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John T Fasullo - One of the best experts on this subject based on the ideXlab platform.
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Evaluating Simulated Climate Patterns from theCMIP Archives Using Satellite and Reanalysis Datasets
2020Co-Authors: John T FasulloAbstract:Abstract. An objective approach is presented for scoring coupled climate simulations through an evaluation against satellite and reanalysis datasets during the satellite era (i.e. since 1979). Here, the approach is described and applied to available Coupled Model Intercomparison Project (CMIP) archives and the Community Earth System Model Version 1 Large Ensemble archives, with the goal of benchmarking model performance and its evolution across CMIP generations. The approach adopted is designed to minimize the sensitivity of scores to internal variability, external forcings, and model tuning. Toward this end, models are scored based on pattern correlations of their simulated mean state, seasonal contrasts, and ENSO teleconnections. A broad range of feedback-relevant fields is considered and summarized on various timescales (climatology, seasonal, interannual) and physical realms (energy budget, water cycle, dynamics). Fields are also generally chosen for which observational uncertainty is small compared to model structural differences and error. Highest mean variable scores across models are reported for well-observed fields such as sea level pressure, precipitable water, and outgoing longwave radiation while the lowest scores are reported for 500 hPa vertical velocity, net surface energy flux, and precipitation minus evaporation. The fidelity of CMIP models is found to vary widely both within and across CMIP generations. Systematic increases in model fidelity across CMIP generations are identified with the greatest improvements in dynamic and energetic fields. Examples include 500 hPa eddy geopotential height and relative humidity, and shortwave cloud forcing. Improvements for ENSO scores are substantially greater than for the annual mean or seasonal contrasts. Analysis output data generated by this approach is made freely available online for a broad range of model ensembles, including the CMIP archives and various single-model large ensembles. These multi-model archives allow for an exploration of relationships between metrics across a range of simulations while the single-model large ensemble archives enable an estimation of the influence of internal variability on reported scores. The entire output archive, updated regularly, can be accessed at: http://webext.cgd.ucar.edu/Multi-Case/CMAT/index.html chosen for which observational uncertainty is small compared to model structural error. 20 Highest mean variable scores across models are reported for well-observed fields such as sea level pressure, precipitable water, and outgoing longwave radiation while the lowest scores are reported for 500 hPa vertical velocity, net surface energy flux, and precipitation minus evaporation. The fidelity of CMIP models is found to vary widely both within and across CMIP generations. CMATv1 scores report systematic increases in model fidelity across CMIP generations with the greatest improvements in dynamic and energetic fields. Examples include 500 hPa eddy geopotential height and relative humidity, 25 and shortwave cloud forcing. Improvements for ENSO scores are substantially greater than for the annual mean or seasonal contrasts. Analysis output data is made freely available online for a broad range of model ensembles, including the CMIP archives and various single-model large ensembles. These multi-model archives allow for an exploration of relationships between metrics 30 across a range of simulations while the single-model large ensemble archives enable an estimation of the influence of internal variability on CMATV1 scores. The entire CMATv1 archive, updated regularly, can be accessed at: http://webext.cgd.ucar.edu/Multi-Case/CMAT/index.html .
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reexamining the relationship between climate sensitivity and the southern hemisphere radiation budget in CMIP models
Journal of Climate, 2015Co-Authors: Kevin M Grise, Lorenzo M Polvani, John T FasulloAbstract:AbstractRecent efforts to narrow the spread in equilibrium climate sensitivity (ECS) across global climate models have focused on identifying observationally based constraints, which are rooted in empirical correlations between ECS and biases in the models’ present-day climate. This study reexamines one such constraint identified from CMIP3 models: the linkage between ECS and net top-of-the-atmosphere radiation biases in the Southern Hemisphere (SH).As previously documented, the intermodel spread in the ECS of CMIP3 models is linked to present-day cloud and net radiation biases over the midlatitude Southern Ocean, where higher cloud fraction in the present-day climate is associated with larger values of ECS. However, in this study, no physical explanation is found to support this relationship. Furthermore, it is shown here that this relationship disappears in CMIP5 models and is unique to a subset of CMIP models characterized by unrealistically bright present-day clouds in the SH subtropics. In view of th...
Kevin M Grise - One of the best experts on this subject based on the ideXlab platform.
