Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both g...Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.展开更多
Revealing regional climate changes is vital for policymaking activities related to climate change adaptation and mitigation.South China is a well-developed region with a dense population,but the level of uncertainty i...Revealing regional climate changes is vital for policymaking activities related to climate change adaptation and mitigation.South China is a well-developed region with a dense population,but the level of uncertainty in climate projections remains to be evaluated in detail.In this study,we comprehensively assessed the historical simulations and future projections of climate change in South China based on CMIP5/CMIP6 models.We show evidence that CMIP5/CMIP6 models can skillfully reproduce the observed distributions of annual/seasonal mean temperature but show much lower skill for precipitation.CMIP6 outperforms CMIP5 in the historical simulations,as evidenced by more models with lower bias magnitude and higher skill scores.During 2021–2100,the annual mean temperature over South China is projected to increase significantly at a rate of 0.53(0.42–0.63)and 0.59(0.52–0.66)℃(10 yr)^(-1),while precipitation is projected to increase slightly at a rate of 0.78(0.15–1.56)and 1.52(0.91–2.30)%(10 yr)^(-1),under the RCP8.5 and SSP5-8.5 scenarios,respectively.CMIP6 models project larger annual/seasonal mean temperature and precipitation trends than CMIP5 models under equivalent scenarios.The temperature in South China is projected to increase robustly by more than1.5℃during 2041–2060 under RCP4.5 and SSP2-4.5,but by 4.5℃during 2081–2100,under RCP8.5 and SSP5-8.5 with respect to 1850–1900.The uncertainty in temperature projections is mainly dominated by model uncertainty and scenario uncertainty,while internal uncertainty contributes some of the uncertainty during the near-term.The uncertainty in precipitation projection stems mainly from internal uncertainty and model uncertainty.For both the temperature and precipitation projection uncertainty,the relative sizes of contributions from the main contributors vary with time and show obvious seasonal differences.展开更多
In the northern Tarim River Basin,the Weigan River Basin is a critical endorheic system characterized by extreme aridity,where drought poses a major natural hazard to agricultural production and ecological stability.T...In the northern Tarim River Basin,the Weigan River Basin is a critical endorheic system characterized by extreme aridity,where drought poses a major natural hazard to agricultural production and ecological stability.This study assessed the future evolution of drought under climate change by employing the standardized moisture anomaly index(SZI)on the basis of multi-model the Coupled Model Intercomparison Project Phase 6(CMIP6)simulations under historical conditions(1970–2014)and future scenarios(shared socioeconomic pathway(SSP)1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5 for 2015–2100).The results show that precipitation–evapotranspiration anomalies are projected to first decline but then increase over time,with increased fluctuations and uncertainty under high-emission scenarios(SSP5-8.5).These trends indicate intensifying drought risks and reveal a strong influence of emission pathways on regional water cycling.Temporal analysis of SZI indicates a transition from wetting to drying under lowand medium-emission pathways(SSP1-2.6 and SSP2-4.5),whereas high-emission scenarios are characterized by persistent drying and increased variability.The significant lower-tail dependence(0.271)observed under SSP2-4.5 and SSP5-8.5 suggests that extreme droughts may be subject to nonlinear co-amplification across scenarios.The frequency of moderate and more severe drought events is expected to increase substantially,especially under SSP5-8.5,where drought occurrence is predicted to extend into spring and autumn and become more evenly distributed throughout the year.Spatially,drought duration shows significant positive autocorrelation across all scenarios,with hot spots consistently concentrated in the southern and southeastern regions of the basin.Random forest analysis,interpreted as association-based pattern attribution,indicates that meteorological variables(precipitation and potential evapotranspiration(PET))make the greatest contributions to the hot spot pattern,followed by topography and soil moisture.Among land use categories,farmland generally shows higher drought sensitivity than other land use types,as reflected by its relative contribution patterns across scenarios.The spatial pattern of drought is statistically structured by climatic forcing,surface conditions,and soil moisture status,reflecting their coupled associations with hot spot occurrence.In addition,a drought spatial uncertainty index was constructed from multi-scenario hot spot maps,revealing spatially heterogeneous structural variability throughout the basin.Correlation analysis further highlights strong internal couplings among environmental variables(e.g.,elevation-linked hydroclimatic gradients and grassland–bare soil contrasts).These findings offer a scientific basis for developing region-specific drought monitoring and adaptation strategies under future climate change conditions.展开更多
