Climate Change Impacts for the Conterminous USA. An Integrated Assessment. Part 4. Water Resources

International Nuclear Information System (INIS)

Thomson, A.M.; Rosenberg, N.J.; Izaurralde, R.C.; Brown, R.A.; Srinivasan, R.

2005-01-01

Global climate change will impact the hydrologic cycle by increasing the capacity of the atmosphere to hold moisture. Anticipated impacts are generally increased evaporation at low latitudes and increased precipitation at middle and high latitudes. General Circulation Models (GCMs) used to simulate climate disagree on whether the U.S. as a whole and its constituent regions will receive more or less precipitation as global warming occurs. The impacts on specific regions will depend on changes in weather patterns and are certain to be complex. Here we apply the suite of 12 potential climate change scenarios, previously described in Part 1, to the Hydrologic Unit Model of the United States (HUMUS) to simulate water supply in the conterminous United States in reference to a baseline scenario. We examine the sufficiency of this water supply to meet changing demands of irrigated agriculture. The changes in water supply driven by changes in climate will likely be most consequential in the semi-arid western parts of the country where water yield is currently scarce and the resource is intensively managed. Changes of greater than ±50% with respect to present day water yield are projected in parts of the Midwest and Southwest U.S. Interannual variability in the water supply is likely to increase where conditions become drier and to decrease under wetter conditions

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...

The CSIRO Mk3L climate system model version 1.0 – Part 1: Description and evaluation

Directory of Open Access Journals (Sweden)

S. J. Phipps

2011-06-01

Full Text Available The CSIRO Mk3L climate system model is a coupled general circulation model, designed primarily for millennial-scale climate simulations and palaeoclimate research. Mk3L includes components which describe the atmosphere, ocean, sea ice and land surface, and combines computational efficiency with a stable and realistic control climatology. This paper describes the model physics and software, analyses the control climatology, and evaluates the ability of the model to simulate the modern climate.

Mk3L incorporates a spectral atmospheric general circulation model, a z-coordinate ocean general circulation model, a dynamic-thermodynamic sea ice model and a land surface scheme with static vegetation. The source code is highly portable, and has no dependence upon proprietary software. The model distribution is freely available to the research community. A 1000-yr climate simulation can be completed in around one-and-a-half months on a typical desktop computer, with greater throughput being possible on high-performance computing facilities.

Mk3L produces realistic simulations of the larger-scale features of the modern climate, although with some biases on the regional scale. The model also produces reasonable representations of the leading modes of internal climate variability in both the tropics and extratropics. The control state of the model exhibits a high degree of stability, with only a weak cooling trend on millennial timescales. Ongoing development work aims to improve the model climatology and transform Mk3L into a comprehensive earth system model.

Production functions for climate policy modeling. An empirical analysis

International Nuclear Information System (INIS)

Van der Werf, Edwin

2008-01-01

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

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.

TRACKING CLIMATE MODELS

Data.gov (United States)

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

On climate prediction: how much can we expect from climate memory?

Science.gov (United States)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Subtropical Low Cloud Response to a Warmer Climate in an Superparameterized Climate Model: Part I. Regime Sorting and Physical Mechanisms

Directory of Open Access Journals (Sweden)

Peter N Blossey

2009-07-01

Full Text Available The subtropical low cloud response to a climate with SST uniformly warmed by 2 K is analyzed in the SP- CAM superparameterized climate model, in which each grid column is replaced by a two-dimensional cloud-resolving model (CRM. Intriguingly, SP-CAM shows substantial low cloud increases over the subtropical oceans in the warmer climate. The paper aims to understand the mechanism for these increases. The subtropical low cloud increase is analyzed by sorting grid-column months of the climate model into composite cloud regimes using percentile ranges of lower tropospheric stability (LTS. LTS is observed to be well correlated to subtropical low cloud amount and boundary layer vertical structure. The low cloud increase in SP-CAM is attributed to boundary-layer destabilization due to increased clear-sky radiative cooling in the warmer climate. This drives more shallow cumulus convection and a moister boundary layer, inducing cloud increases and further increasing the radiative cooling. The boundary layer depth does not change substantially, due to compensation between increased radiative cooling (which promotes more turbulent mixing and boundary-layer deepening and slight strengthening of the boundary-layer top inversion (which inhibits turbulent entrainment and promotes a shallower boundary layer. The widespread changes in low clouds do not appear to be driven by changes in mean subsidence.
In a companion paper we use column-mode CRM simulations based on LTS-composite profiles to further study the low cloud response mechanisms and to explore the sensitivity of low cloud response to grid resolution in SP-CAM.

Historical and idealized climate model experiments: an EMIC intercomparison

DEFF Research Database (Denmark)

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

2012-01-01

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

Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

Science.gov (United States)

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

2017-04-01

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

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 greening of the McGill Paleoclimate Model. Part II: Simulation of Holocene millennial-scale natural climate changes

Energy Technology Data Exchange (ETDEWEB)

Wang, Yi; Mysak, Lawrence A.; Wang, Zhaomin [McGill University, Department of Atmospheric and Oceanic Sciences and Global Environmental and Climate Change Centre (GEC3), Montreal, Quebec (Canada); Brovkin, Victor [Potsdam Institute for Climate Impact Research (PIK), 601203, Potsdam (Germany)

2005-04-01

Various proxy data reveal that in many regions of the Northern Hemisphere (NH), the middle Holocene (6 kyr BP) was warmer than the early Holocene (8 kyr BP) as well as the later Holocene, up to the end of the pre-industrial period (1800 AD). This pattern of warming and then cooling in the NH represents the response of the climate system to changes in orbital forcing, vegetation cover and the Laurentide Ice Sheet (LIS) during the Holocene. In an attempt to better understand these changes in the climate system, the McGill Paleoclimate Model (MPM) has been coupled to the dynamic global vegetation model known as VECODE (see Part I of this two-part paper), and a number of sensitivity experiments have been performed with the ''green'' MPM. The model results illustrate the following: (1) the orbital forcing together with the vegetation - albedo feedback result in the gradual cooling of global SAT from about 6 kyr BP to the end of the pre-industrial period; (2) the disappearance of the LIS over the period 8-6 kyr BP, associated with vegetation - albedo feedback, allows the global SAT to increase and reach its maximum at around 6 kyr BP; (3) the northern limit of the boreal forest moves northward during the period 8-6.4 kyr BP due to the LIS retreat; (4) during the period 6.4-0 kyr BP, the northern limit of the boreal forest moves southward about 120 km in response to the decreasing summer insolation in the NH; and (5) the desertification of northern Africa during the period 8-2.6 kyr BP is mainly explained by the decreasing summer monsoon precipitation. (orig.)

Modelling Interglacial Climate

DEFF Research Database (Denmark)

Pedersen, Rasmus Anker

the impact of a changing sea ice cover. The first part focusses on the last interglacial climate (125,000 years before present) which was characterized by substantial warming at high northern latitudes due to an increased insolation during summer. The simulations reveal that the oceanic changes dominate......Past warm climate states could potentially provide information on future global warming. The past warming was driven by changed insolation rather than an increased greenhouse effect, and thus the warm climate states are expected to be different. Nonetheless, the response of the climate system......, with maximum warming occurring in winter. The three scenarios all affect the climate beyond the Arctic, especially the mid-latitude circulation which is sensitive to the location of the ice loss. Together, the results presented in this thesis illustrate that the changes in the Arctic sea ice cover...

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

Energy Technology Data Exchange (ETDEWEB)

Palma, J.H.N.

2017-11-01

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

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

International Nuclear Information System (INIS)

Palma, J.H.N.

2017-01-01

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

Climate change hotspots in the CMIP5 global climate model ensemble.

Science.gov (United States)

Diffenbaugh, Noah S; Giorgi, Filippo

2012-01-10

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

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

DEFF Research Database (Denmark)

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

2013-01-01

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE...... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20...

The Norwegian Earth System Model, NorESM1-M – Part 2: Climate response and scenario projections

Directory of Open Access Journals (Sweden)

T. Iversen

2013-03-01

Full Text Available NorESM is a generic name of the Norwegian earth system model. The first version is named NorESM1, and has been applied with medium spatial resolution to provide results for CMIP5 (http://cmip-pcmdi.llnl.gov/cmip5/index.html without (NorESM1-M and with (NorESM1-ME interactive carbon-cycling. Together with the accompanying paper by Bentsen et al. (2012, this paper documents that the core version NorESM1-M is a valuable global climate model for research and for providing complementary results to the evaluation of possible anthropogenic climate change. NorESM1-M is based on the model CCSM4 operated at NCAR, but the ocean model is replaced by a modified version of MICOM and the atmospheric model is extended with online calculations of aerosols, their direct effect and their indirect effect on warm clouds. Model validation is presented in the companion paper (Bentsen et al., 2012. NorESM1-M is estimated to have equilibrium climate sensitivity of ca. 2.9 K and a transient climate response of ca. 1.4 K. This sensitivity is in the lower range amongst the models contributing to CMIP5. Cloud feedbacks dampen the response, and a strong AMOC reduces the heat fraction available for increasing near-surface temperatures, for evaporation and for melting ice. The future projections based on RCP scenarios yield a global surface air temperature increase of almost one standard deviation lower than a 15-model average. Summer sea-ice is projected to decrease considerably by 2100 and disappear completely for RCP8.5. The AMOC is projected to decrease by 12%, 15–17%, and 32% for the RCP2.6, 4.5, 6.0, and 8.5, respectively. Precipitation is projected to increase in the tropics, decrease in the subtropics and in southern parts of the northern extra-tropics during summer, and otherwise increase in most of the extra-tropics. Changes in the atmospheric water cycle indicate that precipitation events over continents will become more intense and dry spells more frequent. Extra

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

Science.gov (United States)

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

2002-12-01

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

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

Science.gov (United States)

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

2014-05-01

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

Climate models with delay differential equations.

Science.gov (United States)

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

2017-11-01

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

Climate models with delay differential equations

Science.gov (United States)

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

2017-11-01

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

Cpl6: The New Extensible, High-Performance Parallel Coupler forthe Community Climate System Model

Energy Technology Data Exchange (ETDEWEB)

Craig, Anthony P.; Jacob, Robert L.; Kauffman, Brain; Bettge,Tom; Larson, Jay; Ong, Everest; Ding, Chris; He, Yun

2005-03-24

Coupled climate models are large, multiphysics applications designed to simulate the Earth's climate and predict the response of the climate to any changes in the forcing or boundary conditions. The Community Climate System Model (CCSM) is a widely used state-of-art climate model that has released several versions to the climate community over the past ten years. Like many climate models, CCSM employs a coupler, a functional unit that coordinates the exchange of data between parts of climate system such as the atmosphere and ocean. This paper describes the new coupler, cpl6, contained in the latest version of CCSM,CCSM3. Cpl6 introduces distributed-memory parallelism to the coupler, a class library for important coupler functions, and a standardized interface for component models. Cpl6 is implemented entirely in Fortran90 and uses Model Coupling Toolkit as the base for most of its classes. Cpl6 gives improved performance over previous versions and scales well on multiple platforms.

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

Science.gov (United States)

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

2013-04-01

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

Very high resolution regional climate model simulations over Greenland: Identifying added value

DEFF Research Database (Denmark)

Lucas-Picher, P.; Wulff-Nielsen, M.; Christensen, J.H.

2012-01-01

models. However, the bias between the simulations and the few available observations does not reduce with higher resolution. This is partly explained by the lack of observations in regions where the higher resolution is expected to improve the simulated climate. The RCM simulations show......This study presents two simulations of the climate over Greenland with the regional climate model (RCM) HIRHAM5 at 0.05° and 0.25° resolution driven at the lateral boundaries by the ERA-Interim reanalysis for the period 1989–2009. These simulations are validated against observations from...... that the temperature has increased the most in the northern part of Greenland and at lower elevations over the period 1989–2009. Higher resolution increases the relief variability in the model topography and causes the simulated precipitation to be larger on the coast and smaller over the main ice sheet compared...

Climate Model Diagnostic Analyzer

Science.gov (United States)

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

2015-01-01

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

Using an ensemble of regional climate models to assess climate change impacts on water scarcity in European river basins.

Science.gov (United States)

Gampe, David; Nikulin, Grigory; Ludwig, Ralf

2016-12-15

Climate change will likely increase pressure on the water balances of Mediterranean basins due to decreasing precipitation and rising temperatures. To overcome the issue of data scarcity the hydrological relevant variables total runoff, surface evaporation, precipitation and air temperature are taken from climate model simulations. The ensemble applied in this study consists of 22 simulations, derived from different combinations of four General Circulation Models (GCMs) forcing different Regional Climate Models (RCMs) and two Representative Concentration Pathways (RCPs) at ~12km horizontal resolution provided through the EURO-CORDEX initiative. Four river basins (Adige, Ebro, Evrotas and Sava) are selected and climate change signals for the future period 2035-2065 as compared to the reference period 1981-2010 are investigated. Decreased runoff and evaporation indicate increased water scarcity over the Ebro and the Evrotas, as well as the southern parts of the Adige and the Sava, resulting from a temperature increase of 1-3° and precipitation decrease of up to 30%. Most severe changes are projected for the summer months indicating further pressure on the river basins already at least partly characterized by flow intermittency. The widely used Falkenmark indicator is presented and confirms this tendency and shows the necessity for spatially distributed analysis and high resolution projections. Related uncertainties are addressed by the means of a variance decomposition and model agreement to determine the robustness of the projections. The study highlights the importance of high resolution climate projections and represents a feasible approach to assess climate impacts on water scarcity also in regions that suffer from data scarcity. Copyright © 2016. Published by Elsevier B.V.

Effects of climatic changes on carbon dioxide and water vapor fluxes in boreal forest ecosystems of European part of Russia

International Nuclear Information System (INIS)

Olchev, A; Kurbatova, J; Novenko, E; Desherevskaya, O; Krasnorutskaya, K

2009-01-01

Effects of possible climatic and vegetation changes on H 2 O and CO 2 fluxes in boreal forest ecosystems of the central part of European Russia were quantified using modeling and experimental data. The future pattern of climatic conditions for the period up to 2100 was derived using the global climatic model ECHAM5 (Roeckner et al 2003 The Atmospheric General Circulation Model ECHAM 5. PART I: Model Description, Report 349 (Hamburg: Max-Planck Institute for Meteorology) p 127) with the A1B emission scenario. The possible trends of future vegetation changes were obtained by reconstructions of vegetation cover and paleoclimatic conditions in the Late Pleistocene and Holocene, as provided from pollen and plant macrofossil analysis of profiles in the Central Forest State Natural Biosphere Reserve (CFSNBR). Applying the method of paleoanalogues demonstrates that increasing the mean annual temperature, even by 1-2 deg. C, could result in reducing the proportion of spruce in boreal forest stands by up to 40%. Modeling experiments, carried out using a process-based Mixfor-SVAT model, show that the expected future climatic and vegetation changes lead to a significant increase of net ecosystem exchange (NEE) and gross primary productivity (GPP) of the boreal forests. Despite the expected warming and moistening of the climate, the modeling experiments indicate a relatively weak increase of annual evapotranspiration (ET) and even a reduction of transpiration (TR) rates of forest ecosystems compared to present conditions.

Climate change between the mid and late Holocene in northern high latitudes – Part 2: Model-data comparisons

Directory of Open Access Journals (Sweden)

K. Holmgren

2010-09-01

Full Text Available The climate response over northern high latitudes to the mid-Holocene orbital forcing has been investigated in three types of PMIP (Paleoclimate Modelling Intercomparison Project simulations with different complexity of the modelled climate system. By first undertaking model-data comparison, an objective selection method has been applied to evaluate the capability of the climate models to reproduce the spatial response pattern seen in proxy data. The possible feedback mechanisms behind the climate response have been explored based on the selected model simulations. Subsequent model-model comparisons indicate the importance of including the different physical feedbacks in the climate models. The comparisons between the proxy-based reconstructions and the best fit selected simulations show that over the northern high latitudes, summer temperature change follows closely the insolation change and shows a common feature with strong warming over land and relatively weak warming over ocean at 6 ka compared to 0 ka. Furthermore, the sea-ice-albedo positive feedback enhances this response. The reconstructions of temperature show a stronger response to enhanced insolation in the annual mean temperature than winter and summer temperature. This is verified in the model simulations and the behaviour is attributed to the larger contribution from the large response in autumn. Despite a smaller insolation during winter at 6 ka, a pronounced warming centre is found over Barents Sea in winter in the simulations, which is also supported by the nearby northern Eurasian continental and Fennoscandian reconstructions. This indicates that in the Arctic region, the response of the ocean and the sea ice to the enhanced summer insolation is more important for the winter temperature than the synchronous decrease of the insolation.

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

Science.gov (United States)

Lau, William K. M.

2002-01-01

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

Climate change impact assessment on Veneto and Friuli plain groundwater. Part I: An integrated modeling approach for hazard scenario construction

International Nuclear Information System (INIS)

Baruffi, F.; Cisotto, A.; Cimolino, A.; Ferri, M.; Monego, M.; Norbiato, D.; Cappelletto, M.; Bisaglia, M.; Pretner, A.; Galli, A.; Scarinci, A.; Marsala, V.; Panelli, C.; Gualdi, S.; Bucchignani, E.; Torresan, S.; Pasini, S.; Critto, A.

2012-01-01

Climate change impacts on water resources, particularly groundwater, is a highly debated topic worldwide, triggering international attention and interest from both researchers and policy makers due to its relevant link with European water policy directives (e.g. 2000/60/EC and 2007/118/EC) and related environmental objectives. The understanding of long-term impacts of climate variability and change is therefore a key challenge in order to address effective protection measures and to implement sustainable management of water resources. This paper presents the modeling approach adopted within the Life + project TRUST (Tool for Regional-scale assessment of groUndwater Storage improvement in adaptation to climaTe change) in order to provide climate change hazard scenarios for the shallow groundwater of high Veneto and Friuli Plain, Northern Italy. Given the aim to evaluate potential impacts on water quantity and quality (e.g. groundwater level variation, decrease of water availability for irrigation, variations of nitrate infiltration processes), the modeling approach integrated an ensemble of climate, hydrologic and hydrogeologic models running from the global to the regional scale. Global and regional climate models and downscaling techniques were used to make climate simulations for the reference period 1961–1990 and the projection period 2010–2100. The simulation of the recent climate was performed using observed radiative forcings, whereas the projections have been done prescribing the radiative forcings according to the IPCC A1B emission scenario. The climate simulations and the downscaling, then, provided the precipitation, temperatures and evapo-transpiration fields used for the impact analysis. Based on downscaled climate projections, 3 reference scenarios for the period 2071–2100 (i.e. the driest, the wettest and the mild year) were selected and used to run a regional geomorphoclimatic and hydrogeological model. The final output of the model ensemble

Climate change impact assessment on Veneto and Friuli plain groundwater. Part I: An integrated modeling approach for hazard scenario construction

Energy Technology Data Exchange (ETDEWEB)

Baruffi, F. [Autorita di Bacino dei Fiumi dell' Alto Adriatico, Cannaregio 4314, 30121 Venice (Italy); Cisotto, A., E-mail: segreteria@adbve.it [Autorita di Bacino dei Fiumi dell' Alto Adriatico, Cannaregio 4314, 30121 Venice (Italy); Cimolino, A.; Ferri, M.; Monego, M.; Norbiato, D.; Cappelletto, M.; Bisaglia, M. [Autorita di Bacino dei Fiumi dell' Alto Adriatico, Cannaregio 4314, 30121 Venice (Italy); Pretner, A.; Galli, A. [SGI Studio Galli Ingegneria, via della Provvidenza 13, 35030 Sarmeola di Rubano (PD) (Italy); Scarinci, A., E-mail: andrea.scarinci@sgi-spa.it [SGI Studio Galli Ingegneria, via della Provvidenza 13, 35030 Sarmeola di Rubano (PD) (Italy); Marsala, V.; Panelli, C. [SGI Studio Galli Ingegneria, via della Provvidenza 13, 35030 Sarmeola di Rubano (PD) (Italy); Gualdi, S., E-mail: silvio.gualdi@bo.ingv.it [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), via Augusto Imperatore 16, 73100 Lecce (Italy); Bucchignani, E., E-mail: e.bucchignani@cira.it [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), via Augusto Imperatore 16, 73100 Lecce (Italy); Torresan, S., E-mail: torresan@cmcc.it [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), via Augusto Imperatore 16, 73100 Lecce (Italy); Pasini, S., E-mail: sara.pasini@stud.unive.it [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), via Augusto Imperatore 16, 73100 Lecce (Italy); Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, Calle Larga S. Marta 2137, 30123 Venice (Italy); Critto, A., E-mail: critto@unive.it [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), via Augusto Imperatore 16, 73100 Lecce (Italy); Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, Calle Larga S. Marta 2137, 30123 Venice (Italy); and others

2012-12-01

Climate change impacts on water resources, particularly groundwater, is a highly debated topic worldwide, triggering international attention and interest from both researchers and policy makers due to its relevant link with European water policy directives (e.g. 2000/60/EC and 2007/118/EC) and related environmental objectives. The understanding of long-term impacts of climate variability and change is therefore a key challenge in order to address effective protection measures and to implement sustainable management of water resources. This paper presents the modeling approach adopted within the Life + project TRUST (Tool for Regional-scale assessment of groUndwater Storage improvement in adaptation to climaTe change) in order to provide climate change hazard scenarios for the shallow groundwater of high Veneto and Friuli Plain, Northern Italy. Given the aim to evaluate potential impacts on water quantity and quality (e.g. groundwater level variation, decrease of water availability for irrigation, variations of nitrate infiltration processes), the modeling approach integrated an ensemble of climate, hydrologic and hydrogeologic models running from the global to the regional scale. Global and regional climate models and downscaling techniques were used to make climate simulations for the reference period 1961-1990 and the projection period 2010-2100. The simulation of the recent climate was performed using observed radiative forcings, whereas the projections have been done prescribing the radiative forcings according to the IPCC A1B emission scenario. The climate simulations and the downscaling, then, provided the precipitation, temperatures and evapo-transpiration fields used for the impact analysis. Based on downscaled climate projections, 3 reference scenarios for the period 2071-2100 (i.e. the driest, the wettest and the mild year) were selected and used to run a regional geomorphoclimatic and hydrogeological model. The final output of the model ensemble produced

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.

