

We investigate the climates of the present-day, inception of the last glaciation (115000 y ago) and last glacial maximum (21000 y ago) in the extratropical north Atlantic and Europe, as simulated by the laboratoire de Meteorologie dynamique atmospheric general circulation model. We use these simulations to investigate the low-frequency variability of the model in different climates. The aim is to evaluate whether changes in the intraseasonal variability, which we characterize using weather regimes, can help describe the impact of different boundary conditions on climate and give a better understanding of climate change processes. Weather regimes are defined as the most recurrent patterns in the 500 hPa geopotential height, using a clustering algorithm method. The regimes found in the climate simulations of the present-day and inception of the last glaciation are similar in their number and their structure. It is the regimes' populations which are found to be different for these climates, with an increase of the model's blocked regime and a decrease in the zonal regime at the inception of the last glaciation. This description reinforces the conclusions from a study of the differences between the climatological averages of the different runs and confirms the northeastward shift to the tail of the Atlantic storm-track, which would favour more precipitation over the site of growth of the Fennoscandian ice-sheet. On the other hand, the last glacial maximum results over this sector are not found to be classifiable, showing that the change in boundary conditions can be responsible for severe changes in the weather regime and low-frequency dynamics. The LGM Atlantic low-frequency variability appears to be dominated by a large-scale retrogressing wave with a period 40 to 50 days. (orig.)

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

GFDL's CM2 global coupled climate models. Part I: Formulation and simulation characteristics

Science.gov (United States)

Delworth, T.L.; Broccoli, A.J.; Rosati, A.; Stouffer, R.J.; Balaji, V.; Beesley, J.A.; Cooke, W.F.; Dixon, K.W.; Dunne, J.; Dunne, K.A.; Durachta, J.W.; Findell, K.L.; Ginoux, P.; Gnanadesikan, A.; Gordon, C.T.; Griffies, S.M.; Gudgel, R.; Harrison, M.J.; Held, I.M.; Hemler, R.S.; Horowitz, L.W.; Klein, S.A.; Knutson, T.R.; Kushner, P.J.; Langenhorst, A.R.; Lee, H.-C.; Lin, S.-J.; Lu, J.; Malyshev, S.L.; Milly, P.C.D.; Ramaswamy, V.; Russell, J.; Schwarzkopf, M.D.; Shevliakova, E.; Sirutis, J.J.; Spelman, M.J.; Stern, W.F.; Winton, M.; Wittenberg, A.T.; Wyman, B.; Zeng, F.; Zhang, R.

2006-01-01

The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved. Tw o versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2?? latitude ?? 2.5?? longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1?? in latitude and longitude, with meridional resolution equatorward of 30?? becoming progressively finer, such that the meridional resolution is 1/3?? at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments. The co ntrol simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and

A review on vegetation models and applicability to climate simulations at regional scale

Science.gov (United States)

Myoung, Boksoon; Choi, Yong-Sang; Park, Seon Ki

2011-11-01

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson's rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.

Do downscaled general circulation models reliably simulate historical climatic conditions?

Science.gov (United States)

Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

2018-01-01

The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

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....

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.

How realistic are air quality hindcasts driven by forcings from climate model simulations?

Science.gov (United States)

Lacressonnière, G.; Peuch, V.-H.; Arteta, J.; Josse, B.; Joly, M.; Marécal, V.; Saint Martin, D.; Déqué, M.; Watson, L.

2012-12-01

Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period; analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run results in a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 5-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure, etc.) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities, etc.). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O3, NOx, SO2 and, with some bias that can be explained by the set-up, PM10. We study how the simulations driven by climate

Comparison of Explicitly Simulated and Downscaled Tropical Cyclone Activity in a High-Resolution Global Climate Model

Directory of Open Access Journals (Sweden)

Hirofumi Tomita

2010-01-01

Full Text Available The response of tropical cyclone activity to climate change is a matter of great inherent interest and practical importance. Most current global climate models are not, however, capable of adequately resolving tropical cyclones; this has led to the development of downscaling techniques designed to infer tropical cyclone activity from the large-scale fields produced by climate models. Here we compare the statistics of tropical cyclones simulated explicitly in a very high resolution (~14 km grid mesh global climate model to the results of one such downscaling technique driven by the same global model. This is done for a simulation of the current climate and also for a simulation of a climate warmed by the addition of carbon dioxide. The explicitly simulated and downscaled storms are similarly distributed in space, but the intensity distribution of the downscaled events has a somewhat longer high-intensity tail, owing to the higher resolution of the downscaling model. Both explicitly simulated and downscaled events show large increases in the frequency of events at the high-intensity ends of their respective intensity distributions, but the downscaled storms also show increases in low-intensity events, whereas the explicitly simulated weaker events decline in number. On the regional scale, there are large differences in the responses of the explicitly simulated and downscaled events to global warming. In particular, the power dissipation of downscaled events shows a 175% increase in the Atlantic, while the power dissipation of explicitly simulated events declines there.

Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

Science.gov (United States)

Tao, F.; Rötter, R.

2013-12-01

Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for

A comparison of simulation results from two terrestrial carbon cycle models using three climate data sets

International Nuclear Information System (INIS)

Ito, Akihiko; Sasai, Takahiro

2006-01-01

This study addressed how different climate data sets influence simulations of the global terrestrial carbon cycle. For the period 1982-2001, we compared the results of simulations based on three climate data sets (NCEP/NCAR, NCEP/DOE AMIP-II and ERA40) employed in meteorological, ecological and biogeochemical studies and two different models (BEAMS and Sim-CYCLE). The models differed in their parameterizations of photosynthetic and phenological processes but used the same surface climate (e.g. shortwave radiation, temperature and precipitation), vegetation, soil and topography data. The three data sets give different climatic conditions, especially for shortwave radiation, in terms of long-term means, linear trends and interannual variability. Consequently, the simulation results for global net primary productivity varied by 16%-43% only from differences in the climate data sets, especially in these regions where the shortwave radiation data differed markedly: differences in the climate data set can strongly influence simulation results. The differences among the climate data set and between the two models resulted in slightly different spatial distribution and interannual variability in the net ecosystem carbon budget. To minimize uncertainty, we should pay attention to the specific climate data used. We recommend developing an accurate standard climate data set for simulation studies

An ARM data-oriented diagnostics package to evaluate the climate model simulation

Science.gov (United States)

Zhang, C.; Xie, S.

2016-12-01

A set of diagnostics that utilize long-term high frequency measurements from the DOE Atmospheric Radiation Measurement (ARM) program is developed for evaluating the regional simulation of clouds, radiation and precipitation in climate models. The diagnostics results are computed and visualized automatically in a python-based package that aims to serve as an easy entry point for evaluating climate simulations using the ARM data, as well as the CMIP5 multi-model simulations. Basic performance metrics are computed to measure the accuracy of mean state and variability of simulated regional climate. The evaluated physical quantities include vertical profiles of clouds, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, radiative fluxes, aerosol and cloud microphysical properties. Process-oriented diagnostics focusing on individual cloud and precipitation-related phenomena are developed for the evaluation and development of specific model physical parameterizations. Application of the ARM diagnostics package will be presented in the AGU session. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, IM release number is: LLNL-ABS-698645.

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

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

The physics and dynamics of the climate system simulation of climate change

International Nuclear Information System (INIS)

Mitchell, J.F.B.

1991-01-01

The use of climate models is described, using examples related to: the greenhouse effect, the principal absorbers, past, present and future, climate feedbacks in CO2 experiments, equilibrium climate change due to increased CO2, modelling the transient response to increases in trace gases, uncertainties in the simulation and detection of the climatic effect of increased trace gas, simulations for 9000 years before present

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.)

Uncertainty in Simulating Wheat Yields Under Climate Change

Science.gov (United States)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

Large-scale atmospheric circulation biases and changes in global climate model simulations and their importance for climate change in Central Europe

Directory of Open Access Journals (Sweden)

A. P. van Ulden

2006-01-01

Full Text Available The quality of global sea level pressure patterns has been assessed for simulations by 23 coupled climate models. Most models showed high pattern correlations. With respect to the explained spatial variance, many models showed serious large-scale deficiencies, especially at mid-latitudes. Five models performed well at all latitudes and for each month of the year. Three models had a reasonable skill. We selected the five models with the best pressure patterns for a more detailed assessment of their simulations of the climate in Central Europe. We analysed observations and simulations of monthly mean geostrophic flow indices and of monthly mean temperature and precipitation. We used three geostrophic flow indices: the west component and south component of the geostrophic wind at the surface and the geostrophic vorticity. We found that circulation biases were important, and affected precipitation in particular. Apart from these circulation biases, the models showed other biases in temperature and precipitation, which were for some models larger than the circulation induced biases. For the 21st century the five models simulated quite different changes in circulation, precipitation and temperature. Precipitation changes appear to be primarily caused by circulation changes. Since the models show widely different circulation changes, especially in late summer, precipitation changes vary widely between the models as well. Some models simulate severe drying in late summer, while one model simulates significant precipitation increases in late summer. With respect to the mean temperature the circulation changes were important, but not dominant. However, changes in the distribution of monthly mean temperatures, do show large indirect influences of circulation changes. Especially in late summer, two models simulate very strong warming of warm months, which can be attributed to severe summer drying in the simulations by these models. The models differ also

Adjoint-Based Climate Model Tuning: Application to the Planet Simulator

Science.gov (United States)

Lyu, Guokun; Köhl, Armin; Matei, Ion; Stammer, Detlef

2018-01-01

The adjoint method is used to calibrate the medium complexity climate model "Planet Simulator" through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA-Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models.

Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms.

Science.gov (United States)

Vautard, Robert; Thais, Françoise; Tobin, Isabelle; Bréon, François-Marie; Devezeaux de Lavergne, Jean-Guy; Colette, Augustin; Yiou, Pascal; Ruti, Paolo Michele

2014-01-01

The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions.

Heat waves over Central Europe in regional climate model simulations

Science.gov (United States)

Lhotka, Ondřej; Kyselý, Jan

2014-05-01

Regional climate models (RCMs) have become a powerful tool for exploring impacts of global climate change on a regional scale. The aim of the study is to evaluate the capability of RCMs to reproduce characteristics of major heat waves over Central Europe in their simulations of the recent climate (1961-2000), with a focus on the most severe and longest Central European heat wave that occurred in 1994. We analyzed 7 RCM simulations with a high resolution (0.22°) from the ENSEMBLES project, driven by the ERA-40 reanalysis. In observed data (the E-OBS 9.0 dataset), heat waves were defined on the basis of deviations of daily maximum temperature (Tmax) from the 95% quantile of summer Tmax distribution in grid points over Central Europe. The same methodology was applied in the RCM simulations; we used corresponding 95% quantiles (calculated for each RCM and grid point) in order to remove the bias of modelled Tmax. While climatological characteristics of heat waves are reproduced reasonably well in the RCM ensemble, we found major deficiencies in simulating heat waves in individual years. For example, METNOHIRHAM simulated very severe heat waves in 1996, when no heat wave was observed. Focusing on the major 1994 heat wave, considerable differences in simulated temperature patterns were found among the RCMs. The differences in the temperature patterns were clearly linked to the simulated amount of precipitation during this event. The 1994 heat wave was almost absent in all RCMs that did not capture the observed precipitation deficit, while it was by far most pronounced in KNMI-RACMO that simulated virtually no precipitation over Central Europe during the 15-day period of the heat wave. By contrast to precipitation, values of evaporative fraction in the RCMs were not linked to severity of the simulated 1994 heat wave. This suggests a possible major contribution of other factors such as cloud cover and associated downward shortwave radiation. Therefore, a more detailed

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.

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.

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.)

Vegetation-climate feedback causes reduced precipitation in CMIP5 regional Earth system model simulation over Africa

Science.gov (United States)

Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick

2013-04-01

Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and

A new synoptic scale resolving global climate simulation using the Community Earth System Model

Science.gov (United States)

Small, R. Justin; Bacmeister, Julio; Bailey, David; Baker, Allison; Bishop, Stuart; Bryan, Frank; Caron, Julie; Dennis, John; Gent, Peter; Hsu, Hsiao-ming; Jochum, Markus; Lawrence, David; Muñoz, Ernesto; diNezio, Pedro; Scheitlin, Tim; Tomas, Robert; Tribbia, Joseph; Tseng, Yu-heng; Vertenstein, Mariana

2014-12-01

High-resolution global climate modeling holds the promise of capturing planetary-scale climate modes and small-scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state-of-the-art high-resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of "present-day" simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El-Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small-scale features of the climate system to be represented, such as air-sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high-resolution run employed 23,404 cores, costing 250 thousand processor-hours per simulated year and made about two simulated years per day on the NCAR-Wyoming supercomputer "Yellowstone."

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.

Errors and uncertainties introduced by a regional climate model in climate impact assessments: example of crop yield simulations in West Africa

International Nuclear Information System (INIS)

Ramarohetra, Johanna; Pohl, Benjamin; Sultan, Benjamin

2015-01-01

The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting (WRF) regional climate model to downscale ERA-Interim (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model (LSM) is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments. (letter)

Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures

Science.gov (United States)

Lucas, D. D.; Klein, R.; Tannahill, J.; Brandon, S.; Covey, C. C.; Domyancic, D.; Ivanova, D. P.

2012-12-01

Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Statistical 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 failures of the Parallel Ocean Program (POP2). About 8.5% of our POP2 runs failed for numerical reasons at certain combinations of parameter values. We apply support vector machine (SVM) classification from the fields of pattern recognition and machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. The SVM classifiers readily predict POP2 failures in an independent validation ensemble, and are subsequently used to determine the causes of the failures via a global sensitivity analysis. Four parameters related to ocean mixing and viscosity are identified as the major sources of POP2 failures. Our method can be used to improve the robustness of complex scientific models to parameter perturbations and to better steer UQ ensembles. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).

An application of a hydraulic model simulator in flood risk assessment under changing climatic conditions

Science.gov (United States)

Doroszkiewicz, J. M.; Romanowicz, R. J.

2016-12-01

The standard procedure of climate change impact assessment on future hydrological extremes consists of a chain of consecutive actions, starting from the choice of GCM driven by an assumed CO2 scenario, through downscaling of climatic forcing to a catchment scale, estimation of hydrological extreme indices using hydrological modelling tools and subsequent derivation of flood risk maps with the help of a hydraulic model. Among many possible sources of uncertainty, the main are the uncertainties related to future climate scenarios, climate models, downscaling techniques and hydrological and hydraulic models. Unfortunately, we cannot directly assess the impact of these different sources of uncertainties on flood risk in future due to lack of observations of future climate realizations. The aim of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the processes involved, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-sections. The study shows that the application of a simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the

Next-Generation Climate Modeling Science Challenges for Simulation, Workflow and Analysis Systems

Science.gov (United States)

Koch, D. M.; Anantharaj, V. G.; Bader, D. C.; Krishnan, H.; Leung, L. R.; Ringler, T.; Taylor, M.; Wehner, M. F.; Williams, D. N.

2016-12-01

We will present two examples of current and future high-resolution climate-modeling research that are challenging existing simulation run-time I/O, model-data movement, storage and publishing, and analysis. In each case, we will consider lessons learned as current workflow systems are broken by these large-data science challenges, as well as strategies to repair or rebuild the systems. First we consider the science and workflow challenges to be posed by the CMIP6 multi-model HighResMIP, involving around a dozen modeling groups performing quarter-degree simulations, in 3-member ensembles for 100 years, with high-frequency (1-6 hourly) diagnostics, which is expected to generate over 4PB of data. An example of science derived from these experiments will be to study how resolution affects the ability of models to capture extreme-events such as hurricanes or atmospheric rivers. Expected methods to transfer (using parallel Globus) and analyze (using parallel "TECA" software tools) HighResMIP data for such feature-tracking by the DOE CASCADE project will be presented. A second example will be from the Accelerated Climate Modeling for Energy (ACME) project, which is currently addressing challenges involving multiple century-scale coupled high resolution (quarter-degree) climate simulations on DOE Leadership Class computers. ACME is anticipating production of over 5PB of data during the next 2 years of simulations, in order to investigate the drivers of water cycle changes, sea-level-rise, and carbon cycle evolution. The ACME workflow, from simulation to data transfer, storage, analysis and publication will be presented. Current and planned methods to accelerate the workflow, including implementing run-time diagnostics, and implementing server-side analysis to avoid moving large datasets will be presented.

Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

Directory of Open Access Journals (Sweden)

Dmitry V. Sein

2014-07-01

Full Text Available The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis. Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the

Capturing flood-to-drought transitions in regional climate model simulations

Science.gov (United States)

Anders, Ivonne; Haslinger, Klaus; Hofstätter, Michael; Salzmann, Manuela; Resch, Gernot

2017-04-01

In previous studies atmospheric cyclones have been investigated in terms of related precipitation extremes in Central Europe. Mediterranean (Vb-like) cyclones are of special relevance as they are frequently related to high atmospheric moisture fluxes leading to floods and landslides in the Alpine region. Another focus in this area is on droughts, affecting soil moisture and surface and sub-surface runoff as well. Such events develop differently depending on available pre-saturation of water in the soil. In a first step we investigated two time periods which encompass a flood event and a subsequent drought on very different time scales, one long lasting transition (2002/2003) and a rather short one between May and August 2013. In a second step we extended the investigation to the long time period 1950-2016. We focused on high spatial and temporal scales and assessed the currently achievable accuracy in the simulation of the Vb-events on one hand and following drought events on the other hand. The state-of-the-art regional climate model CCLM is applied in hindcast-mode simulating the single events described above, but also the time from 1948 to 2016 to evaluate the results from the short runs to be valid for the long time period. Besides the conventional forcing of the regional climate model at its lateral boundaries, a spectral nudging technique is applied. The simulations covering the European domain have been varied systematically different model parameters. The resulting precipitation amounts have been compared to E-OBS gridded European precipitation data set and a recent high spatially resolved precipitation data set for Austria (GPARD-6). For the drought events the Standardized Precipitation Evapotranspiration Index (SPEI), soil moisture and runoff has been investigated. Varying the spectral nudging setup helps us to understand the 3D-processes during these events, but also to identify model deficiencies. To improve the simulation of such events in the past

Climate in Sweden during the past millennium - Evidence from proxy data, instrumental data and model simulations

Energy Technology Data Exchange (ETDEWEB)

Moberg, Anders; Gouirand, Isabelle; Schoning, Kristian; Wohlfarth, Barbara [Stockholm Univ. (Sweden). Dept. of Physical Geography and Quaternary Geology; Kjellstroem, Erik; Rummukainen, Markku [Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden). Rossby Centre; Jong, Rixt de [Lund Univ. (Sweden). Dept. of Quaternary Geology; Linderholm, Hans [Goeteborg Univ. (Sweden). Dept. of Earth Sciences; Zorita, Eduardo [GKSS Research Centre, Geesthacht (Germany)

2006-12-15

Knowledge about climatic variations is essential for SKB in its safety assessments of a geological repository for spent nuclear waste. There is therefore a need for information about possible future climatic variations under a range of possible climatic states. However, predictions of future climate in any deterministic sense are still beyond our reach. We can, nevertheless, try to estimate the magnitude of future climate variability and change due to natural forcing factors, by means of inferences drawn from natural climate variability in the past. Indeed, the climate of the future will be shaped by the sum of natural and anthropogenic climate forcing, as well as the internal climate variability. The aim here is to review and analyse the knowledge about Swedish climate variability, essentially during the past millennium. Available climate proxy data and long instrumental records provide empirical information on past climatic changes. We also demonstrate how climate modelling can be used to extend such knowledge. We use output from a global climate model driven with reconstructed radiative forcings (solar, volcanic and greenhouse gas forcing), to provide boundary conditions for a regional climate model. The regional model provides more details of the climate than the global model, and we develop a simulated climate history for Sweden that is complete in time and space and physically consistent. We use output from a regional model simulation for long periods in the last millennium, to study annual mean temperature, precipitation and runoff for the northern and southern parts of Sweden. The simulated data are used to place corresponding instrumental records for the 20th century into a plausible historical perspective. We also use output from the regional model to study how the frequency distribution of the daily temperature, precipitation, runoff and evaporation at Forsmark and Oskarshamn could have varied between unusually warm and cold 30-year periods during the

Climate in Sweden during the past millennium - Evidence from proxy data, instrumental data and model simulations

International Nuclear Information System (INIS)

Moberg, Anders; Gouirand, Isabelle; Schoning, Kristian; Wohlfarth, Barbara

2006-12-01

Knowledge about climatic variations is essential for SKB in its safety assessments of a geological repository for spent nuclear waste. There is therefore a need for information about possible future climatic variations under a range of possible climatic states. However, predictions of future climate in any deterministic sense are still beyond our reach. We can, nevertheless, try to estimate the magnitude of future climate variability and change due to natural forcing factors, by means of inferences drawn from natural climate variability in the past. Indeed, the climate of the future will be shaped by the sum of natural and anthropogenic climate forcing, as well as the internal climate variability. The aim here is to review and analyse the knowledge about Swedish climate variability, essentially during the past millennium. Available climate proxy data and long instrumental records provide empirical information on past climatic changes. We also demonstrate how climate modelling can be used to extend such knowledge. We use output from a global climate model driven with reconstructed radiative forcings (solar, volcanic and greenhouse gas forcing), to provide boundary conditions for a regional climate model. The regional model provides more details of the climate than the global model, and we develop a simulated climate history for Sweden that is complete in time and space and physically consistent. We use output from a regional model simulation for long periods in the last millennium, to study annual mean temperature, precipitation and runoff for the northern and southern parts of Sweden. The simulated data are used to place corresponding instrumental records for the 20th century into a plausible historical perspective. We also use output from the regional model to study how the frequency distribution of the daily temperature, precipitation, runoff and evaporation at Forsmark and Oskarshamn could have varied between unusually warm and cold 30-year periods during the

Assessing the impact of model and climate uncertainty in malaria simulations for the Kenyan Highlands.

Science.gov (United States)

Tompkins, A. M.; Thomson, M. C.

2017-12-01

Simulations of the impact of climate variations on a vector-bornedisease such as malaria are subject to a number of sources ofuncertainty. These include the model structure and parameter settingsin addition to errors in the climate data and the neglect of theirspatial heterogeneity, especially over complex terrain. We use aconstrained genetic algorithm to confront these two sources ofuncertainty for malaria transmission in the highlands of Kenya. Thetechnique calibrates the parameter settings of a process-based,mathematical model of malaria transmission to vary within theirassessed level of uncertainty and also allows the calibration of thedriving climate data. The simulations show that in highland settingsclose to the threshold for sustained transmission, the uncertainty inclimate is more important to address than the malaria modeluncertainty. Applications of the coupled climate-malaria modelling system are briefly presented.

Uncertainty in Simulating Wheat Yields Under Climate Change

Energy Technology Data Exchange (ETDEWEB)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Hatfield, Jerry; Ruane, Alex; Boote, K. J.; Thorburn, Peter; Rotter, R.P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P.K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, AJ; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, Robert; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, Roberto C.; Kersebaum, K.C.; Mueller, C.; Naresh Kumar, S.; Nendel, C.; O' Leary, G.O.; Olesen, JE; Osborne, T.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stockle, Claudio O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Williams, J.R.; Wolf, J.

2013-09-01

Anticipating the impacts of climate change on crop yields is critical for assessing future food security. Process-based crop simulation models are the most commonly used tools in such assessments1,2. Analysis of uncertainties in future greenhouse gas emissions and their impacts on future climate change has been increasingly described in the literature3,4 while assessments of the uncertainty in crop responses to climate change are very rare. Systematic and objective comparisons across impact studies is difficult, and thus has not been fully realized5. Here we present the largest coordinated and standardized crop model intercomparison for climate change impacts on wheat production to date. We found that several individual crop models are able to reproduce measured grain yields under current diverse environments, particularly if sufficient details are provided to execute them. However, simulated climate change impacts can vary across models due to differences in model structures and algorithms. The crop-model component of uncertainty in climate change impact assessments was considerably larger than the climate-model component from Global Climate Models (GCMs). Model responses to high temperatures and temperature-by-CO2 interactions are identified as major sources of simulated impact uncertainties. Significant reductions in impact uncertainties through model improvements in these areas and improved quantification of uncertainty through multi-model ensembles are urgently needed for a more reliable translation of climate change scenarios into agricultural impacts in order to develop adaptation strategies and aid policymaking.