This article evaluates the performance of 20 Coupled Model Intercomparison Project phase 6(CMIP6)models in simulating temperature and precipitation over China through comparisons with gridded observation data for the ...This article evaluates the performance of 20 Coupled Model Intercomparison Project phase 6(CMIP6)models in simulating temperature and precipitation over China through comparisons with gridded observation data for the period of 1995–2014,with a focus on spatial patterns and interannual variability.The evaluations show that the CMIP6 models perform well in reproducing the climatological spatial distribution of temperature and precipitation,with better performance for temperature than for precipitation.Their interannual variability can also be reasonably captured by most models,however,poor performance is noted regarding the interannual variability of winter precipitation.Based on the comprehensive performance for the above two factors,the“highest-ranked”models are selected as an ensemble(BMME).The BMME outperforms the ensemble of all models(AMME)in simulating annual and winter temperature and precipitation,particularly for those subregions with complex terrain but it shows little improvement for summer temperature and precipitation.The AMME and BMME projections indicate annual increases for both temperature and precipitation across China by the end of the 21st century,with larger increases under the scenario of the Shared Socioeconomic Pathway 5/Representative Concentration Pathway 8.5(SSP585)than under scenario of the Shared Socioeconomic Pathway 2/Representative Concentration Pathway 4.5(SSP245).The greatest increases of annual temperature are projected for higher latitudes and higher elevations and the largest percentage-based increases in annual precipitation are projected to occur in northern and western China,especially under SSP585.However,the BMME,which generally performs better in these regions,projects lower changes in annual temperature and larger variations in annual precipitation when compared to the AMME projections.展开更多
Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate...Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate models to project future changes in precipitation extremes.The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs).The results were derived using the modified Mann-Kendall test,Sen's slope estimator,student's t-test,and probability density function approach.Eight extreme precipitation indices were assessed,including wet days(RR1mm),heavy precipitation days(RR10mm),very heavy precipitation days(RR20mm),severe precipitation days(RR50mm),consecutive wet days(CWD),consecutive dry days(CDD),maximum 5-day precipitation amount(RX5day),and simple daily intensity index(SDII).The future changes were estimated in two time periods for the 21^(st) century(i.e.,near future(NF;2021-2060)and far future(FF;2061-2100))under two Shared Socioeconomic Pathway(SSP)scenarios(SSP2-4.5 and SSP5-8.5).The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^(st) century(2061-2100).Moreover,from the results of multimodel ensemble means(MMEMs),extreme precipitation indices of RR1mm,RR10mm,RR20mm,CWD,and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario.The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part.The probability density function of extreme precipitation indices suggests a frequent(intense)occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario,with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD.The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding,soil erosion,water resource management,food security,and agriculture development.展开更多
Precipitation over the Tibetan Plateau(TP)is important to local and downstream ecosystems.Based on a weighting method considering model skill and independence,changes in the TP precipitation for near-term(2021-40),mid...Precipitation over the Tibetan Plateau(TP)is important to local and downstream ecosystems.Based on a weighting method considering model skill and independence,changes in the TP precipitation for near-term(2021-40),mid-term(2041-60)and long-term(2081-2100)under shared socio-economic pathways(SSP1-1.9,SSP1-2.6,SSP2-4.5,SSSP3-7.0,SSP5-8.5)are projected with 27 models from the latest Sixth Phase of the Couple Model Intercomparison Project.The annual mean precipitation is projected to increase by 7.4%-21.6%under five SSPs with a stronger change in the northern TP by the end of the 21st century relative to the present climatology.Changes in the TP precipitation at seasonal scales show a similar moistening trend to that of annual mean precipitation,except for the drying trend in winter precipitation along the southern edges of the TP.Weighting generally suggests a slightly stronger increase in TP precipitation with reduced model uncertainty compared to equally-weighted projections.The effect of weighting exhibits spatial and seasonal differences.Seasonally,weighting leads to a prevailing enhancement of increase in spring precipitation over the TP.Spatially,the influence of weighting is more remarkable over the northwestern TP regarding the annual,summer and autumn precipitation.Differences between weighted and original MMEs can give us more confidence in a stronger increase in precipitation over the TP,especially for the season of spring and the region of the northwestern TP,which requires additional attention in decision making.展开更多