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.

Modeling glacial climates

Science.gov (United States)

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

1984-01-01

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

Modelling the climate and surface mass balance of polar ice sheets using RACMO2 - Part 1: Greenland (1958-2016)

Science.gov (United States)

Noël, Brice; van de Berg, Willem Jan; Melchior van Wessem, J.; van Meijgaard, Erik; van As, Dirk; Lenaerts, Jan T. M.; Lhermitte, Stef; Kuipers Munneke, Peter; Smeets, C. J. P. Paul; van Ulft, Lambertus H.; van de Wal, Roderik S. W.; van den Broeke, Michiel R.

2018-03-01

We evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 (1958-2016). The new model version, referred to as RACMO2.3p2, incorporates updated glacier outlines, topography and ice albedo fields. Parameters in the cloud scheme governing the conversion of cloud condensate into precipitation have been tuned to correct inland snowfall underestimation: snow properties are modified to reduce drifting snow and melt production in the ice sheet percolation zone. The ice albedo prescribed in the updated model is lower at the ice sheet margins, increasing ice melt locally. RACMO2.3p2 shows good agreement compared to in situ meteorological data and point SEB/SMB measurements, and better resolves the spatial patterns and temporal variability of SMB compared with the previous model version, notably in the north-east, south-east and along the K-transect in south-western Greenland. This new model version provides updated, high-resolution gridded fields of the GrIS present-day climate and SMB, and will be used for projections of the GrIS climate and SMB in response to a future climate scenario in a forthcoming study.

Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

KAUST Repository

Sang, Huiyan

2011-12-01

This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models. Our method allows for a nonseparable and nonstationary cross-covariance structure. We also present a covariance approximation approach to facilitate the computation in the modeling and analysis of very large multivariate spatial data sets. The covariance approximation consists of two parts: a reduced-rank part to capture the large-scale spatial dependence, and a sparse covariance matrix to correct the small-scale dependence error induced by the reduced rank approximation. We pay special attention to the case that the second part of the approximation has a block-diagonal structure. Simulation results of model fitting and prediction show substantial improvement of the proposed approximation over the predictive process approximation and the independent blocks analysis. We then apply our computational approach to the joint statistical modeling of multiple climate model errors. © 2012 Institute of Mathematical Statistics.

Bringing a Realistic Global Climate Modeling Experience to a Broader Audience

Science.gov (United States)

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

2010-12-01

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

Linking models of human behaviour and climate alters projected climate change

Science.gov (United States)

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

2018-01-01

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

The CSIRO Mk3L climate system model version 1.0 – Part 2: Response to external forcings

Directory of Open Access Journals (Sweden)

S. J. Phipps

2012-05-01

Full Text Available The CSIRO Mk3L climate system model is a coupled general circulation model, designed primarily for millennial-scale climate simulation and palaeoclimate research. Mk3L includes components which describe the atmosphere, ocean, sea ice and land surface, and combines computational efficiency with a stable and realistic control climatology. It is freely available to the research community. This paper evaluates the response of the model to external forcings which correspond to past and future changes in the climate system.

A simulation of the mid-Holocene climate is performed, in which changes in the seasonal and meridional distribution of incoming solar radiation are imposed. Mk3L correctly simulates increased summer temperatures at northern mid-latitudes and cooling in the tropics. However, it is unable to capture some of the regional-scale features of the mid-Holocene climate, with the precipitation over Northern Africa being deficient. The model simulates a reduction of between 7 and 15% in the amplitude of El Niño-Southern Oscillation, a smaller decrease than that implied by the palaeoclimate record. However, the realism of the simulated ENSO is limited by the model's relatively coarse spatial resolution.

Transient simulations of the late Holocene climate are then performed. The evolving distribution of insolation is imposed, and an acceleration technique is applied and assessed. The model successfully captures the temperature changes in each hemisphere and the upward trend in ENSO variability. However, the lack of a dynamic vegetation scheme does not allow it to simulate an abrupt desertification of the Sahara.

To assess the response of Mk3L to other forcings, transient simulations of the last millennium are performed. Changes in solar irradiance, atmospheric greenhouse gas concentrations and volcanic emissions are applied to the model. The model is again broadly successful at simulating larger-scale changes in the

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

Directory of Open Access Journals (Sweden)

Rachel D. Cavanagh

2017-09-01

Full Text Available Increasing concern about the impacts of climate change on ecosystems is prompting ecologists and ecosystem managers to seek reliable projections of physical drivers of change. The use of global climate models in ecology is growing, although drawing ecologically meaningful conclusions can be problematic. The expertise required to access and interpret output from climate and earth system models is hampering progress in utilizing them most effectively to determine the wider implications of climate change. To address this issue, we present a joint approach between climate scientists and ecologists that explores key challenges and opportunities for progress. As an exemplar, our focus is the Southern Ocean, notable for significant change with global implications, and on sea ice, given its crucial role in this dynamic ecosystem. We combined perspectives to evaluate the representation of sea ice in global climate models. With an emphasis on ecologically-relevant criteria (sea ice extent and seasonality we selected a subset of eight models that reliably reproduce extant sea ice distributions. While the model subset shows a similar mean change to the full ensemble in sea ice extent (approximately 50% decline in winter and 30% decline in summer, there is a marked reduction in the range. This improved the precision of projected future sea ice distributions by approximately one third, and means they are more amenable to ecological interpretation. We conclude that careful multidisciplinary evaluation of climate models, in conjunction with ongoing modeling advances, should form an integral part of utilizing model output.

Crop modelling for integrated assessment of risk to food production from climate change

DEFF Research Database (Denmark)

Ewert, F.; Rötter, R.P.; Bindi, M.

2015-01-01

. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming...... climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables...

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.

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.

Numerical simulation of surface solar radiation over Southern Africa. Part 1: Evaluation of regional and global climate models

Science.gov (United States)

Tang, Chao; Morel, Béatrice; Wild, Martin; Pohl, Benjamin; Abiodun, Babatunde; Bessafi, Miloud

2018-02-01

This study evaluates the performance of climate models in reproducing surface solar radiation (SSR) over Southern Africa (SA) by validating five Regional Climate Models (RCM, including CCLM4, HIRHAM5, RACMO22T, RCA4 and REMO2009) that participated in the Coordinated Regional Downscaling Experiment program over Africa (CORDEX-Africa) along with their ten driving General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 over SA. The model simulated SSR was thereby compared to reference data from ground-based measurements, satellite-derived products and reanalyses over the period 1990-2005. Results show that (1) the references obtained from satellite retrievals and reanalyses overall overestimate SSR by up to 10 W/m2 on average when compared to ground-based measurements from the Global Energy Balance Archive, which are located mainly over the eastern part of the southern African continent. (2) Compared to one of the satellite products (Surface Solar Radiation Data Set—Heliosat Edition 2; SARAH-2): GCMs overestimate SSR over SA in terms of their multi-model mean by about 1 W/m2 (compensation of opposite biases over sub-regions) and 7.5 W/m2 in austral summer and winter respectively; RCMs driven by GCMs show in their multimodel mean underestimations of SSR in both seasons with Mean Bias Errors (MBEs) of about - 30 W/m2 in austral summer and about - 14 W/m2 in winter compared to SARAH-2. This multi-model mean low bias is dominated by the simulations of the CCLM4, with negative biases up to - 76 W/m2 in summer and - 32 W/m2 in winter. (3) The discrepancies in the simulated SSR over SA are larger in the RCMs than in the GCMs. (4) In terms of trend during the "brightening" period 1990-2005, both GCMs and RCMs (driven by European Centre for Medium-Range Weather Forecasts Reanalysis ERA-Interim, short as ERAINT and GCMs) simulate an SSR trend of less than 1 W/m2 per decade. However, variations of SSR trend exist among different references data

Biotic interactions in the face of climate change: a comparison of three modelling approaches.

Directory of Open Access Journals (Sweden)

Anja Jaeschke

Full Text Available Climate change is expected to alter biotic interactions, and may lead to temporal and spatial mismatches of interacting species. Although the importance of interactions for climate change risk assessments is increasingly acknowledged in observational and experimental studies, biotic interactions are still rarely incorporated in species distribution models. We assessed the potential impacts of climate change on the obligate interaction between Aeshna viridis and its egg-laying plant Stratiotes aloides in Europe, based on an ensemble modelling technique. We compared three different approaches for incorporating biotic interactions in distribution models: (1 We separately modelled each species based on climatic information, and intersected the future range overlap ('overlap approach'. (2 We modelled the potential future distribution of A. viridis with the projected occurrence probability of S. aloides as further predictor in addition to climate ('explanatory variable approach'. (3 We calibrated the model of A. viridis in the current range of S. aloides and multiplied the future occurrence probabilities of both species ('reference area approach'. Subsequently, all approaches were compared to a single species model of A. viridis without interactions. All approaches projected a range expansion for A. viridis. Model performance on test data and amount of range gain differed depending on the biotic interaction approach. All interaction approaches yielded lower range gains (up to 667% lower than the model without interaction. Regarding the contribution of algorithm and approach to the overall uncertainty, the main part of explained variation stems from the modelling algorithm, and only a small part is attributed to the modelling approach. The comparison of the no-interaction model with the three interaction approaches emphasizes the importance of including obligate biotic interactions in projective species distribution modelling. We recommend the use of

Agricultural drought in a future climate: results from 15 global climate models participating in the IPCC 4th assessment

Science.gov (United States)

Wang, Guiling

2005-12-01

This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June July August (JJA) season and the Asian monsoon region in the December January February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.

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.)

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

Modelling coffee leaf rust risk in Colombia with climate reanalysis data.

Science.gov (United States)

Bebber, Daniel P; Castillo, Ángela Delgado; Gurr, Sarah J

2016-12-05

Many fungal plant diseases are strongly controlled by weather, and global climate change is thus likely to have affected fungal pathogen distributions and impacts. Modelling the response of plant diseases to climate change is hampered by the difficulty of estimating pathogen-relevant microclimatic variables from standard meteorological data. The availability of increasingly sophisticated high-resolution climate reanalyses may help overcome this challenge. We illustrate the use of climate reanalyses by testing the hypothesis that climate change increased the likelihood of the 2008-2011 outbreak of Coffee Leaf Rust (CLR, Hemileia vastatrix) in Colombia. We develop a model of germination and infection risk, and drive this model using estimates of leaf wetness duration and canopy temperature from the Japanese 55-Year Reanalysis (JRA-55). We model germination and infection as Weibull functions with different temperature optima, based upon existing experimental data. We find no evidence for an overall trend in disease risk in coffee-growing regions of Colombia from 1990 to 2015, therefore, we reject the climate change hypothesis. There was a significant elevation in predicted CLR infection risk from 2008 to 2011 compared with other years. JRA-55 data suggest a decrease in canopy surface water after 2008, which may have helped terminate the outbreak. The spatial resolution and accuracy of climate reanalyses are continually improving, increasing their utility for biological modelling. Confronting disease models with data requires not only accurate climate data, but also disease observations at high spatio-temporal resolution. Investment in monitoring, storage and accessibility of plant disease observation data are needed to match the quality of the climate data now available.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Authors.

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.

Modelling the climate and surface mass balance of polar ice sheets using RACMO2 - Part 2: Antarctica (1979-2016)

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Melchior van Wessem, Jan; van de Berg, Willem Jan; Noël, Brice P. Y.; van Meijgaard, Erik; Amory, Charles; Birnbaum, Gerit; Jakobs, Constantijn L.; Krüger, Konstantin; Lenaerts, Jan T. M.; Lhermitte, Stef; Ligtenberg, Stefan R. M.; Medley, Brooke; Reijmer, Carleen H.; van Tricht, Kristof; Trusel, Luke D.; van Ulft, Lambertus H.; Wouters, Bert; Wuite, Jan; van den Broeke, Michiel R.

2018-04-01

We evaluate modelled Antarctic ice sheet (AIS) near-surface climate, surface mass balance (SMB) and surface energy balance (SEB) from the updated polar version of the regional atmospheric climate model, RACMO2 (1979-2016). The updated model, referred to as RACMO2.3p2, incorporates upper-air relaxation, a revised topography, tuned parameters in the cloud scheme to generate more precipitation towards the AIS interior and modified snow properties reducing drifting snow sublimation and increasing surface snowmelt. Comparisons of RACMO2 model output with several independent observational data show that the existing biases in AIS temperature, radiative fluxes and SMB components are further reduced with respect to the previous model version. The model-integrated annual average SMB for the ice sheet including ice shelves (minus the Antarctic Peninsula, AP) now amounts to 2229 Gt y-1, with an interannual variability of 109 Gt y-1. The largest improvement is found in modelled surface snowmelt, which now compares well with satellite and weather station observations. For the high-resolution ( ˜ 5.5 km) AP simulation, results remain comparable to earlier studies. The updated model provides a new, high-resolution data set of the contemporary near-surface climate and SMB of the AIS; this model version will be used for future climate scenario projections in a forthcoming study.

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

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

2007-12-01

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

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

Science.gov (United States)

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

2012-04-01

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

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

Science.gov (United States)

Alexandru, Adelina; Sushama, Laxmi

2015-08-01

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

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...

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

Science.gov (United States)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is

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

International Nuclear Information System (INIS)

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

1992-08-01

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

Climate simulations for 1880-2003 with GISS modelE

International Nuclear Information System (INIS)

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

2007-01-01

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

Drivers of soil organic matter vulnerability to climate change, Part II: RothC modelling of carbon dynamics including radiocarbon data

Science.gov (United States)

Studer, Mirjam S.; Abiven, Samuel; González Domínguez, Beatriz R.; Hagedorn, Frank; Reisser, Moritz; Walthert, Lorenz; Zimmermann, Stephan; Niklaus, Pascal A.

2016-04-01

It is still largely unknown what drives the vulnerability of soil organic carbon (SOC) stocks to climate change, i.e. the likelihood of a soil to loose its SOC along with the change in environmental conditions. Our objective is to assess the SOC vulnerability of Swiss forest soils and identify its potential drivers: climate (temperature, soil moisture), soil (clay content, pH) and landscape (slope, aspect) properties. Fifty-four sites were selected for balanced spatial and driver magnitudes distribution. We measured the SOC characteristics (content and radiocarbon) and studied the C decomposition by laboratory soil incubations (details in Part I, abstract by B. González Domínguez). In order to assess the current SOC pool distribution and its radiocarbon signatures, we extended the Rothamsted Carbon (RothC) model with radiocarbon (14C) isotope modelling (RothCiso). The RothC model distinguishes four active SOC pools, decomposable and resistant plant material, microbial biomass and humified organic matter, and an inert SOC pool (Jenkinson 1990). The active pools are decomposed and mineralized to CO2 by first order kinetics. The RothCiso assigns all pools a 14C signature, based on the atmospheric 14C concentrations of the past century (plant C inputs) and their turnover. Currently we constrain the model with 14C signatures measured on the 54 fresh and their corresponding archived bulk soil samples, taken 12-24 years before. We were able to reproduce the measured radiocarbon concentrations of the SOC with the RothCiso and first results indicate, that the assumption of an inert SOC pool, that is radiocarbon dead, is not appropriate. In a second step we will compare the SOC mean residence time assessed by the two methodological approaches - incubation (C efflux based) and modelling (C stock based) - and relate it to the environmental drivers mentioned above. With the combination of the two methodological approaches and 14C analysis we hope to gain more insights into

Climate change projections: past and future mysteries of climate science

International Nuclear Information System (INIS)

Meehl, Gerald A.

2007-01-01

Full text: Full text: The history of climate change has been wrapped in mysteries. Some have been solved, and we await the outcome of others. The major mystery of 20th century climate was why did temperatures rise in the early part of the century, level off, and then rise rapidly again after the 1970s? It has only been in the past seven years that advances in climate modelling have allowed us to deconstruct 20th century climate to pull apart the separate influences of natural and human-caused factors. This has allowed us to understand the subtle interplay between these various influences that produced the temperature time evolution. Another mystery has involved extreme weather and climate events. Again, climate models have allowed us to quantify how the small changes in average climate translate into much larger changes of regional extremes. The biggest remaining mysteries in climate science involve the future, and how the climate will evolve over the coming century. Up until now, various scenarios postulating different possible outcomes for 21st century climate, assuming different types of human activities, have been run in the climate models to provide a wide range of possible futures. However, more recently the outlook for global warming is being framed as a combination of mitigation and adaptation. If policy actions are taken to mitigate part of the problem of global warming, then climate models must be relied on to quantify the time-evolving picture of how much regional climate change we must adapt to. Solving this mystery will be the biggest and most important challenge ever taken on by the climate modelling community

Reconstructing a lost Eocene Paradise, Part II: On the utility of dynamic global vegetation models in pre-Quaternary climate studies

Science.gov (United States)

Shellito, Cindy J.; Sloan, Lisa C.

2006-02-01

Models that allow vegetation to respond to and interact with climate provide a unique method for addressing questions regarding feedbacks between the ecosystem and climate in pre-Quaternary time periods. In this paper, we consider how Dynamic Global Vegetation Models (DGVMs), which have been developed for simulations with present day climate, can be used for paleoclimate studies. We begin with a series of tests in the NCAR Land Surface Model (LSM)-DGVM with Eocene geography to examine (1) the effect of removing C 4 grasses from the available plant functional types in the model; (2) model sensitivity to a change in soil texture; and (3), model sensitivity to a change in the value of pCO 2 used in the photosynthetic rate equations. The tests were designed to highlight some of the challenges of using these models and prompt discussion of possible improvements. We discuss how lack of detail in model boundary conditions, uncertainties in the application of modern plant functional types to paleo-flora simulations, and inaccuracies in the model climatology used to drive the DGVM can affect interpretation of model results. However, we also review a number of DGVM features that can facilitate understanding of past climates and offer suggestions for improving paleo-DGVM studies.

Coupling Climate Models and Forward-Looking Economic Models

Science.gov (United States)

Judd, K.; Brock, W. A.

2010-12-01

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

The MARKAL-MACRO model and the climate change

International Nuclear Information System (INIS)

Kypreos, S.

1996-07-01

MARKAL-MACRO and its extensions is a model appropriate to study partial and general equilibrium in the energy markets and the implications of the carbon dioxide mitigation policy. The main advantage of MM is the explicit treatment of energy demand, supply and conversion technologies, including emission control and conservation options, within a general equilibrium framework. The famous gap between top-down and bottom-up models is resolved and the economic implications of environmental and supply policy constraints can be captured either in an aggregated (Macro) or in a sectorial (Micro) level. The multi-regional trade version of the model allows to study questions related to efficient and equitable allocation of cost and benefits associated with the climate change issue. Finally, the stochastic version of the model allows to assess policies related to uncertain and even catastrophic effects and define appropriate hedging strategies. The report is divided in three parts: - the first part gives an overview of the new model structure. It describes its macro economic part and explains its calibration, - the second part refers to the model applications for Switzerland when analyzing the economic implications of curbing CO 2 emissions or policies related to the introduction of a carbon tax, including a hedging strategy, - the last part is organized in form of Appendices and gives a mathematical description and some potential extensions of the model. It describes also a sensitivity analysis done with MARKAL-MACRO in 1992. (author) figs., tabs., refs

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.

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

Science.gov (United States)

Somerville, R. C.

2010-12-01

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

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.

Validating predictions from climate envelope models

Science.gov (United States)

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

2013-01-01

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

Validating predictions from climate envelope models.

Directory of Open Access Journals (Sweden)

James I Watling

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

Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part I: Projected emissions, simulation design, and model evaluation.