Coupled Model Intercomparison Project 5 (CMIP5) simulations of climate following volcanic eruptions

KAUST Repository

Driscoll, Simon; Bozzo, Alessio; Gray, Lesley J.; Robock, Alan; Stenchikov, Georgiy L.

2012-01-01

The ability of the climate models submitted to the Coupled Model Intercomparison Project 5 (CMIP5) database to simulate the Northern Hemisphere winter climate following a large tropical volcanic eruption is assessed. When sulfate aerosols are produced by volcanic injections into the tropical stratosphere and spread by the stratospheric circulation, it not only causes globally averaged tropospheric cooling but also a localized heating in the lower stratosphere, which can cause major dynamical feedbacks. Observations show a lower stratospheric and surface response during the following one or two Northern Hemisphere (NH) winters, that resembles the positive phase of the North Atlantic Oscillation (NAO). Simulations from 13 CMIP5 models that represent tropical eruptions in the 19th and 20th century are examined, focusing on the large-scale regional impacts associated with the large-scale circulation during the NH winter season. The models generally fail to capture the NH dynamical response following eruptions. They do not sufficiently simulate the observed post-volcanic strengthened NH polar vortex, positive NAO, or NH Eurasian warming pattern, and they tend to overestimate the cooling in the tropical troposphere. The findings are confirmed by a superposed epoch analysis of the NAO index for each model. The study confirms previous similar evaluations and raises concern for the ability of current climate models to simulate the response of a major mode of global circulation variability to external forcings. This is also of concern for the accuracy of geoengineering modeling studies that assess the atmospheric response to stratosphere-injected particles.

Coupled Model Intercomparison Project 5 (CMIP5) simulations of climate following volcanic eruptions

KAUST Repository

Driscoll, Simon

2012-09-16

The ability of the climate models submitted to the Coupled Model Intercomparison Project 5 (CMIP5) database to simulate the Northern Hemisphere winter climate following a large tropical volcanic eruption is assessed. When sulfate aerosols are produced by volcanic injections into the tropical stratosphere and spread by the stratospheric circulation, it not only causes globally averaged tropospheric cooling but also a localized heating in the lower stratosphere, which can cause major dynamical feedbacks. Observations show a lower stratospheric and surface response during the following one or two Northern Hemisphere (NH) winters, that resembles the positive phase of the North Atlantic Oscillation (NAO). Simulations from 13 CMIP5 models that represent tropical eruptions in the 19th and 20th century are examined, focusing on the large-scale regional impacts associated with the large-scale circulation during the NH winter season. The models generally fail to capture the NH dynamical response following eruptions. They do not sufficiently simulate the observed post-volcanic strengthened NH polar vortex, positive NAO, or NH Eurasian warming pattern, and they tend to overestimate the cooling in the tropical troposphere. The findings are confirmed by a superposed epoch analysis of the NAO index for each model. The study confirms previous similar evaluations and raises concern for the ability of current climate models to simulate the response of a major mode of global circulation variability to external forcings. This is also of concern for the accuracy of geoengineering modeling studies that assess the atmospheric response to stratosphere-injected particles.

Do Climate Models Simulate the Right Sea Ice Trends for the Wrong Reasons?

Science.gov (United States)

Rosenblum, E. J.; Eisenman, I.

2016-02-01

Observations indicate that the Arctic sea ice cover is rapidly retreating while the Antarctic sea ice cover is steadily expanding. State-of-the-art climate models, by contrast, predict a moderate decrease in both the Arctic and Antarctic sea ice cover. A number of recent studies have attributed this discrepancy in each hemisphere to natural variability. Here we examine sea ice changes during 1979-2013 in simulations from the most recent Coupled Model Intercomparison Project as well as the Community Earth System Model Large Ensemble. We find that after accounting for biases in the level of global warming in each simulation, the possibility that natural variability alone could explain the difference between models and observations becomes exceedingly small. This suggests instead that there is a systematic bias in the climate models or possibly the observations.

Spontaneous abrupt climate change due to an atmospheric blocking-sea-ice-ocean feedback in an unforced climate model simulation.

Science.gov (United States)

Drijfhout, Sybren; Gleeson, Emily; Dijkstra, Henk A; Livina, Valerie

2013-12-03

Abrupt climate change is abundant in geological records, but climate models rarely have been able to simulate such events in response to realistic forcing. Here we report on a spontaneous abrupt cooling event, lasting for more than a century, with a temperature anomaly similar to that of the Little Ice Age. The event was simulated in the preindustrial control run of a high-resolution climate model, without imposing external perturbations. Initial cooling started with a period of enhanced atmospheric blocking over the eastern subpolar gyre. In response, a southward progression of the sea-ice margin occurred, and the sea-level pressure anomaly was locked to the sea-ice margin through thermal forcing. The cold-core high steered more cold air to the area, reinforcing the sea-ice concentration anomaly east of Greenland. The sea-ice surplus was carried southward by ocean currents around the tip of Greenland. South of 70 °N, sea ice already started melting and the associated freshwater anomaly was carried to the Labrador Sea, shutting off deep convection. There, surface waters were exposed longer to atmospheric cooling and sea surface temperature dropped, causing an even larger thermally forced high above the Labrador Sea. In consequence, east of Greenland, anomalous winds changed from north to south, terminating the event with similar abruptness to its onset. Our results imply that only climate models that possess sufficient resolution to correctly represent atmospheric blocking, in combination with a sensitive sea-ice model, are able to simulate this kind of abrupt climate change.

Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

Science.gov (United States)

Singh, U. K.; Singh, G. P.; Singh, Vikas

2015-04-01

The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread

Towards Better Simulation of US Maize Yield Responses to Climate in the Community Earth System Model

Science.gov (United States)

Peng, B.; Guan, K.; Chen, M.; Lawrence, D. M.; Jin, Z.; Bernacchi, C.; Ainsworth, E. A.; DeLucia, E. H.; Lombardozzi, D. L.; Lu, Y.

2017-12-01

Global food security is undergoing continuing pressure from increased population and climate change despites the potential advancement in breeding and management technologies. Earth system models (ESMs) are essential tools to study the impacts of historical and future climate on regional and global food production, as well as to assess the effectiveness of possible adaptations and their potential feedback to climate. Here we developed an improved maize representation within the Community Earth System Model (CESM) by combining the strengths of both the Community Land Model version 4.5 (CLM4.5) and the Agricultural Production Systems sIMulator (APSIM) models. Specifically, we modified the maize planting scheme, incorporated the phenology scheme adopted from the APSIM model, added a new carbon allocation scheme into CLM4.5, and improved the estimation of canopy structure parameters including leaf area index (LAI) and canopy height. Unique features of the new model (CLM-APSIM) include more detailed phenology stages, an explicit implementation of the impacts of various abiotic environmental stresses (including nitrogen, water, temperature and heat stresses) on maize phenology and carbon allocation, as well as an explicit simulation of grain number and grain size. We conducted a regional simulation of this new model over the US Corn Belt during 1990 to 2010. The simulated maize yield as well as its responses to climate (growing season mean temperature and precipitation) are benchmarked with data from UADA NASS statistics. Our results show that the CLM-APSIM model outperforms the CLM4.5 in simulating county-level maize yield production and reproduces more realistic yield responses to climate variations than CLM4.5. However, some critical processes (such as crop failure due to frost and inundation and suboptimal growth condition due to biotic stresses) are still missing in both CLM-APSIM and CLM4.5, making the simulated yield responses to climate slightly deviate from the

Validation of precipitation over Japan during 1985-2004 simulated by three regional climate models and two multi-model ensemble means

Energy Technology Data Exchange (ETDEWEB)

Ishizaki, Yasuhiro [Meteorological Research Institute, Tsukuba (Japan); National Institute for Environmental Studies, Tsukuba (Japan); Nakaegawa, Toshiyuki; Takayabu, Izuru [Meteorological Research Institute, Tsukuba (Japan)

2012-07-15

We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate. (orig.)

Simulations of future climate with a coupled atmosphere-ocean general circulation model

International Nuclear Information System (INIS)

Stendel, M.; Schmith, T.; Hesselbjerg Christensen, J.

2001-01-01

A coupled atmosphere/ocean general circulation model to study the time-dependent climate response to changing concentrations of greenhouse gases, chlorofluorocarbons and aerosols according to the new IPCC SRES scenarios A2 and B2 has been used. The results of these experiments are compared to an unforced 300-year control experiment. The changes in the last three decades of the scenario simulations (2071-2100) are furthermore compared to the simulation of present-day climate (1961-1990). In accordance with previous experiments we find that greenhouse warming is reduced when aerosol effects are considered. Sulfur emissions, however, are lower than in the IS92a scenario. Consequently, the greenhouse warming effect, which leads to a bigger temperature increase than in the GSDIO experiment can outweigh the aerosol cooling effect. The result shows that there still are serious difficulties and uncertainties in this type of model simulation. Those are partially due to oversimplifications in the model, concerning the radiative properties of aerosols in particular, and therefore the indirect aerosol effect. Another inherent problem, however, is the uncertainty in the scenarios themselves. This is the case for short-lived substances with an inhomogeneous spatial and temporal distribution, such as aerosols. Therefore, on a decadal horizon, changes in the emissions of those substance can exert a significant effect on anthropogenic climate change. (LN)

Spontaneous abrupt climate change due to an atmospheric blocking–sea-ice–ocean feedback in an unforced climate model simulation

NARCIS (Netherlands)

Drijfhout, S.S.; Gleeson, E.; Dijkstra, H.A.|info:eu-repo/dai/nl/073504467; Livina, V.

2013-01-01

Abrupt climate change is abundant in geological records, but climate models rarely have been able to simulate such events in response to realistic forcing. Here we report on a spontaneous abrupt cooling event, lasting for more than a century, with a temperature anomaly similar to that of the Little

The influence of atmospheric grid resolution in a climate model-forced ice sheet simulation

Science.gov (United States)

Lofverstrom, Marcus; Liakka, Johan

2018-04-01

Coupled climate-ice sheet simulations have been growing in popularity in recent years. Experiments of this type are however challenging as ice sheets evolve over multi-millennial timescales, which is beyond the practical integration limit of most Earth system models. A common method to increase model throughput is to trade resolution for computational efficiency (compromise accuracy for speed). Here we analyze how the resolution of an atmospheric general circulation model (AGCM) influences the simulation quality in a stand-alone ice sheet model. Four identical AGCM simulations of the Last Glacial Maximum (LGM) were run at different horizontal resolutions: T85 (1.4°), T42 (2.8°), T31 (3.8°), and T21 (5.6°). These simulations were subsequently used as forcing of an ice sheet model. While the T85 climate forcing reproduces the LGM ice sheets to a high accuracy, the intermediate resolution cases (T42 and T31) fail to build the Eurasian ice sheet. The T21 case fails in both Eurasia and North America. Sensitivity experiments using different surface mass balance parameterizations improve the simulations of the Eurasian ice sheet in the T42 case, but the compromise is a substantial ice buildup in Siberia. The T31 and T21 cases do not improve in the same way in Eurasia, though the latter simulates the continent-wide Laurentide ice sheet in North America. The difficulty to reproduce the LGM ice sheets in the T21 case is in broad agreement with previous studies using low-resolution atmospheric models, and is caused by a substantial deterioration of the model climate between the T31 and T21 resolutions. It is speculated that this deficiency may demonstrate a fundamental problem with using low-resolution atmospheric models in these types of experiments.

White book Escrime. Climatic simulation studies

International Nuclear Information System (INIS)

Terray, L.; Braconnot, P.

2007-01-01

The ESCRIME project aims to manage the analysis realized on the climatic simulations on the framework of the fourth report of the GIEC (group of intergovernmental experts on the climate evolution), in particularly the simulations based on french models. This white book is constituted by 8 chapters: the global scenario, the climatic sensibility, the variation modes, the regionalization and the extremes, the hydrological cycle, the polar regions and the cryo-sphere, the carbon cycle, detection and attributions. (A.L.B.)

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.)

The physics and dynamics of the climate system simulation of climate change

International Nuclear Information System (INIS)

Mitchell, J.F.B.

1991-01-01

The increases in atmospheric Greenhouse gases since 1860 have a radiative effect equivalent to a 40% increase in carbon dioxide concentrations, and by the middle of the next century, are expected to be equivalent to a doubling of carbon dioxide concentration. Simulations with detailed climate models indicate that this would produce a warming of 2 to 5 K in global mean surface temperature at equilibrium, with accompanying changes in precipitation, sea level and other parameters. The observed increase of 0.5 K since 1900 is consistent with the lower range of the estimated potential increase, allowing for a possible slowing of the global mean warming due to the ocean's large thermal inertia. There is an ever pressing need to predict the likely changes in climate due to increases in trace gases and detailed 3-dimensional models of climate are the most promising method of providing the detailed information required for climatic impact assessment. This paper is arranged as follows: 1. Introduction, why model climate. 2. The Greenhouse effect. 3. The principal gases, past, present and future. 4. Climate feedbacks in CO 2 experiments. 5. Equilibrium climate change due to increased CO 2 . 6. Modelling the transient response to increases in trace gases. 7. Uncertainties in the simulation and detection of the climatic effect of increased trace gases. 8. Appeals to the past; simulations for 9000 years before present (9 K bp). 13 figs., 3 tabs., 33 refs

Simulation and Modelling of Climate Change Effects on River Awara Flow Discharge using WEAP Model

Directory of Open Access Journals (Sweden)

Oyati E.N.

2017-11-01

Full Text Available Modelling of stream flow and discharge of river Awara under changed climate conditions using CLIMGEN for stochastic weather generation and WEAP model was used to simulate reserviour storage volume, water demand and river discharges at high spatial resolution (0.5°×0.5°, total 66,420 grid cells. Results of CLM-Based flow measurement shows a linear regression with R 2 = 0.99 for IFPRI-MNP- IGSM_WRS calibration. Sensitivity simulation of ambient long-term shows an increase in temperature with 0.5 o c thus the results of the studies generally show that annual runoff and river discharges could largely decrease. The projection of water demand 150 million m 3 by 2020 against the reservoir storage volume 60 million m 3 and decrease in rainfall depth by -5.7 mm. The output of the combined models used in this study is veritable to create robust water management system under different climate change scenarios.

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.

Simulating Pacific Northwest Forest Response to Climate Change: How We Made Model Results Useful for Vulnerability Assessments

Science.gov (United States)

Kim, J. B.; Kerns, B. K.; Halofsky, J.

2014-12-01

GCM-based climate projections and downscaled climate data proliferate, and there are many climate-aware vegetation models in use by researchers. Yet application of fine-scale DGVM based simulation output in national forest vulnerability assessments is not common, because there are technical, administrative and social barriers for their use by managers and policy makers. As part of a science-management climate change adaptation partnership, we performed simulations of vegetation response to climate change for four national forests in the Blue Mountains of Oregon using the MC2 dynamic global vegetation model (DGVM) for use in vulnerability assessments. Our simulation results under business-as-usual scenarios suggest a starkly different future forest conditions for three out of the four national forests in the study area, making their adoption by forest managers a potential challenge. However, using DGVM output to structure discussion of potential vegetation changes provides a suitable framework to discuss the dynamic nature of vegetation change compared to using more commonly available model output (e.g. species distribution models). From the onset, we planned and coordinated our work with national forest managers to maximize the utility and the consideration of the simulation results in planning. Key lessons from this collaboration were: (1) structured and strategic selection of a small number climate change scenarios that capture the range of variability in future conditions simplified results; (2) collecting and integrating data from managers for use in simulations increased support and interest in applying output; (3) a structured, regionally focused, and hierarchical calibration of the DGVM produced well-validated results; (4) simple approaches to quantifying uncertainty in simulation results facilitated communication; and (5) interpretation of model results in a holistic context in relation to multiple lines of evidence produced balanced guidance. This latest

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

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.

High Resolution Simulations of Future Climate in West Africa Using a Variable-Resolution Atmospheric Model

Science.gov (United States)

Adegoke, J. O.; Engelbrecht, F.; Vezhapparambu, S.

2013-12-01

In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.

Evaluation of skill at simulating heatwave and heat-humidity indices in Global and Regional Climate Models

Science.gov (United States)

Goldie, J. K.; Alexander, L. V.; Lewis, S. C.; Sherwood, S. C.

2017-12-01

A wide body of literature now establishes the harm of extreme heat on human health, and work is now emerging on the projection of future health impacts. However, heat-health relationships vary across different populations (Gasparrini et al. 2015), so accurate simulation of regional climate is an important component of joint health impact projection. Here, we evaluate the ability of nine Global Climate Models (GCMs) from CMIP5 and the NARCliM Regional Climate Model to reproduce a selection of 15 health-relevant heatwave and heat-humidity indices over the historical period (1990-2005) using the Perkins skill score (Perkins et al. 2007) in five Australian cities. We explore the reasons for poor model skill, comparing these modelled distributions to both weather station observations and gridded reanalysis data. Finally, we show changes in the modelled distributions from the highest-performing models under RCP4.5 and RCP8.5 greenhouse gas scenarios and discuss the implications of simulated heat stress for future climate change adaptation. ReferencesGasparrini, Antonio, Yuming Guo, Masahiro Hashizume, Eric Lavigne, Antonella Zanobetti, Joel Schwartz, Aurelio Tobias, et al. "Mortality Risk Attributable to High and Low Ambient Temperature: A Multicountry Observational Study." The Lancet 386, no. 9991 (July 31, 2015): 369-75. doi:10.1016/S0140-6736(14)62114-0. Perkins, S. E., A. J. Pitman, N. J. Holbrook, and J. McAneney. "Evaluation of the AR4 Climate Models' Simulated Daily Maximum Temperature, Minimum Temperature, and Precipitation over Australia Using Probability Density Functions." Journal of Climate 20, no. 17 (September 1, 2007): 4356-76. doi:10.1175/JCLI4253.1.

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Science.gov (United States)

Makowski, David; Asseng, Senthold; Ewert, Frank; Bassu, Simona; Durand, Jean-Louis; Martre, Pierre; Adam, Myriam; Aggarwal, Pramod K.; Angulo, Carlos; Baron, Chritian;

Quasi-decadal Oscillation in the CMIP5 and CMIP3 Climate Model Simulations: California Case

Science.gov (United States)

Wang, J.; Yin, H.; Reyes, E.; Chung, F. I.

2014-12-01

The ongoing three drought years in California are reminding us of two other historical long drought periods: 1987-1992 and 1928-1934. This kind of interannual variability is corresponding to the dominating 7-15 yr quasi-decadal oscillation in precipitation and streamflow in California. When using global climate model projections to assess the climate change impact on water resources planning in California, it is natural to ask if global climate models are able to reproduce the observed interannual variability like 7-15 yr quasi-decadal oscillation. Further spectral analysis to tree ring retrieved precipitation and historical precipitation record proves the existence of 7-15 yr quasi-decadal oscillation in California. But while implementing spectral analysis to all the CMIP5 and CMIP3 global climate model historical simulations using wavelet analysis approach, it was found that only two models in CMIP3 , CGCM 2.3.2a of MRI and NCAP PCM1.0, and only two models in CMIP5, MIROC5 and CESM1-WACCM, have statistically significant 7-15 yr quasi-decadal oscillations in California. More interesting, the existence of 7-15 yr quasi-decadal oscillation in the global climate model simulation is also sensitive to initial conditions. 12-13 yr quasi-decadal oscillation occurs in one ensemble run of CGCM 2.3.2a of MRI but does not exist in the other four ensemble runs.

Evaluation of uncertainties in regional climate change simulations

DEFF Research Database (Denmark)

Pan, Z.; Christensen, J. H.; Arritt, R. W.

2001-01-01

, an atmosphere-ocean coupled general circulation model (GCM) current climate, and a future scenario of transient climate change. Common precipitation climatology features simulated by both models included realistic orographic precipitation, east-west transcontinental gradients, and reasonable annual cycles over...... to different subgrid scale processes in individual models. The ratio of climate change to biases, which we use as one measure of confidence in projected climate changes, is substantially larger than 1 in several seasons and regions while the ratios are always less than 1 in summer. The largest ratios among all...... regions are in California. Spatial correlation coefficients of precipitation were computed between simulation pairs in the 2x3 set. The climate change correlation is highest and the RCM performance correlation is lowest while boundary forcing and intermodel correlations are intermediate. The high spatial...

Influence of feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

Science.gov (United States)

van Walsum, P. E. V.

2011-11-01

Climate change impact modelling of hydrologic responses is hampered by climate-dependent model parameterizations. Reducing this dependency was one of the goals of extending the regional hydrologic modelling system SIMGRO with a two-way coupling to the crop growth simulation model WOFOST. The coupling includes feedbacks to the hydrologic model in terms of the root zone depth, soil cover, leaf area index, interception storage capacity, crop height and crop factor. For investigating whether such feedbacks lead to significantly different simulation results, two versions of the model coupling were set up for a test region: one with exogenous vegetation parameters, the "static" model, and one with endogenous simulation of the crop growth, the "dynamic" model WOFOST. The used parameterization methods of the static/dynamic vegetation models ensure that for the current climate the simulated long-term average of the actual evapotranspiration is the same for both models. Simulations were made for two climate scenarios. Owing to the higher temperatures in combination with a higher CO2-concentration of the atmosphere, a forward time shift of the crop development is simulated in the dynamic model; the used arable land crop, potatoes, also shows a shortening of the growing season. For this crop, a significant reduction of the potential transpiration is simulated compared to the static model, in the example by 15% in a warm, dry year. In consequence, the simulated crop water stress (the unit minus the relative transpiration) is lower when the dynamic model is used; also the simulated increase of crop water stress due to climate change is lower; in the example, the simulated increase is 15 percentage points less (of 55) than when a static model is used. The static/dynamic models also simulate different absolute values of the transpiration. The difference is most pronounced for potatoes at locations with ample moisture supply; this supply can either come from storage release of a

Regional Community Climate Simulations with variable resolution meshes in the Community Earth System Model

Science.gov (United States)

Zarzycki, C. M.; Gettelman, A.; Callaghan, P.

2017-12-01

Accurately predicting weather extremes such as precipitation (floods and droughts) and temperature (heat waves) requires high resolution to resolve mesoscale dynamics and topography at horizontal scales of 10-30km. Simulating such resolutions globally for climate scales (years to decades) remains computationally impractical. Simulating only a small region of the planet is more tractable at these scales for climate applications. This work describes global simulations using variable-resolution static meshes with multiple dynamical cores that target the continental United States using developmental versions of the Community Earth System Model version 2 (CESM2). CESM2 is tested in idealized, aquaplanet and full physics configurations to evaluate variable mesh simulations against uniform high and uniform low resolution simulations at resolutions down to 15km. Different physical parameterization suites are also evaluated to gauge their sensitivity to resolution. Idealized variable-resolution mesh cases compare well to high resolution tests. More recent versions of the atmospheric physics, including cloud schemes for CESM2, are more stable with respect to changes in horizontal resolution. Most of the sensitivity is due to sensitivity to timestep and interactions between deep convection and large scale condensation, expected from the closure methods. The resulting full physics model produces a comparable climate to the global low resolution mesh and similar high frequency statistics in the high resolution region. Some biases are reduced (orographic precipitation in the western United States), but biases do not necessarily go away at high resolution (e.g. summertime JJA surface Temp). The simulations are able to reproduce uniform high resolution results, making them an effective tool for regional climate studies and are available in CESM2.