The outputs of the Chinese Academy of Sciences(CAS) Flexible Global Ocean–Atmosphere–Land System(FGOALS-f3-L) model for the baseline experiment of the Atmospheric Model Intercomparison Project simulation in the Diag...The outputs of the Chinese Academy of Sciences(CAS) Flexible Global Ocean–Atmosphere–Land System(FGOALS-f3-L) model for the baseline experiment of the Atmospheric Model Intercomparison Project simulation in the Diagnostic,Evaluation and Characterization of Klima common experiments of phase 6 of the Coupled Model Intercomparison Project(CMIP6) are described in this paper. The CAS FGOALS-f3-L model, experiment settings, and outputs are all given. In total,there are three ensemble experiments over the period 1979–2014, which are performed with different initial states. The model outputs contain a total of 37 variables and include the required three-hourly mean, six-hourly transient, daily and monthly mean datasets. The baseline performances of the model are validated at different time scales. The preliminary evaluation suggests that the CAS FGOALS-f3-L model can capture the basic patterns of atmospheric circulation and precipitation well, including the propagation of the Madden–Julian Oscillation, activities of tropical cyclones, and the characterization of extreme precipitation. These datasets contribute to the benchmark of current model behaviors for the desired continuity of CMIP.展开更多
The datasets of two Ocean Model Intercomparison Project(OMIP)simulation experiments from the LASG/IAP Climate Ocean Model,version 3(LICOM3),forced by two different sets of atmospheric surface data,are described in thi...The datasets of two Ocean Model Intercomparison Project(OMIP)simulation experiments from the LASG/IAP Climate Ocean Model,version 3(LICOM3),forced by two different sets of atmospheric surface data,are described in this paper.The experiment forced by CORE-II(Co-ordinated Ocean–Ice Reference Experiments,Phase II)data(1948–2009)is called OMIP1,and that forced by JRA55-do(surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis)data(1958–2018)is called OMIP2.First,the improvement of LICOM from CMIP5 to CMIP6 and the configurations of the two experiments are described.Second,the basic performances of the two experiments are validated using the climatological-mean and interannual time scales from observation.We find that the mean states,interannual variabilities,and long-term linear trends can be reproduced well by the two experiments.The differences between the two datasets are also discussed.Finally,the usage of these data is described.These datasets are helpful toward understanding the origin system bias of the fully coupled model.展开更多
Based on 20 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),this article explored possible reasons for differences in simulation biases and projected changes in precipitation in northern China ...Based on 20 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),this article explored possible reasons for differences in simulation biases and projected changes in precipitation in northern China among the allmodel ensemble(AMME),“highest-ranked”model ensemble(BMME),and“lowest-ranked”model ensemble(WMME),from the perspective of atmospheric circulations and moisture budgets.The results show that the BMME and AMME reproduce the East Asian winter circulations better than the WMME.Compared with the AMME and WMME,the BMME reduces the overestimation of evaporation,thereby improving the simulation of winter precipitation.The three ensemble simulated biases for the East Asian summer circulations are generally similar,characterized by a stronger zonal pressure gradient between the mid-latitudes of the North Pacific and East Asia and a northward displacement of the East Asian westerly jet.However,the simulated vertical moisture advection is improved in the BMME,contributing to the slightly higher performance of the BMME than the AMME and WMME on summer precipitation in North and Northeast China.Compared to the AMME and WMME,the BMME projects larger increases in precipitation in northern China during both seasons by the end of the 21st century under the Shared Socioeconomic Pathway 5-8.5(SSP5-8.5).One of the reasons is that the increase in evaporation projected by the BMME is larger.The projection of a greater dynamic contribution by the BMME also plays a role.In addition,larger changes in the nonlinear components in the BMME projection contribute to a larger increase in winter precipitation in northern China.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.U2342210 and 42275043)the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant Nos.J2223806,ZDJ2024-25 and ZDJ2025-34)。
文摘Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.