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reexamining the relationship between climate sensitivity and the southern hemisphere radiation budget in CMIP models
Journal of Climate, 2015Co-Authors: Kevin M Grise, Lorenzo M Polvani, John T FasulloAbstract:AbstractRecent efforts to narrow the spread in equilibrium climate sensitivity (ECS) across global climate models have focused on identifying observationally based constraints, which are rooted in empirical correlations between ECS and biases in the models’ present-day climate. This study reexamines one such constraint identified from CMIP3 models: the linkage between ECS and net top-of-the-atmosphere radiation biases in the Southern Hemisphere (SH).As previously documented, the intermodel spread in the ECS of CMIP3 models is linked to present-day cloud and net radiation biases over the midlatitude Southern Ocean, where higher cloud fraction in the present-day climate is associated with larger values of ECS. However, in this study, no physical explanation is found to support this relationship. Furthermore, it is shown here that this relationship disappears in CMIP5 models and is unique to a subset of CMIP models characterized by unrealistically bright present-day clouds in the SH subtropics. In view of th...
H Y - One of the best experts on this subject based on the ideXlab platform.
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characterizing and understanding radiation budget biases in CMIP3 CMIP5 gcms contemporary gcm and reanalysis
Journal of Geophysical Research, 2013Co-Authors: J.-l. F. Li, Duane E Waliser, Graeme L Stephens, Tristan Lecuyer, Seiji Kato, Norman G Loeb, H YAbstract:[1] We evaluate the annual mean radiative shortwave flux downward at the surface (RSDS) and reflected shortwave (RSUT) and radiative longwave flux upward at top of atmosphere (RLUT) from the twentieth century Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 3 (CMIP3) simulations as well as from the NASA GEOS5 model and Modern-Era Retrospective Analysis for Research and Applications analysis. The results show that a majority of the models have significant regional biases in the annual means of RSDS, RLUT, and RSUT, with biases from −30 to 30 W m−2. While the global average CMIP5 ensemble mean biases of RSDS, RLUT, and RSUT are reduced compared to CMIP3 by about 32% (e.g., −6.9 to 2.5 W m−2), 43%, and 56%, respectively. This reduction arises from a more complete cancellation of the pervasive negative biases over ocean and newly larger positive biases over land. In fact, based on these biases in the annual mean, Taylor diagram metrics, and RMSE, there is virtually no progress in the simulation fidelity of RSDS, RLUT, and RSUT fluxes from CMIP3 to CMIP5. A persistent systematic bias in CMIP3 and CMIP5 is the underestimation of RSUT and overestimation of RSDS and RLUT in the convectively active regions of the tropics. The amount of total ice and liquid atmospheric water content in these areas is also underestimated. We hypothesize that at least a part of these persistent biases stem from the common global climate model practice of ignoring the effects of precipitating and/or convective core ice and liquid in their radiation calculations.
Ronald J Stouffer - One of the best experts on this subject based on the ideXlab platform.
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Representation of Southern Ocean Properties across Coupled Model Intercomparison Project Generations: CMIP3 to CMIP6
eScholarship University of California, 2020Co-Authors: Rl Beadling, Ronald J Stouffer, Jl Russell, Mazloff M, Ld Talley, Pj Goodman, Jb Sallée, Ht Hewitt, Hyder P, Pandde AmarjiitAbstract:Abstract The air–sea exchange of heat and carbon in the Southern Ocean (SO) plays an important role in mediating the climate state. The dominant role the SO plays in storing anthropogenic heat and carbon is a direct consequence of the unique and complex ocean circulation that exists there. Previous generations of climate models have struggled to accurately represent key SO properties and processes that influence the large-scale ocean circulation. This has resulted in low confidence ascribed to twenty-first-century projections of the state of the SO from previous generations of models. This analysis provides a detailed assessment of the ability of models contributed to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to represent important observationally based SO properties. Additionally, a comprehensive overview of CMIP6 performance relative to CMIP3 and CMIP5 is presented. CMIP6 models show improved performance in the surface wind stress forcing, simulating stronger and less equatorward-biased wind fields, translating into an improved representation of the Ekman upwelling over the Drake Passage latitudes. An increased number of models simulate an Antarctic Circumpolar Current (ACC) transport within observational uncertainty relative to previous generations; however, several models exhibit extremely weak transports. Generally, the upper SO remains biased warm and fresh relative to observations, and Antarctic sea ice extent remains poorly represented. While generational improvement is found in many metrics, persistent systematic biases are highlighted that should be a priority during model development. These biases need to be considered when interpreting projected trends or biogeochemical properties in this region
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overview of the coupled model intercomparison project phase 6 CMIP6 experimental design and organization
Geoscientific Model Development, 2015Co-Authors: Veronika Eyring, Catherine A, Bjorn Stevens, Sandrine Bony, Ronald J Stouffer, Gerald A Meehl, K E TaylorAbstract:Abstract. By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.