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.

Visualization and Analysis of Climate Simulation Performance Data

Science.gov (United States)

Röber, Niklas; Adamidis, Panagiotis; Behrens, Jörg

2015-04-01

Visualization is the key process of transforming abstract (scientific) data into a graphical representation, to aid in the understanding of the information hidden within the data. Climate simulation data sets are typically quite large, time varying, and consist of many different variables sampled on an underlying grid. A large variety of climate models - and sub models - exist to simulate various aspects of the climate system. Generally, one is mainly interested in the physical variables produced by the simulation runs, but model developers are also interested in performance data measured along with these simulations. Climate simulation models are carefully developed complex software systems, designed to run in parallel on large HPC systems. An important goal thereby is to utilize the entire hardware as efficiently as possible, that is, to distribute the workload as even as possible among the individual components. This is a very challenging task, and detailed performance data, such as timings, cache misses etc. have to be used to locate and understand performance problems in order to optimize the model implementation. Furthermore, the correlation of performance data to the processes of the application and the sub-domains of the decomposed underlying grid is vital when addressing communication and load imbalance issues. High resolution climate simulations are carried out on tens to hundreds of thousands of cores, thus yielding a vast amount of profiling data, which cannot be analyzed without appropriate visualization techniques. This PICO presentation displays and discusses the ICON simulation model, which is jointly developed by the Max Planck Institute for Meteorology and the German Weather Service and in partnership with DKRZ. The visualization and analysis of the models performance data allows us to optimize and fine tune the model, as well as to understand its execution on the HPC system. We show and discuss our workflow, as well as present new ideas and

Influence of ecohydrologic feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

Science.gov (United States)

van Walsum, P. E. V.; Supit, I.

2012-06-01

Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated

Uncertainty in simulating wheat yields under climate change

DEFF Research Database (Denmark)

Asseng, A; Ewert, F; Rosenzweig, C

2013-01-01

of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models...... than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi...

The ACPI Climate Change Simulations

International Nuclear Information System (INIS)

Dai, A.; Washington, W.M.; Meehl, G.A.; Bettge, T.W.; Strand, W.G.

2004-01-01

The Parallel Climate Model (PCM) has been used in the Accelerated Climate Prediction Initiative (ACPI) Program to simulate the global climate response to projected CO2, sulfate, and other greenhouse gas forcing under a business-as-usual emissions scenario during the 21st century. In these runs, the oceans were initialized to 1995 conditions by a group from the Scripps Institution of Oceanography and other institutions. An ensemble of three model runs was then carried out to the year 2099 using the projected forcing. Atmospheric data from these runs were saved at 6-hourly intervals (hourly for certain critical fields) to support the ACPI objective of accurately modeling hydrological cycles over the western U.S. It is shown that the initialization to 1995 conditions partly removes the un-forced oceanic temperature and salinity drifts that occurred in the standard 20th century integration. The ACPI runs show a global surface temperature increase of 3-8C over northern high-latitudes by the end of the 21st century, and 1-2C over the oceans. This is generally within ±0.1C of model runs without the 1995 ocean initialization. The exception is in the Antarctic circumpolar ocean where surface air temperature is cooler in the ACPI run; however the ensemble scatter is large in this region. Although the difference in climate at the end of the 21st century is minimal between the ACPI runs and traditionally spun up runs, it might be larger for CGCMs with higher climate sensitivity or larger ocean drifts. Our results suggest that the effect of small errors in the oceans (such as those associated with climate drifts) on CGCM-simulated climate changes for the next 50-100 years may be negligible

Using climate model simulations to assess the current climate risk to maize production

Science.gov (United States)

Kent, Chris; Pope, Edward; Thompson, Vikki; Lewis, Kirsty; Scaife, Adam A.; Dunstone, Nick

2017-05-01

The relationship between the climate and agricultural production is of considerable importance to global food security. However, there has been relatively little exploration of climate-variability related yield shocks. The short observational yield record does not adequately sample natural inter-annual variability thereby limiting the accuracy of probability assessments. Focusing on the United States and China, we present an innovative use of initialised ensemble climate simulations and a new agro-climatic indicator, to calculate the risk of severe water stress. Combined, these regions provide 60% of the world’s maize, and therefore, are crucial to global food security. To probe a greater range of inter-annual variability, the indicator is applied to 1400 simulations of the present day climate. The probability of severe water stress in the major maize producing regions is quantified, and in many regions an increased risk is found compared to calculations from observed historical data. Analysis suggests that the present day climate is also capable of producing unprecedented severe water stress conditions. Therefore, adaptation plans and policies based solely on observed events from the recent past may considerably under-estimate the true risk of climate-related maize shocks. The probability of a major impact event occurring simultaneously across both regions—a multi-breadbasket failure—is estimated to be up to 6% per decade and arises from a physically plausible climate state. This novel approach highlights the significance of climate impacts on crop production shocks and provides a platform for considerably improving food security assessments, in the present day or under a changing climate, as well as development of new risk based climate services.

An efficient regional energy-moisture balance model for simulation of the Greenland Ice Sheet response to climate change

Directory of Open Access Journals (Sweden)

A. Robinson

2010-04-01

Full Text Available In order to explore the response of the Greenland ice sheet (GIS to climate change on long (centennial to multi-millennial time scales, a regional energy-moisture balance model has been developed. This model simulates seasonal variations of temperature and precipitation over Greenland and explicitly accounts for elevation and albedo feedbacks. From these fields, the annual mean surface temperature and surface mass balance can be determined and used to force an ice sheet model. The melt component of the surface mass balance is computed here using both a positive degree day approach and a more physically-based alternative that includes insolation and albedo explicitly. As a validation of the climate model, we first simulated temperature and precipitation over Greenland for the prescribed, present-day topography. Our simulated climatology compares well to observations and does not differ significantly from that of a simple parameterization used in many previous simulations. Furthermore, the calculated surface mass balance using both melt schemes falls within the range of recent regional climate model results. For a prescribed, ice-free state, the differences in simulated climatology between the regional energy-moisture balance model and the simple parameterization become significant, with our model showing much stronger summer warming. When coupled to a three-dimensional ice sheet model and initialized with present-day conditions, the two melt schemes both allow realistic simulations of the present-day GIS.

Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations

NARCIS (Netherlands)

Pelt, van S.C.; Beersma, J.J.; Buishand, T.A.; Hurk, van den B.J.J.M.; Kabat, P.

2012-01-01

Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks.

A statistical-dynamical downscaling procedure for global climate simulations

International Nuclear Information System (INIS)

Frey-Buness, A.; Heimann, D.; Sausen, R.; Schumann, U.

1994-01-01

A statistical-dynamical downscaling procedure for global climate simulations is described. The procedure is based on the assumption that any regional climate is associated with a specific frequency distribution of classified large-scale weather situations. The frequency distributions are derived from multi-year episodes of low resolution global climate simulations. Highly resolved regional distributions of wind and temperature are calculated with a regional model for each class of large-scale weather situation. They are statistically evaluated by weighting them with the according climate-specific frequency. The procedure is exemplarily applied to the Alpine region for a global climate simulation of the present climate. (orig.)

Evaluation of the regional climate response in Australia to large-scale climate modes in the historical NARCliM simulations

Science.gov (United States)

Fita, L.; Evans, J. P.; Argüeso, D.; King, A.; Liu, Y.

2017-10-01

NARCliM (New South Wales (NSW)/Australian Capital Territory (ACT) Regional Climate Modelling project) is a regional climate modeling project for the Australian area. It is providing a comprehensive dynamically downscaled climate dataset for the CORDEX-AustralAsia region at 50-km resolution, and south-East Australia at a resolution of 10 km. The first phase of NARCliM produced 60-year long reanalysis driven regional simulations to allow evaluation of the regional model performance. This long control period (1950-2009) was used so that the model ability to capture the impact of large scale climate modes on Australian climate could be examined. Simulations are evaluated using a gridded observational dataset. Results show that using model independence as a criteria for choosing atmospheric model configuration from different possible sets of parameterizations may contribute to the regional climate models having different overall biases. The regional models generally capture the regional climate response to large-scale modes better than the driving reanalysis, though no regional model improves on all aspects of the simulated climate.

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

Simulating the Current Water Cycle with the NASA Ames Mars Global Climate Model

Science.gov (United States)

Kahre, M. A.; Haberle, R. M.; Hollingsworth, J. L.; Brecht, A. S.; Urata, R. A.; Montmessin, F.

2017-12-01

The water cycle is a critical component of the current Mars climate system, and it is now widely recognized that water ice clouds significantly affect the nature of the simulated water cycle. Two processes are key to implementing clouds in a Mars global climate model (GCM): the microphysical processes of formation and dissipation, and their radiative effects on atmospheric heating/cooling rates. Together, these processes alter the thermal structure, change the atmospheric dynamics, and regulate inter-hemispheric transport. We have made considerable progress using the NASA Ames Mars GCM to simulate the current-day water cycle with radiatively active clouds. Cloud fields from our baseline simulation are in generally good agreement with observations. The predicted seasonal extent and peak IR optical depths are consistent MGS/TES observations. Additionally, the thermal response to the clouds in the aphelion cloud belt (ACB) is generally consistent with observations and other climate model predictions. Notably, there is a distinct gap in the predicted clouds over the North Residual Cap (NRC) during local summer, but the clouds reappear in this simulation over the NRC earlier than the observations indicate. Polar clouds are predicted near the seasonal CO2 ice caps, but the column thicknesses of these clouds are generally too thick compared to observations. Our baseline simulation is dry compared to MGS/TES-observed water vapor abundances, particularly in the tropics and subtropics. These areas of disagreement appear to be a consistent with other current water cycle GCMs. Future avenues of investigation will target improving our understanding of what controls the vertical extent of clouds and the apparent seasonal evolution of cloud particle sizes within the ACB.

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.

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

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.

Serious Simulation Role-Playing Games for Transformative Climate Change Education: "World Climate" and "Future Climate"

Science.gov (United States)

Rooney-Varga, J. N.; Sterman, J.; Sawin, E.; Jones, A.; Merhi, H.; Hunt, C.

2012-12-01

Climate change, its mitigation, and adaption to its impacts are among the greatest challenges of our times. Despite the importance of societal decisions in determining climate change outcomes, flawed mental models about climate change remain widespread, are often deeply entrenched, and present significant barriers to understanding and decision-making around climate change. Here, we describe two simulation role-playing games that combine active, affective, and analytical learning to enable shifts of deeply held conceptions about climate change. The games, World Climate and Future Climate, use a state-of-the-art decision support simulation, C-ROADS (Climate Rapid Overview and Decision Support) to provide users with immediate feedback on the outcomes of their mitigation strategies at the national level, including global greenhouse gas (GHG) emissions and concentrations, mean temperature changes, sea level rise, and ocean acidification. C-ROADS outcomes are consistent with the atmosphere-ocean general circulation models (AOGCMS), such as those used by the IPCC, but runs in less than one second on ordinary laptops, providing immediate feedback to participants on the consequences of their proposed policies. Both World Climate and Future Climate role-playing games provide immersive, situated learning experiences that motivate active engagement with climate science and policy. In World Climate, participants play the role of United Nations climate treaty negotiators. Participant emissions reductions proposals are continually assessed through interactive exploration of the best available science through C-ROADS. Future Climate focuses on time delays in the climate and energy systems. Participants play the roles of three generations: today's policymakers, today's youth, and 'just born.' The game unfolds in three rounds 25 simulated years apart. In the first round, only today's policymakers make decisions; In the next round, the young become the policymakers and inherit the

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.

Aspect of ECMWF downscaled Regional Climate Modeling in simulating Indian summer monsoon rainfall and dependencies on lateral boundary conditions

Science.gov (United States)

Ghosh, Soumik; Bhatla, R.; Mall, R. K.; Srivastava, Prashant K.; Sahai, A. K.

2018-03-01

Climate model faces considerable difficulties in simulating the rainfall characteristics of southwest summer monsoon. In this study, the dynamical downscaling of European Centre for Medium-Range Weather Forecast's (ECMWF's) ERA-Interim (EIN15) has been utilized for the simulation of Indian summer monsoon (ISM) through the Regional Climate Model version 4.3 (RegCM-4.3) over the South Asia Co-Ordinated Regional Climate Downscaling EXperiment (CORDEX) domain. The complexities of model simulation over a particular terrain are generally influenced by factors such as complex topography, coastal boundary, and lack of unbiased initial and lateral boundary conditions. In order to overcome some of these limitations, the RegCM-4.3 is employed for simulating the rainfall characteristics over the complex topographical conditions. For reliable rainfall simulation, implementations of numerous lower boundary conditions are forced in the RegCM-4.3 with specific horizontal grid resolution of 50 km over South Asia CORDEX domain. The analysis is considered for 30 years of climatological simulation of rainfall, outgoing longwave radiation (OLR), mean sea level pressure (MSLP), and wind with different vertical levels over the specified region. The dependency of model simulation with the forcing of EIN15 initial and lateral boundary conditions is used to understand the impact of simulated rainfall characteristics during different phases of summer monsoon. The results obtained from this study are used to evaluate the activity of initial conditions of zonal wind circulation speed, which causes an increase in the uncertainty of regional model output over the region under investigation. Further, the results showed that the EIN15 zonal wind circulation lacks sufficient speed over the specified region in a particular time, which was carried forward by the RegCM output and leads to a disrupted regional simulation in the climate model.

Micro Climate Simulation in new Town 'Hashtgerd'

Science.gov (United States)

Sodoudi, S.; Langer, I.; Cubasch, U.

2012-04-01

One of the objectives of climatological part of project Young Cities 'Developing Energy-Efficient Urban Fabric in the Tehran-Karaj Region' is to simulate the micro climate (with 1m resolution) in 35ha of new town Hashtgerd, which is located 65 km far from mega city Tehran. The Project aims are developing, implementing and evaluating building and planning schemes and technologies which allow to plan and build sustainable, energy-efficient and climate sensible form mass housing settlements in arid and semi-arid regions ("energy-efficient fabric"). Climate sensitive form also means designing and planning for climate change and its related effects for Hashtgerd New Town. By configuration of buildings and open spaces according to solar radiation, wind and vegetation, climate sensitive urban form can create outdoor thermal comfort. To simulate the climate on small spatial scales, the micro climate model Envi-met has been used to simulate the micro climate in 35 ha. The Eulerian model ENVI-met is a micro-scale climate model which gives information about the influence of architecture and buildings as well as vegetation and green area on the micro climate up to 1 m resolution. Envi-met has been run with information from topography, downscaled climate data with neuro-fuzzy method, meteorological measurements, building height and different vegetation variants (low and high number of trees) Through the optimal Urban Design and Planning for the 35ha area the microclimate results shows, that with vegetation the microclimate in streets will be change: • 2 m temperature is decreased by about 2 K • relative humidity increase by about 10 % • soil temperature is decreased by about 3 K • wind speed is decreased by about 60% The style of buildings allows free movement of air, which is of high importance for fresh air supply. The increase of inbuilt areas in 35 ha reduces the heat island effect through cooling caused by vegetation and increase of air humidity which caused by

Progress Towards Achieving the Challenge of Indian Summer Monsoon Climate Simulation in a Coupled Ocean-Atmosphere Model

Science.gov (United States)

Hazra, Anupam; Chaudhari, Hemantkumar S.; Saha, Subodh Kumar; Pokhrel, Samir; Goswami, B. N.

2017-10-01

Simulation of the spatial and temporal structure of the monsoon intraseasonal oscillations (MISOs), which have effects on the seasonal mean and annual cycle of Indian summer monsoon (ISM) rainfall, remains a grand challenge for the state-of-the-art global coupled models. Biases in simulation of the amplitude and northward propagation of MISOs and related dry rainfall bias over ISM region in climate models are limiting the current skill of monsoon prediction. Recent observations indicate that the convective microphysics of clouds may be critical in simulating the observed MISOs. The hypothesis is strongly supported by high fidelity in simulation of the amplitude and space-time spectra of MISO by a coupled climate model, when our physically based modified cloud microphysics scheme is implemented in conjunction with a modified new Simple Arakawa Schubert (nSAS) convective parameterization scheme. Improved simulation of MISOs appears to have been aided by much improved simulation of the observed high cloud fraction and convective to stratiform rain fractions and resulted into a much improved simulation of the ISM rainfall, monsoon onset, and the annual cycle.

Vegetation-climate feedback causes reduced precipitation and tropical rainforest cover in CMIP5 regional Earth system model simulation over Africa

Science.gov (United States)

Wu, M.; Smith, B.; Samuelsson, P.; Rummukainen, M.; Schurgers, G.

2012-12-01

We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feed back to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feed back to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical

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.)

Analysis of winter climate simulations performed with ARPEGE-Climat (T63) in the framework of PROVOST

Energy Technology Data Exchange (ETDEWEB)

Parey, S.; Dichampt-Martineu, Ch.; Caneill, J.Y. [Electricite de France, 78 - Chatou (France). Research Branch, Environment

1997-12-01

The interest of EDF for seasonal forecasting is a consequence of the high sensitivity of electricity consumption to temperature, especially during the winter season. That is why the Research branch of EDF is involved in the PROVOST project (PRediction Of climate Variations On Seasonal and inter-annual Timescales). Two sets of simulations are studied. The first one was calculated apart from the PROVOST experiments with the LMD model covering the 1970 to 1992 winters with eleven simulations per winter. The second one was calculated at EDF in the framework of PROVOST with ARPEGE-Climat model, covering the 1979 to 1994 winters (nine simulations per winter). The probabilistic formulation of climatic scenarios in function of the seasonal simulations with ARPEGE-Climat gives good results if the monthly mean temperature is taken into account. (R.P.) 3 refs.

Evaluation of simulated corn yields and associated uncertainty in different climate zones of China using Daycent Model

Science.gov (United States)

Fu, A.; Xue, Y.

2017-12-01

Corn is one of most important agricultural production in China. Research on the simulation of corn yields and the impacts of climate change and agricultural management practices on corn yields is important in maintaining the stable corn production. After climatic data including daily temperature, precipitation, solar radiation, relative humidity, and wind speed from 1948 to 2010, soil properties, observed corn yields, and farmland management information were collected, corn yields grown in humidity and hot environment (Sichuang province) and cold and dry environment (Hebei province) in China in the past 63 years were simulated by Daycent, and the results was evaluated based on published yield record. The relationship between regional climate change, global warming and corn yield were analyzed, the uncertainties of simulation derived from agricultural management practices by changing fertilization levels, land fertilizer maintenance and tillage methods were reported. The results showed that: (1) Daycent model is capable to simulate corn yields under the different climatic background in China. (2) When studying the relationship between regional climate change and corn yields, it has been found that observed and simulated corn yields increased along with total regional climate change. (3) When studying the relationship between the global warming and corn yields, It was discovered that newly-simulated corn yields after removing the global warming trend of original temperature data were lower than before.

Simulation of glacial ocean biogeochemical tracer and isotope distributions based on the PMIP3 suite of climate models

Science.gov (United States)

Khatiwala, Samar; Muglia, Juan; Kvale, Karin; Schmittner, Andreas

2016-04-01

In the present climate system, buoyancy forced convection at high-latitudes together with internal mixing results in a vigorous overturning circulation whose major component is North Atlantic Deep Water. One of the key questions of climate science is whether this "mode" of circulation persisted during glacial periods, and in particular at the Last Glacial Maximum (LGM; 21000 years before present). Resolving this question is both important for advancing our understanding of the climate system, as well as a critical test of numerical models' ability to reliably simulate different climates. The observational evidence, based on interpreting geochemical tracers archived in sediments, is conflicting, as are simulations carried out with state-of-the-art climate models (e.g., as part of the PMIP3 suite), which, due to the computational cost involved, do not by and large include biogeochemical and isotope tracers that can be directly compared with proxy data. Here, we apply geochemical observations to evaluate the ability of several realisations of an ocean model driven by atmospheric forcing from the PMIP3 suite of climate models to simulate global ocean circulation during the LGM. This results in a wide range of circulation states that are then used to simulate biogeochemical tracer and isotope (13C, 14C and Pa/Th) distributions using an efficient, "offline" computational scheme known as the transport matrix method (TMM). One of the key advantages of this approach is the use of a uniform set of biogeochemical and isotope parameterizations across all the different circulations based on the PMIP3 models. We compare these simulated distributions to both modern observations and data from LGM ocean sediments to identify similarities and discrepancies between model and data. We find, for example, that when the ocean model is forced with wind stress from the PMIP3 models the radiocarbon age of the deep ocean is systematically younger compared with reconstructions. Changes in

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

Science.gov (United States)

Miller, Brian W.; Frid, Leonardo; Chang, Tony; Piekielek, N. B.; Hansen, Andrew J.; Morisette, Jeffrey T.

2015-01-01

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine (Pinus albicaulis). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

Micro climate Simulation in new Town `Hashtgerd' using downscaled climate data

Science.gov (United States)

Sodoudi, S.

2010-12-01

One of the objectives of climatological part of project Young Cities ‘Developing Energy-Efficient Urban Fabric in the Tehran-Karaj Region’ is to simulate the micro climate (with 1m resolution) in 35ha of new town Hashtgerd, which is located 65 km far from mega city Tehran. The Project aims are developing, implementing and evaluating building and planning schemes and technologies which allow to plan and build sustainable, energy-efficient and climate sensible form mass housing settlements in arid and semi-arid regions (energy-efficient fabric). Climate sensitive form also means designing and planning for climate change and its related effects for Hashtgerd New Town. By configuration of buildings and open spaces according to solar radiation, wind and vegetation, climate sensitive urban form can create outdoor thermal comfort. To simulate the climate on small spatial scales, the micro climate model Envi-met has been used to simulate the micro climate in 35 ha. The Eulerian model ENVI-met is a micro-scale climate model which gives information about the influence of architecture and buildings as well as vegetation and green area on the micro climate up to 1 m resolution. Envi-met has been run with information from topography, downscaled climate data with neuro-fuzzy method, meteorological measurements, building height and different vegetation variants (low and high number of trees) The first results were compared with each other and show In semi-arid climates the protection from solar radiation is of major importance. This can be achieved by implementation of vegetation and geometry of buildings. Due to the geographical location and related sun’s orbit the degree of shading in this area is rather low. Technical construction such awnings have to be implemented. A second important factor is wind. The design follows the idea to block the prevailing winds from west and northwest as well as the hot and dusty winds in summer time from the southeast but at the same time

Simulation of climate variability and anthropogenic climate change

International Nuclear Information System (INIS)

Bengtsson, Lennart

1999-01-01

The climatic changes in the last century were discussed and focus was on the questions: 1) What are the causes of the rapid climate fluctuations and 2) Is the global warming, which is observed during the last century, caused by natural or anthropogenic effects. It is concluded that an understanding of climate based on the interpretation of observational data only is not feasible, unless supported by an adequate theoretical interpretation. The capabilities of climatic models were discussed and the importance of incorporating 1) calculations of the internal variability of the atmosphere when forced from an ocean with prescribed sea surface temperature as well as for a system consisting of an atmosphere and a mixed ocean of limited depth, 2) a fully coupled atmospheric and ocean model and finally, 3) a fully coupled system including transiently changing greenhouse gases and aerosols. A short summation of the results is presented. The pronounced warming during the last century is not reproduced under the assumption of constant forcing and pollution emissions have to be incorporated into the models in order to bring the simulated data in agreement with observations

Simulating vegetation response to climate change in the Blue Mountains with MC2 dynamic global vegetation model

Directory of Open Access Journals (Sweden)

John B. Kim

2018-04-01

Full Text Available Warming temperatures are projected to greatly alter many forests in the Pacific Northwest. MC2 is a dynamic global vegetation model, a climate-aware, process-based, and gridded vegetation model. We calibrated and ran MC2 simulations for the Blue Mountains Ecoregion, Oregon, USA, at 30 arc-second spatial resolution. We calibrated MC2 using the best available spatial datasets from land managers. We ran future simulations using climate projections from four global circulation models (GCM under representative concentration pathway 8.5. Under this scenario, forest productivity is projected to increase as the growing season lengthens, and fire occurrence is projected to increase steeply throughout the century, with burned area peaking early- to mid-century. Subalpine forests are projected to disappear, and the coniferous forests to contract by 32.8%. Large portions of the dry and mesic forests are projected to convert to woodlands, unless precipitation were to increase. Low levels of change are projected for the Umatilla National Forest consistently across the four GCM’s. For the Wallowa-Whitman and the Malheur National Forest, forest conversions are projected to vary more across the four GCM-based simulations, reflecting high levels of uncertainty arising from climate. For simulations based on three of the four GCMs, sharply increased fire activity results in decreases in forest carbon stocks by the mid-century, and the fire activity catalyzes widespread biome shift across the study area. We document the full cycle of a structured approach to calibrating and running MC2 for transparency and to serve as a template for applications of MC2. Keywords: Climate change, Regional change, Simulation, Calibration, Forests, Fire, Dynamic global vegetation model

White book Escrime. Climatic simulation studies; Livre blanc Escrime. Etude des simulations climatiques

Energy Technology Data Exchange (ETDEWEB)

Terray, L [CERFACS, 31 - Toulouse (France); Braconnot, P [Institut Pierre-Simon Laplace IPSL/LSCE, CEA-Orme des Merisiers, 91 - Gif-sur-Yvette (France)

2007-01-15

The ESCRIME project aims to manage the analysis realized on the climatic simulations on the framework of the fourth report of the GIEC (group of intergovernmental experts on the climate evolution), in particularly the simulations based on french models. This white book is constituted by 8 chapters: the global scenario, the climatic sensibility, the variation modes, the regionalization and the extremes, the hydrological cycle, the polar regions and the cryo-sphere, the carbon cycle, detection and attributions. (A.L.B.)