Science.gov (United States)

Campbell, Patrick; Zhang, Yang; Yan, Fang; Lu, Zifeng; Streets, David

2018-07-01

Emissions from the transportation sector are rapidly changing worldwide; however, the interplay of such emission changes in the face of climate change are not as well understood. This two-part study examines the impact of projected emissions from the U.S. transportation sector (Part I) on ambient air quality in the face of climate change (Part II). In Part I of this study, we describe the methodology and results of a novel Technology Driver Model (see graphical abstract) that includes 1) transportation emission projections (including on-road vehicles, non-road engines, aircraft, rail, and ship) derived from a dynamic technology model that accounts for various technology and policy options under an IPCC emission scenario, and 2) the configuration/evaluation of a dynamically downscaled Weather Research and Forecasting/Community Multiscale Air Quality modeling system. By 2046-2050, the annual domain-average transportation emissions of carbon monoxide (CO), nitrogen oxides (NO x ), volatile organic compounds (VOCs), ammonia (NH 3 ), and sulfur dioxide (SO 2 ) are projected to decrease over the continental U.S. The decreases in gaseous emissions are mainly due to reduced emissions from on-road vehicles and non-road engines, which exhibit spatial and seasonal variations across the U.S. Although particulate matter (PM) emissions widely decrease, some areas in the U.S. experience relatively large increases due to increases in ship emissions. The on-road vehicle emissions dominate the emission changes for CO, NO x , VOC, and NH 3 , while emissions from both the on-road and non-road modes have strong contributions to PM and SO 2 emission changes. The evaluation of the baseline 2005 WRF simulation indicates that annual biases are close to or within the acceptable criteria for meteorological performance in the literature, and there is an overall good agreement in the 2005 CMAQ simulations of chemical variables against both surface and satellite observations. Copyright © 2018

Coupled Climate-Economy-Biosphere (CoCEB) model - Part 1: Abatement share and investment in low-carbon technologies

Science.gov (United States)

Ogutu, K. B. Z.; D'Andrea, F.; Ghil, M.; Nyandwi, C.; Manene, M. M.; Muthama, J. N.

2015-04-01

The Coupled Climate-Economy-Biosphere (CoCEB) model described herein takes an integrated assessment approach to simulating global change. By using an endogenous economic growth module with physical and human capital accumulation, this paper considers the sustainability of economic growth, as economic activity intensifies greenhouse gas emissions that in turn cause economic damage due to climate change. Different types of fossil fuels and different technologies produce different volumes of carbon dioxide in combustion. The shares of different fuels and their future evolution are not known. We assume that the dynamics of hydrocarbon-based energy share and their replacement with renewable energy sources in the global energy balance can be modeled into the 21st century by use of logistic functions. Various climate change mitigation policy measures are considered. While many integrated assessment models treat abatement costs merely as an unproductive loss of income, we consider abatement activities also as an investment in overall energy efficiency of the economy and decrease of overall carbon intensity of the energy system. The paper shows that these efforts help to reduce the volume of industrial carbon dioxide emissions, lower temperature deviations, and lead to positive effects in economic growth.

Climate forcings and climate sensitivities diagnosed from atmospheric global circulation models

Energy Technology Data Exchange (ETDEWEB)

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

2010-12-15

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

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

NARCIS (Netherlands)

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

2016-01-01

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

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

NARCIS (Netherlands)

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

2016-01-01

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

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

DEFF Research Database (Denmark)

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

2016-01-01

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

Can model weighting improve probabilistic projections of climate change?

Energy Technology Data Exchange (ETDEWEB)

Raeisaenen, Jouni; Ylhaeisi, Jussi S. [Department of Physics, P.O. Box 48, University of Helsinki (Finland)

2012-10-15

Recently, Raeisaenen and co-authors proposed a weighting scheme in which the relationship between observable climate and climate change within a multi-model ensemble determines to what extent agreement with observations affects model weights in climate change projection. Within the Third Coupled Model Intercomparison Project (CMIP3) dataset, this scheme slightly improved the cross-validated accuracy of deterministic projections of temperature change. Here the same scheme is applied to probabilistic temperature change projection, under the strong limiting assumption that the CMIP3 ensemble spans the actual modeling uncertainty. Cross-validation suggests that probabilistic temperature change projections may also be improved by this weighting scheme. However, the improvement relative to uniform weighting is smaller in the tail-sensitive logarithmic score than in the continuous ranked probability score. The impact of the weighting on projection of real-world twenty-first century temperature change is modest in most parts of the world. However, in some areas mainly over the high-latitude oceans, the mean of the distribution is substantially changed and/or the distribution is considerably narrowed. The weights of individual models vary strongly with location, so that a model that receives nearly zero weight in some area may still get a large weight elsewhere. Although the details of this variation are method-specific, it suggests that the relative strengths of different models may be difficult to harness by weighting schemes that use spatially uniform model weights. (orig.)

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

Energy Technology Data Exchange (ETDEWEB)

DeLong, Edward; Harwood, Caroline; Reid, Ann

2011-01-01

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

What lessons from part 2 of the fifth UN's Intergovernmental Panel on Climate Change (IPCC) report?

International Nuclear Information System (INIS)

Laville, Bettina

2014-04-01

This paper analyses part 2 of the fifth UN's Intergovernmental Panel on Climate Change (IPCC) report which describes with a detailed mapping the global warming impacts on species, oceans and economy. The IPCC proposes a geopolitical model of continuous and smooth adaptation to climate change which would imply a new cooperation-creating economy and would mitigate the risks of international conflicts. This new economy must rely on strong public organisations which implies a beforehand restoration of public accounts

Modeling Uncertainty in Climate Change: A Multi-Model Comparison

Energy Technology Data Exchange (ETDEWEB)

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

2015-10-01

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

Climate-model induced differences in the 21st century global and regional glacier contributions to sea-level rise

NARCIS (Netherlands)

Giesen, R.H.|info:eu-repo/dai/nl/304831603; Oerlemans, J.|info:eu-repo/dai/nl/06833656X

2013-01-01

The large uncertainty in future global glacier volume projections partly results from a substantial range in future climate conditions projected by global climate models. This study addresses the effect of global and regional differences in climate input data on the projected twenty-first century

Bayesian hierarchical models for regional climate reconstructions of the last glacial maximum

Science.gov (United States)

Weitzel, Nils; Hense, Andreas; Ohlwein, Christian

2017-04-01

Spatio-temporal reconstructions of past climate are important for the understanding of the long term behavior of the climate system and the sensitivity to forcing changes. Unfortunately, they are subject to large uncertainties, have to deal with a complex proxy-climate structure, and a physically reasonable interpolation between the sparse proxy observations is difficult. Bayesian Hierarchical Models (BHMs) are a class of statistical models that is well suited for spatio-temporal reconstructions of past climate because they permit the inclusion of multiple sources of information (e.g. records from different proxy types, uncertain age information, output from climate simulations) and quantify uncertainties in a statistically rigorous way. BHMs in paleoclimatology typically consist of three stages which are modeled individually and are combined using Bayesian inference techniques. The data stage models the proxy-climate relation (often named transfer function), the process stage models the spatio-temporal distribution of the climate variables of interest, and the prior stage consists of prior distributions of the model parameters. For our BHMs, we translate well-known proxy-climate transfer functions for pollen to a Bayesian framework. In addition, we can include Gaussian distributed local climate information from preprocessed proxy records. The process stage combines physically reasonable spatial structures from prior distributions with proxy records which leads to a multivariate posterior probability distribution for the reconstructed climate variables. The prior distributions that constrain the possible spatial structure of the climate variables are calculated from climate simulation output. We present results from pseudoproxy tests as well as new regional reconstructions of temperatures for the last glacial maximum (LGM, ˜ 21,000 years BP). These reconstructions combine proxy data syntheses with information from climate simulations for the LGM that were

An overview of the Yucca Mountain Global/Regional Climate Modeling Program

International Nuclear Information System (INIS)

Sandoval, R.P.; Behl, Y.K.; Thompson, S.L.

1992-01-01

The US Department of Energy (DOE) has developed a site characterization plan (SCP) to collect detailed information on geology, geohydrology, geochemistry, geoengineering, hydrology, climate, and meteorology (collectively referred to as ''geologic information'') of the Yucca Mountain site. This information will be used to determine if a mined geologic disposal system (MGDS) capable of isolating high-level radioactive waste without adverse effects to public health and safety over 10,000 years, as required by regulations 40 CFR Part 191 and 10 CFR Part 60, could be constructed at the Yucca Mountain site. Forecasts of future climates conditions for the Yucca Mountain area will be based on both empirical and numerical techniques. The empirical modeling is based on the assumption that future climate change will follow past patterns. In this approach, paleclimate records will be analyzed to estimate the nature, timing, and probability of occurrence of certain climate states such as glacials and interglacials over the next 10,000 years. For a given state, key climate parameters such as precipitation and temperature will be assumed to be the same as determined from the paleoclimate data. The numerical approach, which is the primary focus of this paper, involves the numerical solution of basic equations associated with atmospheric motions. This paper describes these equations and the strategy for solving them to predict future climate conditions around Yucca Mountain

Model confirmation in climate economics

Science.gov (United States)

Millner, Antony; McDermott, Thomas K. J.

2016-01-01

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

On the statistical comparison of climate model output and climate data

International Nuclear Information System (INIS)

Solow, A.R.

1991-01-01

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

On the statistical comparison of climate model output and climate data

International Nuclear Information System (INIS)

Solow, A.R.

1990-01-01

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

Making the climate part of the human world: Why addressing beliefs and biases is necessary part of effective climate change education

Science.gov (United States)

Donner, S. D.

2009-12-01

Efforts to raise public awareness and understanding of the social, cultural and economic consequences of climate change often encounter skepticism. The primary causes of this skepticism, whether in the form of a mild rejection of proposed policy responses or an outright rejection of the basic scientific findings, is often cited to be the poor framing of issues by the scientific community, the quality of science education or public science literacy, disinformation campaigns by representatives of the coal and gas industry, individual resistance to behavioral change, and the hyperactive nature of the modern information culture. However, the root cause may be that the weather and climate, and by association climate change, is viewed as independent of the sphere of human influence in ancient and modern societies. In this presentation, I will outline how long-standing human beliefs in the separation between the earth and the sky and the modern framing of climate change as an “environmental” issue are limiting efforts to education the public about the causes, effects and possible response to climate change. First, sociological research in the Pacific Islands (Fiji, Kiribati, Tuvalu) finds strong evidence that beliefs in divine control of the weather and climate limit public acceptance of human-induced climate change. Second, media analysis and polling data from North America supports the role of belief and provides further evidence that climate change is viewed as a threat to an “other” labeled “the environment”, rather than a threat to people or society. The consequences of these mental models of the climate can be an outright reject of scientific theory related to climate change, a milder distrust of climate change predictions, a lack of urgency about mitigation, and an underestimate of the effort required to adapt to climate change. In order to be effective, public education about climate change needs to directly address the two, critical beliefs held by

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

Science.gov (United States)

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

2014-12-01

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

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)

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

Science.gov (United States)

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

2017-04-01

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

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.

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

DEFF Research Database (Denmark)

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

2013-01-01

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

Characterizing and Addressing the Need for Statistical Adjustment of Global Climate Model Data

Science.gov (United States)

White, K. D.; Baker, B.; Mueller, C.; Villarini, G.; Foley, P.; Friedman, D.

2017-12-01

As part of its mission to research and measure the effects of the changing climate, the U. S. Army Corps of Engineers (USACE) regularly uses the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset. However, these data are generated at a global level and are not fine-tuned for specific watersheds. This often causes CMIP5 output to vary from locally observed patterns in the climate. Several downscaling methods have been developed to increase the resolution of the CMIP5 data and decrease systemic differences to support decision-makers as they evaluate results at the watershed scale. Evaluating preliminary comparisons of observed and projected flow frequency curves over the US revealed a simple framework for water resources decision makers to plan and design water resources management measures under changing conditions using standard tools. Using this framework as a basis, USACE has begun to explore to use of statistical adjustment to alter global climate model data to better match the locally observed patterns while preserving the general structure and behavior of the model data. When paired with careful measurement and hypothesis testing, statistical adjustment can be particularly effective at navigating the compromise between the locally observed patterns and the global climate model structures for decision makers.

Climate Model Diagnostic Analyzer Web Service System

Science.gov (United States)

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

2015-12-01

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

Twenty first century climate change as simulated by European climate models

International Nuclear Information System (INIS)

Cubasch, Ulrich

2007-01-01

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

Cyclones and extreme windstorm events over Europe under climate change: Global and regional climate model diagnostics

Science.gov (United States)

Leckebusch, G. C.; Ulbrich, U.

2003-04-01

More than any changes of the climate system mean state conditions, the development of extreme events may influence social, economic and legal aspects of our society. This linkage results from the impact of extreme climate events (natural hazards) on environmental systems which again are directly linked to human activities. Prominent examples from the recent past are the record breaking rainfall amounts of August 2002 in central Europe which produced widespread floodings or the wind storm Lothar of December 1999. Within the MICE (Modelling the Impact of Climate Extremes) project framework an assessment of the impact of changes in extremes will be done. The investigation is carried out for several different impact categories as agriculture, energy use and property damage. Focus is laid on the diagnostics of GCM and RCM simulations under different climate change scenarios. In this study we concentrate on extreme windstorms and their relationship to cyclone activity in the global HADCM3 as well as in the regional HADRM3 model under two climate change scenarios (SRESA2a, B2a). In order to identify cyclones we used an objective algorithm from Murry and Simmonds which was widely tested under several different conditions. A slight increase in the occurrence of systems is identified above northern parts of central Europe for both scenarios. For more severe systems (core pressure Spain) a shift to more deep cyclones connected with an increasing number of strong wind events is found.

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.

Future directions in climate modeling: A climate impacts perspective

International Nuclear Information System (INIS)

Mearns, L.O.

1990-01-01

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

A Scalable and Extensible Earth System Model for Climate Change Science

Energy Technology Data Exchange (ETDEWEB)

Gent, Peter; Lamarque, Jean-Francois; Conley, Andrew; Vertenstein, Mariana; Craig, Anthony

2013-02-13

The objective of this award was to build a scalable and extensible Earth System Model that can be used to study climate change science. That objective has been achieved with the public release of the Community Earth System Model, version 1 (CESM1). In particular, the development of the CESM1 atmospheric chemistry component was substantially funded by this award, as was the development of the significantly improved coupler component. The CESM1 allows new climate change science in areas such as future air quality in very large cities, the effects of recovery of the southern hemisphere ozone hole, and effects of runoff from ice melt in the Greenland and Antarctic ice sheets. Results from a whole series of future climate projections using the CESM1 are also freely available via the web from the CMIP5 archive at the Lawrence Livermore National Laboratory. Many research papers using these results have now been published, and will form part of the 5th Assessment Report of the United Nations Intergovernmental Panel on Climate Change, which is to be published late in 2013.

Multi-model Projection of July-August Climate Extreme Changes over China under CO2 Doubling. Part Ⅰ:Precipitation

Institute of Scientific and Technical Information of China (English)

LI Hongmei; FENG Lei; ZHOU Tianjun

2011-01-01

Potential changes in precipitation extremes in July-August over China in response to CO2 doubling are analyzed based on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models (20C3M) experiment and the 1％ per year CO2 increase experiment (to doubling) (lpctto2x) of phase 3 of the Coupled Model Inter-comparison Project (CMIP3). Evaluation of the models' performance in simulating the mean state shows that the majority of models fairly reproduce the broad spatial pattern of observed precipitation. However, all the models underestimate extreme precipitation by ～50％. The spread among the models over the Tibetan Plateau is ～2-3 times larger than that over the other areas.Models with higher resolution generally perform better than those with lower resolutions in terms of spatial pattern and precipitation amount. Under the lpctto2x scenario, the ratio between the absolute value of MME extreme precipitation change and model spread is larger than that of total precipitation, indicating a relatively robust change of extremes. The change of extreme precipitation is more homogeneous than the total precipitation. Analysis on the output of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 (GFDL-CM2.1) indicates that the spatially consistent increase of surface temperature and water vapor content contribute to the large increase of extreme precipitation over contiguous China,which follows the Clausius-Clapeyron relationship. Whereas, the meridionally tri-polar pattern of mean precipitation change over eastern China is dominated by the change of water vapor convergence, which is determined by the response of monsoon circulation to global warming.

Vulnerability of hydropower generation to climate change in China: Results based on Grey forecasting model

International Nuclear Information System (INIS)

Wang, Bing; Liang, Xiao-Jie; Zhang, Hao; Wang, Lu; Wei, Yi-Ming

2014-01-01

This paper analyzes the long-term relationships between hydropower generation and climate factors (precipitation), hydropower generation capacity (installed capacity of hydropower station) to quantify the vulnerability of renewable energy production in China for the case of hydropower generation. Furthermore, this study applies Grey forecasting model to forecast precipitation in different provinces, and then sets up different scenarios for precipitation based on the IPCC Special Report on Emission Scenarios and results from PRECIS (Providing Regional Climate projections for Impacts Studies) model. The most important result found in this research is the increasing hydropower vulnerability of the poorest regions and the main hydropower generation provinces of China to climate change. Other main empirical results reveal that the impacts of climate change on the supply of hydropower generation in China will be noteworthy for the society. Different scenarios have different effects on hydropower generation, of which A2 scenario (pessimistic, high emission) has the largest. Meanwhile, the impacts of climate change on hydropower generation of every province are distinctly different, of which the Southwest part has the higher vulnerability than the average level while the central part lower. - Highlights: • The hydropower vulnerability will be enlarged with the rapid increase of hydropower capacity. • Modeling the vulnerability of hydropower in different scenarios and different provinces. • The increasing hydropower vulnerability of the poorest regions to climate change. • The increasing hydropower vulnerability of the main hydropower generation provinces. • Rainfall pattern caused by climate change would be the reason for the increasing vulnerability

Climate change as a three-part ethical problem: a response to Jamieson and Gardiner.

Science.gov (United States)

Kingston, Ewan

2014-12-01

Dale Jamieson has claimed that conventional human-directed ethical concepts are an inadequate means for accurately understanding our duty to respond to climate change. Furthermore, he suggests that a responsibility to respect nature can instead provide the appropriate framework with which to understand such a duty. Stephen Gardiner has responded by claiming that climate change is a clear case of ethical responsibility, but the failure of institutions to respond to it creates a (not unprecedented) political problem. In assessing the debate between Gardiner and Jamieson, I develop an analysis which shows a three-part structure to the problem of climate change, in which the problem Gardiner identifies is only one of three sub-problems of climate change. This analysis highlights difficulties with Jamieson's argument that the duty of respect for nature is necessary for a full understanding of climate ethics, and suggests how a human-directed approach based on the three-part analysis can avoid Jamieson's charge of inadequacy.

Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration

Directory of Open Access Journals (Sweden)

M. Meinshausen

2011-02-01

Full Text Available Current scientific knowledge on the future response of the climate system to human-induced perturbations is comprehensively captured by various model intercomparison efforts. In the preparation of the Fourth Assessment Report (AR4 of the Intergovernmental Panel on Climate Change (IPCC, intercomparisons were organized for atmosphere-ocean general circulation models (AOGCMs and carbon cycle models, named "CMIP3" and "C⁴MIP", respectively. Despite their tremendous value for the scientific community and policy makers alike, there are some difficulties in interpreting the results. For example, radiative forcings were not standardized across the various AOGCM integrations and carbon cycle runs, and, in some models, key forcings were omitted. Furthermore, the AOGCM analysis of plausible emissions pathways was restricted to only three SRES scenarios. This study attempts to address these issues. We present an updated version of MAGICC, the simple carbon cycle-climate model used in past IPCC Assessment Reports with enhanced representation of time-varying climate sensitivities, carbon cycle feedbacks, aerosol forcings and ocean heat uptake characteristics. This new version, MAGICC6, is successfully calibrated against the higher complexity AOGCMs and carbon cycle models. Parameterizations of MAGICC6 are provided. The mean of the emulations presented here using MAGICC6 deviates from the mean AOGCM responses by only 2.2% on average for the SRES scenarios. This enhanced emulation skill in comparison to previous calibrations is primarily due to: making a "like-with-like comparison" using AOGCM-specific subsets of forcings; employing a new calibration procedure; as well as the fact that the updated simple climate model can now successfully emulate some of the climate-state dependent effective climate sensitivities of AOGCMs. The diagnosed effective climate sensitivity at the time of CO₂ doubling for the AOGCMs is on average 2.88 °C, about

Climate Ocean Modeling on Parallel Computers

Science.gov (United States)

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

1998-01-01

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

Regional climate change: Precipitation variability in mountainous part of Bulgaria

Directory of Open Access Journals (Sweden)

Nikolova Nina

2007-01-01

Full Text Available The aim of paper is to analyze temporal and spatial changes in monthly precipitation as well as extremely dry and wet months in mountainous part of Bulgaria. Study precipitation variability in mountainous part is very important because this part is the region where the rivers take its source from. Extreme values of monthly precipitation are important information for better understanding of the whole variability and trends in precipitation time series. The mean investigated period is 1951-2005 and the reference period is so called temporary climate - 1961- 1990. Extreme dry precipitation months are defined as a month whose monthly precipitation is lower than 10% of gamma distribution in the reference period 1961-1990. Extreme wet months are determined with respect to 90% percentiles of gamma distribution (monthly precipitation is higher than 90%. The result of the research show that in mountainous part of Bulgaria during 1950s and 1960s number of extremely wet months is higher than number of dry months. Decreasing of monthly precipitation is a feature for 1980s. This dry period continues till 2004. The years 2000 makes impression as driest year in high mountains with about 7 extremely dry months. The second dry year is 1993. The negative precipitation anomaly is most clearly determined during last decade at study area. The present research points out that fluctuation of precipitation in mountainous part of Bulgaria are coinciding with regional and global climate trends.