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Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organisation
Geoscientific Model Development Discussions, 2015Co-Authors: Veronika Eyring, Bjorn Stevens, Sandrine Bony, Ronald J Stouffer, Gerald A Meehl, C. Senior, K E TaylorAbstract:Abstract. By coordinating the design and distribution of global climate model simulations of the past, current and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima experiments) and the CMIP Historical Simulation (1850–near-present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP, (2) common standards, coordination, infrastructure and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble, and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and the CMIP Historical Simulation to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP Historical Simulation, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. The participation in the CMIP6-Endorsed MIPs will be at the discretion of the modelling groups, and will depend on scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: (i) how does the Earth system respond to forcing?, (ii) what are the origins and consequences of systematic model biases?, and (iii) how can we assess future climate changes given climate variability, predictability and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and the CMIP6 Historical Simulation, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.
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Climate model intercomparisons: Preparing for the next phase
Eos Transactions American Geophysical Union, 2014Co-Authors: Gerald A Meehl, Veronika Eyring, Sandrine Bony, Ronald J Stouffer, Richard H. Moss, Karl E. Taylor, Bjorn StevensAbstract:Since 1995, the Coupled Model Intercomparison Project (CMIP) has coordinated climate model experiments involving multiple international modeling teams. Through CMIP, climate modelers and scientists from around the world have analyzed and compared state-of-the-art climate model simulations to gain insights into the processes, mechanisms, and consequences of climate variability and climate change. This has led to a better understanding of past, present, and future climate, and CMIP model experiments have routinely been the basis for future climate change assessments made by the Intergovernmental Panel on Climate Change (IPCC) [e.g., IPCC, 2013, and references therein].
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overview of the coupled model intercomparison project
Bulletin of the American Meteorological Society, 2005Co-Authors: Gerald A Meehl, B J Mcavaney, Curt Covey, Mojib Latif, Ronald J StoufferAbstract:Abstract The Coupled Model Intercomparison Project (CMIP) involves study and intercomparison of multi-model simulations of present and future climate. The simulations of the future use idealized forcing in increase is compounded which CO2 1% yr−1 until it doubles (near year 70) with global coupled models that contain, typically, components representing atmosphere, ocean, sea ice, and land surface. Results from CMIP diagnostic subprojects were presented at the Second CMIP Workshop held at the Max Planck Institute for Meteorology in Hamburg, Germany, in September 2003. Significant progress in diagnosing and understanding results from global coupled models has been made since the time of the First CMIP Workshop in Melbourne, Australia, in 1998. For example, the issue of flux adjustment is slowly fading as more and more models obtain stable multi-century surface climates without them. El Nino variability, usually about half the observed amplitude in the previous generation of coupled models, is now more accur...
G. M. Flato - One of the best experts on this subject based on the ideXlab platform.
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Sea-ice and its response to CO_2 forcing as simulated by global climate models
Climate Dynamics, 2004Co-Authors: G. M. FlatoAbstract:The simulation of sea-ice in global climate models participating in the Coupled Model Intercomparison Project (CMIP1 and CMIP2) is analyzed. CMIP1 simulations are of the unpertubed “control” climate whereas in CMIP2, all models have been forced with the same 1% yr^–1 increase in CO_2 concentration, starting from a near equilibrium initial condition. These simulations are not intended as forecasts of climate change, but rather provide a means of evaluating the response of current climate models to the same forcing. The difference in modeled response therefore indicates the range (or uncertainty) in model sensitivity to greenhouse gas and other climatic perturbations. The results illustrate a wide range in the ability of climate models to reproduce contemporary sea-ice extent and thickness; however, the errors are not obviously related to the manner in which sea-ice processes are represented in the models (e.g. the inclusion or neglect of sea-ice motion). The implication is that errors in the ocean and atmosphere components of the climate model are at least as important. There is also a large range in the simulated sea-ice response to CO_2 change, again with no obvious stratification in terms of model attributes. In contrast to results obtained earlier with a particular model, the CMIP ensemble yields rather mixed results in terms of the dependence of high-latitude warming on sea-ice initial conditions. There is an indication that, in the Arctic, models that produce thick ice in their control integration exhibit less warming than those with thin ice. The opposite tendency appears in the Antarctic (albeit with low statistical significance). There is a tendency for models with more extensive ice coverage in the Southern Hemisphere to exhibit greater Antarctic warming. Results for the Arctic indicate the opposite tendency (though with low statistical significance).