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

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.

Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

Science.gov (United States)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The

NASA Center for Climate Simulation (NCCS) Presentation

Science.gov (United States)

Webster, William P.

2012-01-01

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

On the Representation of Ice Nucleation in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

Science.gov (United States)

Storelvmo, T.

2015-12-01

Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

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

Downscaling a global climate model to simulate climate change over the US and the implication on regional and urban air quality

Directory of Open Access Journals (Sweden)

M. Trail

2013-09-01

Full Text Available Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US, one region during summer (Texas, and one region where changes potentially would lead to better air quality during spring (Northeast. Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

Directory of Open Access Journals (Sweden)

Brian W. Miller

2015-05-01

Full Text Available State-and-transition simulation models (STSMs are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM. SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine (Pinus albicaulis. We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae, and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

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.

Performance of Regional Climate Model in Simulating Monsoon Onset Over Indian Subcontinent

Science.gov (United States)

Bhatla, R.; Mandal, B.; Verma, Shruti; Ghosh, Soumik; Mall, R. K.

2018-06-01

The performance of various Convective Parameterization Schemes (CPSs) of Regional Climate Model version 4.3 (RegCM-4.3) for simulation of onset phase of Indian summer monsoon (ISM) over Kerala was studied for the period of 2001-2010. The onset date and its associated spatial variation were simulated using RegCM-4.3 four core CPS, namely Kuo, Tiedtke, Emanuel and Grell; and with two mixed convection schemes Mix98 (Emanuel over land and Grell over ocean) and Mix99 (Grell over land and Emanuel over ocean) on the basis of criteria given by the India Meteorological Department (IMD) (Pai and Rajeevan in Indian summer monsoon onset: variability and prediction. National Climate Centre, India Meteorological Department, 2007). It has been found that out of six CPS, two schemes, namely Tiedtke and Mix99 simulated the onset date properly. The onset phase is characterized with several transition phases of atmosphere. Therefore, to study the thermal response or the effect of different sea surface temperature (SST), namely ERA interim (ERSST) and weekly optimal interpolation (OI_WK SST) on Indian summer monsoon, the role of two different types of SST has been used to investigate the simulated onset date. In addition, spatial atmospheric circulation pattern during onset phase were analyzed using reanalyze dataset of ERA Interim (EIN15) and National Oceanic and Atmospheric Administration (NOAA), respectively, for wind and outgoing long-wave radiation (OLR) pattern. Among the six convective schemes of RegCM-4.3 model, Tiedtke is in good agreement with actual onset dates and OI_WK SST forcing is better for simulating onset of ISM over Kerala.

Albedo and heat transport in 3-D model simulations of the early Archean climate

Directory of Open Access Journals (Sweden)

H. Kienert

2013-08-01

Full Text Available At the beginning of the Archean eon (ca. 3.8 billion years ago, the Earth's climate state was significantly different from today due to the lower solar luminosity, smaller continental fraction, higher rotation rate and, presumably, significantly larger greenhouse gas concentrations. All these aspects play a role in solutions to the "faint young Sun paradox" which must explain why the ocean surface was not fully frozen at that time. Here, we present 3-D model simulations of climate states that are consistent with early Archean boundary conditions and have different CO2 concentrations, aiming at an understanding of the fundamental characteristics of the early Archean climate system. In order to do so, we have appropriately modified an intermediate complexity climate model that couples a statistical-dynamical atmosphere model (involving parameterizations of the dynamics to an ocean general circulation model and a thermodynamic-dynamic sea-ice model. We focus on three states: one of them is ice-free, one has the same mean surface air temperature of 288 K as today's Earth and the third one is the coldest stable state in which there is still an area with liquid surface water (i.e. the critical state at the transition to a "snowball Earth". We find a reduction in meridional heat transport compared to today, which leads to a steeper latitudinal temperature profile and has atmospheric as well as oceanic contributions. Ocean surface velocities are largely zonal, and the strength of the atmospheric meridional circulation is significantly reduced in all three states. These aspects contribute to the observed relation between global mean temperature and albedo, which we suggest as a parameterization of the ice-albedo feedback for 1-D model simulations of the early Archean and thus the faint young Sun problem.

Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

Science.gov (United States)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim

2016-04-01

The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

Future Precipitation Extremes in China Under Climate Change and Their Possible Mechanisms by Regional Climate Model and Earth System Model Simulations

Science.gov (United States)

Qin, P.; Xie, Z.

2017-12-01

Future precipitation extremes in China for the mid and end of 21st century were detected with six simulations using the regional climate model RegCM4 (RCM) and 17 global climate models (GCM) participated in the coupled Model Intercomparison Project Phase 5 (CMIP5). Prior to understanding the future changes in precipitation extremes, we overviewed the performance of precipitation extremes simulated by the CMIP5s and RCMs, and found both CMIP5s and RCMs could capture the temporal and spatial pattern of the historical precipitation extremes in China. In the mid-future period 2039-2058 (MF) and far-future 2079-2098 (FF), more wet precipitation extremes will occur in most area of China relative to the present period 1982-2001 (RF). We quantified the rates of the changes in precipitation extremes in China with the changes in air surface temperature (T2M) for the MF and FF period. Changes in precipitation extremes R95p were found around 5% K-1 for the MF period and 10% K-1 for the FF period, and changes in maximum 5 day precipitation (Rx5day) were detected around 4% K-1 for the MF period and 7% K-1 for the FF period, respectively. Finally, the possible physical mechanisms behind the changes in precipitation extremes in China were also discussed through the changes in specific humidity and vertical wind.

Real-Time Climate Simulations in the Interactive 3D Game Universe Sandbox ²

Science.gov (United States)

Goldenson, N. L.

2014-12-01

Exploration in an open-ended computer game is an engaging way to explore climate and climate change. Everyone can explore physical models with real-time visualization in the educational simulator Universe Sandbox ² (universesandbox.com/2), which includes basic climate simulations on planets. I have implemented a time-dependent, one-dimensional meridional heat transport energy balance model to run and be adjustable in real time in the midst of a larger simulated system. Universe Sandbox ² is based on the original game - at its core a gravity simulator - with other new physically-based content for stellar evolution, and handling collisions between bodies. Existing users are mostly science enthusiasts in informal settings. We believe that this is the first climate simulation to be implemented in a professionally developed computer game with modern 3D graphical output in real time. The type of simple climate model we've adopted helps us depict the seasonal cycle and the more drastic changes that come from changing the orbit or other external forcings. Users can alter the climate as the simulation is running by altering the star(s) in the simulation, dragging to change orbits and obliquity, adjusting the climate simulation parameters directly or changing other properties like CO2 concentration that affect the model parameters in representative ways. Ongoing visuals of the expansion and contraction of sea ice and snow-cover respond to the temperature calculations, and make it accessible to explore a variety of scenarios and intuitive to understand the output. Variables like temperature can also be graphed in real time. We balance computational constraints with the ability to capture the physical phenomena we wish to visualize, giving everyone access to a simple open-ended meridional energy balance climate simulation to explore and experiment with. The software lends itself to labs at a variety of levels about climate concepts including seasons, the Greenhouse effect

Climate change and international tourism: a simulation study

Energy Technology Data Exchange (ETDEWEB)

Hamilton, J.M. [University of Hamburg (Germany). Centre for Marine and Climate Research, Research Unit Sustainability and Global Change; Maddison, D.J. [University of Southern Denmark, Odense (Denmark). Economics Institute; Centre for Cultural Economics and Management, London (United Kingdom); Tol, R.S.J. [University of Hamburg (Germany). Centre for Marine and Climate Research, Research Unit Sustainability and Global Change; Vrije Universiteit, Amsterdam (Netherlands). Institute for Environmental Studies; Carnegie Mellon University, Pittsburgh (United States). Center for Integrated Study of the Human Dimensions of Global Change

2005-10-01

The literature on tourism and climate change lacks an analysis of the global changes in tourism demand. Here, a simulation model of international tourism is presented that fills that gasp. The current pattern of international tourist flows is modelled using 1995 data on departures and arrivals for 207 countries. Using this basic model the impact on arrivals and departures through changes un population, per capita income and climate change are analysed. In the medium to long term, tourism will grow, however, the change from climate change is smaller than from population and income changes. (author)

Simulation of the last glacial cycle with a coupled climate ice-sheet model of intermediate complexity

Directory of Open Access Journals (Sweden)

A. Ganopolski

2010-04-01

Full Text Available A new version of the Earth system model of intermediate complexity, CLIMBER-2, which includes the three-dimensional polythermal ice-sheet model SICOPOLIS, is used to simulate the last glacial cycle forced by variations of the Earth's orbital parameters and atmospheric concentration of major greenhouse gases. The climate and ice-sheet components of the model are coupled bi-directionally through a physically-based surface energy and mass balance interface. The model accounts for the time-dependent effect of aeolian dust on planetary and snow albedo. The model successfully simulates the temporal and spatial dynamics of the major Northern Hemisphere (NH ice sheets, including rapid glacial inception and strong asymmetry between the ice-sheet growth phase and glacial termination. Spatial extent and elevation of the ice sheets during the last glacial maximum agree reasonably well with palaeoclimate reconstructions. A suite of sensitivity experiments demonstrates that simulated ice-sheet evolution during the last glacial cycle is very sensitive to some parameters of the surface energy and mass-balance interface and dust module. The possibility of a considerable acceleration of the climate ice-sheet model is discussed.

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...

A regional climate simulation over the Iberian Peninsula for the last millennium

Directory of Open Access Journals (Sweden)

J. J. Gómez-Navarro

2011-04-01

Full Text Available A high-resolution (30 km regional paleoclimate simulation of the last millennium over the Iberian Peninsula (IP is presented. The simulation was performed with a climate version of the mesoscale model MM5 driven by the global model ECHO-G. Both models were driven by the same reconstructions of several external forcing factors. The high spatial resolution of the regional model allows climatologists to realistically simulate many aspects of the climate in the IP, as compared to an observational data set in the reference period 1961–1990. Although the spatial-averaged values developed by the regional model are tightly driven by the boundary conditions, it is capable to develop a different realisation of the past climate at regional scales, especially in the high-frequency domain and for precipitation. This has to be considered when comparing the results of climate simulations versus proxy reconstructions. A preliminary comparison of the simulation results with reconstructions of temperature and precipitation over the IP shows good agreement in the warming trends in the last century of the simulation, although there are large disagreements in key periods such as the precipitation anomalies in the Maunder Minimum.

Identifying a key physical factor sensitive to the performance of Madden-Julian oscillation simulation in climate models

Science.gov (United States)

Kim, Go-Un; Seo, Kyong-Hwan

2018-01-01

A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.

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)

Climatology and internal variability in a 1000-year control simulation with the coupled climate model ECHO-G

Energy Technology Data Exchange (ETDEWEB)

Min, S.K.; Hense, A. [Bonn Univ. (Germany). Meteorologisches Inst.; Legutke, S.; Kwon, W.T. [Korea Meteorological Administration, Seoul (Korea). Meteorological Research Inst.

2004-03-01

The climatology and internal variability in a 1000-year control simulation of the coupled atmosphere-ocean global climate model ECHO-G are analyzed and compared with observations and other coupled climate model simulations. ECHO-G requires annual mean flux corrections for heat and freshwater in order to simulate no climate drift for 1000 years, but no flux corrections for momentum. The ECHO-G control run captures well most aspects of the observed seasonal and annual climatology and of the interannual to decadal variability. Model biases are very close to those in ECHAM4 stand-alone integrations with prescribed observed sea surface temperature. A trend comparison between observed and modeled near surface temperatures shows that the observed global warming at near surface level is beyond the range of internal variability produced by ECHO-G. The simulated global mean near surface temperatures, however, show a two-year spectral peak which is linked with a strong biennial bias of energy in the ENSO signal. Consequently, the interannual variability (3-9 years) is underestimated. The overall ENSO structure such as the tropical SST climate and its seasonal cycle, a single ITCZ in the eastern tropical Pacific, and the ENSO phase-locking to the annual cycle are simulated reasonably well by ECHO-G. However, the amplitude of SST variability is overestimated in the eastern equatorial pacific and the observed westward propagation of zonal wind stress over the equatorial pacific is not captured by the model. ENSO-related teleconnection patterns of near surface temperature, precipitation, and mean sea level pressure are reproduced realistically. The station-based NAO index in the model exhibits a 'white' noise spectrum similar to the observed and the NAO-related patterns of near surface temperature, precipitation, and mean sea level pressure are also simulated successfully. However, the model overestimates the additional warming over the north pacific in the high index

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.

Eco-hydrologic model cascades: Simulating land use and climate change impacts on hydrology, hydraulics and habitats for fish and macroinvertebrates.

Science.gov (United States)

Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola

2015-11-15

Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on

Coupled model simulations of climate changes in the 20th century and beyond

Science.gov (United States)

Yu, Yongqiang; Zhi, Hai; Wang, Bin; Wan, Hui; Li, Chao; Liu, Hailong; Li, Wei; Zheng, Weipeng; Zhou, Tianjun

2008-07-01

Several scenario experiments of the IPCC 4th Assessment Report (AR4) are performed by version g1.0 of a Flexible coupled Ocean-Atmosphere-Land System Model (FGOALS) developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS), including the “Climate of the 20th century experiment”, “CO2 1% increase per year to doubling experiment” and two separate IPCC greenhouse gases emission scenarios A1B and B1 experiments. To distinguish between the different impacts of natural variations and human activities on the climate change, three-member ensemble runs are performed for each scenario experiment. The coupled model simulations show: (1) from 1900 to 2000, the global mean temperature increases about 0.5°C and the major increase occurs during the later half of the 20th century, which is in consistent with the observations that highlights the coupled model’s ability to reproduce the climate changes since the industrial revolution; (2) the global mean surface air temperature increases about 1.6°C in the CO2 doubling experiment and 1.5°C and 2.4°C in the A1B and B1 scenarios, respectively. The global warming is indicated by not only the changes of the surface temperature and precipitation but also the temperature increase in the deep ocean. The thermal expansion of the sea water would induce the rise of the global mean sea level. Both the control run and the 20th century climate change run are carried out again with version g1.1 of FGOALS, in which the cold biases in the high latitudes were removed. They are then compared with those from version g1.0 of FGOALS in order to distinguish the effect of the model biases on the simulation of global warming.

Spatial-Scale Characteristics of Precipitation Simulated by Regional Climate Models and the Implications for Hydrological Modeling

DEFF Research Database (Denmark)

Rasmussen, S.H.; Christensen, J. H.; Drews, Martin

2012-01-01

Precipitation simulated by regional climate models (RCMs) is generally biased with respect to observations, especially at the local scale of a few tens of kilometers. This study investigates how well two different RCMs are able to reproduce the spatial correlation patterns of observed summer...... length scales on the order of 130 km are found in both observed data and RCM simulations. When simulations and observations are aggregated to different grid sizes, the pattern correlation significantly decreases when the aggregation length is less than roughly 100 km. Furthermore, the intermodel standard......, reflecting larger predictive certainty of the RCMs at larger scales. The findings on aggregated grid scales are shown to be largely independent of the underlying RCMs grid resolutions but not of the overall size of RCM domain. With regard to hydrological modeling applications, these findings indicate...

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.

Merging Methods to Manage Uncertainty: Combining Simulation Modeling and Scenario Planning to Inform Resource Management Under Climate Change

Science.gov (United States)

Miller, B. W.; Schuurman, G. W.; Symstad, A.; Fisichelli, N. A.; Frid, L.

2017-12-01

Managing natural resources in this era of anthropogenic climate change is fraught with uncertainties around how ecosystems will respond to management actions and a changing climate. Scenario planning (oftentimes implemented as a qualitative, participatory exercise for exploring multiple possible futures) is a valuable tool for addressing this challenge. However, this approach may face limits in resolving responses of complex systems to altered climate and management conditions, and may not provide the scientific credibility that managers often require to support actions that depart from current practice. Quantitative information on projected climate changes and ecological responses is rapidly growing and evolving, but this information is often not at a scale or in a form that is `actionable' for resource managers. We describe a project that sought to create usable information for resource managers in the northern Great Plains by combining qualitative and quantitative methods. In particular, researchers, resource managers, and climate adaptation specialists co-produced a simulation model in conjunction with scenario planning workshops to inform natural resource management in southwest South Dakota. Scenario planning for a wide range of resources facilitated open-minded thinking about a set of divergent and challenging, yet relevant and plausible, climate scenarios and management alternatives that could be implemented in the simulation. With stakeholder input throughout the process, we built a simulation of key vegetation types, grazing, exotic plants, fire, and the effects of climate and management on rangeland productivity and composition. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between herd sizes and vegetation composition, and between the short- versus long-term costs of invasive species management. It also identified impactful uncertainties related to the

Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

Energy Technology Data Exchange (ETDEWEB)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Flörke, M.; Huang, S.; Motovilov, Y.; Buda, S.; Yang, T.; Müller, C.; Leng, G.; Tang, Q.; Portmann, F. T.; Hagemann, S.; Gerten, D.; Wada, Y.; Masaki, Y.; Alemayehu, T.; Satoh, Y.; Samaniego, L.

2017-01-04

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.

Quality assessment of atmospheric surface fields over the Baltic Sea from an ensemble of regional climate model simulations with respect to ocean dynamics

Directory of Open Access Journals (Sweden)

H. E. Markus Meier

2011-05-01

Full Text Available Climate model results for the Baltic Sea region from an ensemble of eight simulations using the Rossby Centre Atmosphere model version 3 (RCA3 driven with lateral boundary data from global climate models (GCMs are compared with results from a downscaled ERA40 simulation and gridded observations from 1980-2006. The results showed that data from RCA3 scenario simulations should not be used as forcing for Baltic Sea models in climate change impact studies because biases of the control climate significantly affect the simulated changes of future projections. For instance, biases of the sea ice cover in RCA3 in the present climate affect the sensitivity of the model's response to changing climate due to the ice-albedo feedback. From the large ensemble of available RCA3 scenario simulations two GCMs with good performance in downscaling experiments during the control period 1980-2006 were selected. In this study, only the quality of atmospheric surface fields over the Baltic Sea was chosen as a selection criterion. For the greenhouse gas emission scenario A1B two transient simulations for 1961-2100 driven by these two GCMs were performed using the regional, fully coupled atmosphere-ice-ocean model RCAO. It was shown that RCAO has the potential to improve the results in downscaling experiments driven by GCMs considerably, because sea surface temperatures and sea ice concentrations are calculated more realistically with RCAO than when RCA3 has been forced with surface boundary data from GCMs. For instance, the seasonal 2 m air temperature cycle is closer to observations in RCAO than in RCA3 downscaling simulations. However, the parameterizations of air-sea fluxes in RCAO need to be improved.

Using sea surface temperatures to improve performance of single dynamical downscaling model in flood simulation under climate change

Science.gov (United States)

Chao, Y.; Cheng, C. T.; Hsiao, Y. H.; Hsu, C. T.; Yeh, K. C.; Liu, P. L.

2017-12-01

There are 5.3 typhoons hit Taiwan per year on average in last decade. Typhoon Morakot in 2009, the most severe typhoon, causes huge damage in Taiwan, including 677 casualties and roughly NT 110 billion (3.3 billion USD) in economic loss. Some researches documented that typhoon frequency will decrease but increase in intensity in western North Pacific region. It is usually preferred to use high resolution dynamical model to get better projection of extreme events; because coarse resolution models cannot simulate intense extreme events. Under that consideration, dynamical downscaling climate data was chosen to describe typhoon satisfactorily, this research used the simulation data from AGCM of Meteorological Research Institute (MRI-AGCM). Considering dynamical downscaling methods consume massive computing power, and typhoon number is very limited in a single model simulation, using dynamical downscaling data could cause uncertainty in disaster risk assessment. In order to improve the problem, this research used four sea surfaces temperatures (SSTs) to increase the climate change scenarios under RCP 8.5. In this way, MRI-AGCMs project 191 extreme typhoons in Taiwan (when typhoon center touches 300 km sea area of Taiwan) in late 21th century. SOBEK, a two dimensions flood simulation model, was used to assess the flood risk under four SSTs climate change scenarios in Tainan, Taiwan. The results show the uncertainty of future flood risk assessment is significantly decreased in Tainan, Taiwan in late 21th century. Four SSTs could efficiently improve the problems of limited typhoon numbers in single model simulation.

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

Dynamically downscaled climate simulations over North America: Methods, evaluation, and supporting documentation for users

Science.gov (United States)

Hostetler, S.W.; Alder, J.R.; Allan, A.M.

2011-01-01

We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968-1999), common periods of the future (2040-2069), and two simulations continuously cover 2010-2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968-1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and

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.

Investigating added value of regional climate modeling in North American winter storm track simulations

Science.gov (United States)

Poan, E. D.; Gachon, P.; Laprise, R.; Aider, R.; Dueymes, G.

2018-03-01

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981-2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal `seriality', as a measure of their temporal variability at a given

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

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.

The Medieval Warm Period, the Little Ice Age and simulated climatic variability

Energy Technology Data Exchange (ETDEWEB)

Hunt, B.G. [CSIRO Marine and Atmospheric Research, Aspendale, VIC (Australia)

2006-12-15

The CSIRO Mark 2 coupled global climatic model has been used to generate a 10,000-year simulation for 'present' climatic conditions. The model output has been analysed to identify sustained climatic fluctuations, such as those attributed to the Medieval Warm Period (MWP) and the Little Ice Age (LIA). Since no external forcing was permitted during the model run all such fluctuations are attributed to naturally occurring climatic variability associated with the nonlinear processes inherent in the climatic system. Comparison of simulated climatic time series for different geographical locations highlighted the lack of synchronicity between these series. The model was found to be able to simulate climatic extremes for selected observations for century timescales, as well as identifying the associated spatial characteristics. Other examples of time series simulated by the model for the USA and eastern Russia had similar characteristics to those attributed to the MWP and the LIA, but smaller amplitudes, and clearly defined spatial patterns. A search for the frequency of occurrence of specified surface temperature anomalies, defined via duration and mean value, revealed that these were primarily confined to polar regions and northern latitudes of Europe, Asia and North America. Over the majority of the oceans and southern hemisphere such climatic fluctuations could not be sustained, for reasons explained in the paper. Similarly, sustained sea-ice anomalies were mainly confined to the northern hemisphere. An examination of mechanisms associated with the sustained climatic fluctuations failed to identify a role for the North Atlantic Oscillation, the El Nino-Southern Oscillation or the Pacific Decadal Oscillation. It was therefore concluded that these fluctuations were generated by stochastic processes intrinsic to the nonlinear climatic system. While a number of characteristics of the MWP and the LIA could have been partially caused by natural processes within

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...