Selection of climate change scenario data for impact modelling

DEFF Research Database (Denmark)

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

2012-01-01

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

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

KAUST Repository

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

2014-01-01

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

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

KAUST Repository

Merlis, Timothy M.

2014-10-01

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

Climate change impacts utilizing regional models for agriculture, hydrology and natural ecosystems

Science.gov (United States)

Kafatos, M.; Asrar, G. R.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Medvigy, D.; Prasad, A. K.; Smith, E.; Stack, D. H.; Tremback, C.; Walko, R. L.

2012-12-01

Climate change impacts the entire Earth but with crucial and often catastrophic impacts at local and regional levels. Extreme phenomena such as fires, dust storms, droughts and other natural hazards present immediate risks and challenges. Such phenomena will become more extreme as climate change and anthropogenic activities accelerate in the future. We describe a major project funded by NIFA (Grant # 2011-67004-30224), under the joint NSF-DOE-USDA Earth System Models (EaSM) program, to investigate the impacts of climate variability and change on the agricultural and natural (i.e. rangeland) ecosystems in the Southwest USA using a combination of historical and present observations together with climate, and ecosystem models, both in hind-cast and forecast modes. The applicability of the methodology to other regions is relevant (for similar geographic regions as well as other parts of the world with different agriculture and ecosystems) and should advance the state of knowledge for regional impacts of climate change. A combination of multi-model global climate projections from the decadal predictability simulations, to downscale dynamically these projections using three regional climate models, combined with remote sensing MODIS and other data, in order to obtain high-resolution climate data that can be used with hydrological and ecosystem models for impacts analysis, is described in this presentation. Such analysis is needed to assess the future risks and potential impacts of projected changes on these natural and managed ecosystems. The results from our analysis can be used by scientists to assist extended communities to determine agricultural coping strategies, and is, therefore, of interest to wide communities of stakeholders. In future work we will be including surface hydrologic modeling and water resources, extend modeling to higher resolutions and include significantly more crops and geographical regions with different weather and climate conditions

Physical-Socio-Economic Modeling of Climate Change

Science.gov (United States)

Chamberlain, R. G.; Vatan, F.

2008-12-01

Because of the global nature of climate change, any assessment of the effects of plans, policies, and response to climate change demands a model that encompasses the entire Earth System, including socio- economic factors. Physics-based climate models of the factors that drive global temperatures, rainfall patterns, and sea level are necessary but not sufficient to guide decision making. Actions taken by farmers, industrialists, environmentalists, politicians, and other policy makers may result in large changes to economic factors, international relations, food production, disease vectors, and beyond. These consequences will not be felt uniformly around the globe or even across a given region. Policy models must comprehend all of these considerations. Combining physics-based models of the Earth's climate and biosphere with societal models of population dynamics, economics, and politics is a grand challenge with high stakes. We propose to leverage our recent advances in modeling and simulation of military stability and reconstruction operations to models that address all these areas of concern. Following over twenty years' experience of successful combat simulation, JPL has started developing Minerva, which will add demographic, economic, political, and media/information models to capabilities that already exist. With these new models, for which we have design concepts, it will be possible to address a very wide range of potential national and international problems that were previously inaccessible. Our climate change model builds on Minerva and expands the geographical horizon from playboxes containing regions and neighborhoods to the entire globe. This system consists of a collection of interacting simulation models that specialize in different aspects of the global situation. They will each contribute to and draw from a pool of shared data. The basic models are: the physical model; the demographic model; the political model; the economic model; and the media

Quantifying the relevance of adaptive thermal comfort models in moderate thermal climate zones

Energy Technology Data Exchange (ETDEWEB)

Hoof, Joost van; Hensen, Jan L.M. [Faculty of Architecture, Building and Planning, Technische Universiteit Eindhoven, Vertigo 6.18, P.O. Box 513, 5600 MB Eindhoven (Netherlands)

2007-01-15

Standards governing thermal comfort evaluation are on a constant cycle of revision and public review. One of the main topics being discussed in the latest round was the introduction of an adaptive thermal comfort model, which now forms an optional part of ASHRAE Standard 55. Also on a national level, adaptive thermal comfort guidelines come into being, such as in the Netherlands. This paper discusses two implementations of the adaptive comfort model in terms of usability and energy use for moderate maritime climate zones by means of literature study, a case study comprising temperature measurements, and building performance simulation. It is concluded that for moderate climate zones the adaptive model is only applicable during summer months, and can reduce energy for naturally conditioned buildings. However, the adaptive thermal comfort model has very limited application potential for such climates. Additionally we suggest a temperature parameter with a gradual course to replace the mean monthly outdoor air temperature to avoid step changes in optimum comfort temperatures. (author)

A simple conceptual model of abrupt glacial climate events

Directory of Open Access Journals (Sweden)

H. Braun

2007-11-01

Full Text Available Here we use a very simple conceptual model in an attempt to reduce essential parts of the complex nonlinearity of abrupt glacial climate changes (the so-called Dansgaard-Oeschger events to a few simple principles, namely (i the existence of two different climate states, (ii a threshold process and (iii an overshooting in the stability of the system at the start and the end of the events, which is followed by a millennial-scale relaxation. By comparison with a so-called Earth system model of intermediate complexity (CLIMBER-2, in which the events represent oscillations between two climate states corresponding to two fundamentally different modes of deep-water formation in the North Atlantic, we demonstrate that the conceptual model captures fundamental aspects of the nonlinearity of the events in that model. We use the conceptual model in order to reproduce and reanalyse nonlinear resonance mechanisms that were already suggested in order to explain the characteristic time scale of Dansgaard-Oeschger events. In doing so we identify a new form of stochastic resonance (i.e. an overshooting stochastic resonance and provide the first explicitly reported manifestation of ghost resonance in a geosystem, i.e. of a mechanism which could be relevant for other systems with thresholds and with multiple states of operation. Our work enables us to explicitly simulate realistic probability measures of Dansgaard-Oeschger events (e.g. waiting time distributions, which are a prerequisite for statistical analyses on the regularity of the events by means of Monte-Carlo simulations. We thus think that our study is an important advance in order to develop more adequate methods to test the statistical significance and the origin of the proposed glacial 1470-year climate cycle.

Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

Science.gov (United States)

West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.

2016-01-01

Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

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

Investigations of the Climate System Response to Climate Engineering in a Hierarchy of Models

Science.gov (United States)

McCusker, Kelly E.

Global warming due to anthropogenic emissions of greenhouse gases is causing negative impacts on diverse ecological and human systems around the globe, and these impacts are projected to worsen as climate continues to warm. In the absence of meaningful greenhouse gas emissions reductions, new strategies have been proposed to engineer the climate, with the aim of preventing further warming and avoiding associated climate impacts. We investigate one such strategy here, falling under the umbrella of `solar radiation management', in which sulfate aerosols are injected into the stratosphere. We use a global climate model with a coupled mixed-layer depth ocean and with a fully-coupled ocean general circulation model to simulate the stabilization of climate by balancing increasing carbon dioxide with increasing stratospheric sulfate concentrations. We evaluate whether or not severe climate impacts, such as melting Arctic sea ice, tropical crop failure, or destabilization of the West Antarctic ice sheet, could be avoided. We find that while tropical climate emergencies might be avoided by use of stratospheric aerosol injections, avoiding polar emergencies cannot be guaranteed due to large residual climate changes in those regions, which are in part due to residual atmospheric circulation anomalies. We also find that the inclusion of a fully-coupled ocean is important for determining the regional climate response because of its dynamical feedbacks. The efficacy of stratospheric sulfate aerosol injections, and solar radiation management more generally, depends on its ability to be maintained indefinitely, without interruption from a variety of possible sources, such as technological failure, a breakdown in global cooperation, lack of funding, or negative unintended consequences. We next consider the scenario in which stratospheric sulfate injections are abruptly terminated after a multi- decadal period of implementation while greenhouse gas emissions have continued unabated

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

Science.gov (United States)

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

2012-12-01

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

Modeling lakes and reservoirs in the climate system

Science.gov (United States)

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

2009-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2018-01-01

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

An analytical model for climatic predictions

International Nuclear Information System (INIS)

Njau, E.C.

1990-12-01

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

Climatic change and impacts: a general introduction

International Nuclear Information System (INIS)

Fantechi, R.; Almeida-Teixeira, M.E.; Maracchi, G.

1991-01-01

These proceedings are divided into six parts containing 29 technical papers. 1. An Overview of the Climatic System, 2. Past climate Changes, 3. Climate Processes and Climate Modelling, 4. Greenhouse Gas Induced Climate Change, 5. Climatic Impacts, 6. STUDENTS' PAPERS

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

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

Energy Technology Data Exchange (ETDEWEB)

Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States)

2016-10-17

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate through polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.

Abilities and limitations in the use of regional climate models

Energy Technology Data Exchange (ETDEWEB)

Koeltzov, Morten Andreas Oedegaard

2012-11-01

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

Business models for maximising the diffusion of technological innovations for climate-smart agriculture

NARCIS (Netherlands)

Long, Thomas B.; Blok, Vincent; Poldner, Kim

2017-01-01

Technological innovations will play a prominent role in the transition to climate-smart agriculture (CSA). However, CSA technological innovation diffusion is subject to socio-economic barriers. The success of innovations is partly dependent on the business models that are used to diffuse them.

Modelling and observing urban climate in the Netherlands

International Nuclear Information System (INIS)

Van Hove, B.; Steeneveld, G.J.; Heusinkveld, B.; Holtslag, B.; Jacobs, C.; Ter Maat, H.; Elbers, J.; Moors, E.

2011-06-01

impression of the model performance under Dutch climatic conditions is obtained from a number of online simulations with the non-calibrated versions of NSLUCM-WRF (NSLUCM stands for NOAH land surface model/Single-layer Urban Canopy model) and TEB-RAMS (Town Energy Balance - Regional Atmospheric Modeling System). These simulations have been carried out for the city of Rotterdam and their results are discussed in Chapter 4. Chapter 5 gives an inventory of the available datasets for model validation and parameterization. Also, the possibility to use data from hobby meteorologists will be discussed. Chapter 6 deals with the 'measuring strategy' that will be illustrated by the measurements carried out as part of the Hotspot Heat Stress Rotterdam project. Finally, in chapter 7, conclusions and recommendations are presented.

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

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

Natural and anthropogenic climate change

International Nuclear Information System (INIS)

Ko, M.K.W.; Clough, S.A.; Molnar, G.I.; Iacono, M.; Wang, W.C.; State Univ. of New York, Albany, NY

1992-03-01

This report consists of two parts: (1) progress for the period 9/1/91--3/31/92 and (2) the plan for the remaining period 4/1/92--8/31/92. The project includes two tasks: atmospheric radiation and improvement of climate models to evaluate the climatic effects of radiation changes. The atmospheric radiation task includes four subtasks: (1) Intercomparison of Radiation Codes in Climate Models (ICRCCM), (2) analysis of the water vapor continuum using line-by-line calculations to develop a parameterization for use in climate models, (3) parameterization of longwave radiation and (4) climate/radiation interactions of desert aerosols. Our effort in this period is focused on the first three subtasks. The improvement of climate models to evaluate the subtasks: (1) general circulation model study and (2) 2- D model development and application

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

Science.gov (United States)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as "field" or "global" significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Monthly temperature climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the

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

Science.gov (United States)

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

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

A Michelle Lawing

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

Consistency and discrepancy in the atmospheric response to Arctic sea-ice loss across climate models

Science.gov (United States)

Screen, James A.; Deser, Clara; Smith, Doug M.; Zhang, Xiangdong; Blackport, Russell; Kushner, Paul J.; Oudar, Thomas; McCusker, Kelly E.; Sun, Lantao

2018-03-01

The decline of Arctic sea ice is an integral part of anthropogenic climate change. Sea-ice loss is already having a significant impact on Arctic communities and ecosystems. Its role as a cause of climate changes outside of the Arctic has also attracted much scientific interest. Evidence is mounting that Arctic sea-ice loss can affect weather and climate throughout the Northern Hemisphere. The remote impacts of Arctic sea-ice loss can only be properly represented using models that simulate interactions among the ocean, sea ice, land and atmosphere. A synthesis of six such experiments with different models shows consistent hemispheric-wide atmospheric warming, strongest in the mid-to-high-latitude lower troposphere; an intensification of the wintertime Aleutian Low and, in most cases, the Siberian High; a weakening of the Icelandic Low; and a reduction in strength and southward shift of the mid-latitude westerly winds in winter. The atmospheric circulation response seems to be sensitive to the magnitude and geographic pattern of sea-ice loss and, in some cases, to the background climate state. However, it is unclear whether current-generation climate models respond too weakly to sea-ice change. We advocate for coordinated experiments that use different models and observational constraints to quantify the climate response to Arctic sea-ice loss.

Modelling the Impacts of Climate Change on Tropospheric Ozone over three Centuries

Science.gov (United States)

Brandt Hedegaard, Gitte; Brandt, Jørgen; Christensen, Jesper H.; Gross, Allan; May, Wihelm; Hansen, Kaj M.; Skjøth, Carsten A.

2010-05-01

populated areas with high NOx concentrations the ozone concentration will increase significantly in the future solely due to climate change and the resulting changes in biogenic emissions. REFERENCES Christensen, J. H., The Danish Eulerian Hemispheric Model - a Three-Dimensional Air Pollution Model Used for the Arctic: Atmospheric Environment, 31, 4169-4191, 1997. Frohn, L. M., Christensen, J. H., and Brandt, J. , Development and testing of numerical methods for two-way nested air pollution modelling: Physics and Chemistry of the Earth, 27, 1487-1494, 2002a. Frohn, L. M., Christensen, J. H., and Brandt, J. , Development of a high-resolution nested air pollution model - The numerical approach: Journal of Computational Physics, 179, 68-94, 2002b. May, W., Climatic changes associated with a global "2 degrees C-stabilization" scenario simulated by the ECHAM5/MPI-OM coupled climate model: Climate Dynamics, 31, 283-313, 2008. Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U., and Tompkins, A. 2003 , The atmospheric general circulation model ECHAM5. Part I. Report No. 349. Max-Planck-Institute für Meteorologie, Hamburg, Germany, pp 127.

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.

Economy-Energy-Climate Interaction. The Model Wiagem

International Nuclear Information System (INIS)

Kemfert, C.

2001-09-01

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

Atmospheric sulfur and climate changes: a modelling study at mid and high-southern latitudes

International Nuclear Information System (INIS)

Castebrunet, H.

2007-09-01

The mid and high-southern latitudes are still marginally affected by anthropogenic sulfur emissions. They are the only regions in the world where the natural cycle of the atmospheric sulfur may still be observed. Sulfur aerosols are well-known for their radiative impact, and thus interact with climate. Climate can in turn affect atmospheric sulfur sources, distribution and chemistry. Antarctic ice cores provide information on the evolution of climate and sulfur deposition at the surface of the ice sheet at glacial-interglacial time scales. The aim of this thesis is to develop and use modeling towards a better understanding of the atmospheric sulfur cycle in antarctic and sub-antarctic regions. Ice core data are used to validate model results under glacial climate conditions. An Atmospheric General Circulation Model (AGCM) coupled to a sulfur chemistry module is used: the LMD-ZTSulfur model, version 4. An update of both the physical and chemical parts of the model. The model was first performed. The impact of there changes on modelled sulfur cycle are evaluated for modern climate. Further, boundary conditions are adapted to simulate the atmospheric circulation and sulfur cycle at the Last Glacial Maximum, approximately 20,000 years ago. In the model, sulfur is found to be highly sensitive to antarctic sea-ice coverage, which is still poorly known during the ice age. An original dataset of ice-age sea-ice coverage was developed. Its impact on the oceanic emissions of dimethyl sulfide, main precursor of sulfur aerosols at high-southern latitudes, is discussed. Using the same oceanic sulfur reservoirs as for present day climate, the model broadly reproduces the glacial deposits of sulfur aerosols on the Antarctic plateau, suggesting little impact of climate on oceanic sulfur production in the Antarctic region. Sensitivity tests were carried out to draw an up-to-date status of major uncertainties and difficulties facing future progress in understanding atmospheric

Assessing NARCCAP climate model effects using spatial confidence regions

Directory of Open Access Journals (Sweden)

J. P. French

2017-07-01

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

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

Science.gov (United States)

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

2017-12-01

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

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

International Nuclear Information System (INIS)

Husain, T.; Chowdhury, S.

2009-01-01

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

Developing climatic scenarios for pesticide fate modelling in Europe

International Nuclear Information System (INIS)

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

2008-01-01

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

Long-term climate: interpretation of the Vostok Antarctica drilling data, development of a zonally averaged dynamic model of the atmosphere

International Nuclear Information System (INIS)

Genthon, Christophe

1988-01-01

In a first part of the dissertation, data related to the evolution of the Earth climate and environment are analysed in order to elucidate some possible mechanisms of climatic transition on the time scale of the recent Pleistocene glacial to interglacial cycles. The Vostok (East Antarctica) temperature and the carbon dioxide atmospheric concentration (global) profiles, obtained on a time range of ∼160000 years from analysing a deep ice core drilled at Vostok are the basis of this study. A simple model for statistically reconstructing the temperature profile is implemented, the input functions of which are selected from hypotheses on the forcing of the climate at Vostok. These hypotheses are supported by the presence of the astronomical theory of paleo-climate's characteristic spectral bands in the two signals, by the high correlation between the variations of temperature with that of CO 2 , and by the fair coherence of these records with other paleo-climatic series from ocean sediment cores. An important contribution of the thermal greenhouse effect of CO 2 is suggested through this approach, in reasonable agreement with results obtained by other researchers using general circulation models. We also describe a dynamical model of the atmosphere which uses the zonally averaged primitive equations. This model is being developed as part of a project on modelling the globally coupled climatic System (atmosphere, ocean, cryo-sphere). For both the dynamical and diabatic physical parts, it is a reduction to two dimensions (latitude and altitude) of a general circulation atmospheric model. The large scale turbulence of the middle and high latitudes cannot be resolved with such a configuration: we describe parametrizations of the transports of sensible and latent heat by the baro-clinic eddies, and a preliminary study of the transport of momentum. These parametrizations make use of the mixing length theory, the mixing coefficients being determined from the local

A Caveat Note on Tuning in the Development of Coupled Climate Models

Science.gov (United States)

Dommenget, Dietmar; Rezny, Michael

2018-01-01

State-of-the-art coupled general circulation models (CGCMs) have substantial errors in their simulations of climate. In particular, these errors can lead to large uncertainties in the simulated climate response (both globally and regionally) to a doubling of CO2. Currently, tuning of the parameterization schemes in CGCMs is a significant part of the developed. It is not clear whether such tuning actually improves models. The tuning process is (in general) neither documented, nor reproducible. Alternative methods such as flux correcting are not used nor is it clear if such methods would perform better. In this study, ensembles of perturbed physics experiments are performed with the Globally Resolved Energy Balance (GREB) model to test the impact of tuning. The work illustrates that tuning has, in average, limited skill given the complexity of the system, the limited computing resources, and the limited observations to optimize parameters. While tuning may improve model performance (such as reproducing observed past climate), it will not get closer to the "true" physics nor will it significantly improve future climate change projections. Tuning will introduce artificial compensating error interactions between submodels that will hamper further model development. In turn, flux corrections do perform well in most, but not all aspects. A main advantage of flux correction is that it is much cheaper, simpler, more transparent, and it does not introduce artificial error interactions between submodels. These GREB model experiments should be considered as a pilot study to motivate further CGCM studies that address the issues of model tuning.

Assessing climate change impact by integrated hydrological modelling

Science.gov (United States)

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

2013-04-01

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

Climate versus carbon dioxide controls on biomass burning: a model analysis of the glacial-interglacial contrast

Science.gov (United States)

Calvo, M. Martin; Prentice, I. C.; Harrison, S. P.

2014-11-01

Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness. CO2 concentration constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence on CO2 concentration, the quantitative relationship between atmospheric CO2 concentration and biomass burning is not well understood. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial-interglacial changes in biomass burning to an increase in CO2, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided last glacial maximum (LGM) climate anomalies - that is, differences from the pre-industrial (PI) control climate - from the Palaeoclimate Modelling Intercomparison Project Phase~2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes from biomass burning were corrected for the model's observed prediction biases in contemporary regional average values for biomes. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux at the LGM was in the range of 1.0-1.4 Pg C year-1, about a third less than that modelled for PI time. LGM climate with pre-industrial CO2 (280 ppm) yielded unrealistic results, with global biomass burning fluxes similar to or even greater than in the pre-industrial climate. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on primary production and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to project future fire risks.