基金jointly supported by the Joint Funds of the National Natural Science Foundation of China(Grant No.U2242203)the National Natural Science Foundation of China(Grant No.41905070)+4 种基金the Guangdong Basic and Applied Basic Research Foundation(Grant Nos.2021A1515011421,2023A1515240067,2023B1515020009)the National Key R&D Program of China(Grant No.2018YFC1505801)supported by the Guangdong Provincial Marine Meteorology Science Data Center(2024B1212070014)the China Meteorology Administration Key Innovation Team of Tropical Meteorology(Grant No.CMA2023ZD08)State Key Laboratory of Tropical Oceanography,South China Sea Institute of Oceanology,Chinese Academy of Sciences(Project No.LTO2311)。
文摘Revealing regional climate changes is vital for policymaking activities related to climate change adaptation and mitigation.South China is a well-developed region with a dense population,but the level of uncertainty in climate projections remains to be evaluated in detail.In this study,we comprehensively assessed the historical simulations and future projections of climate change in South China based on CMIP5/CMIP6 models.We show evidence that CMIP5/CMIP6 models can skillfully reproduce the observed distributions of annual/seasonal mean temperature but show much lower skill for precipitation.CMIP6 outperforms CMIP5 in the historical simulations,as evidenced by more models with lower bias magnitude and higher skill scores.During 2021–2100,the annual mean temperature over South China is projected to increase significantly at a rate of 0.53(0.42–0.63)and 0.59(0.52–0.66)℃(10 yr)^(-1),while precipitation is projected to increase slightly at a rate of 0.78(0.15–1.56)and 1.52(0.91–2.30)%(10 yr)^(-1),under the RCP8.5 and SSP5-8.5 scenarios,respectively.CMIP6 models project larger annual/seasonal mean temperature and precipitation trends than CMIP5 models under equivalent scenarios.The temperature in South China is projected to increase robustly by more than1.5℃during 2041–2060 under RCP4.5 and SSP2-4.5,but by 4.5℃during 2081–2100,under RCP8.5 and SSP5-8.5 with respect to 1850–1900.The uncertainty in temperature projections is mainly dominated by model uncertainty and scenario uncertainty,while internal uncertainty contributes some of the uncertainty during the near-term.The uncertainty in precipitation projection stems mainly from internal uncertainty and model uncertainty.For both the temperature and precipitation projection uncertainty,the relative sizes of contributions from the main contributors vary with time and show obvious seasonal differences.
基金supported by the Key Research and Development Project of Xinjiang Uygur Autonomous Region,China(2022B02049)the Major Science and Technology Special Project of Xinjiang Uygur Autonomous Region,China(2024A03007-5).
文摘In the northern Tarim River Basin,the Weigan River Basin is a critical endorheic system characterized by extreme aridity,where drought poses a major natural hazard to agricultural production and ecological stability.This study assessed the future evolution of drought under climate change by employing the standardized moisture anomaly index(SZI)on the basis of multi-model the Coupled Model Intercomparison Project Phase 6(CMIP6)simulations under historical conditions(1970–2014)and future scenarios(shared socioeconomic pathway(SSP)1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5 for 2015–2100).The results show that precipitation–evapotranspiration anomalies are projected to first decline but then increase over time,with increased fluctuations and uncertainty under high-emission scenarios(SSP5-8.5).These trends indicate intensifying drought risks and reveal a strong influence of emission pathways on regional water cycling.Temporal analysis of SZI indicates a transition from wetting to drying under lowand medium-emission pathways(SSP1-2.6 and SSP2-4.5),whereas high-emission scenarios are characterized by persistent drying and increased variability.The significant lower-tail dependence(0.271)observed under SSP2-4.5 and SSP5-8.5 suggests that extreme droughts may be subject to nonlinear co-amplification across scenarios.The frequency of moderate and more severe drought events is expected to increase substantially,especially under SSP5-8.5,where drought occurrence is predicted to extend into spring and autumn and become more evenly distributed throughout the year.Spatially,drought duration shows significant positive autocorrelation across all scenarios,with hot spots consistently concentrated in the southern and southeastern regions of the basin.Random forest analysis,interpreted as association-based pattern attribution,indicates that meteorological variables(precipitation and potential evapotranspiration(PET))make the greatest contributions to the hot spot pattern,followed by topography and soil moisture.Among land use categories,farmland generally shows higher drought sensitivity than other land use types,as reflected by its relative contribution patterns across scenarios.The spatial pattern of drought is statistically structured by climatic forcing,surface conditions,and soil moisture status,reflecting their coupled associations with hot spot occurrence.In addition,a drought spatial uncertainty index was constructed from multi-scenario hot spot maps,revealing spatially heterogeneous structural variability throughout the basin.Correlation analysis further highlights strong internal couplings among environmental variables(e.g.,elevation-linked hydroclimatic gradients and grassland–bare soil contrasts).These findings offer a scientific basis for developing region-specific drought monitoring and adaptation strategies under future climate change conditions.