Tropical climate and vegetation cover during Heinrich event 1: Simulations with coupled climate vegetation models

OpenAIRE

Handiani, Dian Noor

2012-01-01

This study focuses on the climate and vegetation responses to abrupt climate change in the Northern Hemisphere during the last glacial period. Two abrupt climate events are explored: the abrupt cooling of the Heinrich event 1 (HE1), followed by the abrupt warming of the Bølling-Allerød interstadial (BA). These two events are simulated by perturbing the freshwater balance of the Atlantic Ocean, with the intention of altering the Atlantic Meridional Overturning Circulation (AMOC) and also of in...

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.

Multiscale combination of climate model simulations and proxy records over the last millennium

Science.gov (United States)

Chen, Xin; Xing, Pei; Luo, Yong; Nie, Suping; Zhao, Zongci; Huang, Jianbin; Tian, Qinhua

2018-05-01

To highlight the compatibility of climate model simulation and proxy reconstruction at different timescales, a timescale separation merging method combining proxy records and climate model simulations is presented. Annual mean surface temperature anomalies for the last millennium (851-2005 AD) at various scales over the land of the Northern Hemisphere were reconstructed with 2° × 2° spatial resolution, using an optimal interpolation (OI) algorithm. All target series were decomposed using an ensemble empirical mode decomposition method followed by power spectral analysis. Four typical components were obtained at inter-annual, decadal, multidecadal, and centennial timescales. A total of 323 temperature-sensitive proxy chronologies were incorporated after screening for each component. By scaling the proxy components using variance matching and applying a localized OI algorithm to all four components point by point, we obtained merged surface temperatures. Independent validation indicates that the most significant improvement was for components at the inter-annual scale, but this became less evident with increasing timescales. In mid-latitude land areas, 10-30% of grids were significantly corrected at the inter-annual scale. By assimilating the proxy records, the merged results reduced the gap in response to volcanic forcing between a pure reconstruction and simulation. Difficulty remained in verifying the centennial information and quantifying corresponding uncertainties, so additional effort should be devoted to this aspect in future research.

Shift of biome patterns due to simulated climate variability and climate change

International Nuclear Information System (INIS)

Claussen, M.

1993-01-01

The variability of simulated equilibrium-response patterns of biomes caused by simulated climate variability and climate shift is analysed. This investigation is based on various realisations of simulated present-day climate and climate shift. It has been found that the difference between biomes computed from three 10-year climatologies and from the corresponding 30-year climatology, simulated by the Hamburg climate model at T21 resolution, amounts to approximately 6% of the total land area, Antarctica excluded. This difference is mainly due to differences in annual moisture availability and winter temperatures. When intercomparing biomes from the 10-year climatologies a 10% difference is seen, but there is no unique difference pattern. In contrast to the interdecadal variability, the shift of conditions favorable for biomes due to a shift in climate in the next 100 years, caused by an increase in sea-surface temperatures and atmospheric CO 2 , reveals a unique trend pattern. It turns out that the strongest and most significant signal is the north-east shift of conditions for boreal biomes. This signal is caused by an increase of annual temperature sums as well as mean temperatures of the coldest and warmest months. Trends in annual moisture availability are of secondary importance globally. Regionally, a decrease in water availability affects biomes in Central and East Europe and an increase of water availability leads to a potential increase in tropical rain forest. In total, all differences amount to roughly 30% of the total land surface, Antarctica excluded. (orig./KW)

Changes in snow cover over China in the 21st century as simulated by a high resolution regional climate model

International Nuclear Information System (INIS)

Shi Ying; Gao Xuejie; Wu Jia; Giorgi, Filippo

2011-01-01

On the basis of the climate change simulations conducted using a high resolution regional climate model, the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model, RegCM3, at 25 km grid spacing, future changes in snow cover over China are analyzed. The simulations are carried out for the period of 1951–2100 following the IPCC SRES A1B emission scenario. The results suggest good performances of the model in simulating the number of snow cover days and the snow cover depth, as well as the starting and ending dates of snow cover to the present day (1981–2000). Their spatial distributions and amounts show fair consistency between the simulation and observation, although with some discrepancies. In general, decreases in the number of snow cover days and the snow cover depth, together with postponed snow starting dates and advanced snow ending dates, are simulated for the future, except in some places where the opposite appears. The most dramatic changes are found over the Tibetan Plateau among the three major snow cover areas of Northeast, Northwest and the Tibetan Plateau in China.

a New Framework for Characterising Simulated Droughts for Future Climates

Science.gov (United States)

Sharma, A.; Rashid, M.; Johnson, F.

2017-12-01

Significant attention has been focussed on metrics for quantifying drought. Lesser attention has been given to the unsuitability of current metrics in quantifying drought in a changing climate due to the clear non-stationarity in potential and actual evapotranspiration well into the future (Asadi-Zarch et al, 2015). This talk presents a new basis for simulating drought designed specifically for use with climate model simulations. Given the known uncertainty of climate model rainfall simulations, along with their inability to represent low-frequency variability attributes, the approach here adopts a predictive model for drought using selected atmospheric indicators. This model is based on a wavelet decomposition of relevant atmospheric predictors to filter out less relevant frequencies and formulate a better characterisation of the drought metric chosen as response. Once ascertained using observed precipication and associated atmospheric variables, these can be formulated from GCM simulations using a multivariate bias correction tool (Mehrotra and Sharma, 2016) that accounts for low-frequency variability, and a regression tool that accounts for nonlinear dependence (Sharma and Mehrotra, 2014). Use of only the relevant frequencies, as well as the corrected representation of cross-variable dependence, allows greater accuracy in characterising observed drought, from GCM simulations. Using simulations from a range of GCMs across Australia, we show here that this new method offers considerable advantages in representing drought compared to traditionally followed alternatives that rely on modelled rainfall instead. Reference:Asadi Zarch, M. A., B. Sivakumar, and A. Sharma (2015), Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI), Journal of Hydrology, 526, 183-195. Mehrotra, R., and A. Sharma (2016), A Multivariate Quantile-Matching Bias Correction Approach with Auto- and Cross

Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

Science.gov (United States)

Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

2013-01-01

Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

Large-scale tropospheric transport in the Chemistry-Climate Model Initiative (CCMI) simulations

Science.gov (United States)

Orbe, Clara; Yang, Huang; Waugh, Darryn W.; Zeng, Guang; Morgenstern, Olaf; Kinnison, Douglas E.; Lamarque, Jean-Francois; Tilmes, Simone; Plummer, David A.; Scinocca, John F.; Josse, Beatrice; Marecal, Virginie; Jöckel, Patrick; Oman, Luke D.; Strahan, Susan E.; Deushi, Makoto; Tanaka, Taichu Y.; Yoshida, Kohei; Akiyoshi, Hideharu; Yamashita, Yousuke; Stenke, Andreas; Revell, Laura; Sukhodolov, Timofei; Rozanov, Eugene; Pitari, Giovanni; Visioni, Daniele; Stone, Kane A.; Schofield, Robyn; Banerjee, Antara

2018-05-01

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry-Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI simulations

Directory of Open Access Journals (Sweden)

C. Orbe

2018-05-01

Full Text Available Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI. Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

Flexible Environments for Grand-Challenge Simulation in Climate Science

Science.gov (United States)

Pierrehumbert, R.; Tobis, M.; Lin, J.; Dieterich, C.; Caballero, R.

2004-12-01

Current climate models are monolithic codes, generally in Fortran, aimed at high-performance simulation of the modern climate. Though they adequately serve their designated purpose, they present major barriers to application in other problems. Tailoring them to paleoclimate of planetary simulations, for instance, takes months of work. Theoretical studies, where one may want to remove selected processes or break feedback loops, are similarly hindered. Further, current climate models are of little value in education, since the implementation of textbook concepts and equations in the code is obscured by technical detail. The Climate Systems Center at the University of Chicago seeks to overcome these limitations by bringing modern object-oriented design into the business of climate modeling. Our ultimate goal is to produce an end-to-end modeling environment capable of configuring anything from a simple single-column radiative-convective model to a full 3-D coupled climate model using a uniform, flexible interface. Technically, the modeling environment is implemented as a Python-based software component toolkit: key number-crunching procedures are implemented as discrete, compiled-language components 'glued' together and co-ordinated by Python, combining the high performance of compiled languages and the flexibility and extensibility of Python. We are incrementally working towards this final objective following a series of distinct, complementary lines. We will present an overview of these activities, including PyOM, a Python-based finite-difference ocean model allowing run-time selection of different Arakawa grids and physical parameterizations; CliMT, an atmospheric modeling toolkit providing a library of 'legacy' radiative, convective and dynamical modules which can be knitted into dynamical models, and PyCCSM, a version of NCAR's Community Climate System Model in which the coupler and run-control architecture are re-implemented in Python, augmenting its flexibility

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

Science.gov (United States)

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Extreme climate in China. Facts, simulation and projection

Energy Technology Data Exchange (ETDEWEB)

Wang, Hui-Jun; Sun, Jian-Qi; Chen, Huo-Po; Zhu, Ya-Li; Zhang, Ying; Jiang, Da-Bang; Lang, Xian-Mei; Fan, Ke; Yu, En-Tao [Chinese Academy of Sciences, Beijing (China). Inst. of Atmospheric Physics; Yang, Song [NOAA Climate Prediction Center, Camp Springs, MD (United States)

2012-06-15

In this paper, studies on extreme climate in China including extreme temperature and precipitation, dust weather activity, tropical cyclone activity, intense snowfall and cold surge activity, floods, and droughts are reviewed based on the peer-reviewed publications in recent decades. The review is focused first on the climatological features, variability, and trends in the past half century and then on simulations and projections based on global and regional climate models. As the annual mean surface air temperature (SAT) increased throughout China, heat wave intensity and frequency overall increased in the past half century, with a large rate after the 1980s. The daily or yearly minimum SAT increased more significantly than the mean or maximum SAT. The long-term change in precipitation is predominantly characterized by the so-called southern flood and northern drought pattern in eastern China and by the overall increase over Northwest China. The interdecadal variation of monsoon, represented by the monsoon weakening in the end of 1970s, is largely responsible for this change in mean precipitation. Precipitation-related extreme events (e.g., heavy rainfall and intense snowfall) have become more frequent and intense generally over China in the recent years, with large spatial features. Dust weather activity, however, has become less frequent over northern China in the recent years, as result of weakened cold surge activity, reinforced precipitation, and improved vegetation condition. State-of-the-art climate models are capable of reproducing some features of the mean climate and extreme climate events. However, discrepancies among models in simulating and projecting the mean and extreme climate are also demonstrated by many recent studies. Regional models with higher resolutions often perform better than global models. To predict and project climate variations and extremes, many new approaches and schemes based on dynamical models, statistical methods, or their

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

Science.gov (United States)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2017-12-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

Science.gov (United States)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

Science.gov (United States)

Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Influence of hydrological models on cumulative flow simulation under climate change scenarios : an application in the Baskatong watershed

International Nuclear Information System (INIS)

Chartier, I.

2006-01-01

Since Hydro-Quebec owns and operates many hydroelectric power plants, from which it draws 96 per cent of its electricity, the electric utility found it necessary to study the impact of climate change on water resources and cumulative flow. This paper described Hydro-Quebec's method for evaluating climatic change impacts using hydrological simulations, with particular reference to the Baskatong watershed in the Outaouais region of Quebec. This basin is one of 5 sub-basins within the Gatineau River. Hydro-Quebec's studies were conducted using 3 hydrological models known as MOHYSE, HSAMI and HYDROTEL; 4 general circulation models (GCM) known as HadCM3, CSIRO, ECHAM4 and CGCM3; and, 4 greenhouse gas scenarios called A1, B1, A2 and B2. GCMs were shown to have a larger impact on the final hydrological simulation result compared to greenhouse gas scenarios or the hydrological models, although the latter two did have a significant impact on the final result of the simulation. Each scenario provided long term predictions despite the use of different models. The study demonstrated that many regions will have to rely on a range of GCM for more elaborate climatic scenarios. 9 refs., 1 tab., 9 figs

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NARCIS (Netherlands)

Makowski, D.; Asseng, S.; Ewert, F.; Bassu, S.; Durand, J.L.; Martre, P.; Adam, M.; Aggarwal, P.K.; Angulo, C.; Baron, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Boogaard, H.; Boote, K.J.; Brisson, N.; Cammarano, D.; Challinor, A.J.; Conijn, J.G.; Corbeels, M.; Deryng, D.; Sanctis, De G.; Doltra, J.; Gayler, S.; Goldberg, R.; Grassini, P.; Hatfield, J.L.; Heng, L.; Hoek, S.B.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, C.; Jongschaap, R.E.E.; Jones, J.W.; Kemanian, R.A.; Kersebaum, K.C.; Kim, S.H.; Lizaso, J.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.J.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Pravia, M.V.; Priesack, E.; Ripoche, D.; Rosenzweig, C.; Ruane, A.C.; Sau, F.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Teixeira, E.; Thorburn, P.; Timlin, D.; Travasso, M.; Roetter, R.P.; Waha, K.; Wallach, D.; White, J.W.; Williams, J.R.; Wolf, J.

2015-01-01

Many simulation studies have been carried out to predict the effect of climate change on crop yield. Typically, in such study, one or several crop models are used to simulate series of crop yield values for different climate scenarios corresponding to different hypotheses of temperature, CO2

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.

simulating rice yields under climate change scenarios using

African Journals Online (AJOL)

Prof. Adipala Ekwamu

The effects of climate change on rice production and yield cannot be overlooked in finding measures to increase production and yield. The CERES-Rice (Ver. 4.0) model was calibrated and evaluated for use in simulating rice yields under different climate change scenarios in Ghana using data from the Anum Valley ...

Greenhouse-gas-induced climatic change: A critical appraisal of simulations and observations

International Nuclear Information System (INIS)

Schlesinger, M.E.

1990-01-01

This book is the culmination of a Workshop on Greenhouse-Gas-Induced Climatic Change: A Critical Appraisal of Simulations and Observations which was held at the University of Massachusetts, Amherst, during 8--12 May 1989. The objectives of the Workshop were to: (1) present and evaluate the current status of climate model simulations of greenhouse-gas-induced changes of both the equilibrium and nonequilibrium (transient) climates; (2) present and assess the current status of the observations of global and regional climates from the beginning of the industrial revolution to the present, circa 1850 to 1989; (3) present reconstructions of climatic change during the last millennium to determine the ''natural variability'' of climate on the intra-century time scale; (4) critically evaluate whether or not the climate has changes from circa 1850 to 1989; and (5) compare the observations with the model simulations to ascertain whether a greenhouse-gas-induced climatic change has occurred and, if not, to estimate when in the future such a climatic change will likely become detectable against the background of the ''natural variability.''

Hydrological simulations driven by RCM climate scenarios at basin scale in the Po River, Italy

Directory of Open Access Journals (Sweden)

R. Vezzoli

2014-09-01

Full Text Available River discharges are the main expression of the hydrological cycle and are the results of climate natural variability. The signal of climate changes occurrence raises the question of how it will impact on river flows and on their extreme manifestations: floods and droughts. This question can be addressed through numerical simulations spanning from the past (1971 to future (2100 under different climate change scenarios. This work addresses the capability of a modelling chain to reproduce the observed discharge of the Po River over the period 1971–2000. The modelling chain includes climate and hydrological/hydraulic models and its performance is evaluated through indices based on the flow duration curve. The climate datasets used for the 1971–2000 period are (a a high resolution observed climate dataset, and COSMO-CLM regional climate model outputs with (b perfect boundary condition, ERA40 Reanalysis, and (c suboptimal boundary conditions provided by the global climate model CMCC–CM. The aim of the different simulations is to evaluate how the uncertainties introduced by the choice of the regional and/or global climate models propagate in the simulated discharges. This point is relevant to interpret the results of the simulated discharges when scenarios for the future are considered. The hydrological/hydraulic components are simulated through a physically-based distributed model (TOPKAPI and a water balance model at the basin scale (RIBASIM. The aim of these first simulations is to quantify the uncertainties introduced by each component of the modelling chain and their propagation. Estimation of the overall uncertainty is relevant to correctly understand the future river flow regimes. The results show how bias correction algorithms can help in reducing the overall uncertainty associated to the different stages of the modelling chain.

Improvement of snowpack simulations in a regional climate model

Energy Technology Data Exchange (ETDEWEB)

Jin, J.; Miller, N.L.

2011-01-10

To improve simulations of regional-scale snow processes and related cold-season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth-generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5–CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5–CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land-surface model. One important cause for the underestimated SWE in Noah is its unrealistic land-surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow-season surface albedo overestimated by MM5–Noah is now more accurately predicted by MM5–CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near-surface cold bias in MM5–Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5–CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5–Noah. In addition, the over-predicted precipitation in the Pacific Northwest as shown in MM5–Noah is significantly decreased in MM5 CLM3 due to the lower evaporation resulting from the

Simulation of the modern arctic climate by the NCAR CCM1

Science.gov (United States)

Bromwich, David H.; Tzeng, Ren-Yow; Parish, Thomas, R.

1994-01-01

The National Center of Atmospheric Research (NCAR) Community Climate Model Version 1 (CCM1's) simulation of the modern arctic climate is evaluated by comparing a five-year seasonal cycle simulation with the European Center for Medium-Range Weather Forecasts (ECMWF) global analyses. The sea level pressure (SLP), storm tracks, vertical cross section of height, 500-hPa height, total energy budget, and moisture budget are analyzed to investigate the biases in the simulated arctic climate. The results show that the model simulates anomalously low SLP, too much storm activity, and anomalously strong baroclinicity to the west of Greenland and vice versa to the east of Greenland. This bias is mainly attributed to the model's topographic representation of Greenland. First, the broadened Greenland topography in the model distorts the path of cyclone waves over the North Atlantic Ocean. Second, the model oversimulates the ridge over Greenland, which intensifies its blocking effect and steers the cyclone waves clockwise around it and hence produces an artificial circum-Greenland trough. These biases are significantly alleviated when the horizontal resolution increases to T42. Over the Arctic basin, the model simulates large amounts of low-level (stratus) clouds in winter and almost no stratus in summer, which is opposite to the observations. This bias is mainly due to the location of the simulated SLP features and the negative anomaly of storm activity, which prevent the transport of moisture into this region during summer but favor this transport in winter. The moisture budget analysis shows that the model's net annual precipitation (P-E) between 70 deg N and the North Pole is 6.6 times larger than the observations and the model transports six times more moisture into this region. The bias in the advection term is attributed to the positive moisture fixer scheme and the distorted flow pattern. However, the excessive moisture transport into the Arctic basin does not solely

A piecewise-integration method for simulating the influence of external forcing on climate

Institute of Scientific and Technical Information of China (English)

Zhifu Zhang; Chongjian Qiu; Chenghai Wang

2008-01-01

Climate drift occurs in most general circulation models (GCMs) as a result of incomplete physical and numerical representation of the complex climate system,which may cause large uncertainty in sensitivity experiments evaluating climate response to changes in external forcing.To solve this problem,we propose a piecewise-integration method to reduce the systematic error in climate sensitivity studies.The observations are firstly assimilated into a numerical model by using the dynamic relaxation technique to relax to the current state of atmosphere,and then the assimilated fields are continuously used to reinitialize the simulation to reduce the error of climate simulation.When the numerical model is integrated with changed external forcing,the results can be split into two parts,background and perturbation fields,and the background is the state before the external forcing is changed.The piecewise-integration method is used to continuously reinitialize the model with the assimilated field,instead of the background.Therefore,the simulation error of the model with the external forcing can be reduced.In this way,the accuracy of climate sensitivity experiments is greatly improved.Tests with a simple low-order spectral model show that this approach can significantly reduce the uncertainty of climate sensitivity experiments.

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.

Just-in-time Time Data Analytics and Visualization of Climate Simulations using the Bellerophon Framework

Science.gov (United States)

Anantharaj, V. G.; Venzke, J.; Lingerfelt, E.; Messer, B.

2015-12-01

Climate model simulations are used to understand the evolution and variability of earth's climate. Unfortunately, high-resolution multi-decadal climate simulations can take days to weeks to complete. Typically, the simulation results are not analyzed until the model runs have ended. During the course of the simulation, the output may be processed periodically to ensure that the model is preforming as expected. However, most of the data analytics and visualization are not performed until the simulation is finished. The lengthy time period needed for the completion of the simulation constrains the productivity of climate scientists. Our implementation of near real-time data visualization analytics capabilities allows scientists to monitor the progress of their simulations while the model is running. Our analytics software executes concurrently in a co-scheduling mode, monitoring data production. When new data are generated by the simulation, a co-scheduled data analytics job is submitted to render visualization artifacts of the latest results. These visualization output are automatically transferred to Bellerophon's data server located at ORNL's Compute and Data Environment for Science (CADES) where they are processed and archived into Bellerophon's database. During the course of the experiment, climate scientists can then use Bellerophon's graphical user interface to view animated plots and their associated metadata. The quick turnaround from the start of the simulation until the data are analyzed permits research decisions and projections to be made days or sometimes even weeks sooner than otherwise possible! The supercomputer resources used to run the simulation are unaffected by co-scheduling the data visualization jobs, so the model runs continuously while the data are visualized. Our just-in-time data visualization software looks to increase climate scientists' productivity as climate modeling moves into exascale era of computing.

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

Energy Technology Data Exchange (ETDEWEB)

Di Luca, Alejandro; Laprise, Rene [Universite du Quebec a Montreal (UQAM), Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Departement des Sciences de la Terre et de l' Atmosphere, PK-6530, Succ. Centre-ville, B.P. 8888, Montreal, QC (Canada); De Elia, Ramon [Universite du Quebec a Montreal, Ouranos Consortium, Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal (Canada)

2012-03-15

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions. (orig.)

Integrating components of the earth system to model global climate changes: implications for the simulation of the climate of the next million years

International Nuclear Information System (INIS)

Duplessy, J.C.

2009-01-01

The climate system is complex because it is made up of several components (atmosphere, ocean, sea ice, continental surface, ice sheets), each of which has its own response time. The paleo-climate record provides ample evidence that these components interact nonlinearly with each other and also with global biogeochemical cycles, which drive greenhouse gas concentration in the atmosphere. Forecasting the evolution of future climate is therefore an extremely complex problem. In addition, since the nineteenth century, human activities are releasing great quantities of greenhouse gases (CO 2 , CH 4 , CFC, etc.) into the atmosphere. As a consequence, the atmospheric content of these gases has tremendously increased. As they have a strong greenhouse effect, their concentration is now large enough to perturb the natural evolution of the earth's climate. In this paper, we shall review the strategy which has been used to develop and validate tools that would allow to simulate the future long-term behaviour of the Earth's climate. This strategy rests on two complementary approaches: developing numerical models of the climate system and validating them by comparing their output with present-day meteorological data and paleo-climatic reconstructions. We shall then evaluate the methods available to simulate climate at the regional scale and the major uncertainties that must be solved to reasonable estimate the long-term evolution of a region, which would receive a geological repository for nuclear wastes. (author)

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

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

Science.gov (United States)

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

Directory of Open Access Journals (Sweden)

Holger Hoffmann

Full Text Available We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil.