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

Directory of Open Access Journals (Sweden)

Xian-Ge Hu

2017-12-01

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

A paradigm shift toward a consistent modeling framework to assess climate impacts

Science.gov (United States)

Monier, E.; Paltsev, S.; Sokolov, A. P.; Fant, C.; Chen, H.; Gao, X.; Schlosser, C. A.; Scott, J. R.; Dutkiewicz, S.; Ejaz, Q.; Couzo, E. A.; Prinn, R. G.; Haigh, M.

2017-12-01

Estimates of physical and economic impacts of future climate change are subject to substantial challenges. To enrich the currently popular approaches of assessing climate impacts by evaluating a damage function or by multi-model comparisons based on the Representative Concentration Pathways (RCPs), we focus here on integrating impacts into a self-consistent coupled human and Earth system modeling framework that includes modules that represent multiple physical impacts. In a sample application we show that this framework is capable of investigating the physical impacts of climate change and socio-economic stressors. The projected climate impacts vary dramatically across the globe in a set of scenarios with global mean warming ranging between 2.4°C and 3.6°C above pre-industrial by 2100. Unabated emissions lead to substantial sea level rise, acidification that impacts the base of the oceanic food chain, air pollution that exceeds health standards by tenfold, water stress that impacts an additional 1 to 2 billion people globally and agricultural productivity that decreases substantially in many parts of the world. We compare the outcomes from these forward-looking scenarios against the common goal described by the target-driven scenario of 2°C, which results in much smaller impacts. It is challenging for large internationally coordinated exercises to respond quickly to new policy targets. We propose that a paradigm shift toward a self-consistent modeling framework to assess climate impacts is needed to produce information relevant to evolving global climate policy and mitigation strategies in a timely way.

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

Surface energy balances of three general circulation models: Current climate and response to increasing atmospheric CO2

International Nuclear Information System (INIS)

Gutowski, W.J.; Gutzler, D.S.; Portman, D.; Wang, W.C.

1988-04-01

The surface energy balance simulated by state-of-the-art general circulation models at GFDL, GISS and NCAR for climates with current levels of atmospheric CO 2 concentration (control climate) and with twice the current levels. The work is part of an effort sponsored by the US Department of Energy to assess climate simulations produced by these models. The surface energy balance enables us to diagnose differences between models in surface temperature climatology and sensitivity to doubling CO 2 in terms of the processes that control surface temperature. Our analysis compares the simulated balances by averaging the fields of interest over a hierarchy of spatial domains ranging from the entire globe down to regions a few hundred kilometers across

Tropical convection regimes in climate models: evaluation with satellite observations

Directory of Open Access Journals (Sweden)

A. K. Steiner

2018-04-01

Full Text Available High-quality observations are powerful tools for the evaluation of climate models towards improvement and reduction of uncertainty. Particularly at low latitudes, the most uncertain aspect lies in the representation of moist convection and interaction with dynamics, where rising motion is tied to deep convection and sinking motion to dry regimes. Since humidity is closely coupled with temperature feedbacks in the tropical troposphere, a proper representation of this region is essential. Here we demonstrate the evaluation of atmospheric climate models with satellite-based observations from Global Positioning System (GPS radio occultation (RO, which feature high vertical resolution and accuracy in the troposphere to lower stratosphere. We focus on the representation of the vertical atmospheric structure in tropical convection regimes, defined by high updraft velocity over warm surfaces, and investigate atmospheric temperature and humidity profiles. Results reveal that some models do not fully capture convection regions, particularly over land, and only partly represent strong vertical wind classes. Models show large biases in tropical mean temperature of more than 4 K in the tropopause region and the lower stratosphere. Reasonable agreement with observations is given in mean specific humidity in the lower to mid-troposphere. In moist convection regions, models tend to underestimate moisture by 10 to 40 % over oceans, whereas in dry downdraft regions they overestimate moisture by 100 %. Our findings provide evidence that RO observations are a unique source of information, with a range of further atmospheric variables to be exploited, for the evaluation and advancement of next-generation climate models.

Tropical convection regimes in climate models: evaluation with satellite observations

Science.gov (United States)

Steiner, Andrea K.; Lackner, Bettina C.; Ringer, Mark A.

2018-04-01

High-quality observations are powerful tools for the evaluation of climate models towards improvement and reduction of uncertainty. Particularly at low latitudes, the most uncertain aspect lies in the representation of moist convection and interaction with dynamics, where rising motion is tied to deep convection and sinking motion to dry regimes. Since humidity is closely coupled with temperature feedbacks in the tropical troposphere, a proper representation of this region is essential. Here we demonstrate the evaluation of atmospheric climate models with satellite-based observations from Global Positioning System (GPS) radio occultation (RO), which feature high vertical resolution and accuracy in the troposphere to lower stratosphere. We focus on the representation of the vertical atmospheric structure in tropical convection regimes, defined by high updraft velocity over warm surfaces, and investigate atmospheric temperature and humidity profiles. Results reveal that some models do not fully capture convection regions, particularly over land, and only partly represent strong vertical wind classes. Models show large biases in tropical mean temperature of more than 4 K in the tropopause region and the lower stratosphere. Reasonable agreement with observations is given in mean specific humidity in the lower to mid-troposphere. In moist convection regions, models tend to underestimate moisture by 10 to 40 % over oceans, whereas in dry downdraft regions they overestimate moisture by 100 %. Our findings provide evidence that RO observations are a unique source of information, with a range of further atmospheric variables to be exploited, for the evaluation and advancement of next-generation climate models.

Instructional Climates in Preschool Children Who Are At-Risk. Part II: Perceived Physical Competence

Science.gov (United States)

Robinson, Leah E.; Rudisill, Mary E.; Goodway, Jacqueline D.

2009-01-01

In Part II of this study, we examined the effect of two 9-week instructional climates (low-autonomy [LA] and mastery motivational climate [MMC]) on perceived physical competence (PPC) in preschoolers (N = 117). Participants were randomly assigned to an LA, MMC, or comparison group. PPC was assessed by a pretest, posttest, and retention test with…

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.)

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

Science.gov (United States)

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

2004-06-01

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

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

CSIR Research Space (South Africa)

Engelbrecht, FA

2011-12-01

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

The regional climate model RegCM3 performances over several regions and climate regimes

Science.gov (United States)

Coppola, E.; Rauscher, S.; Gao, X.; Giorgi, F.; Im, E. S.; Mariotti, L.; Seth, A.; Sylla, M. B.

2009-04-01

Regional Climate models are more and more needed to provide high resolution regional climate information in climate impact studies. Water availability in a future scenario is the main request of policy makers for adaptation and mitigation purposes. However precipitation changes are unlikely to be as spatially coherent as temperature changes and they are closely related to the regional model itself. In addition model skill varies regionally. An example of several ICTP regional climate model (RegCM3) simulations is reported over China, Korea, Africa, Central and Southern America, Europe and Australia. Over China, Australia, and Korea the regional model improves the simulation compared to the driving GCM when compared with CRU observations. In China, for example, the higher resolution of the regional model inhibits the penetration of the monsoon precipitation front from the southern slope of the Himalaya onto the Tibetan Plateau. In Korea the nested domain simulation (20 km) shows an encouraging performance with regard to capturing extreme precipitation episodes and the finer spatial distribution reflects the detailed geography of the Korean Peninsula. Over South America, RegCM captures the annual cycle of precipitation over Northeast Brazil and the South American Monsoon region, although the monsoon onset occurs too early in the model. Precipitation over the Amazon is not well captured, with too little precipitation associated with weak easterlies and reduced moisture transport into the interior of the continent. RegCM simulates the annual cycle of precipitation over Central America and the Caribbean fairly well; in particular, the complex spatial distribution of the Mid-Summer Drought, a decrease in precipitation that occurs during the middle of the rainy season in July and August, is better captured by RegCM than by the GCM. In addition, RegCM simulates the strength and position of the Caribbean low level jet, a mesoscale feature related to precipitation anomalies

Assessing and addressing moral distress and ethical climate Part II: neonatal and pediatric perspectives.

Science.gov (United States)

Sauerland, Jeanie; Marotta, Kathleen; Peinemann, Mary Anne; Berndt, Andrea; Robichaux, Catherine

2015-01-01

Moral distress remains a pervasive and, at times, contested concept in nursing and other health care disciplines. Ethical climate, the conditions and practices in which ethical situations are identified, discussed, and decided, has been shown to exacerbate or ameliorate perceptions of moral distress. The purpose of this mixed-methods study was to explore perceptions of moral distress, moral residue, and ethical climate among registered nurses working in an academic medical center. Two versions of the Moral Distress Scale in addition to the Hospital Ethical Climate Survey were used, and participants were invited to respond to 2 open-ended questions. Part I reported the findings among nurses working in adult acute and critical care units. Part II presents the results from nurses working in pediatric/neonatal units. Significant differences in findings between the 2 groups are discussed. Subsequent interventions developed are also presented.

Different parts, different stories: climate sensitivity of growth is stronger in root collars vs. stems in tundra shrubs.

Science.gov (United States)

Ropars, Pascale; Angers-Blondin, Sandra; Gagnon, Marianne; Myers-Smith, Isla H; Lévesque, Esther; Boudreau, Stéphane

2017-08-01

Shrub densification has been widely reported across the circumpolar arctic and subarctic biomes in recent years. Long-term analyses based on dendrochronological techniques applied to shrubs have linked this phenomenon to climate change. However, the multi-stemmed structure of shrubs makes them difficult to sample and therefore leads to non-uniform sampling protocols among shrub ecologists, who will favor either root collars or stems to conduct dendrochronological analyses. Through a comparative study of the use of root collars and stems of Betula glandulosa, a common North American shrub species, we evaluated the relative sensitivity of each plant part to climate variables and assessed whether this sensitivity is consistent across three different types of environments in northwestern Québec, Canada (terrace, hilltop and snowbed). We found that root collars had greater sensitivity to climate than stems and that these differences were maintained across the three types of environments. Growth at the root collar was best explained by spring precipitation and summer temperature, whereas stem growth showed weak and inconsistent responses to climate variables. Moreover, sensitivity to climate was not consistent among plant parts, as individuals having climate-sensitive root collars did not tend to have climate-sensitive stems. These differences in sensitivity of shrub parts to climate highlight the complexity of resource allocation in multi-stemmed plants. Whereas stem initiation and growth are driven by microenvironmental variables such as light availability and competition, root collars integrate the growth of all plant parts instead, rendering them less affected by mechanisms such as competition and more responsive to signals of global change. Although further investigations are required to determine the degree to which these findings are generalizable across the tundra biome, our results indicate that consistency and caution in the choice of plant parts are a key

Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts

Science.gov (United States)

Irby, Isaac David

Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research achieves that goal in three parts. First, a set of eight water quality models is used to establish a model mean and assess model skill. All models were found to exhibit similar skill in resolving dissolved oxygen concentrations as well as a number of dissolved oxygen-influencing variables (temperature, salinity, stratification, chlorophyll and nitrate) and the model mean exhibited the highest individual skill. The location of stratification within the water column was found to be a limiting factor in the models' ability to adequately simulate habitat compression resulting from low-oxygen conditions. Second, two of the previous models underwent the regulatory Chesapeake Bay pollution diet mandated by the Environmental Protection Agency. Both models exhibited a similar relative improvement in dissolved oxygen concentrations as a result of the reduction of nutrients stipulated in the pollution diet. A Confidence Index was developed to identify the locations of the Bay where the models are in agreement and disagreement regarding the impacts of the pollution diet. The models were least certain in the deep part of the upper main stem of the Bay and the uncertainty primarily stemmed from the post-processing methodology. Finally, by projecting the impacts of climate change in 2050 on the Bay, the potential success of the

Response of air-sea carbon fluxes and climate to orbital forcing changes in the Community Climate System Model

Science.gov (United States)

Jochum, M.; Peacock, S.; Moore, K.; Lindsay, K.

2010-07-01

A global general circulation model coupled to an ocean ecosystem model is used to quantify the response of carbon fluxes and climate to changes in orbital forcing. Compared to the present-day simulation, the simulation with the Earth's orbital parameters from 115,000 years ago features significantly cooler northern high latitudes but only moderately cooler southern high latitudes. This asymmetry is explained by a 30% reduction of the strength of the Atlantic Meridional Overturning Circulation that is caused by an increased Arctic sea ice export and a resulting freshening of the North Atlantic. The strong northern high-latitude cooling and the direct insolation induced tropical warming lead to global shifts in precipitation and winds to the order of 10%-20%. These climate shifts lead to regional differences in air-sea carbon fluxes of the same order. However, the differences in global net air-sea carbon fluxes are small, which is due to several effects, two of which stand out: first, colder sea surface temperature leads to a more effective solubility pump but also to increased sea ice concentration which blocks air-sea exchange, and second, the weakening of Southern Ocean winds that is predicted by some idealized studies occurs only in part of the basin, and is compensated by stronger winds in other parts.

Understanding National Models for Climate Assessments

Science.gov (United States)

Dave, A.; Weingartner, K.

2017-12-01

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

Nuclear is part of the solution for fighting climate change

International Nuclear Information System (INIS)

Le Ngoc, Boris; Langegger, Eileen; Janin, Denis

2016-11-01

Nuclear for Climate recognize the conclusions of Working Group I of the IPCC (Intergovernmental Panel on Climate Change), which states that human activity and greenhouse gas emissions are - with 95 percent certainty - the dominant cause of current climate change. We welcome the Paris Agreement which was adopted at the 21. Conference of the Parties to the United Nations Framework Convention on Climate Change - widely known as COP 21 - in December 2015 and has entered into force 4 November, just before the COP22. We support its main aim to keep global temperature increases this century well below 2 degrees Celsius, and drive efforts to limit temperature increases to below 1.5 degrees Celsius, which the UNFCCC says is a 'significantly safer' defense against the worst impacts of climate change. We believe that nuclear energy is a key part of the solution for limiting climate change, and that: 1. The world must increase the deployment of all low-carbon energy sources, including nuclear energy, if it is to limit climate change while still meeting development goals. The global challenge is immense: by 2050, according to the IPCC, 80 percent of global electricity will need to be produced with low-carbon technology (compared with 30 percent today) in order to contain climate change below 2 deg. C. During the same period, global demand for electricity should double to meet the basic needs of humanity in terms of population growth and development goals. Low-carbon electricity is expected to play a major role in de-carbonizing other sectors. This challenge requires the use of all low-carbon energy technologies: renewables, nuclear, and fossil fuels with carbon capture and sequestration, and underscores the need for large-scale low- or no-carbon electric generation options. The IPCC recognizes that 'The life cycle greenhouse gas emissions per kilowatt-hour from nuclear power plants are two orders of magnitude lower than those of fossil-fueled electricity generation and

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.

Workshop: Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis: Modeling Climate Change Impacts and Associated Economic Damages (2010 - part 1)

Science.gov (United States)

The purpose of this workshop Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis. focused on conceptual and methodological issues - integrated assessment modeling and valuation.

Chemistry and climate change

International Nuclear Information System (INIS)

Bernier, Jean-Claude; Brasseur, Guy; Brechet, Yves; Candel, Sebastien; Cazenave, Anny; Courtillot, Vincent; Fontecave, Marc; Garnier, Emmanuel; Goebel, Philippe; Legrand, Jack; Legrand, Michel; Le Treut, Herve; Mauberger, Pascal; Dinh-Audouin, Minh-Thu; Olivier, Daniele; Rigny, Paul; Bigot, Bernard

2016-01-01

In its first part, this collective publication addresses the decennial and centuries-old variations of climate: perspectives and implications of climate change for the 21. century, questions remaining about the understanding of climate change from its sources to its modelling, extreme climate variations and societies during the last millennium. The contributions of the second part outline how chemistry is a tool to study climate change: ice chemistry as an archive of our past environment, observations and predictions on sea level rise, relationship between atmosphere chemistry and climate. The third set of contributions discusses the transformation of the energy system for a cleaner atmosphere and the management of the climate risk: the chemical processing of CO_2, actions of chemical companies to support the struggle against climate change, relationship between barrel price and renewable energies, relationship between grid complexity and green energy. The last part outlines the role chemistry can have to be able to do without fossil fuels: chemistry in front of challenges of transformation of the energy system, the use of micro-algae, the use of hydrogen as a vector of energy transition

The international coordination of climate model validation and intercomparison

Energy Technology Data Exchange (ETDEWEB)

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

1996-12-31

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

The international coordination of climate model validation and intercomparison

Energy Technology Data Exchange (ETDEWEB)

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

1995-12-31

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

Climate vs. carbon dioxide controls on biomass burning: a model analysis of the glacial-interglacial contrast

Science.gov (United States)

Calvo, M. Martin; Prentice, I. C.; Harrison, S. P.

2014-02-01

Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness; CO2 availability, in turn, constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence CO2 availability, the links between atmospheric CO2 and biomass burning are not well known. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial-interglacial changes in biomass burning to CO2 increase, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided Last Glacial Maximum (LGM) climate anomalies - that is, differences from the pre-industrial (PI) control climate - from the Palaeoclimate Modelling Intercomparison Project Phase 2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes in biomass burning were corrected for the model's observed biases in contemporary biome-average values. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux was 70 to 80% lower at the LGM than in PI time. LGM climate with pre-industrial CO2 (280 ppm) however yielded unrealistic results, with global and Northern Hemisphere biomass burning fluxes greater than in the pre-industrial climate. Using the PI CO2 concentration increased the modelled LGM biomass burning fluxes for all climate models and latitudinal bands to between four and ten times their values under LGM CO2 concentration. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on productivity and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to

Modeling U.S. water resources under climate change

Science.gov (United States)

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

2014-04-01

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

Poverty and Climate Change. Part 1. Reducing the Vulnerability of the Poor through Adaptation

Energy Technology Data Exchange (ETDEWEB)

Abeygunawardena, P. [Asian Development Bank ADB, Tokyo (Japan); Vyas, Y. [African Development Bank AfDB, Abidjan (Cote d' Ivoire); Knill, P. [Federal German Ministry for Economic Cooperation and Development BMZ, Bonn (Germany); Foy, T.; Harrold, M.; Steele, P.; Tanner, T. [Department for International Developmen DFID, London (United Kingdom); Hirsch, D.; Oosterman, M.; Rooimans, J. [Development Cooperation DGIS, Ministry of Foreign Affairs, Den Haag (Netherlands); Debois, M.; Lamin, M. [Directorate-General for Development, European Commission EC, Brussels (Belgium); Liptow, H.; Mausolf, E.; Verheyen, R. [Deutsche Gesellschaft fuer Technische Zusammenarbeit GTZ, Eschborn (Germany); Agrawala, S.; Caspary, G.; Paris, R. [Organization for Economic Cooperation and Development OECD, Paris (France); Kashyap, A. [United Nations Development Programme UNDP, New York, NY (United States); Sharma, R. [United Nations Environment Programme UNEP, Nairobi (Kenya); Mathur, A.; Sharma, M.; Sperling, F. [World Bank, Washington, DC (United States)

2003-07-01

Despite international efforts, poverty has become more widespread in many countries in the last decade, making poverty reduction the core challenge for development in the 21st century. In the Millennium Declaration, 189 nations have resolved to halve extreme poverty by 2015 and all agencies involved in this paper are committed to contribute to this aim. However, climate change is a serious risk to poverty reduction and threatens to undo decades of development efforts. This paper focuses on the impacts of climate change on poverty reduction efforts in the context of sustaining progress towards the Millennium Development Goals and beyond. It discusses ways of mainstreaming and integrating adaptation to climate change into poverty reduction and sustainable development efforts. The chief messages emerging from this paper are: Climate change is happening and will increasingly affect the poor; and Adaptation is necessary and there is a need to integrate responses to climate change and adaptation measures into strategies for poverty reduction to ensure sustainable development. This decision to focus on adaptation is deliberate and is taken with the understanding that adaptation cannot replace mitigation efforts. The magnitude and rate of climate change will strongly depend on efforts to reduce greenhouse gas (GHG) concentrations in the atmosphere. The higher the concentrations of GHGs, the higher the likelihood of irreversible and grave damage to human and biological systems. Therefore, adaptation is only one part of the solution. Mitigation of climate change by limiting greenhouse gas concentrations in the atmosphere is the indispensable other part.

A modelling and control structure for product quality control in climate-controlled processing of agro-material

NARCIS (Netherlands)

Verdijck, G.J.C.; Straten, van G.

