To assess the performances of state-of-the-art global climate models on simulating the Arctic clouds and surface radiation balance,the 2001–2014 Arctic Basin surface radiation budget,clouds,and the cloud radiative ef...To assess the performances of state-of-the-art global climate models on simulating the Arctic clouds and surface radiation balance,the 2001–2014 Arctic Basin surface radiation budget,clouds,and the cloud radiative effects(CREs)in 22 coupled model intercomparison project 6(CMIP6)models are evaluated against satellite observations.For the results from CMIP6 multi-model mean,cloud fraction(CF)peaks in autumn and is lowest in winter and spring,consistent with that from three satellite observation products(Cloud Sat-CALIPSO,CERESMODIS,and APP-x).Simulated CF also shows consistent spatial patterns with those in observations.However,almost all models overestimate the CF amount throughout the year when compared to CERES-MODIS and APP-x.On average,clouds warm the surface of the Arctic Basin mainly via the longwave(LW)radiation cloud warming effect in winter.Simulated surface energy loss of LW is less than that in CERES-EBAF observation,while the net surface shortwave(SW)flux is underestimated.The biases may result from the stronger cloud LW warming effect and SW cooling effect from the overestimated CF by the models.These two biases compensate each other,yielding similar net surface radiation flux between model output(3.0 W/m2)and CERES-EBAF observation(6.1 W/m2).During 2001–2014,significant increasing trend of spring CF is found in the multi-model mean,consistent with previous studies based on surface and satellite observations.Although most of the 22 CMIP6 models show common seasonal cycles of CF and liquid water path/ice water path(LWP/IWP),large inter-model spreads exist in the amounts of CF and LWP/IWP throughout the year,indicating the influences of different cloud parameterization schemes used in different models.Cloud Feedback Model Intercomparison Project(CFMIP)observation simulator package(COSP)is a great tool to accurately assess the performance of climate models on simulating clouds.More intuitive and credible evaluation results can be obtained based on the COSP model output.In the future,with the release of more COSP output of CMIP6 models,it is expected that those inter-model spreads and the model-observation biases can be substantially reduced.Longer term active satellite observations are also necessary to evaluate models’cloud simulations and to further explore the role of clouds in the rapid Arctic climate changes.展开更多
The role of Arctic clouds in the recent rapid Arctic warming has attracted much attention.However,Arctic cloud water paths(CWPs)from reanalysis datasets have not been well evaluated.This study evaluated the CWPs as we...The role of Arctic clouds in the recent rapid Arctic warming has attracted much attention.However,Arctic cloud water paths(CWPs)from reanalysis datasets have not been well evaluated.This study evaluated the CWPs as well as LWPs(cloud liquid water paths)and IWPs(cloud ice water paths)from five reanalysis datasets(MERRA-2,MERRA,ERA-Interim,JRA-55,and ERA5)against the COSP(Cloud Feedback Model Intercomparison Project Observations Simulator Package)output for MODIS from the MERRA-2 CSP(COSP satellite simulator)collection(defined as M2Modis in short).Averaged over 1980-2015 and over the Arctic region(north of 60°N),the mean CWPs of these five datasets range from 49.5 g/m^(2)(MERRA)to 82.7 g/m^(2)(ERA-Interim),much smaller than that from M2Modis(140.0 g/m^(2)).However,the spatial distributions of CWPs,show similar patterns among these reanalyses,with relatively small values over Greenland and large values over the North Atlantic.Consistent with M2Modis,these reanalyses show larger LWPs than IWPs,except for ERA-Interim.However,MERRA-2 and MERRA underestimate the ratio of IWPs to CWPs over the entire Arctic,while ERA-Interim and JRA-55 overestimate this ratio.ERA5 shows the best performance in terms of the ratio of IWPs to CWPs.All datasets exhibit larger CWPs and LWPs in summer than in winter.For M2Modis,IWPs hold seasonal variation similar with LWPs over the land but opposite over the ocean.Following the Arctic warming,the trends in LWPs and IWPs during 1980~2015 show that LWPs increase and IWPs decrease across all datasets,although not statistically significant.Correlation analysis suggests that all datasets have similar interannual variability.The study further found that the inclusion of re-evaporation processes increases the humidity in the atmosphere over the land and that a more realistic liquid/ice phase can be obtained by independently treating the liquid and ice water contents.展开更多