Science.gov (United States)

Battisti, R; Sentelhas, P C; Boote, K J

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha -1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .

Impacts of climate change on peanut yield in China simulated by CMIP5 multi-model ensemble projections

Science.gov (United States)

Xu, Hanqing; Tian, Zhan; Zhong, Honglin; Fan, Dongli; Shi, Runhe; Niu, Yilong; He, Xiaogang; Chen, Maosi

2017-09-01

Peanut is one of the major edible vegetable oil crops in China, whose growth and yield are very sensitive to climate change. In addition, agriculture climate resources are expected to be redistributed under climate change, which will further influence the growth, development, cropping patterns, distribution and production of peanut. In this study, we used the DSSAT-Peanut model to examine the climate change impacts on peanut production, oil industry and oil food security in China. This model is first calibrated using site observations including 31 years' (1981-2011) climate, soil and agronomy data. This calibrated model is then employed to simulate the future peanut yield based on 20 climate scenarios from 5 Global Circulation Models (GCMs) developed by the InterSectoral Impact Model Intercomparison Project (ISIMIP) driven by 4 Representative Concentration Pathways (RCPs). Results indicate that the irrigated peanut yield will decrease 2.6% under the RCP 2.6 scenario, 9.9% under the RCP 4.5 scenario and 29% under the RCP 8.5 scenario, respectively. Similarly, the rain-fed peanut yield will also decrease, with a 2.5% reduction under the RCP 2.6 scenario, 11.5% reduction under the RCP 4.5 scenario and 30% reduction under the RCP 8.5 scenario, respectively.

On the Representation of Cloud Phase in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

Science.gov (United States)

Storelvmo, Trude; Sagoo, Navjit; Tan, Ivy

2016-04-01

Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

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.

Simulated Climate Impacts of Mexico City's Historical Urban Expansion

Science.gov (United States)

Benson-Lira, Valeria

Urbanization, a direct consequence of land use and land cover change, is responsible for significant modification of local to regional scale climates. It is projected that the greatest urban growth of this century will occur in urban areas in the developing world. In addition, there is a significant research gap in emerging nations concerning this topic. Thus, this research focuses on the assessment of climate impacts related to urbanization on the largest metropolitan area in Latin America: Mexico City. Numerical simulations using a state-of-the-science regional climate model are utilized to address a trio of scientifically relevant questions with wide global applicability. The importance of an accurate representation of land use and land cover is first demonstrated through comparison of numerical simulations against observations. Second, the simulated effect of anthropogenic heating is quantified. Lastly, numerical simulations are performed using pre-historic scenarios of land use and land cover to examine and quantify the impact of Mexico City's urban expansion and changes in surface water features on its regional climate.

Impact of an observational time window on coupled data assimilation: simulation with a simple climate model

Directory of Open Access Journals (Sweden)

Y. Zhao

2017-11-01

Full Text Available Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.

Forecasting carbon budget under climate change and CO2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

Science.gov (United States)

Zhu, Q.; Jiang, H.; Liu, J.; Peng, C.; Fang, X.; Yu, S.; Zhou, G.; Wei, X.; Ju, W.

2011-01-01

The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr-1 during the last half of the 21st century. An NPP increase of about 24 Mt C by the end of the 21st century was estimated with the combined effects of increasing CO2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr-1. NEP will increase to about 5 Mt C yr-1 by the end of the 21st century with the increasing atmospheric CO2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO2 concentration will have little

[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.

Temperature sensitivity to the land-surface model in MM5 climate simulations over the Iberian Peninsula

Energy Technology Data Exchange (ETDEWEB)

Jerez, Sonia; Montavez, Juan P.; Gomez-Navarro, Juan J.; Jimenez-Guerrero, Pedro [Dept. de Fisica, Univ. de Murcia (Spain); Jimenez, Jose M.; Gonzalez-Rouco, Jesus F. [Dept. de Astrofisica y CC. de la Atmosfera, Univ. Complutense de Madrid (Spain)

2010-06-15

Three different Land Surface Models have been used in three high resolution climate simulations performed with the mesoscale model MM5 over the Iberian Peninsula. The main difference among them lies in the soil moisture treatment, which is dynamically modelled by only two of them (Noah and Pleim and Xiu models), while in the simplest model (Simple Five-Layers) it is fixed to climatological values. The simulated period covers 1958-2002, using the ERA40 reanalysis data as driving conditions. Focusing on near-surface air temperature, this work evaluates the skill of each simulation in reproducing mean values and temporal variability, by comparing the simulations with observed temperature series. When the simplest simulation was analyzed, the greatest discrepances were observed for the summer season, when both, the mean values and the temporal variability of the temperature series, were badly underestimated. These weaknesses are largely overcome in the other two simulations (performed by coupling a more advanced soil model to MM5), and there was greater concordance between the simulated and observed spatial patterns. The influence of a dynamic soil moisture parameterization and, therefore, a more realistic simulation of the latent and sensible heat fluxes between the land and the atmosphere, helps to explain these results. (orig.)

Regional Spectral Model simulations of the summertime regional climate over Taiwan and adjacent areas

Science.gov (United States)

Ching-Teng Lee; Ming-Chin Wu; Shyh-Chin Chen

2005-01-01

The National Centers for Environmental Prediction (NCEP) regional spectral model (RSM) version 97 was used to investigate the regional summertime climate over Taiwan and adjacent areas for June-July-August of 1990 through 2000. The simulated sea-level-pressure and wind fields of RSM1 with 50-km grid space are similar to the reanalysis, but the strength of the...

Comparative analysis of the influence of climate change and nitrogen deposition on carbon sequestration in forest ecosystems in European Russia: simulation modelling approach

Directory of Open Access Journals (Sweden)

A. S. Komarov

2012-11-01

Full Text Available An individual-based simulation model, EFIMOD, was used to simulate the response of forest ecosystems to climate change and additional nitrogen deposition. The general scheme of the model includes forest growth depending on nitrogen uptake by plants and mineralization of soil organic matter. The mineralization rate is dependent on nitrogen content in litter and forest floor horizons. Three large forest areas in European Central Russia with a total area of about 17 000 km² in distinct environmental conditions were chosen. Simulations were carried out with two climatic scenarios (ambient climate and climate change and different levels of nitrogen deposition (ambient value and increase by 6 and 12 kg N ha⁻¹ yr⁻¹. The simulations showed that increased nitrogen deposition leads to increased productivity of trees, increased organic matter content in organic soil horizons, and an increased portion of deciduous tree species. For the climate change scenario, the same effects on forest productivity and similar shifts in species composition were predicted but the accumulation of organic matter in soil was decreased.

Regional climate simulations with COSMO-CLM over MENA-CORDEX domain

Science.gov (United States)

Galluccio, Salvatore; Bucchignani, Edoardo; Mercogliano, Paola; Montesarchio, Myriam

2014-05-01

In the frame of WCRP Coordinated Regional Downscaling Experiment (CORDEX), a set of common Regional Climate Downscaling (RCD) domains has been defined, as a prerequisite for the development of model evaluation and climate projection frameworks. CORDEX domains encompass the majority of land areas of the world. In this work, climate simulations have been performed over MENA-CORDEX domain, which includes North-Africa, southern Europe and the whole Arabian peninsula. The non-hydrostatic regional climate model COSMO-CLM has been used. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A series of simulations has been conducted over the MENA-CORDEX area at spatial resolution of 0.44°. A sensitivity analysis was conducted to adjust the model configuration to better reproduce the observed climate data. The numerical simulations were driven by ERA-Interim reanalysis (horizontal resolution of 0.703°) for the period 1979-1984; the first year, was considered as a spin up period. The validation was performed by using several data sets: CRU data set was used to validate temperature, precipitation and cloud cover; MERRA data set was used to validate temperature and precipitation and GPCP for precipitation. The model sensitivity to the external parameters was tested considering two different configurations for the surface albedo. In the first one, albedo is only function of soil-type whereas in the second configuration it is prescribed by two external fields for dry and saturated soil based on MODIS data. Moreover, we tested two aerosol distributions as well, namely the default Tanre aerosol distribution and aerosol maps according to Tegen (NASA/GISS). We found, as expected, a significant sensitivity, in particular on the African region. We also varied tuning and physical parameters, such

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.

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

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.

Simulating the characteristics of tropical cyclones over the South West Indian Ocean using a Stretched-Grid Global Climate Model

Science.gov (United States)

Maoyi, Molulaqhooa L.; Abiodun, Babatunde J.; Prusa, Joseph M.; Veitch, Jennifer J.

2018-03-01

Tropical cyclones (TCs) are one of the most devastating natural phenomena. This study examines the capability of a global climate model with grid stretching (CAM-EULAG, hereafter CEU) in simulating the characteristics of TCs over the South West Indian Ocean (SWIO). In the study, CEU is applied with a variable increment global grid that has a fine horizontal grid resolution (0.5° × 0.5°) over the SWIO and coarser resolution (1° × 1°—2° × 2.25°) over the rest of the globe. The simulation is performed for the 11 years (1999-2010) and validated against the Joint Typhoon Warning Center (JTWC) best track data, global precipitation climatology project (GPCP) satellite data, and ERA-Interim (ERAINT) reanalysis. CEU gives a realistic simulation of the SWIO climate and shows some skill in simulating the spatial distribution of TC genesis locations and tracks over the basin. However, there are some discrepancies between the observed and simulated climatic features over the Mozambique channel (MC). Over MC, CEU simulates a substantial cyclonic feature that produces a higher number of TC than observed. The dynamical structure and intensities of the CEU TCs compare well with observation, though the model struggles to produce TCs with a deep pressure centre as low as the observed. The reanalysis has the same problem. The model captures the monthly variation of TC occurrence well but struggles to reproduce the interannual variation. The results of this study have application in improving and adopting CEU for seasonal forecasting over the SWIO.

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.

Simulation of the summer circulation over South America by two regional climate models. Part I: Mean climatology

Science.gov (United States)

Fernandez, J. P. R.; Franchito, S. H.; Rao, V. B.

2006-09-01

This study investigates the capabilities of two regional models (the ICTP RegCM3 and the climate version of the CPTEC Eta model - EtaClim) in simulating the mean climatological features of the summer quasi-stationary circulations over South America. Comparing the results with the NCEP/DOE reanalysis II data it is seen that the RegCM3 simulates a weaker and southward shifted Bolivian high (BH). But, the Nordeste low (NL) is located close to its climatological position. In the EtaClim the position of the BH is reproduced well, but the NL is shifted towards the interior of the continent. To the east of Andes, the RegCM3 simulates a weaker low level jet and a weaker basic flow from the tropical Atlantic to Amazonia while they are stronger in the EtaClim. In general, the RegCM3 and EtaClim show, respectively a negative and positive bias in the surface temperature in almost all regions of South America. For both models, the correlation coefficients between the simulated precipitation and the GPCP data are high over most of South America. Although the RegCM3 and EtaClim overestimate the precipitation in the Andes region they show a negative bias in general over the entire South America. The simulations of upper and lower level circulations and precipitation fields in EtaClim were better than that of the RegCM3. In central Amazonia both models were unable to simulate the precipitation correctly. The results showed that although the RegCM3 and EtaClim are capable of simulating the main climatological features of the summer climate over South America, there are areas which need improvement. This indicates that the models must be more adequately tuned in order to give reliable predictions in the different regions of South America.

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...

Failure of CMIP5 climate models in simulating post-1950 decreasing trend of Indian monsoon

Science.gov (United States)

Saha, Anamitra; Ghosh, Subimal; Sahana, A. S.; Rao, E. P.

2014-10-01

Impacts of climate change on Indian Summer Monsoon Rainfall (ISMR) and the growing population pose a major threat to water and food security in India. Adapting to such changes needs reliable projections of ISMR by general circulation models. Here we find that, majority of new generation climate models from Coupled Model Intercomparison Project phase5 (CMIP5) fail to simulate the post-1950 decreasing trend of ISMR. The weakening of monsoon is associated with the warming of Southern Indian Ocean and strengthening of cyclonic formation in the tropical western Pacific Ocean. We also find that these large-scale changes are not captured by CMIP5 models, with few exceptions, which is the reason of this failure. Proper representation of these highlighted geophysical processes in next generation models may improve the reliability of ISMR projections. Our results also alert the water resource planners to evaluate the CMIP5 models before using them for adaptation strategies.

Toward 10-km mesh global climate simulations

Science.gov (United States)

Ohfuchi, W.; Enomoto, T.; Takaya, K.; Yoshioka, M. K.

2002-12-01

An atmospheric general circulation model (AGCM) that runs very efficiently on the Earth Simulator (ES) was developed. The ES is a gigantic vector-parallel computer with the peak performance of 40 Tflops. The AGCM, named AFES (AGCM for ES), was based on the version 5.4.02 of an AGCM developed jointly by the Center for Climate System Research, the University of Tokyo and the Japanese National Institute for Environmental Sciences. The AFES was, however, totally rewritten in FORTRAN90 and MPI while the original AGCM was written in FORTRAN77 and not capable of parallel computing. The AFES achieved 26 Tflops (about 65 % of the peak performance of the ES) at resolution of T1279L96 (10-km horizontal resolution and 500-m vertical resolution in middle troposphere to lower stratosphere). Some results of 10- to 20-day global simulations will be presented. At this moment, only short-term simulations are possible due to data storage limitation. As ten tera flops computing is achieved, peta byte data storage are necessary to conduct climate-type simulations at this super-high resolution global simulations. Some possibilities for future research topics in global super-high resolution climate simulations will be discussed. Some target topics are mesoscale structures and self-organization of the Baiu-Meiyu front over Japan, cyclogenecsis over the North Pacific and typhoons around the Japan area. Also improvement in local precipitation with increasing horizontal resolution will be demonstrated.

Modeling of hydrologic conditions and solute movement in processed oil shale waste embankments under simulated climatic conditions

International Nuclear Information System (INIS)

Reeves, T.L.; Turner, J.P.; Hasfurther, V.R.; Skinner, Q.D.

1992-06-01

The scope of this program is to study interacting hydrologic, geotechnical, and chemical factors affecting the behavior and disposal of combusted processed oil shale. The research combines bench-scale testing with large scale research sufficient to describe commercial scale embankment behavior. The large scale approach was accomplished by establishing five lysimeters, each 7.3 x 3.0 x 3.0 m deep, filled with processed oil shale that has been retorted and combusted by the Lurgi-Ruhrgas (Lurgi) process. Approximately 400 tons of Lurgi processed oil shale waste was provided by RBOSC to carry out this study. Research objectives were designed to evaluate hydrologic, geotechnical, and chemical properties and conditions which would affect the design and performance of large-scale embankments. The objectives of this research are: assess the unsaturated movement and redistribution of water and the development of potential saturated zones and drainage in disposed processed oil shale under natural and simulated climatic conditions; assess the unsaturated movement of solubles and major chemical constituents in disposed processed oil shale under natural and simulated climatic conditions; assess the physical and constitutive properties of the processed oil shale and determine potential changes in these properties caused by disposal and weathering by natural and simulated climatic conditions; assess the use of previously developed computer model(s) to describe the infiltration, unsaturated movement, redistribution, and drainage of water in disposed processed oil shale; evaluate the stability of field scale processed oil shale solid waste embankments using computer models

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.

ANN Model-Based Simulation of the Runoff Variation in Response to Climate Change on the Qinghai-Tibet Plateau, China

Directory of Open Access Journals (Sweden)

Chang Juan

2017-01-01

Full Text Available Precisely quantitative assessments of stream flow response to climatic change and permafrost thawing are highly challenging and urgent in cold regions. However, due to the notably harsh environmental conditions, there is little field monitoring data of runoff in permafrost regions, which has limited the development of physically based models in these regions. To identify the impacts of climate change in the runoff process in the Three-River Headwater Region (TRHR on the Qinghai-Tibet Plateau, two artificial neural network (ANN models, one with three input variables (previous runoff, air temperature, and precipitation and another with two input variables (air temperature and precipitation only, were developed to simulate and predict the runoff variation in the TRHR. The results show that the three-input variable ANN model has a superior real-time prediction capability and performs well in the simulation and forecasting of the runoff variation in the TRHR. Under the different scenarios conditions, the forecasting results of ANN model indicated that climate change has a great effect on the runoff processes in the TRHR. The results of this study are of practical significance for water resources management and the evaluation of the impacts of climatic change on the hydrological regime in long-term considerations.

Climate change and international tourism: A simulation study

NARCIS (Netherlands)

Hamilton, J.M.; Maddison, D.J.; Tol, R.S.J.

2005-01-01

The literature on tourism and climate change lacks an analysis of the global changes in tourism demand. Here, a simulation model of international tourism is presented that fills that gap. The current pattern of international tourist flows is modelled using 1995 data on departures and arrivals for

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

Accelerating Climate Simulations Through Hybrid Computing

Science.gov (United States)

Zhou, Shujia; Sinno, Scott; Cruz, Carlos; Purcell, Mark

2009-01-01

Unconventional multi-core processors (e.g., IBM Cell B/E and NYIDIDA GPU) have emerged as accelerators in climate simulation. However, climate models typically run on parallel computers with conventional processors (e.g., Intel and AMD) using MPI. Connecting accelerators to this architecture efficiently and easily becomes a critical issue. When using MPI for connection, we identified two challenges: (1) identical MPI implementation is required in both systems, and; (2) existing MPI code must be modified to accommodate the accelerators. In response, we have extended and deployed IBM Dynamic Application Virtualization (DAV) in a hybrid computing prototype system (one blade with two Intel quad-core processors, two IBM QS22 Cell blades, connected with Infiniband), allowing for seamlessly offloading compute-intensive functions to remote, heterogeneous accelerators in a scalable, load-balanced manner. Currently, a climate solar radiation model running with multiple MPI processes has been offloaded to multiple Cell blades with approx.10% network overhead.

Evaluating the Dominant Components of Warming in Pliocene Climate Simulations

Science.gov (United States)

Hill, D. J.; Haywood, A. M.; Lunt, D. J.; Hunter, S. J.; Bragg, F. J.; Contoux, C.; Stepanek, C.; Sohl, L.; Rosenbloom, N. A.; Chan, W.-L.;

Investigation of tropical diurnal convection biases in a climate model using TWP-ICE observations and convection-permitting simulations

Science.gov (United States)

Lin, W.; Xie, S.; Jackson, R. C.; Endo, S.; Vogelmann, A. M.; Collis, S. M.; Golaz, J. C.

2017-12-01

Climate models are known to have difficulty in simulating tropical diurnal convections that exhibit distinct characteristics over land and open ocean. While the causes are rooted in deficiencies in convective parameterization in general, lack of representations of mesoscale dynamics in terms of land-sea breeze, convective organization, and propagation of convection-induced gravity waves also play critical roles. In this study, the problem is investigated at the process-level with the U.S. Department of Energy Accelerated Climate Modeling for Energy (ACME) model in short-term hindcast mode using the Cloud Associated Parameterization Testbed (CAPT) framework. Convective-scale radar retrievals and observation-driven convection-permitting simulations for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) cases are used to guide the analysis of the underlying processes. The emphasis will be on linking deficiencies in representation of detailed process elements to the model biases in diurnal convective properties and their contrast among inland, coastal and open ocean conditions.

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

Evaluating adaptation options for urban flooding based on new high-end emission scenario regional climate model simulations

DEFF Research Database (Denmark)

Arnbjerg-Nielsen, Karsten; Leonardsen, L.; Madsen, Henrik

2015-01-01

Climate change adaptation studies on urban flooding are often based on a model chain approach from climate forcing scenarios to analysis of adaptation measures. Previous analyses of climate change impacts in Copenhagen, Denmark, were supplemented by 2 high-end scenario simulations. These include...... a regional climate model projection forced to a global temperature increase of 6 degrees C in 2100 as well as a projection based on a high radiative forcing scenario (RCP8.5). With these scenarios, projected impacts of extreme precipitation increase significantly. For extreme sea surges, the impacts do...... by almost 4 and 8 times the current EAD for the RCP8.5 and 6 degrees C scenario, respectively. For both hazards, business-as-usual is not a possible scenario, since even in the absence of policy-driven changes, significant autonomous adaptation is likely to occur. Copenhagen has developed an adaptation plan...

WASCAL - West African Science Service Center on Climate Change and Adapted Land Use Regional Climate Simulations and Land-Atmosphere Simulations for West Africa at DKRZ and elsewhere

Science.gov (United States)

Hamann, Ilse; Arnault, Joel; Bliefernicht, Jan; Klein, Cornelia; Heinzeller, Dominikus; Kunstmann, Harald

2014-05-01

Changing climate and hydro-meteorological boundary conditions are among the most severe challenges to Africa in the 21st century. In particular West Africa faces an urgent need to develop effective adaptation and mitigation strategies to cope with negative impacts on humans and environment due to climate change, increased hydro-meteorological variability and land use changes. To help meet these challenges, the German Federal Ministry of Education and Research (BMBF) started an initiative with institutions in Germany and West African countries to establish together a West African Science Service Center on Climate Change and Adapted Land Use (WASCAL). This activity is accompanied by an establishment of trans-boundary observation networks, an interdisciplinary core research program and graduate research programs on climate change and related issues for strengthening the analytical capabilities of the Science Service Center. A key research activity of the WASCAL Competence Center is the provision of regional climate simulations in a fine spatio-temporal resolution for the core research sites of WASCAL for the present and the near future. The climate information is needed for subsequent local climate impact studies in agriculture, water resources and further socio-economic sectors. The simulation experiments are performed using regional climate models such as COSMO-CLM, RegCM and WRF and statistical techniques for a further refinement of the projections. The core research sites of WASCAL are located in the Sudanian Savannah belt in Northern Ghana, Southern Burkina Faso and Northern Benin. The climate in this region is semi-arid with six rainy months. Due to the strong population growth in West Africa, many areas of the Sudanian Savannah have been already converted to farmland since the majority of the people are living directly or indirectly from the income produced in agriculture. The simulation experiments of the Competence Center and the Core Research Program are

GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics

Science.gov (United States)

Dunne, John P.; John, Jasmin G.; Adcroft, Alistair J.; Griffies, Stephen M.; Hallberg, Robert W.; Shevalikova, Elena; Stouffer, Ronald J.; Cooke, William; Dunne, Krista A.; Harrison, Matthew J.; Krasting, John P.; Malyshev, Sergey L.; Milly, P.C.D.; Phillipps, Peter J.; Sentman, Lori A.; Samuels, Bonita L.; Spelman, Michael J.; Winton, Michael; Wittenberg, Andrew T.; Zadeh, Niki

2012-01-01

We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

21st Century Carbon-Climate Change as Simulated by the Canadian Earth System Model CanESM1

Science.gov (United States)

Curry, C.; Christian, J. R.; Arora, V.; Boer, G. J.; Denman, K. L.; Flato, G. M.; Scinocca, J. F.; Merryfield, W. J.; Lee, W. G.; Yang, D.

2009-12-01

The Canadian Earth System Model CanESM1 is a fully coupled climate/carbon-cycle model with prognostic ocean and terrestrial components. The model has been used to simulate the 1850-2000 climate using historical greenhouse gas emissions, and future climates using IPCC emission scenarios. Modelled globally averaged CO2 concentration, land and ocean carbon uptake compare well with observation-based values at year 2000, as do the annual cycle and latitudinal distribution of CO2, instilling confidence that the model is suitable for future projections of carbon cycle behaviour in a changing climate. Land use change emissions are calculated explicitly using an observation-based time series of fractional coverage of different plant functional types. A more complete description of the model may be found in Arora et al. (2009). Differences in the land-atmosphere CO2 flux from the present to the future period under the SRES A2 emissions scenario show an increase in land sinks by a factor of 7.5 globally, mostly the result of CO2 fertilization. By contrast, the magnitude of the global ocean CO2 sink increases by a factor of only 2.3 by 2100. Expressed as a fraction of total emissions, ocean carbon uptake decreases throughout the 2000-2100 period, while land carbon uptake increases until around 2050, then declines. The result is an increase in airborne CO2 fraction after the mid-21st century, reaching a value of 0.55 by 2100. The simulated decline in ocean carbon uptake over the 21st century occurs despite steadily rising atmospheric CO2. This behaviour is usually attributed to climate-induced changes in surface temperature and salinity that reduce CO2 solubility, and increasing ocean stratification that weakens the biological pump. However, ocean biological processes such as dinitrogen fixation and calcification may also play an important role. Although not well understood at present, improved parameterizations of these processes will increase confidence in projections of

Simulated effects of climate change on the Death Valley regional ground-water flow system, Nevada and California

International Nuclear Information System (INIS)

D'Agnese, F.A.; O'Brien, G.M.; Faunt, C.C.; San Juan, C.A.