2002-01-01

In this paper a modelling and control structure for product quality control is presented for a class of operations that processes agro-material. This class can be characterised as climate-controlled operations, such as storage, transport and drying. The basic model consists of three parts. These are

The science behind Kyoto: the role of universities in the climate change debate. Part I

Energy Technology Data Exchange (ETDEWEB)

O' Keefe, W.F. (American Petroleum Institute, Washington, DC (United States))

1999-01-01

In the debate over climate change pseudo-arguments have become more important than scientific evidence, as there is little evidence of fossil fuel burning affecting the climate. The lobbyists claims must be refuted by disinterested scientific analysis, and in this the universities must play their part.

A dynamic, climate-driven model of Rift Valley fever

Directory of Open Access Journals (Sweden)

Joseph Leedale

2016-03-01

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

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

Overview of climate information needs for ecological effects models

Energy Technology Data Exchange (ETDEWEB)

Peer, R.L.

1990-01-01

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

Effects of lateral boundary condition resolution and update frequency on regional climate model predictions

Science.gov (United States)

Pankatz, Klaus; Kerkweg, Astrid

2015-04-01

The work presented is part of the joint project "DecReg" ("Regional decadal predictability") which is in turn part of the project "MiKlip" ("Decadal predictions"), an effort funded by the German Federal Ministry of Education and Research to improve decadal predictions on a global and regional scale. In MiKlip, one big question is if regional climate modeling shows "added value", i.e. to evaluate, if regional climate models (RCM) produce better results than the driving models. However, the scope of this study is to look more closely at the setup specific details of regional climate modeling. As regional models only simulate a small domain, they have to inherit information about the state of the atmosphere at their lateral boundaries from external data sets. There are many unresolved questions concerning the setup of lateral boundary conditions (LBC). External data sets come from global models or from global reanalysis data-sets. A temporal resolution of six hours is common for this kind of data. This is mainly due to the fact, that storage space is a limiting factor, especially for climate simulations. However, theoretically, the coupling frequency could be as high as the time step of the driving model. Meanwhile, it is unclear if a more frequent update of the LBCs has a significant effect on the climate in the domain of the RCM. The first study examines how the RCM reacts to a higher update frequency. The study is based on a 30 year time slice experiment for three update frequencies of the LBC, namely six hours, one hour and six minutes. The evaluation of means, standard deviations and statistics of the climate in the regional domain shows only small deviations, some statistically significant though, of 2m temperature, sea level pressure and precipitation. The second part of the first study assesses parameters linked to cyclone activity, which is affected by the LBC update frequency. Differences in track density and strength are found when comparing the simulations

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

Directory of Open Access Journals (Sweden)

S. Hagemann

2013-05-01

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

Modeling key processes causing climate change and variability

Energy Technology Data Exchange (ETDEWEB)

Henriksson, S.

2013-09-01

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

European climate change at global mean temperature increases of 1.5 and 2 °C above pre-industrial conditions as simulated by the EURO-CORDEX regional climate models

Science.gov (United States)

Kjellström, Erik; Nikulin, Grigory; Strandberg, Gustav; Bøssing Christensen, Ole; Jacob, Daniela; Keuler, Klaus; Lenderink, Geert; van Meijgaard, Erik; Schär, Christoph; Somot, Samuel; Sørland, Silje Lund; Teichmann, Claas; Vautard, Robert

2018-05-01

We investigate European regional climate change for time periods when the global mean temperature has increased by 1.5 and 2 °C compared to pre-industrial conditions. Results are based on regional downscaling of transient climate change simulations for the 21st century with global climate models (GCMs) from the fifth-phase Coupled Model Intercomparison Project (CMIP5). We use an ensemble of EURO-CORDEX high-resolution regional climate model (RCM) simulations undertaken at a computational grid of 12.5 km horizontal resolution covering Europe. The ensemble consists of a range of RCMs that have been used for downscaling different GCMs under the RCP8.5 forcing scenario. The results indicate considerable near-surface warming already at the lower 1.5 °C of warming. Regional warming exceeds that of the global mean in most parts of Europe, being the strongest in the northernmost parts of Europe in winter and in the southernmost parts of Europe together with parts of Scandinavia in summer. Changes in precipitation, which are less robust than the ones in temperature, include increases in the north and decreases in the south with a borderline that migrates from a northerly position in summer to a southerly one in winter. Some of these changes are already seen at 1.5 °C of warming but are larger and more robust at 2 °C. Changes in near-surface wind speed are associated with a large spread among individual ensemble members at both warming levels. Relatively large areas over the North Atlantic and some parts of the continent show decreasing wind speed while some ocean areas in the far north show increasing wind speed. The changes in temperature, precipitation and wind speed are shown to be modified by changes in mean sea level pressure, indicating a strong relationship with the large-scale circulation and its internal variability on decade-long timescales. By comparing to a larger ensemble of CMIP5 GCMs we find that the RCMs can alter the results, leading either to

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.

Use of a crop climate modeling system to evaluate climate change adaptation practices: maize yield in East Africa

Science.gov (United States)

Moore, N. J.; Alagarswamy, G.; Andresen, J.; Olson, J.; Thornton, P.

2013-12-01

/ha in many areas. The simulated yield changes in the future were both spatially explicit and dependent on the GCM used. The effectiveness of agronomic practices was highly varied across the region depending on soil type, agro-ecological zone and projected climate change. The results have critical implications for agronomic research and policy. The study challenges using a ';one size fits all' approach in the identification of potential adaptation strategies. The goal is to use models to target local, optimized solutions as part of the broader need for impact assessments at coarser scales.

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

Reconstructing Climate Change: The Model-Data Ping-Pong

Science.gov (United States)

Stocker, T. F.

2017-12-01

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

Use of regional climate models data for groundwater recharge modelling in Baltic artesian basin

Science.gov (United States)

Timuhins, A.; Klints, I.; Sennikovs, J.; Virbulis, J.

2012-04-01

Baltic artesian basin (BAB) covers about 480000 square kilometres. BAB includes territory of Latvia, Lithuania, Estonia, parts of Poland, Russia, Belarus and Baltic Sea. The closed hydrogeological mathematical model for the BAB is developed in University of Latvia and reference calculations made in steady state mode. No-flow boundary condition is applied on the bottom and side boundaries of BAB. Hydraulic head is fixed on the seabed and largest lakes, and along the main river lines. Main water supply wells also are presented in the model as a pointwise water extraction. Precipitation is the main source of the groundwater recharge in the BAB region. Infiltration parameterization is responsible for this water source in BAB model. During the early stage of calibration of BAB hydrogeological model an automatic calibration for the hydraulic conductivities of permeable layers and single infiltration rate was attempted. Performing BAB model calibration it was noted that the differences of calculated and observed hydraulic heads (used for calculating the calibration penalty function) can be reduced by introducing a spatially distributed infiltration model. The aim of the present study is improving of the infiltration model, as well as preserving a short computation time (several minutes) for the piezometric head. Direct solution of improvement of the infiltration would be a usage of the advanced hydrological models. However, an accurate hydrological model requires a lot of computational power. It should couple meteorological and hydrological parameters and requires additional calibration. The regional climate model (KNMI-RACMO2 25 km resolution) results from ENSEMBLES project are used for the spatially distributed infiltration field calculation. The infiltration field is constructed as weighted difference of 30 year averaged precipitation and evaporation fields. The weight value is calibrated and a considerable decrease of the value of penalty function of the groundwater

The climate: Earth and men

International Nuclear Information System (INIS)

Poitou, Jean; Braconnot, Pascale; Masson-Delmotte, Valerie

2015-01-01

In this book, the authors first present the climate system as it operates under the influence of the atmosphere and oceans: Earth heated by the Sun, temperatures and movements within the atmosphere, surface and deep circulation in the oceans, exchanges between the atmosphere and the oceans. They present the various actors of climate and their interactions: water cycle, carbon cycle, greenhouse effect, clouds, aerosols, ocean, cryosphere-climate interaction, interaction between continental biosphere and climate, interactions between climate, continents and lithosphere, feedbacks and climate sensitivity. They comment the variety of climates and their variability when considered on a large scale (role of the Sun, ocean-atmosphere oscillations in El Nino and La Nina, North Atlantic oscillation, other examples of oscillations). The next part addresses climate modelling: model fundamentals (parameters and other components, coupling between components), model adjustment (simulation types, multi-model sets, and model assessment), models of intermediate complexity, regional models. The authors discuss the warming phenomenon: history of temperature measurements, clues of global warming, how to make climate change. They propose a presentation and discussion of anthropogenic and natural factors which disturb the climate: CO 2 and other greenhouse gases, changes in soil uses, other possible causes of climate disturbance (aerosol, aircraft wakes, volcanoes, and sun), combination of these disturbances, and identification of anthropogenic disturbances. They discuss past climate evolutions, and finally discuss how the climate could evolve in the future

Modeling of the climate system and of its response to a greenhouse effect increase

International Nuclear Information System (INIS)

Li, L.

2005-01-01

The anthropic disturbance of the Earth's greenhouse effect is already visible and will enhance in the coming years or decades. In front of the rapidity and importance of the global warming effect, the socio-economical management of this change will rise problems and must be studied by the scientific community. At the modeling level, finding a direct strategy for the validation of climate models is not easy: many uncertainties exist because energy transformations take place at a low level and several processes take place at the same time. The variability observed at the seasonal, inter-annual or paleo- scales allows to validate the models at the process level but not the evolution of the whole system. The management of these uncertainties is an integral part of the global warming problem. Thus, several scenarios can be proposed and their risk of occurrence must be estimated. This paper presents first the greenhouse effect, the climatic changes during geologic times, the anthropic disturbance of the greenhouse effect, the modeling of climate and the forecasting of its evolution. (J.S.)

A Web-Based Polar Firn Model to Motivate Interest in Climate Change

Science.gov (United States)

Harris, P. D.; Lundin, J.; Stevens, C.; Leahy, W.; Waddington, E. D.

2013-12-01

How long would you have to dig straight down in Greenland before you reached solid ice? This is one of many questions that could be answered by a typical high school student using our online firn model. Firn is fallen snow that compacts under its own weight and eventually turns into glacial ice. The Herron and Langway (1980) firn model describes this process. An important component of predicting future climate change is researching past climate change. Some details of our past climate are discovered by analyzing polar ice and the firn process. Firn research can also be useful for understanding how changes in ice surface levels reflect changes in the ice mass. We have produced an online version of the Herron and Langway model that provides a simple way for students to learn how polar snow turns into ice. As a user, you can enter some climatic conditions (accumulation rate, temperature, and surface density) into our graphical user interface and press 'Submit'. We take the numbers you enter in your internet browser, send them to the model written in Python that is running on our server, and provide links to your results, all within seconds. The model produces firn depth, density, and age data. The results appear on the webpage in both text and graphical format. We have developed an example lesson plan appropriate for a high-school physics or environmental science class. The online model offers students an opportunity to apply their scientific knowledge in order to understand real-world physical processes. Additionally, students learn about scientific research and the tools scientists use to conduct it. The model can be used as a standalone lesson or as a part of a larger climate-science unit. The online model was created with funding from the Washington NASA Space Grant Consortium and the National Science Foundation's Partnerships for International Research and Education program.

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

Directory of Open Access Journals (Sweden)

Asma Foughali

2015-07-01

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

High-Resolution Urban Greenery Mapping for Micro-Climate Modelling Based on 3d City Models

Science.gov (United States)

Hofierka, J.; Gallay, M.; Kaňuk, J.; Šupinský, J.; Šašak, J.

2017-10-01

Urban greenery has various positive micro-climate effects including mitigation of heat islands. The primary root of heat islands in cities is in absorption of solar radiation by the mass of building structures, roads and other solid materials. The absorbed heat is subsequently re-radiated into the surroundings and increases ambient temperatures. The vegetation can stop and absorb most of incoming solar radiation mostly via the photosynthesis and evapotranspiration process. However, vegetation in mild climate of Europe manifests considerable annual seasonality which can also contribute to the seasonal change in the cooling effect of the vegetation on the urban climate. Modern methods of high-resolution mapping and new generations of sensors have brought opportunity to record the dynamics of urban greenery in a high resolution in spatial, spectral, and temporal domains. In this paper, we use the case study of the city of Košice in Eastern Slovakia to demonstrate the methodology of 3D mapping and modelling the urban greenery during one vegetation season in 2016. The purpose of this monitoring is to capture 3D effects of urban greenery on spatial distribution of solar radiation in urban environment. Terrestrial laser scanning was conducted on four selected sites within Košice in ultra-high spatial resolution. The entire study area, which included these four smaller sites, comprised 4 km2 of the central part of the city was flown within a single airborne lidar and photogrammetric mission to capture the upper parts of buildings and vegetation. The acquired airborne data were used to generate a 3D city model and the time series of terrestrial lidar data were integrated with the 3D city model. The results show that the terrestrial and airborne laser scanning techniques can be effectively used to monitor seasonal changes in foliage of trees in order to assess the transmissivity of the canopy for microclimate modelling.

The time scales of the climate-economy feedback and the climatic cost of growth

Energy Technology Data Exchange (ETDEWEB)

Hallegatte, Stephane [CIRED - CNRM, Nogent-sur-Marne (France)

2005-04-01

This paper is based on the perception that the inertia of climate and socio-economic systems are key parameters in the climate change issue. In a first part, it develops and implements a new approach based on a simple integrated model with a particular focus on an innovative transient impact and adaptation modelling. In a second part, a climate-economy feedback is defined and characterized. It is found that: (i) it has a 70-year characteristic time, which is long when compared to the system's other time-scales, and it cannot act as a natural damping process of climate change; (ii) mitigation has to be anticipated since the feedback of an emission reduction on the economy is significant only after a 20-year delay and really efficient after a one-century delay; (iii) the IPCC methodology, that neglects the feedback from impacts to emissions, is acceptable up to 2100, whatever is the level of impacts. This analysis allows also to define a climatic cost of growth as the additional climate change damages due to the additional emissions linked to economic growth. Usefully, this metric for climate change damages is particularly independent of the baseline scenario. (orig.)

The time scales of the climate-economy feedback and the climatic cost of growth

International Nuclear Information System (INIS)

Hallegatte, Stephane

2005-04-01

This paper is based on the perception that the inertia of climate and socio-economic systems are key parameters in the climate change issue. In a first part, it develops and implements a new approach based on a simple integrated model with a particular focus on an innovative transient impact and adaptation modelling. In a second part, a climate-economy feedback is defined and characterized. It is found that: (i) it has a 70-year characteristic time, which is long when compared to the system's other time-scales, and it cannot act as a natural damping process of climate change; (ii) mitigation has to be anticipated since the feedback of an emission reduction on the economy is significant only after a 20-year delay and really efficient after a one-century delay; (iii) the IPCC methodology, that neglects the feedback from impacts to emissions, is acceptable up to 2100, whatever is the level of impacts. This analysis allows also to define a climatic cost of growth as the additional climate change damages due to the additional emissions linked to economic growth. Usefully, this metric for climate change damages is particularly independent of the baseline scenario. (orig.)

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

Directory of Open Access Journals (Sweden)

Dharmaveer Singh

2015-01-01

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

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

Science.gov (United States)

Dessens, Olivier

2016-04-01

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

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

International Nuclear Information System (INIS)

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

2005-01-01

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

Dangerous human-made interference with climate: a GISS modelE study

Directory of Open Access Journals (Sweden)

J. Hansen

2007-01-01

Full Text Available We investigate the issue of "dangerous human-made interference with climate" using simulations with GISS modelE driven by measured or estimated forcings for 1880–2003 and extended to 2100 for IPCC greenhouse gas scenarios as well as the "alternative" scenario of Hansen and Sato (2004. Identification of "dangerous" effects is partly subjective, but we find evidence that added global warming of more than 1°C above the level in 2000 has effects that may be highly disruptive. The alternative scenario, with peak added forcing ~1.5 W/m2 in 2100, keeps further global warming under 1°C if climate sensitivity is ~3°C or less for doubled CO2. The alternative scenario keeps mean regional seasonal warming within 2σ (standard deviations of 20th century variability, but other scenarios yield regional changes of 5–10σ, i.e. mean conditions outside the range of local experience. We conclude that a CO2 level exceeding about 450 ppm is "dangerous", but reduction of non-CO2 forcings can provide modest relief on the CO2 constraint. We discuss three specific sub-global topics: Arctic climate change, tropical storm intensification, and ice sheet stability. We suggest that Arctic climate change has been driven as much by pollutants (O3, its precursor CH4, and soot as by CO2, offering hope that dual efforts to reduce pollutants and slow CO2 growth could minimize Arctic change. Simulated recent ocean warming in the region of Atlantic hurricane formation is comparable to observations, suggesting that greenhouse gases (GHGs may have contributed to a trend toward greater hurricane intensities. Increasing GHGs cause significant warming in our model in submarine regions of ice shelves and shallow methane hydrates, raising concern about the potential for accelerating sea level rise and future positive feedback from methane release. Growth of non-CO2 forcings has slowed in recent years, but CO2 emissions are now surging well above the alternative scenario. Prompt

Dangerous human-made interference with climate: a GISS modelE study

International Nuclear Information System (INIS)

Hansen, J.; Lacis, A.; Miller, R.; Schmidt, G.A.; Russell, G.; Canuto, V.; Del Genio, A.; Hall, T.; Kiang, N.Y.; Rind, D.; Romanou, A.; Shindell, D.; Sun, S.; Hansen, J.; Sato, M.; Kharecha, P.; Nazarenko, L.; Aleinov, I.; Bauer, S.; Chandler, M.; Faluvegi, G.; Jonas, J.; Koch, D.; Lerner, J.; Perlwitz, Ju.; Unger, N.; Zhang, S.; Ruedy, R.; Lo, K.; Cheng, Y.; Oinas, V.; Schmunk, R.; Tausnev, N.; Yao, M.; Lacis, A.; Schmidt, G.A.; Del Genio, A.; Rind, D.; Romanou, A.; Shindell, D.; Thresher, D.; Miller, R.; Cairns, B.; Hall, T.; Perlwitz, Ja.; Baum, E.; Cohen, A.; Fleming, E.; Jackman, C.; Labow, G.; Friend, A.; Kelley, M.

2007-01-01

We investigate the issue of 'dangerous human-made interference with climate' using simulations with GISS modelE driven by measured or estimated forcing for 1880-2003 and extended to 2100 for IPCC greenhouse gas scenarios as well as the 'alternative' scenario of Hansen and Sato (2004). Identification of 'dangerous' effects is partly subjective, but we find evidence that added global warming of more than 1 degrees C above the level in 2000 has effects that may be highly disruptive. The alternative scenario, with peak added forcing similar to 1.5 W/m 2 in 2100, keeps further global warming under 1 degrees C if climate sensitivity is similar to 3 degrees C or less for doubled CO 2 . The alternative scenario keeps mean regional seasonal warming within 2 σ (standard deviations) of 20. century variability, but other scenarios yield regional changes of 5-10 σ, i.e. mean conditions outside the range of local experience. We conclude that a CO 2 level exceeding about 450 ppm is 'dangerous', but reduction of non-CO 2 forcing can provide modest relief on the CO 2 constraint. We discuss three specific sub-global topics: Arctic climate change, tropical storm intensification, and ice sheet stability. We suggest that Arctic climate change has been driven as much by pollutants (O 3 , its precursor CH 4 , and soot) as by CO 2 , offering hope that dual efforts to reduce pollutants and slow CO 2 growth could minimize Arctic change. Simulated recent ocean warming in the region of Atlantic hurricane formation is comparable to observations, suggesting that greenhouse gases (GHGs) may have contributed to a trend toward greater hurricane intensities. Increasing GHGs cause significant warming in our model in submarine regions of ice shelves and shallow methane hydrates, raising concern about the potential for accelerating sea level rise and future positive feedback from methane release. Growth of non-CO 2 forcing has slowed in recent years, but CO 2 emissions are now surging well above the

Agricultural climate impacts assessment for economic modeling and decision support

Science.gov (United States)

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

2013-12-01

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

[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.

Modeling the effect of climate change to the potential invasion range of Piper aduncum Linnaeus

Directory of Open Access Journals (Sweden)

J.C. Paquit

2018-01-01

Full Text Available The potential effect of invasive plant species on biodiversity is one of most important subject of inquiry at present. In many parts of the world, the alarming spread of these plants has been documented. Knowing that climate exerts a dominant control over the distribution of plant species, predictions can therefore be made to determine which areas the species would likely spread under a climate change scenario and that is what this study aims to tackle. In the current study, a total of 211 species occurrence points were used to model the current and projected suitability of Piper aduncum in Bukidnon, Philippines using Maxent. Results revealed that the suitability of the species was determined primarily by climatic factors with Bio 18 (precipitation of the warmest quarter as the strongest influencing variable with a mean percent contribution of 22.1%. The resulting model was highly accurate based on its mean test Area Under Curve that is equal to 0.917. Current prediction shows that suitable areas for Piper are concentrated along the southern portion of Bukidnon. Only 9% of the province is suitable for the species at present but is predicted to increase to 27% because of climate change. The central and southwestern parts of the province are the areas of high threat for invasion by Piper.