基金The Major State Basic Research Development Program of China under contract No.2016YFA0601804the Global Change Research Program of China under contract No.2015CB953900+1 种基金the National Natural Science Foundation of China under contract Nos 41941007 and 41876220the China Postdoctoral Science Foundation under contract No.2020M681661
文摘To assess the performances of state-of-the-art global climate models on simulating the Arctic clouds and surface radiation balance,the 2001–2014 Arctic Basin surface radiation budget,clouds,and the cloud radiative effects(CREs)in 22 coupled model intercomparison project 6(CMIP6)models are evaluated against satellite observations.For the results from CMIP6 multi-model mean,cloud fraction(CF)peaks in autumn and is lowest in winter and spring,consistent with that from three satellite observation products(Cloud Sat-CALIPSO,CERESMODIS,and APP-x).Simulated CF also shows consistent spatial patterns with those in observations.However,almost all models overestimate the CF amount throughout the year when compared to CERES-MODIS and APP-x.On average,clouds warm the surface of the Arctic Basin mainly via the longwave(LW)radiation cloud warming effect in winter.Simulated surface energy loss of LW is less than that in CERES-EBAF observation,while the net surface shortwave(SW)flux is underestimated.The biases may result from the stronger cloud LW warming effect and SW cooling effect from the overestimated CF by the models.These two biases compensate each other,yielding similar net surface radiation flux between model output(3.0 W/m2)and CERES-EBAF observation(6.1 W/m2).During 2001–2014,significant increasing trend of spring CF is found in the multi-model mean,consistent with previous studies based on surface and satellite observations.Although most of the 22 CMIP6 models show common seasonal cycles of CF and liquid water path/ice water path(LWP/IWP),large inter-model spreads exist in the amounts of CF and LWP/IWP throughout the year,indicating the influences of different cloud parameterization schemes used in different models.Cloud Feedback Model Intercomparison Project(CFMIP)observation simulator package(COSP)is a great tool to accurately assess the performance of climate models on simulating clouds.More intuitive and credible evaluation results can be obtained based on the COSP model output.In the future,with the release of more COSP output of CMIP6 models,it is expected that those inter-model spreads and the model-observation biases can be substantially reduced.Longer term active satellite observations are also necessary to evaluate models’cloud simulations and to further explore the role of clouds in the rapid Arctic climate changes.
基金The National Key R&D Program of China under contract No.2018YFA0605904the Global Change Research Program of China under contract No.2015CB953900+1 种基金the Innovative Platform Program of Chinese Arctic and Antarctic Administration under contract No.CXPT2020009the Program of China Scholarships Council under contract No.201908320511.
文摘The role of Arctic clouds in the recent rapid Arctic warming has attracted much attention.However,Arctic cloud water paths(CWPs)from reanalysis datasets have not been well evaluated.This study evaluated the CWPs as well as LWPs(cloud liquid water paths)and IWPs(cloud ice water paths)from five reanalysis datasets(MERRA-2,MERRA,ERA-Interim,JRA-55,and ERA5)against the COSP(Cloud Feedback Model Intercomparison Project Observations Simulator Package)output for MODIS from the MERRA-2 CSP(COSP satellite simulator)collection(defined as M2Modis in short).Averaged over 1980-2015 and over the Arctic region(north of 60°N),the mean CWPs of these five datasets range from 49.5 g/m^(2)(MERRA)to 82.7 g/m^(2)(ERA-Interim),much smaller than that from M2Modis(140.0 g/m^(2)).However,the spatial distributions of CWPs,show similar patterns among these reanalyses,with relatively small values over Greenland and large values over the North Atlantic.Consistent with M2Modis,these reanalyses show larger LWPs than IWPs,except for ERA-Interim.However,MERRA-2 and MERRA underestimate the ratio of IWPs to CWPs over the entire Arctic,while ERA-Interim and JRA-55 overestimate this ratio.ERA5 shows the best performance in terms of the ratio of IWPs to CWPs.All datasets exhibit larger CWPs and LWPs in summer than in winter.For M2Modis,IWPs hold seasonal variation similar with LWPs over the land but opposite over the ocean.Following the Arctic warming,the trends in LWPs and IWPs during 1980~2015 show that LWPs increase and IWPs decrease across all datasets,although not statistically significant.Correlation analysis suggests that all datasets have similar interannual variability.The study further found that the inclusion of re-evaporation processes increases the humidity in the atmosphere over the land and that a more realistic liquid/ice phase can be obtained by independently treating the liquid and ice water contents.