1999-01-01

The US Geological Survey, in cooperation with the US Department of Energy, is evaluating the geologic and hydrologic characteristics of the Death Valley regional flow system as part of the Yucca Mountain Project. As part of the hydrologic investigation, regional, three-dimensional conceptual and numerical ground-water-flow models have been developed to assess the potential effects of past and future climates on the regional flow system. A simulation that is based on climatic conditions 21,000 years ago was evaluated by comparing the simulated results to observation of paleodischarge sites. Following acceptable simulation of a past climate, a possible future ground-water-flow system, with climatic conditions that represent a doubling of atmospheric carbon dioxide, was simulated. The steady-state simulations were based on the present-day, steady-state, regional ground-water-flow model. The finite-difference model consisted of 163 rows, 153 columns, and 3 layers and was simulated using MODFLOWP. Climate changes were implemented in the regional ground-water-flow model by changing the distribution of ground-water recharge. Global-scale, average-annual, simulated precipitation for both past- and future-climate conditions developed elsewhere were resampled to the model-grid resolution. A polynomial function that represents the Maxey-Eakin method for estimating recharge from precipitation was used to develop recharge distributions for simulation

Air traffic simulation in chemistry-climate model EMAC 2.41: AirTraf 1.0

Science.gov (United States)

Yamashita, Hiroshi; Grewe, Volker; Jöckel, Patrick; Linke, Florian; Schaefer, Martin; Sasaki, Daisuke

2016-09-01

Mobility is becoming more and more important to society and hence air transportation is expected to grow further over the next decades. Reducing anthropogenic climate impact from aviation emissions and building a climate-friendly air transportation system are required for a sustainable development of commercial aviation. A climate optimized routing, which avoids climate-sensitive regions by re-routing horizontally and vertically, is an important measure for climate impact reduction. The idea includes a number of different routing strategies (routing options) and shows a great potential for the reduction. To evaluate this, the impact of not only CO2 but also non-CO2 emissions must be considered. CO2 is a long-lived gas, while non-CO2 emissions are short-lived and are inhomogeneously distributed. This study introduces AirTraf (version 1.0) that performs global air traffic simulations, including effects of local weather conditions on the emissions. AirTraf was developed as a new submodel of the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model. Air traffic information comprises Eurocontrol's Base of Aircraft Data (BADA Revision 3.9) and International Civil Aviation Organization (ICAO) engine performance data. Fuel use and emissions are calculated by the total energy model based on the BADA methodology and Deutsches Zentrum für Luft- und Raumfahrt (DLR) fuel flow method. The flight trajectory optimization is performed by a genetic algorithm (GA) with respect to a selected routing option. In the model development phase, benchmark tests were performed for the great circle and flight time routing options. The first test showed that the great circle calculations were accurate to -0.004 %, compared to those calculated by the Movable Type script. The second test showed that the optimal solution found by the algorithm sufficiently converged to the theoretical true-optimal solution. The difference in flight time between the two solutions is less than 0.01 %. The dependence of

Some GCM simulation results on present and possible future climate in northern Europe

Energy Technology Data Exchange (ETDEWEB)

Raeisaenen, J [Helsinki Univ. (Finland). Dept. of Meteorology

1996-12-31

The Intergovernmental Panel on Climate Change initiated in 1993 a project entitled `Evaluation of Regional Climate Simulations`. The two basic aims of this project were to assess the skill of current general circulation models (GCMs) in simulating present climate at a regional level and to intercompare the regional response of various GCMs to increased greenhouse gas concentrations. The public data base established for the comparison included simulation results from several modelling centres, but most of the data were available in the form of time-averaged seasonal means only, and important quantities like precipitation were totally lacking in many cases. This presentation summarizes the intercomparison results for surface air temperature and sea level pressure in northern Europe. The quality of the control simulations and the response of the models to increased CO{sub 2} are addressed in both winter (December-February) and summer (June-August)

Some GCM simulation results on present and possible future climate in northern Europe

Energy Technology Data Exchange (ETDEWEB)

Raeisaenen, J. [Helsinki Univ. (Finland). Dept. of Meteorology

1995-12-31

The Intergovernmental Panel on Climate Change initiated in 1993 a project entitled `Evaluation of Regional Climate Simulations`. The two basic aims of this project were to assess the skill of current general circulation models (GCMs) in simulating present climate at a regional level and to intercompare the regional response of various GCMs to increased greenhouse gas concentrations. The public data base established for the comparison included simulation results from several modelling centres, but most of the data were available in the form of time-averaged seasonal means only, and important quantities like precipitation were totally lacking in many cases. This presentation summarizes the intercomparison results for surface air temperature and sea level pressure in northern Europe. The quality of the control simulations and the response of the models to increased CO{sub 2} are addressed in both winter (December-February) and summer (June-August)

Trend of surface solar radiation over Asia simulated by aerosol transport-climate model

Science.gov (United States)

Takemura, T.; Ohmura, A.

2009-12-01

Long-term records of surface radiation measurements indicate a decrease in the solar radiation between the 1950s and 1980s (“global dimming”), then its recovery afterward (“global brightening”) at many locations all over the globe [Wild, 2009]. On the other hand, the global brightening is delayed over the Asian region [Ohmura, 2009]. It is suggested that these trends of the global dimming and brightening are strongly related with a change in aerosol loading in the atmosphere which affect the climate change through the direct, semi-direct, and indirect effects. In this study, causes of the trend of the surface solar radiation over Asia during last several decades are analyzed with an aerosol transport-climate model, SPRINTARS. SPRINTARS is coupled with MIROC which is a general circulation model (GCM) developed by Center for Climate System Research (CCSR)/University of Tokyo, National Institute for Environmental Studies (NIES), and Frontier Research Center for Global Change (FRCGC) [Takemura et al., 2000, 2002, 2005, 2009]. The horizontal and vertical resolutions are T106 (approximately 1.1° by 1.1°) and 56 layers, respectively. SPRINTARS includes the transport, radiation, cloud, and precipitation processes of all main tropospheric aerosols (black and organic carbons, sulfate, soil dust, and sea salt). The model treats not only the aerosol mass mixing ratios but also the cloud droplet and ice crystal number concentrations as prognostic variables, and the nucleation processes of cloud droplets and ice crystals depend on the number concentrations of each aerosol species. Changes in the cloud droplet and ice crystal number concentrations affect the cloud radiation and precipitation processes in the model. Historical emissions, that is consumption of fossil fuel and biofuel, biomass burning, aircraft emissions, and volcanic eruptions are prescribed from database provided by the Aerosol Model Intercomparison Project (AeroCom) and the latest IPCC inventories

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.

Impacts of land use/cover classification accuracy on regional climate simulations

Science.gov (United States)

Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.

2007-03-01

Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

Role of aerosols on the Indian Summer Monsoon variability, as simulated by state-of-the-art global climate models

Science.gov (United States)

Cagnazzo, Chiara; Biondi, Riccardo; D'Errico, Miriam; Cherchi, Annalisa; Fierli, Federico; Lau, William K. M.

2016-04-01

Recent observational and modeling analyses have explored the interaction between aerosols and the Indian summer monsoon precipitation on seasonal-to-interannual time scales. By using global scale climate model simulations, we show that when increased aerosol loading is found on the Himalayas slopes in the premonsoon period (April-May), intensification of early monsoon rainfall over India and increased low-level westerly flow follow, in agreement with the elevated-heat-pump (EHP) mechanism. The increase in rainfall during the early monsoon season has a cooling effect on the land surface that may also be amplified through solar dimming (SD) by more cloudiness and aerosol loading with subsequent reduction in monsoon rainfall over India. We extend this analyses to a subset of CMIP5 climate model simulations. Our results suggest that 1) absorbing aerosols, by influencing the seasonal variability of the Indian summer monsoon with the discussed time-lag, may act as a source of predictability for the Indian Summer Monsoon and 2) if the EHP and SD effects are operating also in a number of state-of-the-art climate models, their inclusion could potentially improve seasonal forecasts.

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.

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.

Evaluation of regional climate simulations over the Great Lakes region driven by three global data sets

Science.gov (United States)

Shiyuan Zhong; Xiuping Li; Xindi Bian; Warren E. Heilman; L. Ruby Leung; William I. Jr. Gustafson

2012-01-01

The performance of regional climate simulations is evaluated for the Great Lakes region. Three 10-year (1990-1999) current-climate simulations are performed using the MM5 regional climate model (RCM) with 36-km horizontal resolution. The simulations employed identical configuration and physical parameterizations, but different lateral boundary conditions and sea-...

Evaluation of high-resolution climate simulations for West Africa using COSMO-CLM

Science.gov (United States)

Dieng, Diarra; Smiatek, Gerhard; Bliefernicht, Jan; Laux, Patrick; Heinzeller, Dominikus; Kunstmann, Harald; Sarr, Abdoulaye; Thierno Gaye, Amadou

2017-04-01

The climate change modeling activities within the WASCAL program (West African Science Service Center on Climate Change and Adapted Land Use) concentrate on the provisioning of future climate change scenario data at high spatial and temporal resolution and quality in West Africa. Such information is highly required for impact studies in water resources and agriculture for the development of reliable climate change adaptation and mitigation strategies. In this study, we present a detailed evaluation of high simulation runs based on the regional climate model, COSMO model in CLimate Mode (COSMO-CLM). The model is applied over West Africa in a nested approach with two simulation domains at 0.44° and 0.11° resolution using reanalysis data from ERA-Interim (1979-2013). The models runs are compared to several state-of-the-art observational references (e.g., CRU, CHIRPS) including daily precipitation data provided by national meteorological services in West Africa. Special attention is paid to the reproduction of the dynamics of the West African Monsoon (WMA), its associated precipitation patterns and crucial agro-climatological indices such as the onset of the rainy season. In addition, first outcomes of the regional climate change simulations driven by MPI-ESM-LR are presented for a historical period (1980 to 2010) and two future periods (2020 to 2050, 2070 to 2100). The evaluation of the reanalysis runs shows that COSMO-CLM is able to reproduce the observed major climate characteristics including the West African Monsoon within the range of comparable RCM evaluations studies. However, substantial uncertainties remain, especially in the Sahel zone. The added value of the higher resolution of the nested run is reflected in a smaller bias in extreme precipitation statistics with respect to the reference data.

Effects of snow grain non-sphericity on climate simulations: Sensitivity tests with the NorESM model

Science.gov (United States)

Räisänen, Petri; Makkonen, Risto; Kirkevåg, Alf

2017-04-01

Snow grains are non-spherical and generally irregular in shape. Still, in radiative transfer calculations, they are often treated as spheres. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR) model and in the Los Alamos sea ice model, version 4 (CICE4), both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM). In this work, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH) is compared with another (NONSPH) in which the snow shortwave single-scattering properties are based on a combination of non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (≈ 0.78 in the visible region) than in the spherical case (≈ 0.89). Therefore, for a given snow grain size, the use of non-spherical snow grains yields a higher snow broadband albedo, typically by ≈0.03. Consequently, considering the spherical case as the baseline, the use of non-spherical snow grains results in a negative radiative forcing (RF), with a global-mean top-of-the-model value of ≈ -0.22 W m-2. Although this global-mean RF is modest, it has a rather substantial impact on the climate simulated by NoRESM. In particular, the global annual-mean 2-m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further found that the difference between NONSPH and SPH could be largely "tuned away" by adjusting the snow grain size in the NONSPH experiment by ≈ 70%. The impact of snow grain shape on the radiative effect (RE) of absorbing aerosols in snow (black carbon and mineral dust) is also discussed. For an

A Decade-Long European-Scale Convection-Resolving Climate Simulation on GPUs

Science.gov (United States)

Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.

2016-12-01

Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer designs that involve conventional multi-core CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation over Europe using the GPU-enabled COSMO version on a computational domain with 1536x1536x60 gridpoints. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss some of the advantages and prospects from using GPUs, and focus on the performance of the convection-resolving modeling approach on the European scale. Specifically we investigate the organization of convective clouds and on validate hourly rainfall distributions with various high-resolution data sets.

Effects of elevated CO2 and drought on wheat : testing crop simulation models for different experimental and climatic conditions

NARCIS (Netherlands)

Ewert, F.; Rodriguez, D.; Jamieson, P.; Semenov, M.A.; Mitchell, R.A.C.; Goudriaan, J.; Porter, J.R.; Kimball, B.A.; Pinter, P.J.; Manderscheid, R.; Weigel, H.J.; Fangmeier, A.; Fereres, E.; Villalobos, F.

2002-01-01

Effects of increasing carbon dioxide concentration [CO2] on wheat vary depending on water supply and climatic conditions, which are difficult to estimate. Crop simulation models are often used to predict the impact of global atmospheric changes on food production. However, models have rarely been

CMIP5 model simulations of Ethiopian Kiremt-season precipitation: current climate and future changes

Science.gov (United States)

Li, Laifang; Li, Wenhong; Ballard, Tristan; Sun, Ge; Jeuland, Marc

2016-05-01

Kiremt-season (June-September) precipitation provides a significant water supply for Ethiopia, particularly in the central and northern regions. The response of Kiremt-season precipitation to climate change is thus of great concern to water resource managers. However, the complex processes that control Kiremt-season precipitation challenge the capability of general circulation models (GCMs) to accurately simulate precipitation amount and variability. This in turn raises questions about their utility for predicting future changes. This study assesses the impact of climate change on Kiremt-season precipitation using state-of-the-art GCMs participating in the Coupled Model Intercomparison Project Phase 5. Compared to models with a coarse resolution, high-resolution models (horizontal resolution <2°) can more accurately simulate precipitation, most likely due to their ability to capture precipitation induced by topography. Under the Representative Concentration Pathway (RCP) 4.5 scenario, these high-resolution models project an increase in precipitation over central Highlands and northern Great Rift Valley in Ethiopia, but a decrease in precipitation over the southern part of the country. Such a dipole pattern is attributable to the intensification of the North Atlantic subtropical high (NASH) in a warmer climate, which influences Ethiopian Kiremt-season precipitation mainly by modulating atmospheric vertical motion. Diagnosis of the omega equation demonstrates that an intensified NASH increases (decreases) the advection of warm air and positive vorticity into the central Highlands and northern Great Rift Valley (southern part of the country), enhancing upward motion over the northern Rift Valley but decreasing elsewhere. Under the RCP 4.5 scenario, the high-resolution models project an intensification of the NASH by 15 (3 × 105 m2 s-2) geopotential meters (stream function) at the 850-hPa level, contributing to the projected precipitation change over Ethiopia. The

3D visualization of ultra-fine ICON climate simulation data

Science.gov (United States)

Röber, Niklas; Spickermann, Dela; Böttinger, Michael

2016-04-01

Advances in high performance computing and model development allow the simulation of finer and more detailed climate experiments. The new ICON model is based on an unstructured triangular grid and can be used for a wide range of applications, ranging from global coupled climate simulations down to very detailed and high resolution regional experiments. It consists of an atmospheric and an oceanic component and scales very well for high numbers of cores. This allows us to conduct very detailed climate experiments with ultra-fine resolutions. ICON is jointly developed in partnership with DKRZ by the Max Planck Institute for Meteorology and the German Weather Service. This presentation discusses our current workflow for analyzing and visualizing this high resolution data. The ICON model has been used for eddy resolving (developed specific plugins for the free available visualization software ParaView and Vapor, which allows us to read and handle that much data. Within ParaView, we can additionally compare prognostic variables with performance data side by side to investigate the performance and scalability of the model. With the simulation running in parallel on several hundred nodes, an equal load balance is imperative. In our presentation we show visualizations of high-resolution ICON oceanographic and HDCP2 atmospheric simulations that were created using ParaView and Vapor. Furthermore we discuss our current efforts to improve our visualization capabilities, thereby exploring the potential of regular in-situ visualization, as well as of in-situ compression / post visualization.

Hydrological processes in regional climate model simulations of the central United States flood of June-July 1993

DEFF Research Database (Denmark)

Anderson, Christopher J.; Arritt, Raymond W.; Takle, Eugene S.

2003-01-01

Thirteen regional climate model (RCM) simulations of June-July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° X 10° subregion of the upper Mississippi River basin, containing the region of maximum...

Understanding the tropical warm temperature bias simulated by climate models

Science.gov (United States)

Brient, Florent; Schneider, Tapio

2017-04-01

The state-of-the-art coupled general circulation models have difficulties in representing the observed spatial pattern of surface tempertaure. A majority of them suffers a warm bias in the tropical subsiding regions located over the eastern parts of oceans. These regions are usually covered by low-level clouds scattered from stratus along the coasts to more vertically developed shallow cumulus farther from them. Models usually fail to represent accurately this transition. Here we investigate physical drivers of this warm bias in CMIP5 models through a near-surface energy budget perspective. We show that overestimated solar insolation due to a lack of stratocumulus mostly explains the warm bias. This bias also arises partly from inter-model differences in surface fluxes that could be traced to differences in near-surface relative humidity and air-sea temperature gradient. We investigate the role of the atmosphere in driving surface biases by comparing historical and atmopsheric (AMIP) experiments. We show that some differences in boundary-layer characteristics, mostly those related to cloud fraction and relative humidity, are already present in AMIP experiments and may be the drivers of coupled biases. This gives insights in how models can be improved for better simulations of the tropical climate.

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

A new framework for the analysis of continental-scale convection-resolving climate simulations

Science.gov (United States)

Leutwyler, D.; Charpilloz, C.; Arteaga, A.; Ban, N.; Di Girolamo, S.; Fuhrer, O.; Hoefler, T.; Schulthess, T. C.; Christoph, S.

2017-12-01

High-resolution climate simulations at horizontal resolution of O(1-4 km) allow explicit treatment of deep convection (thunderstorms and rain showers). Explicitly treating convection by the governing equations reduces uncertainties associated with parametrization schemes and allows a model formulation closer to physical first principles [1,2]. But kilometer-scale climate simulations with long integration periods and large computational domains are expensive and data storage becomes unbearably voluminous. Hence new approaches to perform analysis are required. In the crCLIM project we propose a new climate modeling framework that allows scientists to conduct analysis at high spatial and temporal resolution. We tackle the computational cost by using the largest available supercomputers such as hybrid CPU-GPU architectures. For this the COSMO model has been adapted to run on such architectures [2]. We then alleviate the I/O-bottleneck by employing a simulation data-virtualizer (SDaVi) that allows to trade-off storage (space) for computational effort (time). This is achieved by caching the simulation outputs and efficiently launching re-simulations in case of cache misses. All this is done transparently from the analysis applications [3]. For the re-runs this approach requires a bit-reproducible version of COSMO. That is to say a model that produces identical results on different architectures to ensure coherent recomputation of the requested data [4]. In this contribution we present a version of SDaVi, a first performance model, and a strategy to obtain bit-reproducibility across hardware architectures.[1] N. Ban, J. Schmidli, C. Schär. Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos., 7889-7907, 2014.[2] D. Leutwyler, O. Fuhrer, X. Lapillonne, D. Lüthi, C. Schär. Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19. Geosci. Model Dev, 3393

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.

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)

Transient simulations of historical climate change including interactive carbon emissions from land-use change.

Science.gov (United States)

Matveev, A.; Matthews, H. D.

2009-04-01

Carbon fluxes from land conversion are among the most uncertain variables in our understanding of the contemporary carbon cycle, which limits our ability to estimate both the total human contribution to current climate forcing and the net effect of terrestrial biosphere changes on atmospheric CO2 increases. The current generation of coupled climate-carbon models have made significant progress in simulating the coupled climate and carbon cycle response to anthropogenic CO2 emissions, but do not typically include land-use change as a dynamic component of the simulation. In this work we have incorporated a book-keeping land-use carbon accounting model into the University of Victoria Earth System Climate Model (UVic ESCM), and intermediate-complexity coupled climate-carbon model. The terrestrial component of the UVic ESCM allows an aerial competition of five plant functional types (PFTs) in response to climatic conditions and area availability, and tracks the associated changes in affected carbon pools. In order to model CO2 emissions from land conversion in the terrestrial component of the model, we calculate the allocation of carbon to short and long-lived wood products following specified land-cover change, and use varying decay timescales to estimate CO2 emissions. We use recently available spatial datasets of both crop and pasture distributions to drive a series of transient simulations and estimate the net contribution of human land-use change to historical carbon emissions and climate change.

The millennium water vapour drop in chemistry–climate model simulations

Directory of Open Access Journals (Sweden)

S. Brinkop

2016-07-01

Full Text Available This study investigates the abrupt and severe water vapour decline in the stratosphere beginning in the year 2000 (the "millennium water vapour drop" and other similarly strong stratospheric water vapour reductions by means of various simulations with the state-of-the-art Chemistry-Climate Model (CCM EMAC (ECHAM/MESSy Atmospheric Chemistry Model. The model simulations differ with respect to the prescribed sea surface temperatures (SSTs and whether nudging is applied or not. The CCM EMAC is able to most closely reproduce the signature and pattern of the water vapour drop in agreement with those derived from satellite observations if the model is nudged. Model results confirm that this extraordinary water vapour decline is particularly obvious in the tropical lower stratosphere and is related to a large decrease in cold point temperature. The drop signal propagates under dilution to the higher stratosphere and to the poles via the Brewer–Dobson circulation (BDC. We found that the driving forces for this significant decline in water vapour mixing ratios are tropical sea surface temperature (SST changes due to a coincidence with a preceding strong El Niño–Southern Oscillation event (1997/1998 followed by a strong La Niña event (1999/2000 and supported by the change of the westerly to the easterly phase of the equatorial stratospheric quasi-biennial oscillation (QBO in 2000. Correct (observed SSTs are important for triggering the strong decline in water vapour. There are indications that, at least partly, SSTs contribute to the long period of low water vapour values from 2001 to 2006. For this period, the specific dynamical state of the atmosphere (overall atmospheric large-scale wind and temperature distribution is important as well, as it causes the observed persistent low cold point temperatures. These are induced by a period of increased upwelling, which, however, has no corresponding pronounced signature in SSTs anomalies in the tropics

An improved ENSO simulation by representing chlorophyll-induced climate feedback in the NCAR Community Earth System Model.

Science.gov (United States)

Kang, Xianbiao; Zhang, Rong-Hua; Gao, Chuan; Zhu, Jieshun

2017-12-07

The El Niño-Southern oscillation (ENSO) simulated in the Community Earth System Model of the National Center for Atmospheric Research (NCAR CESM) is much stronger than in reality. Here, satellite data are used to derive a statistical relationship between interannual variations in oceanic chlorophyll (CHL) and sea surface temperature (SST), which is then incorporated into the CESM to represent oceanic chlorophyll -induced climate feedback in the tropical Pacific. Numerical runs with and without the feedback (referred to as feedback and non-feedback runs) are performed and compared with each other. The ENSO amplitude simulated in the feedback run is more accurate than that in the non-feedback run; quantitatively, the Niño3 SST index is reduced by 35% when the feedback is included. The underlying processes are analyzed and the results show that interannual CHL anomalies exert a systematic modulating effect on the solar radiation penetrating into the subsurface layers, which induces differential heating in the upper ocean that affects vertical mixing and thus SST. The statistical modeling approach proposed in this work offers an effective and economical way for improving climate simulations.