Response of permafrost to projected climate change: Results from global offline model simulations with JSBACH

Science.gov (United States)

Blome, Tanja; Ekici, Altug; Beer, Christian; Hagemann, Stefan

2014-05-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) lacked the sufficient representation of permafrost physics in their land surface schemes. In order to assess the response of permafrost to projected climate change for the 21st century, the land surface scheme of the Max-Planck-Institute for Meteorology, JSBACH, has recently been equipped with the important physical processes for permafrost studies, and was driven globally with bias corrected climate data, thereby spanning a period from 1850 until 2100. The applied land surface scheme JSBACH now considers the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. To address the uncertainty range arising through different greenhouse gas concentrations as well as through different climate realisations when using various climate models, combinations of two Representative Concentration Pathways (RCPs) and two GCMs were used as driving data. In order to focus only on the climatic impact on permafrost, effects due to feedbacks between climate and permafrost (namely via carbon fluxes between land and atmosphere) are excluded in the experiments

Climate Change Modelling and Its Roles to Chinese Crops Yield

Institute of Scientific and Technical Information of China (English)

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

2013-01-01

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

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.;

Climate change decision-making: Model & parameter uncertainties explored

Energy Technology Data Exchange (ETDEWEB)

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

1995-12-31

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

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

Science.gov (United States)

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

2016-12-01

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

The tropical water and energy cycles in a cumulus ensemble model. Part 1: Equilibrium climate

Science.gov (United States)

Sui, C. H.; Lau, K. M.; Tao, W. K.; Simpson, J.

1994-01-01

A cumulus ensemble model is used to study the tropical water and energy cycles and their role in the climate system. The model includes cloud dynamics, radiative processes, and microphysics that incorporate all important production and conversion processes among water vapor and five species of hydrometeors. Radiative transfer in clouds is parameterized based on cloud contents and size distributions of each bulk hydrometeor. Several model integrations have been carried out under a variety of imposed boundary and large-scale conditions. In Part 1 of this paper, the primary focus is on the water and heat budgets of the control experiment, which is designed to simulate the convective - radiative equilibrium response of the model to an imposed vertical velocity and a fixed sea surface temperature at 28 C. The simulated atmosphere is conditionally unstable below the freezing level and close to neutral above the freezing level. The equilibrium water budget shows that the total moisture source, M(sub s), which is contributed by surface evaporation (0.24 M(sub s)) and the large-scale advection (0.76 M(sub s)), all converts to mean surface precipitation bar-P(sub s). Most of M(sub s) is transported verticaly in convective regions where much of the condensate is generated and falls to surface (0.68 bar-P(sub s)). The remaining condensate detrains at a rate of 0.48 bar-P(sub s) and constitutes 65% of the source for stratiform clouds above the melting level. The upper-level stratiform cloud dissipates into clear environment at a rate of 0.14 bar-P(sub s), which is a significant moisture source comparable to the detrained water vapor (0.15 bar-P(sub s)) to the upper troposphere from convective clouds. In the lower troposphere, stratiform clouds evaporate at a rate of 0.41 bar-P(sub s), which is a more dominant moisture source than surface evaporation (0.22 bar-P(sub s)). The precipitation falling to the surface in the stratiform region is about 0.32 bar-P(sub s). The associated

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.

Future climate and surface mass balance of Svalbard glaciers in an RCP8.5 climate scenario: a study with the regional climate model MAR forced by MIROC5

Science.gov (United States)

Lang, C.; Fettweis, X.; Erpicum, M.

2015-05-01

We have performed a future projection of the climate and surface mass balance (SMB) of Svalbard with the MAR (Modèle Atmosphérique Régional) regional climate model forced by MIROC5 (Model for Interdisciplinary Research on Climate), following the RCP8.5 scenario at a spatial resolution of 10 km. MAR predicts a similar evolution of increasing surface melt everywhere in Svalbard followed by a sudden acceleration of melt around 2050, with a larger melt increase in the south compared to the north of the archipelago. This melt acceleration around 2050 is mainly driven by the albedo-melt feedback associated with the expansion of the ablation/bare ice zone. This effect is dampened in part as the solar radiation itself is projected to decrease due to a cloudiness increase. The near-surface temperature is projected to increase more in winter than in summer as the temperature is already close to 0 °C in summer. The model also projects a stronger winter west-to-east temperature gradient, related to the large decrease of sea ice cover around Svalbard. By 2085, SMB is projected to become negative over all of Svalbard's glaciated regions, leading to the rapid degradation of the firn layer.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.

Science.gov (United States)

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960-2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60-70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly

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

Science.gov (United States)

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

2009-04-01

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

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.

Integrated climate and hydrology modelling

DEFF Research Database (Denmark)

Larsen, Morten Andreas Dahl

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

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

Science.gov (United States)

Yhang, Y.

2013-12-01

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

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

Science.gov (United States)

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

2011-12-01

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

Climate change, economics and Buddhism. Part 2. New views and practices for sustainable world economies

International Nuclear Information System (INIS)

Daniels, Peter L.

2010-01-01

The evidence of impending and serious climate and other consequences of an expanding world economy based on fossil carbon energy continues to accumulate. This two-part paper examines the potential contribution of the world view and insights of Buddhism to this search. It presents both a conceptual and practical case that Buddhism can help shape and move towards an alternative and effective paradigmatic basis for sustainable economies - one capable of bringing about and maintaining genuine, high welfare levels across the world's societies. The first paper outlined a comprehensive analytical framework to identify the fundamental nature of anthropogenic climate change. Based on the integration of two of the most influential environmental analysis tools of recent decades (the DPSIR model and IPAT equation), the framework was then broadened to facilitate ideas from the Buddhist world view by injecting two key missing aspects - the interrelated role of (1) beliefs and values (on goals and behavior) and (2) the nature of well-being or human happiness. Finally, the principal linkages between this climate change analysis framework and Buddhism were explored. In this concluding paper, the systems framework is used to demonstrate how Buddhist and related world views can feed into appropriate and effective responses to the impending challenges of climate change. This is undertaken by systematically presenting a specific, if indicative, list of relevant strategies informed by the understanding of interconnectedness and other basic principles about the nature of reality and human well-being as proposed in Buddhism. (author)

Climate change, economics and Buddhism. Part 2. New views and practices for sustainable world economies

Energy Technology Data Exchange (ETDEWEB)

Daniels, Peter L. [Griffith School of Environment, Griffith University, Brisbane, 4111 (Australia)

2010-03-15

The evidence of impending and serious climate and other consequences of an expanding world economy based on fossil carbon energy continues to accumulate. This two-part paper examines the potential contribution of the world view and insights of Buddhism to this search. It presents both a conceptual and practical case that Buddhism can help shape and move towards an alternative and effective paradigmatic basis for sustainable economies - one capable of bringing about and maintaining genuine, high welfare levels across the world's societies. The first paper outlined a comprehensive analytical framework to identify the fundamental nature of anthropogenic climate change. Based on the integration of two of the most influential environmental analysis tools of recent decades (the DPSIR model and IPAT equation), the framework was then broadened to facilitate ideas from the Buddhist world view by injecting two key missing aspects - the interrelated role of (1) beliefs and values (on goals and behavior) and (2) the nature of well-being or human happiness. Finally, the principal linkages between this climate change analysis framework and Buddhism were explored. In this concluding paper, the systems framework is used to demonstrate how Buddhist and related world views can feed into appropriate and effective responses to the impending challenges of climate change. This is undertaken by systematically presenting a specific, if indicative, list of relevant strategies informed by the understanding of interconnectedness and other basic principles about the nature of reality and human well-being as proposed in Buddhism. (author)

Terrestrial biogeochemistry in the community climate system model (CCSM)

International Nuclear Information System (INIS)

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

2006-01-01

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

The Urgent Need for Improved Climate Models and Predictions

Science.gov (United States)

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

2009-09-01

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

Preparing Middle School Teachers to Use Science Models Effectively when Teaching about Weather and Climate Topics

Science.gov (United States)

Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

2012-12-01

According to the National Science Education Standards (NSES), teachers are encouraged to use science models in the classroom as a way to aid in the understanding of the nature of the scientific process. This is of particular importance to the atmospheric science community because climate and weather models are very important when it comes to understanding current and future behaviors of our atmosphere. Although familiar with weather forecasts on television and the Internet, most people do not understand the process of using computer models to generate weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Therefore, it makes sense that recent research in science education indicates that scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum. The purpose of this research study is to describe how three middle school teachers use science models to teach about topics in climate and weather, as well as the challenges they face incorporating models effectively into the classroom. Participants in this study took part in a week long professional development designed to orient them towards appropriate use of science models for a unit on weather, climate, and energy concepts. The course design was based on empirically tested features of effective professional development for science teachers and was aimed at teaching content to the teachers while simultaneously orienting them towards effective use of science models in the classroom in a way that both aids in learning about the content knowledge as well as how models are used in scientific inquiry. Results indicate that teachers perceive models to be physical representations that can be used as evidence to convince students that the teacher's conception of the concept is correct. Additionally, teachers tended to use them as ways to explain an idea to

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Modelling recent and future climatic suitability for fasciolosis in Europe.

Science.gov (United States)

Caminade, Cyril; van Dijk, Jan; Baylis, Matthew; Williams, Diana

2015-03-19

Fasciola hepatica is a parasitic worm responsible for fasciolosis in grazed ruminants in Europe. The free-living stages of this parasite are sensitive to temperature and soil moisture, as are the intermediate snail hosts the parasite depends on for its life-cycle. We used a climate-driven disease model in order to assess the impact of recent and potential future climate changes on the incidence of fasciolosis and to estimate the related uncertainties at the scale of the European landmass. The current climate appears to be highly suitable for fasciolosis throughout the European Union with the exception of some parts of the Mediterranean region. Simulated climatic suitability for fasciolosis significantly increased during the 2000s in central and northwestern Europe, which is consistent with an observed increased in ruminant infections. The simulation showed that recent trends are likely to continue in the future with the estimated pattern of climate change for northern Europe, possibly extending the season suitable for development of the parasite in the environment by up to four months. For southern Europe, the simulated burden of disease may be lower, but the projected climate change will increase the risk during the winter months, since the simulated changes in temperature and moisture support the development of the free-living and intra-molluscan stages between November and March. In the event of predicted climate change, F. hepatica will present a serious risk to the health, welfare and productivity of all ruminant livestock. Improved, bespoke control programmes, both at farm and region levels, will then become imperative if problems, such as resistance of the parasite associated with increased drug use, are to be mitigated.

Alpine snow cover in a changing climate: a regional climate model perspective

Science.gov (United States)

Steger, Christian; Kotlarski, Sven; Jonas, Tobias; Schär, Christoph

2013-08-01

An analysis is presented of an ensemble of regional climate model (RCM) experiments from the ENSEMBLES project in terms of mean winter snow water equivalent (SWE), the seasonal evolution of snow cover, and the duration of the continuous snow cover season in the European Alps. Two sets of simulations are considered, one driven by GCMs assuming the SRES A1B greenhouse gas scenario for the period 1951-2099, and the other by the ERA-40 reanalysis for the recent past. The simulated SWE for Switzerland for the winters 1971-2000 is validated against an observational data set derived from daily snow depth measurements. Model validation shows that the RCMs are capable of simulating the general spatial and seasonal variability of Alpine snow cover, but generally underestimate snow at elevations below 1,000 m and overestimate snow above 1,500 m. Model biases in snow cover can partly be related to biases in the atmospheric forcing. The analysis of climate projections for the twenty first century reveals high inter-model agreement on the following points: The strongest relative reduction in winter mean SWE is found below 1,500 m, amounting to 40-80 % by mid century relative to 1971-2000 and depending upon the model considered. At these elevations, mean winter temperatures are close to the melting point. At higher elevations the decrease of mean winter SWE is less pronounced but still a robust feature. For instance, at elevations of 2,000-2,500 m, SWE reductions amount to 10-60 % by mid century and to 30-80 % by the end of the century. The duration of the continuous snow cover season shows an asymmetric reduction with strongest shortening in springtime when ablation is the dominant factor for changes in SWE. We also find a substantial ensemble-mean reduction of snow reliability relevant to winter tourism at elevations below about 1,800 m by mid century, and at elevations below about 2,000 m by the end of the century.

Development of a climate data analysis tool (CDAT)

Energy Technology Data Exchange (ETDEWEB)

Marlais, S.M.

1997-09-01

The Climate Data Analysis Tool (CDAT) is designed to provide the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at Lawrence Livermore National Laboratory, California, with the capabilities needed to analyze model data with little effort on the part of the scientist, while performing complex mathematical calculations, and graphically displaying the results. This computer software will meet the demanding need of climate scientists by providing the necessary tools to diagnose, validate, and intercompare large observational and global climate model datasets.

Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

Science.gov (United States)

Smith, B.

2015-12-01

In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs

Socioeconomic Drought in a Changing Climate: Modeling and Management

Science.gov (United States)

AghaKouchak, Amir; Mehran, Ali; Mazdiyasni, Omid

2016-04-01

Drought is typically defined based on meteorological, hydrological and land surface conditions. However, in many parts of the world, anthropogenic changes and water management practices have significantly altered local water availability. Socioeconomic drought refers to conditions whereby the available water supply cannot satisfy the human and environmental water needs. Surface water reservoirs provide resilience against local climate variability (e.g., droughts), and play a major role in regional water management. This presentation focuses on a framework for describing socioeconomic drought based on both water supply and demand information. We present a multivariate approach as a measure of socioeconomic drought, termed Multivariate Standardized Reliability and Resilience Index (MSRRI; Mehran et al., 2015). This model links the information on inflow and surface reservoir storage to water demand. MSRRI integrates a "top-down" and a "bottom-up" approach for describing socioeconomic drought. The "top-down" component describes processes that cannot be simply controlled or altered by local decision-makers and managers (e.g., precipitation, climate variability, climate change), whereas the "bottom-up" component focuses on the local resilience, and societal capacity to respond to droughts. The two components (termed, Inflow-Demand Reliability (IDR) indicator and Water Storage Resilience (WSR) indicator) are integrated using a nonparametric multivariate approach. We use this framework to assess the socioeconomic drought during the Australian Millennium Drought (1998-2010) and the 2011-2014 California Droughts. MSRRI provides additional information on socioeconomic drought onset, development and termination based on local resilience and human demand that cannot be obtained from the commonly used drought indicators. We show that MSRRI can be used for water management scenario analysis (e.g., local water availability based on different human water demands scenarios). Finally

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-10-15

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

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.

Groundwater flow modelling of periods with periglacial and glacial climate conditions - Laxemar

Energy Technology Data Exchange (ETDEWEB)

Vidstrand, Patrik (TerraSolve AB, Floda (Sweden)); Rhen, Ingvar (SWECO Environment AB, Falun (Sweden)); Zugec, Nada (Bergab, Goeteborg (Sweden))

2010-12-15

As a part of the license application for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different hydraulic conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. This report is concerned with the modelling of a repository at the Laxemar-Simpevarp site during periglacial and glacial climate conditions as a comparison to corresponding modelling carried out for Forsmark /Vidstrand et al. 2010/. The groundwater flow modelling study reported here comprises a coupled thermal-hydraulic-chemical (T-H-C) analysis of periods with periglacial and glacial climate conditions. The objective of the report is to provide bounding hydrogeological estimates at different stages during glaciation and deglaciation of a glacial cycle at Laxemar. Three cases with different climate conditions are analysed here: (i) Temperate case, (ii) Glacial case without permafrost, and (iii) Glacial case with permafrost. The glacial periods are transient and encompass approximately 13,000 years. The simulation results comprise pressures, Darcy fluxes, and water salinities, as well as advective transport performance measures obtained by particle tracking such as flow path lengths, travel times and flow-related transport resistances. The modelling is accompanied by a sensitivity study that addresses the impact of the following matters: the direction of the ice sheet advance and the bedrock hydraulic and transport properties

Terrestrial biogeochemistry in the community climate system model (CCSM)

Energy Technology Data Exchange (ETDEWEB)

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

2006-09-15

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

Conceptual understanding of climate change with a globally resolved energy balance model

Energy Technology Data Exchange (ETDEWEB)

Dommenget, Dietmar [Monash University, School of Mathematical Sciences, Melbourne, VIC (Australia); Floeter, Janine [Leibniz Institute for Marine Sciences, Kiel (Germany)

2011-12-15

The future climate change projections are essentially based on coupled general circulation model (CGCM) simulations, which give a distinct global warming pattern with arctic winter amplification, an equilibrium land-sea warming contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the Intergovernmental Panel on Climate Change (IPCC) predictions, the conceptual understanding of these predicted structures of climate change and the causes of their uncertainties is very difficult to reach if only based on these highly complex CGCM simulations. In the study presented here we will introduce a very simple, globally resolved energy balance (GREB) model, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the strongly simplified energy balance models and the fully coupled 4-dimensional complex CGCMs. It provides a fast tool for the conceptual understanding and development of hypotheses for climate change studies, which shall build a basis or starting point for more detailed studies of observations and CGCM simulations. It is based on the surface energy balance by very simple representations of solar and thermal radiation, the atmospheric hydrological cycle, sensible turbulent heat flux, transport by the mean atmospheric circulation and heat exchange with the deeper ocean. Despite some limitations in the representations of the basic processes, the models climate sensitivity and the spatial structure of the warming pattern are within the uncertainties of the IPCC models simulations. It is capable of simulating aspects of the arctic winter amplification, the equilibrium land-sea warming contrast and the inter-hemispheric warming gradient with good agreement to the IPCC models in amplitude and structure. The results give some insight into the understanding of the land-sea contrast and the polar amplification. The GREB model suggests that the regional inhomogeneous

Improving poverty and inequality modelling in climate research

Science.gov (United States)

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

2017-12-01

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

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

The Software Architecture of Global Climate Models

Science.gov (United States)

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

2011-12-01

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

Modeling maize response to climate modification in Hungary

OpenAIRE

Angela Anda

2006-01-01

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

A probabilistic model of ecosystem response to climate change

International Nuclear Information System (INIS)

Shevliakova, E.; Dowlatabadi, H.

1994-01-01

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

Oscillations in a simple climate-vegetation model

Science.gov (United States)

Rombouts, J.; Ghil, M.

2015-05-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-04-01

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

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.

Linking seasonal climate forecasts with crop models in Iberian Peninsula

Science.gov (United States)

Capa, Mirian; Ines, Amor; Baethgen, Walter; Rodriguez-Fonseca, Belen; Han, Eunjin; Ruiz-Ramos, Margarita

2015-04-01

Translating seasonal climate forecasts into agricultural production forecasts could help to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. In this study, we use seasonal rainfall forecasts and crop models to improve predictability of wheat yield in the Iberian Peninsula (IP). Additionally, we estimate economic margins and production risks associated with extreme scenarios of seasonal rainfall forecast. This study evaluates two methods for disaggregating seasonal climate forecasts into daily weather data: 1) a stochastic weather generator (CondWG), and 2) a forecast tercile resampler (FResampler). Both methods were used to generate 100 (with FResampler) and 110 (with CondWG) weather series/sequences for three scenarios of seasonal rainfall forecasts. Simulated wheat yield is computed with the crop model CERES-wheat (Ritchie and Otter, 1985), which is included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5, Hoogenboom et al., 2010). Simulations were run at two locations in northeastern Spain where the crop model was calibrated and validated with independent field data. Once simulated yields were obtained, an assessment of farmer's gross margin for different seasonal climate forecasts was accomplished to estimate production risks under different climate scenarios. This methodology allows farmers to assess the benefits and risks of a seasonal weather forecast in IP prior to the crop growing season. The results of this study may have important implications on both, public (agricultural planning) and private (decision support to farmers, insurance companies) sectors. Acknowledgements Research by M. Capa-Morocho has been partly supported by a PICATA predoctoral fellowship of the Moncloa Campus of International Excellence (UCM-UPM) and MULCLIVAR project (CGL2012-38923-C02-02) References Hoogenboom, G. et al., 2010. The Decision

Modelling rainfall erosion resulting from climate change

Science.gov (United States)

Kinnell, Peter

2016-04-01

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

An Overview of the Future Development of Climate and Earth System Models for Scientific and Policy Use (Invited)

Science.gov (United States)

Washington, W. M.

2010-12-01

development pathway, the NSF/Department of Energy supported Community Climate System and Earth System Models will be featured in the presentation. Computational challenges will also part of the discussion.

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.

