Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this st...Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.展开更多
Future climate change is usually projected by coupled earth system models under specific emission sce- narios designed by integrated assessment models （IAMs）, and this offline approach means there is no interaction ...Future climate change is usually projected by coupled earth system models under specific emission sce- narios designed by integrated assessment models （IAMs）, and this offline approach means there is no interaction between the coupled earth system models and the IAMs. This paper introduces a new method to design possible future emission scenarios and corresponding climate change, in which a simple economic and climate damage component is added to the coupled earth system model of Beijing Normal University （BNU-ESM）. With the growth of population and technological expertise and the declining emission-to-output ratio described in the Dynamic Inte- grated Climate-Economy model, the projected carbon emission is 13.7 Gt C, resulting in a 2.4℃ warming by the end of the twenty-first century （2080-2099） compared with 1980-1999. This paper also suggests the importance of the land and ocean carbon cycle in determining the CO2 con- centration in the atmosphere. It is hoped that in the near future the next generation of coupled earth system models that include both the natural system and the social dimension will be developed.展开更多
基金jointly funded by the National Natural Science Foundation of China(NSFC)[grant number 42130608]the China Postdoctoral Science Foundation[grant number 2024M753169]。
文摘Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.
基金supported by the National Natural Science Foundation of China (41605036 and 41305053)the National Key Research and Development Program of China (2016YFA0602703)+1 种基金the National-Level Major Cultivation Project of Guangdong Province (2014GKXM058)the Open Project of the State Key Laboratory of Cryospheric Science (SKLCS-OP-2016-09)
文摘Future climate change is usually projected by coupled earth system models under specific emission sce- narios designed by integrated assessment models （IAMs）, and this offline approach means there is no interaction between the coupled earth system models and the IAMs. This paper introduces a new method to design possible future emission scenarios and corresponding climate change, in which a simple economic and climate damage component is added to the coupled earth system model of Beijing Normal University （BNU-ESM）. With the growth of population and technological expertise and the declining emission-to-output ratio described in the Dynamic Inte- grated Climate-Economy model, the projected carbon emission is 13.7 Gt C, resulting in a 2.4℃ warming by the end of the twenty-first century （2080-2099） compared with 1980-1999. This paper also suggests the importance of the land and ocean carbon cycle in determining the CO2 con- centration in the atmosphere. It is hoped that in the near future the next generation of coupled earth system models that include both the natural system and the social dimension will be developed.