The impact of land-cover modification on the June meteorology of China since 1700, simulated using a regional climate model

NARCIS (Netherlands)

Wang, H.; Pitman, A.J.; Zhao, M.; Leemans, R.

2003-01-01

A series of simulations was conducted using a regional climate model with a domain covering mainland China. Simulations were conducted for a single June using estimated land cover for 1700, 1750, 1800, 1850, 1900, 1950, 1970 and 1990. The conversion of land cover between these periods was extensive

Modeling and simulation of the energy use in an occupied residential building in cold climate

International Nuclear Information System (INIS)

Olofsson, Thomas; Mahlia, T.M.I.

2012-01-01

Highlights: ► An overview of the energy-characteristics based on illustrations in graphical figures. ► Figures to support identification and validation energy refurbishment measures. ► Emphasizing energy efficiency measures in early stage of building design. -- Abstract: In order to reduce the energy use in the building sector there is a demand for tools that can identify significant building energy performance parameters. In the work introduced in this paper presents a methodology, based on a simulation module and graphical figures, for interactive investigations of the building energy performance. The building energy use simulation program is called TEKLA and is using EN832 with an improved procedure in calculating the heat loss through the floor and the solar heat gain. The graphical figures are simple and are illustrating the savings based on retrofit measures and climate conditions. The accuracy of the TEKLA simulation was investigated on a typical single-family building in Sweden for a period of time in a space heating demand of relatively cold and mild climate. The model was found applicable for relative investigations. Further, the methodology was applied on a typical single family reference building. The climate data from three locations in Sweden were collected and a set of relevant measures were studied. The investigated examples illustrate how decisions in the early stages of the building design process can have decisive importance on the final building energy performance.

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.

The last interglacial (Eemian climate simulated by LOVECLIM and CCSM3

Directory of Open Access Journals (Sweden)

I. Nikolova

2013-08-01

Full Text Available This paper presents a detailed analysis of the climate of the last interglacial simulated by two climate models of different complexities, CCSM3 (Community Climate System Model 3 and LOVECLIM (LOch-Vecode-Ecbilt-CLio-agIsm Model. The simulated surface temperature, hydrological cycle, vegetation and ENSO variability during the last interglacial are analyzed through the comparison with the simulated pre-industrial (PI climate. In both models, the last interglacial period is characterized by a significant warming (cooling over almost all the continents during boreal summer (winter leading to a largely increased (reduced seasonal contrast in the Northern (Southern Hemisphere. This is mainly due to the much higher (lower insolation received by the whole Earth in boreal summer (winter during this interglacial. The Arctic is warmer than PI through the whole year, resulting from its much higher summer insolation, its remnant effect in the following fall-winter through the interactions between atmosphere, ocean and sea ice and feedbacks from sea ice and snow cover. Discrepancies exist in the sea-ice formation zones between the two models. Cooling is simulated by CCSM3 in the Greenland and Norwegian seas and near the shelves of Antarctica during DJF but not in LOVECLIM as a result of excessive sea-ice formation. Intensified African monsoon is responsible for the cooling during summer in northern Africa and on the Arabian Peninsula. Over India, the precipitation maximum is found further west, while in Africa the precipitation maximum migrates further north. Trees and grassland expand north in Sahel/Sahara, more clearly seen in LOVECLIM than in CCSM3 results. A mix of forest and grassland occupies continents and expands deep into the high northern latitudes. Desert areas reduce significantly in the Northern Hemisphere, but increase in northern Australia. The interannual SST variability of the tropical Pacific (El-Niño Southern Oscillation of the last

Evaluation of regional climate model simulations versus gridded observed and regional reanalysis products using a combined weighting scheme

Energy Technology Data Exchange (ETDEWEB)

Eum, Hyung-Il; Laprise, Rene [University of Quebec at Montreal, ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada); Gachon, Philippe [University of Quebec at Montreal, ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada); Environment Canada, Adaptation and Impacts Research Section, Climate Research Division, Montreal, QC (Canada); Ouarda, Taha [University of Quebec, INRS-ETE (Institut National de la Recherche Scientifique, Centre Eau-Terre-Environnement), Quebec, QC (Canada)

2012-04-15

This study presents a combined weighting scheme which contains five attributes that reflect accuracy of climate data, i.e. short-term (daily), mid-term (annual), and long-term (decadal) timescales, as well as spatial pattern, and extreme values, as simulated from Regional Climate Models (RCMs) with respect to observed and regional reanalysis products. Southern areas of Quebec and Ontario provinces in Canada are used for the study area. Three series of simulation from two different versions of the Canadian RCM (CRCM4.1.1, and CRCM4.2.3) are employed over 23 years from 1979 to 2001, driven by both NCEP and ERA40 global reanalysis products. One series of regional reanalysis dataset (i.e. NARR) over North America is also used as reference for comparison and validation purpose, as well as gridded historical observed daily data of precipitation and temperatures, both series have been beforehand interpolated on the CRCM 45-km grid resolution. Monthly weighting factors are calculated and then combined into four seasons to reflect seasonal variability of climate data accuracy. In addition, this study generates weight averaged references (WARs) with different weighting factors and ensemble size as new reference climate data set. The simulation results indicate that the NARR is in general superior to the CRCM simulated precipitation values, but the CRCM4.1.1 provides the highest weighting factors during the winter season. For minimum and maximum temperature, both the CRCM4.1.1 and the NARR products provide the highest weighting factors, respectively. The NARR provides more accurate short- and mid-term climate data, but the two versions of the CRCM provide more precise long-term data, spatial pattern and extreme events. Or study confirms also that the global reanalysis data (i.e. NCEP vs. ERA40) used as boundary conditions in the CRCM runs has non-negligible effects on the accuracy of CRCM simulated precipitation and temperature values. In addition, this study demonstrates

Impact of Future Climate Change on Wheat Production: A Simulated Case for China’s Wheat System

OpenAIRE

Dengpan Xiao; Huizi Bai; De Li Liu

2018-01-01

With regard to global climate change due to increasing concentration in greenhouse gases, particularly carbon dioxide (CO2), it is important to examine its potential impact on crop development and production. We used statistically-downscaled climate data from 28 Global Climate Models (GCMs) and the Agricultural Production Systems sIMulator (APSIM)–Wheat model to simulate the impact of future climate change on wheat production. Two future scenarios (RCP4.5 and RCP8.5) were used for atmos...

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

Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

Science.gov (United States)

Quetin, G. R.; Swann, A. L. S.

2017-12-01

Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to

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)

Results from a 2 x CO2 simulation with the Canadian Climate Centre general circulation model

International Nuclear Information System (INIS)

Boer, G.J.

1990-01-01

The Canadian Climate Centre's general circulation model (GCM), GCMII, was used to simulate a doubling of atmospheric carbon dioxide concentration. The experiment was a standard greenhouse gas climate change study, using a three-dimensional atmospheric circulation model coupled to a simple 'slab' ocean and a thermodynamic ice model. This standard experiment retains the sophistication and generality of an atmospheric GCM, is straightforward in its use of simplified ocean and ice models, is comparatively economical of computer time, and permits comparison of results from different models. Features of the second generation GCMII include: higher resolution at T32L10 with a transform grid of 3.75 x 3.75 degree; full diurnal and annual cycles; ocean and sea ice treatment involving specification of ocean transports; modified treatment of land surface processes and hydrology; a parameterization of cloud optical feedback; and a retention of the special application data sets of surface parameters for North America and Europe. Results of the simulation were a globally averaged surface temperature increase of 3.5 degree C; a precipitation and evaporation increase of 3%; an average decrease in soil moisture of 6.6%; a decrease in cloud cover of 2.2%; a 66% decrease in mass of sea ice; and marked changes in other quantities in the polar region. 2 refs., 2 figs., 2 tabs

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.

Vineyard acreage simulations in consideration of climatic changes affecting Rhineland-Palatinate (RLP

Directory of Open Access Journals (Sweden)

Dressler Marc

2015-01-01

Full Text Available An interdisciplinary research project has determined the predictable potential areas suitable for vineyard use in Rhine- land-Palatinate by means of the application of the latest available data and in consideration of climatic changes. The objective was to identify the maximum acreage potential with suitability for viniculture in Rhineland-Palatinate as a theoretical high-case scenario for liberalisation. For this purpose an acreage simulation model was developed and validated to capture and consolidate climate data, simulation runs of regional climate models, geodata, the automated land property map and actual measuring data on frost damage. Full account was taken of anthropogenic, climatic and pedological selection criteria. Finally a GIS-based data blending with the suitable areas yielded the potential acreage for viniculture in Rhineland-Palatinate. The model estimates an additional acreage potential with suitability for viniculture of 335,000 acres (135,000 ha in Rhineland-Palatinate. The analyses further underline the potential for state-of-the art risk management and data based managerial decision making to counter climate induced challenges.

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.

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.

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.

Impact of Amazon deforestation on climate simulations using the NCAR CCM2/BATS model

Energy Technology Data Exchange (ETDEWEB)

Hahmann, A.N.; Dickinson, R.E. [Univ. of Arizona, Tucson, AZ (United States)

1996-12-31

Model validation and results are briefly presented for a simulation of deforestation of the Amazon rainforest. This initial study is made using assumptions regarding deforestation similar to those in earlier studies with several versions of the NCAR Community Climate Model (CCM) couples to the Biosphere-Atmosphere Transfer Scheme (BATS). The model used is a revised version of the NCAR CCM Version 2 coupled to BATS Version 1e. This paper discusses the portion of validation dealing with the distribution of precipitation; the simulation displays very good agreement with observed rainfall rates for the austral summer. Preliminary results from an 8-year simulation of deforestation are similar to that of previous studies. Annual precipitation and evaporation are reduced, while surface air temperatures show a slight increase. A substantial bimodal pattern appears in the results, with the Amazon decrease of precipitation and temperature increase accompanied by changes in the opposite sign to the southeast of the Amazon. Similar patterns have occurred in other studies, but not always in exactly the same locations. Evidently, how much of the region of rainfall increase occurs in the deforested area over the Amazon strongly affects the inferred statistics. It is likely that this pattern depends on the model control climatology and possibly other features. 16 refs., 2 figs., 2 tabs.

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

Stratospheric sulfur and its implications for radiative forcing simulated by the chemistry climate model EMAC.

Science.gov (United States)

Brühl, C; Lelieveld, J; Tost, H; Höpfner, M; Glatthor, N

2015-03-16

Multiyear simulations with the atmospheric chemistry general circulation model EMAC with a microphysical modal aerosol module at high vertical resolution demonstrate that the sulfur gases COS and SO 2 , the latter from low-latitude and midlatitude volcanic eruptions, predominantly control the formation of stratospheric aerosol. Marine dimethyl sulfide (DMS) and other SO 2 sources, including strong anthropogenic emissions in China, are found to play a minor role except in the lowermost stratosphere. Estimates of volcanic SO 2 emissions are based on satellite observations using Total Ozone Mapping Spectrometer and Ozone Monitoring Instrument for total injected mass and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat or Stratospheric Aerosol and Gases Experiment for the spatial distribution. The 10 year SO 2 and COS data set of MIPAS is also used for model evaluation. The calculated radiative forcing of stratospheric background aerosol including sulfate from COS and small contributions by DMS oxidation, and organic aerosol from biomass burning, is about 0.07W/m 2 . For stratospheric sulfate aerosol from medium and small volcanic eruptions between 2005 and 2011 a global radiative forcing up to 0.2W/m 2 is calculated, moderating climate warming, while for the major Pinatubo eruption the simulated forcing reaches 5W/m 2 , leading to temporary climate cooling. The Pinatubo simulation demonstrates the importance of radiative feedback on dynamics, e.g., enhanced tropical upwelling, for large volcanic eruptions.

Greenland ice sheet surface mass balance: evaluating simulations and making projections with regional climate models

Directory of Open Access Journals (Sweden)

J. G. L. Rae

2012-11-01

Full Text Available Four high-resolution regional climate models (RCMs have been set up for the area of Greenland, with the aim of providing future projections of Greenland ice sheet surface mass balance (SMB, and its contribution to sea level rise, with greater accuracy than is possible from coarser-resolution general circulation models (GCMs. This is the first time an intercomparison has been carried out of RCM results for Greenland climate and SMB. Output from RCM simulations for the recent past with the four RCMs is evaluated against available observations. The evaluation highlights the importance of using a detailed snow physics scheme, especially regarding the representations of albedo and meltwater refreezing. Simulations with three of the RCMs for the 21st century using SRES scenario A1B from two GCMs produce trends of between −5.5 and −1.1 Gt yr⁻² in SMB (equivalent to +0.015 and +0.003 mm sea level equivalent yr⁻², with trends of smaller magnitude for scenario E1, in which emissions are mitigated. Results from one of the RCMs whose present-day simulation is most realistic indicate that an annual mean near-surface air temperature increase over Greenland of ~ 2°C would be required for the mass loss to increase such that it exceeds accumulation, thereby causing the SMB to become negative, which has been suggested as a threshold beyond which the ice sheet would eventually be eliminated.

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.

Improved simulation of peak flows under climate change: post-processing or composite opjective calibration?

NARCIS (Netherlands)

Zhang, Xujie; Booij, Martijn J.; Xu, YuePing

2015-01-01

Climate change is expected to have large impacts on peak flows. However, there may be bias in the simulation of peak flows by hydrological models. This study aims to improve the simulation of peak flows under climate change in Lanjiang catchment, east China, by comparing two approaches:

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...

Impact of improved Greenland ice sheet surface representation in the NASA GISS ModelE2 GCM on simulated surface mass balance and regional climate

Science.gov (United States)

Alexander, P. M.; LeGrande, A. N.; Fischer, E.; Tedesco, M.; Kelley, M.; Schmidt, G. A.; Fettweis, X.

2017-12-01

Towards achieving coupled simulations between the NASA Goddard Institute for Space Studies (GISS) ModelE2 general circulation model (GCM) and ice sheet models (ISMs), improvements have been made to the representation of the ice sheet surface in ModelE2. These include a sub-grid-scale elevation class scheme, a multi-layer snow model, a time-variable surface albedo scheme, and adjustments to parameterization of sublimation/evaporation. These changes improve the spatial resolution and physical representation of the ice sheet surface such that the surface is represented at a level of detail closer to that of Regional Climate Models (RCMs). We assess the impact of these changes on simulated Greenland Ice Sheet (GrIS) surface mass balance (SMB). We also compare ModelE2 simulations in which winds have been nudged to match the European Center for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis with simulations from the Modèle Atmosphérique Régionale (MAR) RCM forced by the same reanalysis. Adding surface elevation classes results in a much higher spatial resolution representation of the surface necessary for coupling with ISMs, but has a negligible impact on overall SMB. Implementing a variable surface albedo scheme increases melt by 100%, bringing it closer to melt simulated by MAR. Adjustments made to the representation of topography-influenced surface roughness length in ModelE2 reduce a positive bias in evaporation relative to MAR. We also examine the impact of changes to the GrIS surface on regional atmospheric and oceanic climate in coupled ocean-atmosphere simulations with ModelE2, finding a general warming of the Arctic due to a warmer GrIS, and a cooler North Atlantic in scenarios with doubled atmospheric CO2 relative to pre-industrial levels. The substantial influence of changes to the GrIS surface on the oceans and atmosphere highlight the importance of including these processes in the GCM, in view of potential feedbacks between the ice sheet

The transferability of hydrological models under nonstationary climatic conditions

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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

A synthesis of regional climate change simulations - A Scandinavian perspective

DEFF Research Database (Denmark)

Christensen, J. H.; Räinsänen, J.; Iversen, T.

2001-01-01

Four downscaling experiments of regional climate change for the Nordic countries have been conducted with three different regional climate models (RCMs). A short synthesis of the outcome of the suite of experiments is presented as an ensemble, reflecting the different driving atmosphere-ocean...... general circulation model (AOGCM) conditions, RCM model resolution and domain size, and choice of emission scenarios. This allows the sources of uncertainties in the projections to be assessed. At the same time analysis of the climate change signal for temperature and precipitation over the period 1990......-2050 reveals strong similarities. In particular, all experiments in the suite simulate changes in the precipitation distribution towards a higher frequency of heavy precipitation....

On the spread of changes in marine low cloud cover in climate model simulations of the 21st century

Science.gov (United States)

Qu, Xin; Hall, Alex; Klein, Stephen A.; Caldwell, Peter M.

2014-05-01

In 36 climate change simulations associated with phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5), changes in marine low cloud cover (LCC) exhibit a large spread, and may be either positive or negative. Here we develop a heuristic model to understand the source of the spread. The model's premise is that simulated LCC changes can be interpreted as a linear combination of contributions from factors shaping the clouds' large-scale environment. We focus primarily on two factors—the strength of the inversion capping the atmospheric boundary layer (measured by the estimated inversion strength, EIS) and sea surface temperature (SST). For a given global model, the respective contributions of EIS and SST are computed. This is done by multiplying (1) the current-climate's sensitivity of LCC to EIS or SST variations, by (2) the climate-change signal in EIS or SST. The remaining LCC changes are then attributed to changes in greenhouse gas and aerosol concentrations, and other environmental factors. The heuristic model is remarkably skillful. Its SST term dominates, accounting for nearly two-thirds of the intermodel variance of LCC changes in CMIP3 models, and about half in CMIP5 models. Of the two factors governing the SST term (the SST increase and the sensitivity of LCC to SST perturbations), the SST sensitivity drives the spread in the SST term and hence the spread in the overall LCC changes. This sensitivity varies a great deal from model to model and is strongly linked to the types of cloud and boundary layer parameterizations used in the models. EIS and SST sensitivities are also estimated using observational cloud and meteorological data. The observed sensitivities are generally consistent with the majority of models as well as expectations from prior research. Based on the observed sensitivities and the relative magnitudes of simulated EIS and SST changes (which we argue are also physically reasonable), the heuristic model predicts LCC

Climate variability in Andalusia (southern Spain during the period 1701–1850 based on documentary sources: evaluation and comparison with climate model simulations

Directory of Open Access Journals (Sweden)

J. P. Montávez Gómez

2012-01-01

Full Text Available In this work, a reconstruction of climatic conditions in Andalusia (southern Iberian Peninsula during the period 1701–1850, as well as an evaluation of its associated uncertainties, is presented. This period is interesting because it is characterized by a minimum in solar irradiance (Dalton Minimum, around 1800, as well as intense volcanic activity (for instance, the eruption of Tambora in 1815, at a time when any increase in atmospheric CO2 concentrations was of minor importance. The reconstruction is based on the analysis of a wide variety of documentary data. The reconstruction methodology is based on counting the number of extreme events in the past, and inferring mean value and standard deviation using the assumption of normal distribution for the seasonal means of climate variables. This reconstruction methodology is tested within the pseudoreality of a high-resolution paleoclimate simulation performed with the regional climate model MM5 coupled to the global model ECHO-G. The results show that the reconstructions are influenced by the reference period chosen and the threshold values used to define extreme values. This creates uncertainties which are assessed within the context of climate simulation. An ensemble of reconstructions was obtained using two different reference periods (1885–1915 and 1960–1990 and two pairs of percentiles as threshold values (10–90 and 25–75. The results correspond to winter temperature, and winter, spring and autumn rainfall, and they are compared with simulations of the climate model for the considered period. The mean value of winter temperature for the period 1781–1850 was 10.6 ± 0.1 °C (11.0 °C for the reference period 1960–1990. The mean value of winter rainfall for the period 1701–1850 was 267 ± 18 mm (224 mm for 1960–1990. The mean values of spring and autumn rainfall were 164 ± 11 and 194 ± 16 mm (129 and 162 mm for 1960–1990, respectively. Comparison of the distribution

Coupled atmosphere ocean climate model simulations in the Mediterranean region: effect of a high-resolution marine model on cyclones and precipitation

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A. Sanna

2013-06-01

Full Text Available In this study we investigate the importance of an eddy-permitting Mediterranean Sea circulation model on the simulation of atmospheric cyclones and precipitation in a climate model. This is done by analyzing results of two fully coupled GCM (general circulation models simulations, differing only for the presence/absence of an interactive marine module, at very high-resolution (~ 1/16°, for the simulation of the 3-D circulation of the Mediterranean Sea. Cyclones are tracked by applying an objective Lagrangian algorithm to the MSLP (mean sea level pressure field. On annual basis, we find a statistically significant difference in vast cyclogenesis regions (northern Adriatic, Sirte Gulf, Aegean Sea and southern Turkey and in lifetime, giving evidence of the effect of both land–sea contrast and surface heat flux intensity and spatial distribution on cyclone characteristics. Moreover, annual mean convective precipitation changes significantly in the two model climatologies as a consequence of differences in both air–sea interaction strength and frequency of cyclogenesis in the two analyzed simulations.

The simulation of medicanes in a high-resolution regional climate model

Energy Technology Data Exchange (ETDEWEB)

Cavicchia, Leone [Centro Euro-Mediterraneo per i Cambiamenti Climatici, Bologna (Italy); Helmholtz-Zentrum Geesthacht, Institute of Coastal Research, Geesthacht (Germany); Ca' Foscari University, Venice (Italy); Storch, Hans von [Helmholtz-Zentrum Geesthacht, Institute of Coastal Research, Geesthacht (Germany); University of Hamburg, Meteorological Institute, Hamburg (Germany)

2012-11-15

Medicanes, strong mesoscale cyclones with tropical-like features, develop occasionally over the Mediterranean Sea. Due to the scarcity of observations over sea and the coarse resolution of the long-term reanalysis datasets, it is difficult to study systematically the multidecadal statistics of sub-synoptic medicanes. Our goal is to assess the long-term variability and trends of medicanes, obtaining a long-term climatology through dynamical downscaling of the NCEP/NCAR reanalysis data. In this paper, we examine the robustness of this method and investigate the value added for the study of medicanes. To do so, we performed several climate mode simulations with a high resolution regional atmospheric model (CCLM) for a number of test cases described in the literature. We find that the medicanes are formed in the simulations, with deeper pressures and stronger winds than in the driving global NCEP reanalysis. The tracks are adequately reproduced. We conclude that our methodology is suitable for constructing multi-decadal statistics and scenarios of current and possible future medicane activities. (orig.)

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

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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

Demonstration of a geostatistical approach to physically consistent downscaling of climate modeling simulations

KAUST Repository

Jha, Sanjeev Kumar; Mariethoz, Gregoire; Evans, Jason P.; McCabe, Matthew

2013-01-01

A downscaling approach based on multiple-point geostatistics (MPS) is presented. The key concept underlying MPS is to sample spatial patterns from within training images, which can then be used in characterizing the relationship between different variables across multiple scales. The approach is used here to downscale climate variables including skin surface temperature (TSK), soil moisture (SMOIS), and latent heat flux (LH). The performance of the approach is assessed by applying it to data derived from a regional climate model of the Murray-Darling basin in southeast Australia, using model outputs at two spatial resolutions of 50 and 10 km. The data used in this study cover the period from 1985 to 2006, with 1985 to 2005 used for generating the training images that define the relationships of the variables across the different spatial scales. Subsequently, the spatial distributions for the variables in the year 2006 are determined at 10 km resolution using the 50 km resolution data as input. The MPS geostatistical downscaling approach reproduces the spatial distribution of TSK, SMOIS, and LH at 10 km resolution with the correct spatial patterns over different seasons, while providing uncertainty estimates through the use of multiple realizations. The technique has the potential to not only bridge issues of spatial resolution in regional and global climate model simulations but also in feature sharpening in remote sensing applications through image fusion, filling gaps in spatial data, evaluating downscaled variables with available remote sensing images, and aggregating/disaggregating hydrological and groundwater variables for catchment studies.

Simulating the Holocene climate evolution at northern high latitudes using a coupled atmosphere-sea ice-ocean-vegetation model