Holocene climate dynamics in the central part of the East European plain (Russia)

Science.gov (United States)

Novenko, Elena

2013-04-01

The Holocene climate and vegetation dynamics in the broad-leaved forest zone of the central part of the East European plain have been reconstructed on the base of pollen, plant macrofossil, testate amoebae and radiocarbon data from the mire Klukva (N 53.834812, E 36.252488), located in the kast depression in the Upper Oka River basin (Tula region, European Russia). The reconstruction of main parameters of past climate (the mean annual temperature precipitation) was carried out by the "Best Modern Analog" approach. Reconstructions of vegetation show that in the early Holocene the territory was occupied mainly by birch and pine-birch forests. Significant changes in the plant cover of the Upper Oka River basin are attributed to the 7.5 cal kyr BP). The climatic conditions were favorable for development of the broad-leaved forests those persisted in this area up to industrial period. In the 17th century, when the population density greatly increased and watersheds were ploughed, natural vegetation communities were gradually destroyed and transformed into agricultural landscapes. According to obtained climatic reconstructions the period 10-8.5 cal kyr BP was relatively cold and wet, when the mean annual temperature was in 3°C lower and precipitation was in 50-100 mm higher then nowadays. The significant climate warming occurred in about 7.0-5.0 cal kyr BP (The Holocene thermal maximum): the mean annual temperature in 2°C exceeded the modern value and precipitation was close to that. The environment conditions were drier due to decrease of effective moisture. In the second part of the Holocene the sequence of second-, and even third-order climatic oscillations expressed against the background of the overall slight trend towards cooling have been determined. The most pronounced cool and wet intervals were reconstructed in 2.5-2.0 cal kyr BP and 1.5-1.3 cal kyr BP. The mean annual temperature decreased in 1.5-2 °C and precipitation rose in 200 mm in compare to modern

Regionalization of climate model results for the North Sea

Energy Technology Data Exchange (ETDEWEB)

Kauker, F.

1999-07-01

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

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.

Towards a regional climate model coupled to a comprehensive hydrological model

Science.gov (United States)

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

2010-12-01

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

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

Science.gov (United States)

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

2018-01-01

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

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

Directory of Open Access Journals (Sweden)

Farzin Shabani

2018-03-01

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

IPCC. 4. climate assessment report, 2007; GIEC. 4. rapport d'evaluation du climat, 2007

Energy Technology Data Exchange (ETDEWEB)

NONE

2007-07-01

The mission and challenge of the Intergovernmental panel on climate change (IPCC, GIEC in French) is to evaluate, synthesize and make available the sum of scientific and economic information of the complex domain of climatic change, and in addition to make the results of these works accepted by government representatives of 192 states. This document makes a brief synthesis in three parts of the 4. assessment report of the IPCC: 1 - physical scientific bases of climatic change: characteristic of the phenomenon, greenhouse gas emissions trend, already observed effects, forecasts of climate models; 2 - impacts, adaptations and vulnerabilities of climatic change: types of future impacts, impacts per sector, regional impacts, limits of ecosystems adaptation; 3 - mitigation of climatic changes: past emissions and future trends, possible mitigation actions and cost, possible political levers for emissions abatement. A last part introduces the French researchers involved in IPCC's works. (J.S.)

Computer experiments with a coarse-grid hydrodynamic climate model

International Nuclear Information System (INIS)

Stenchikov, G.L.

1990-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-20

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

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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

Science.gov (United States)

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

2003-12-01

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

Human-Induced Climate Variations Linked to Urbanization: From Observations to Modeling

Science.gov (United States)

Shepherd, J. Marshall; Jin, Menglin

2004-01-01

The goal of this session is to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results focusing on the impact of urbanization on the climate. The discussion will highlight current observational and modeling capabilities being employed for investigating the urban environment and its linkage to the change in the Earth's climate system. The goal of the session is to identify our current stand and the future direction on the topic. Urbanization is one of the extreme cases of land use change. Most of population of the world has moved to urban areas. By 1995, more than 70% of population of North America and Europe were living in cities. By 2025, the United Nations estimates that 60% of the worlds population will live in cities. Although currently only 1.2% of the land is urban, better understanding of how the atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of human activities on this system is critical. Our understanding of urbanization effect is incomplete, partly because human activities induce new changes on climate in addition to the original natural variations, and partly because previously few data available for study urban effect globally. Urban construction changes surface roughness, albedo, heat capacity and vegetation coverage. Traffic and industry increase atmospheric aerosol. It is suggested that urbanization may modify rainfall processes through aerosol-cloud interactions or dynamic feedbacks. Because urbanization effect on climate is determined by many factors including land cover, the city's microscale features, population density, and human lifestyle patterns, it is necessary to study urban areas over globe.

Identifying misbehaving models using baseline climate variance

Science.gov (United States)

Schultz, Colin

2011-06-01

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

Ecological Assimilation of Land and Climate Observations - the EALCO model

Science.gov (United States)

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

2004-05-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2006-08-15

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

Co-benefits of climate policies: a potential keystone of climate negotiations?

International Nuclear Information System (INIS)

Cassen, Christophe; Guivarch, Celine; Lecocq, Franck

2015-01-01

This paper analyzes the challenges related to the assessment of co-benefits of climate policies underpinned by the implementation of multi-objective policies which seek synergies between climate policies and other development objectives (poverty alleviation, employment, health etc.). The analysis highlights the increasing interest in co-benefits in the latest 5. IPCC report, in particular by integrated models. Nevertheless, the quantified evaluation of co-benefits is still confronted to several methodological limitations which reduce the scope of co-benefits, particularly at the global level. In a growing context of climate-development approaches in climate negotiations, this article insists on the need to also assess co-benefits of other policies which induce a significant part of GHG emissions. Considering climate policies focused only on Greenhouse Gases emissions reduction limits the range of policy instruments to carbon taxation, tradable carbon emissions permits or dedicated mitigation and adaptation funds. This also hinders the integration of climate objectives in non-climate policies. Analyzing impacts of development policies on Green Gases emissions in the form of co-benefits requires to broaden the range of policy instruments and to take into account other drivers of emissions such as land dynamics. Including these mechanisms in integrated models therefore represents new scientific frontiers for integrated models in the coming years

Modeling climatic effects of anthropogenic CO2 emissions: Unknowns and uncertainties

Science.gov (United States)

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

2001-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2005-06-01

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

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....

Supercomputing for weather and climate modelling: convenience or necessity

CSIR Research Space (South Africa)

Landman, WA

2009-12-01

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

Solar radiation modelling using ANNs for different climates in China

International Nuclear Information System (INIS)

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

2008-01-01

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

The representation of low-level clouds during the West African monsoon in weather and climate models

Science.gov (United States)

Kniffka, Anke; Hannak, Lisa; Knippertz, Peter; Fink, Andreas

2016-04-01

The West African monsoon is one of the most important large-scale circulation features in the tropics and the associated seasonal rainfalls are crucial to rain-fed agriculture and water resources for hundreds of millions of people. However, numerical weather and climate models still struggle to realistically represent salient features of the monsoon across a wide range of scales. Recently it has been shown that substantial errors in radiation and clouds exist in the southern parts of West Africa (8°W-8°E, 5-10°N) during summer. This area is characterised by strong low-level jets associated with the formation of extensive ultra-low stratus clouds. Often persisting long after sunrise, these clouds have a substantial impact on the radiation budget at the surface and thus the diurnal evolution of the planetary boundary layer (PBL). Here we present some first results from a detailed analysis of the representation of these clouds and the associated PBL features across a range of weather and climate models. Recent climate model simulations for the period 1991-2010 run in the framework of the Year of Tropical Convection (YOTC) offer a great opportunity for this analysis. The models are those used for the latest Assessment Report of the Intergovernmental Panel on Climate Change, but for YOTC the model output has a much better temporal resolution, allowing to resolve the diurnal cycle, and includes diabatic terms, allowing to much better assess physical reasons for errors in low-level temperature, moisture and thus cloudiness. These more statistical climate model analyses are complemented by experiments using ICON (Icosahedral non-hydrostatic general circulation model), the new numerical weather prediction model of the German Weather Service and the Max Planck Institute for Meteorology. ICON allows testing sensitivities to model resolution and numerical schemes. These model simulations are validated against (re-)analysis data, satellite observations (e.g. CM SAF cloud and

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

Science.gov (United States)

Bahari, Siti Fatimah; Clarke, Sharon

2013-06-01

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

A potato model intercomparison across varying climates and productivity levels

DEFF Research Database (Denmark)

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

2017-01-01

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

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

Science.gov (United States)

Parsons, Luke Alexander

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

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.

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.

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.

Observational uncertainty and regional climate model evaluation: A pan-European perspective

Science.gov (United States)

Kotlarski, Sven; Szabó, Péter; Herrera, Sixto; Räty, Olle; Keuler, Klaus; Soares, Pedro M.; Cardoso, Rita M.; Bosshard, Thomas; Pagé, Christian; Boberg, Fredrik; Gutiérrez, José M.; Jaczewski, Adam; Kreienkamp, Frank; Liniger, Mark. A.; Lussana, Cristian; Szepszo, Gabriella

2017-04-01

Local and regional climate change assessments based on downscaling methods crucially depend on the existence of accurate and reliable observational reference data. In dynamical downscaling via regional climate models (RCMs) observational data can influence model development itself and, later on, model evaluation, parameter calibration and added value assessment. In empirical-statistical downscaling, observations serve as predictand data and directly influence model calibration with corresponding effects on downscaled climate change projections. Focusing on the evaluation of RCMs, we here analyze the influence of uncertainties in observational reference data on evaluation results in a well-defined performance assessment framework and on a European scale. For this purpose we employ three different gridded observational reference grids, namely (1) the well-established EOBS dataset (2) the recently developed EURO4M-MESAN regional re-analysis, and (3) several national high-resolution and quality-controlled gridded datasets that recently became available. In terms of climate models five reanalysis-driven experiments carried out by five different RCMs within the EURO-CORDEX framework are used. Two variables (temperature and precipitation) and a range of evaluation metrics that reflect different aspects of RCM performance are considered. We furthermore include an illustrative model ranking exercise and relate observational spread to RCM spread. The results obtained indicate a varying influence of observational uncertainty on model evaluation depending on the variable, the season, the region and the specific performance metric considered. Over most parts of the continent, the influence of the choice of the reference dataset for temperature is rather small for seasonal mean values and inter-annual variability. Here, model uncertainty (as measured by the spread between the five RCM simulations considered) is typically much larger than reference data uncertainty. For

Study of effects of climate change in the Great South East. Stage 1. PACA report - Part I: Context and study summary, Part II: Climate simulations, Part III: Impact sector sheets, General report. Prospective study of effects of climate change in the Great South East (phase 2) - Mission of study of inter-regional and European collaborations

International Nuclear Information System (INIS)

Kornmann, Francois; Guiran, Ghislaine; Sadoux, Emmanuel; Weill, Frederic; Benkhelifa, Fouzi

2008-01-01

After a presentation of study objectives and scope, a first report outlines the actuality of climate change, describes predicted climate changes for the PACA region in terms of warming and decrease of precipitations. Regional social-economic challenges and sector impacts are also briefly described. The second report presents the adopted climate simulation parameters, and discusses results obtained in terms of temperature and of precipitations by 2030, 2050 and 2080 for the whole Great South East region. The third part proposes sector sheets which contain discussions of effects of climate change on the water resource, on biodiversity, on forest, on agriculture, on human health, on tourism, on energy, on building and transports, on natural risks. The next document is based on the previous ones. It discusses and comments the outcome of the first phase, the present situation of the region in terms of territorial dynamics and effects of climate change, and indicators of climate change. It also draws lessons from the prospective study which resulted in three scenarios for which a strategic assessment is proposed

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

Science.gov (United States)

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

2017-12-01

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

Modelling of anthropogenic and natural climate changes

Energy Technology Data Exchange (ETDEWEB)

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

1993-06-01

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

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

Science.gov (United States)

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

2010-12-01

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

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

Czech Academy of Sciences Publication Activity Database

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

2014-01-01

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

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

Ensemble catchment hydrological modelling for climate change impact analysis

Science.gov (United States)

Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

2014-05-01

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

Ensemble of regional climate model projections for Ireland

Science.gov (United States)

Nolan, Paul; McGrath, Ray

2016-04-01

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

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

Science.gov (United States)

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

2018-06-01

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

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

Science.gov (United States)

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

Evaluation of global climate models for Indian monsoon climatology

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Science.gov (United States)

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

2015-10-01

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

Application of the HBV model for assessment of climate change impacts on the elements of hydrological cycle for the Struma River Basin

International Nuclear Information System (INIS)

Stanev, Krassimir

2004-01-01

The model used in this report is a version of the HBV model developed for the project Climate Change and Energy Production, a Nordic project aimed at evaluating the impacts of climate change on the water resources. It has a simple vegetation parametrization including interception, temperature based evapotranspiration. calculations, lake evaporation, lake routing, glacier mass balance simulation, special functions for climate change simulations etc. The HBV model, originally developed at the Swedish Meteorological and Hydrological Institute in the first half of the seventies (Bergstroem 1976) has gained widespread use for a large range of applications both in Scandinavia and beyond. It can be classified as a semi-distributed conceptual model. The version described in this report was developed for the Nordic project 'Climate change and Energy Production' (Saelthun 1996), as a synthesis of several versions used in the different Nordic countries. The main input variables are the average daily temperature, daily totals of the precipitation, the potential evapotranspiration and the daily discharges. The HBV model was applied for assessment of climate change impacts on the elements of hydrological cycle for the Struma river basin. The river Struma flows from North to South up to the Aegean Sea. Considerable part of the river basin is situated in northwest part of Bulgaria, heaving an area of more than 10 000 km 2 and average elevation about 900m asl (cross-section Marino pole). The period of 16 years (1973-1988), four precipitation and temperature stations were used for the model parameters evaluation. The achieved value of R 2 (Nash criterion) is 0.55. The climate change impact calculations (monthly values of temperatures change in o C and precipitation change in %) for two scenarios were used for the input data correction to the HBV model. The obtained results are promising and they show the potential possibility for the HBV model use to assess the climate change

Assessing the impacts of climate change on natural resource systems

Energy Technology Data Exchange (ETDEWEB)

Frederick, K.D.; Rosenberg, N.J. [eds.

1994-11-30

This volume is a collection of papers addressing the theme of potential impacts of climatic change. Papers are entitled Integrated Assessments of the Impacts of Climatic Change on Natural Resources: An Introductory Editorial; Framework for Integrated Assessments of Global Warming Impacts; Modeling Land Use and Cover as Part of Global Environmental Change; Assessing Impacts of Climatic Change on Forests: The State of Biological Modeling; Integrating Climatic Change and Forests: Economic and Ecological Assessments; Environmental Change in Grasslands: Assessment using Models; Assessing the Socio-economic Impacts of Climatic Change on Grazinglands; Modeling the Effects of Climatic Change on Water Resources- A Review; Assessing the Socioeconomic Consequences of Climate Change on Water Resources; and Conclusions, Remaining Issues, and Next Steps.

Nation-wide assessment of climate change impacts on crops in the Philippines and Peru as part of multi-disciplinary modelling framework

Science.gov (United States)

Fujisawa, Mariko; Kanamaru, Hideki

2016-04-01

Agriculture is vulnerable to environmental changes, and climate change has been recognized as one of the most devastating factors. In many developing countries, however, few studies have focused on nation-wide assessment of crop yield and crop suitability in the future, and hence there is a large pressure on science to provide policy makers with solid predictions for major crops in the countries in support of climate risk management policies and programmes. FAO has developed the tool MOSAICC (Modelling System for Agricultural Impacts of Climate Change) where statistical climate downscaling is combined with crop yield projections under climate change scenarios. Three steps are required to get the results: 1. The historical meteorological data such as temperature and precipitation for about 30 years were collected, and future climates were statistically downscaled to the local scale, 2. The historical crop yield data were collected and regression functions were made to estimate the yield by using observed climatic data and water balance during the growing period for each crop, and 3. The yield changes in the future were estimated by using the future climate data, produced by the first step, as an input to the yield regression functions. The yield was first simulated at sub-national scale and aggregated to national scale, which is intended to provide national policies with adaptation options. The methodology considers future changes in characteristics of extreme weather events as the climate projections are on daily scale while crop simulations are on 10-daily scale. Yields were simulated with two greenhouse gas concentration pathways (RCPs) for three GCMs per crop to account for uncertainties in projections. The crop assessment constitutes a larger multi-disciplinary assessment of climate change impacts on agriculture and vulnerability of livelihoods in terms of food security (e.g. water resources, agriculture market, household-level food security from socio

Strategies for Effective Implementation of Science Models into 6-9 Grade Classrooms on Climate, Weather, and Energy Topics

Science.gov (United States)

Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

2011-12-01

As atmospheric scientists, we depend on Numerical Weather Prediction (NWP) models. We use them to predict weather patterns, to understand external forcing on the atmosphere, and as evidence to make claims about atmospheric phenomenon. Therefore, it is important that we adequately prepare atmospheric science students to use computer models. However, the public should also be aware of what models are in order to understand scientific claims about atmospheric issues, such as climate change. Although familiar with weather forecasts on television and the Internet, the general public does not understand the process of using computer models to generate a weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Since computer models are the best method we have to forecast the future of our climate, scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum. According to the National Science Education Standards, teachers are encouraged to science models into the classroom as a way to aid in the understanding of the nature of science. However, there is very little description of what constitutes a science model, so the term is often associated with scale models. Therefore, teachers often use drawings or scale representations of physical entities, such as DNA, the solar system, or bacteria. In other words, models used in classrooms are often used as visual representations, but the purpose of science models is often overlooked. The implementation of a model-based curriculum in the science classroom can be an effective way to prepare students to think critically, problem solve, and make informed decisions as a contributing member of society. However, there are few resources available to help teachers implement science models into the science curriculum effectively. Therefore, this research project looks at

The Alpine snow-albedo feedback in regional climate models

Science.gov (United States)

Winter, Kevin J.-P. M.; Kotlarski, Sven; Scherrer, Simon C.; Schär, Christoph

2017-02-01

The effect of the snow-albedo feedback (SAF) on 2m temperatures and their future changes in the European Alps is investigated in the ENSEMBLES regional climate models (RCMs) with a focus on the spring season. A total of 14 re-analysis-driven RCM experiments covering the period 1961-2000 and 10 GCM-driven transient climate change projections for 1950-2099 are analysed. A positive springtime SAF is found in all RCMs, but the range of the diagnosed SAF is large. Results are compared against an observation-based SAF estimate. For some RCMs, values very close to this estimate are found; other models show a considerable overestimation of the SAF. Net shortwave radiation has the largest influence of all components of the energy balance on the diagnosed SAF and can partly explain its spatial variability. Model deficiencies in reproducing 2m temperatures above snow and ice and associated cold temperature biases at high elevations seem to contribute to a SAF overestimation in several RCMs. The diagnosed SAF in the observational period strongly influences the estimated SAF contribution to twenty first century temperature changes in the European Alps. This contribution is subject to a clear elevation dependency that is governed by the elevation-dependent change in the number of snow days. Elevations of maximum SAF contribution range from 1500 to 2000 m in spring and are found above 2000 m in summer. Here, a SAF contribution to the total simulated temperature change between 0 and 0.5 °C until 2099 (multi-model mean in spring: 0.26 °C) or 0 and 14 % (multi-model mean in spring: 8 %) is obtained for models showing a realistic SAF. These numbers represent a well-funded but only approximate estimate of the SAF contribution to future warming, and a remaining contribution of model-specific SAF misrepresentations cannot be ruled out.

Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa.

Science.gov (United States)

Redding, David W; Tiedt, Sonia; Lo Iacono, Gianni; Bett, Bernard; Jones, Kate E

2017-07-19

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'. © 2017 The Authors.

IPCC. 4. climate assessment report, 2007

International Nuclear Information System (INIS)

2007-01-01

The mission and challenge of the Intergovernmental panel on climate change (IPCC, GIEC in French) is to evaluate, synthesize and make available the sum of scientific and economic information of the complex domain of climatic change, and in addition to make the results of these works accepted by government representatives of 192 states. This document makes a brief synthesis in three parts of the 4. assessment report of the IPCC: 1 - physical scientific bases of climatic change: characteristic of the phenomenon, greenhouse gas emissions trend, already observed effects, forecasts of climate models; 2 - impacts, adaptations and vulnerabilities of climatic change: types of future impacts, impacts per sector, regional impacts, limits of ecosystems adaptation; 3 - mitigation of climatic changes: past emissions and future trends, possible mitigation actions and cost, possible political levers for emissions abatement. A last part introduces the French researchers involved in IPCC's works. (J.S.)

Study on the Impacts of Climate Change on China's Agriculture

Energy Technology Data Exchange (ETDEWEB)

Liu, H.; Li, Xiubin [Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, 100101 (China); Fischer, G.; Sun, Laixiang [International Institute for Applied System Analysis IIASA, A-2361 Laxenburg (Austria)

2004-07-01

This paper measures the economic impacts of climate change on China's agriculture based on the Ricardian model. By using county-level cross-sectional data on agricultural net revenue, climate, and other economic and geographical data for 1275 agriculture dominated counties, we find that under most climate change scenarios both higher temperature and more precipitation would have an overall positive impact on China's agriculture. However, the impacts vary seasonally and regionally. Autumn effect is the most positive, but spring effect is the most negative. Applying the model to five climate scenarios in the year 2050 shows that the East, the Central part, the South, the northern part of the Northeast, and the Plateau would benefit from climate change, but the Southwest, the Northwest and the southern part of the Northeast may be negatively affected. In the North, most scenarios show that they may benefit from climate change. In summary, all of China would benefit from climate change in most scenarios.

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

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