基金the National Key Research and Development Program of China(2018YFA0606301)the National Natural Science Foundation of China(42025502,41991285,42088101).
文摘This article evaluates the performance of 20 Coupled Model Intercomparison Project phase 6(CMIP6)models in simulating temperature and precipitation over China through comparisons with gridded observation data for the period of 1995–2014,with a focus on spatial patterns and interannual variability.The evaluations show that the CMIP6 models perform well in reproducing the climatological spatial distribution of temperature and precipitation,with better performance for temperature than for precipitation.Their interannual variability can also be reasonably captured by most models,however,poor performance is noted regarding the interannual variability of winter precipitation.Based on the comprehensive performance for the above two factors,the“highest-ranked”models are selected as an ensemble(BMME).The BMME outperforms the ensemble of all models(AMME)in simulating annual and winter temperature and precipitation,particularly for those subregions with complex terrain but it shows little improvement for summer temperature and precipitation.The AMME and BMME projections indicate annual increases for both temperature and precipitation across China by the end of the 21st century,with larger increases under the scenario of the Shared Socioeconomic Pathway 5/Representative Concentration Pathway 8.5(SSP585)than under scenario of the Shared Socioeconomic Pathway 2/Representative Concentration Pathway 4.5(SSP245).The greatest increases of annual temperature are projected for higher latitudes and higher elevations and the largest percentage-based increases in annual precipitation are projected to occur in northern and western China,especially under SSP585.However,the BMME,which generally performs better in these regions,projects lower changes in annual temperature and larger variations in annual precipitation when compared to the AMME projections.
基金supported by the National Natural Science Foundation of China(42130405)the Innovative and Entrepreneurial Talent Program of Jiangsu Province(R2020SC04)+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA2006030201)the Research Fund for International Young Scientists of the National Natural Science Foundation of China(42150410381).
文摘Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate models to project future changes in precipitation extremes.The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs).The results were derived using the modified Mann-Kendall test,Sen's slope estimator,student's t-test,and probability density function approach.Eight extreme precipitation indices were assessed,including wet days(RR1mm),heavy precipitation days(RR10mm),very heavy precipitation days(RR20mm),severe precipitation days(RR50mm),consecutive wet days(CWD),consecutive dry days(CDD),maximum 5-day precipitation amount(RX5day),and simple daily intensity index(SDII).The future changes were estimated in two time periods for the 21^(st) century(i.e.,near future(NF;2021-2060)and far future(FF;2061-2100))under two Shared Socioeconomic Pathway(SSP)scenarios(SSP2-4.5 and SSP5-8.5).The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^(st) century(2061-2100).Moreover,from the results of multimodel ensemble means(MMEMs),extreme precipitation indices of RR1mm,RR10mm,RR20mm,CWD,and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario.The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part.The probability density function of extreme precipitation indices suggests a frequent(intense)occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario,with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD.The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding,soil erosion,water resource management,food security,and agriculture development.
基金the Strate-gic Priority Research Program of the Chinese Academy of Sci-ences under Grant No.XDA20060102the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(Grant No 2019QZKK0102)the National Natural Science Foundation of China under Grant No.41988101 and K.C.WONG Education Foun-dation.
文摘Precipitation over the Tibetan Plateau(TP)is important to local and downstream ecosystems.Based on a weighting method considering model skill and independence,changes in the TP precipitation for near-term(2021-40),mid-term(2041-60)and long-term(2081-2100)under shared socio-economic pathways(SSP1-1.9,SSP1-2.6,SSP2-4.5,SSSP3-7.0,SSP5-8.5)are projected with 27 models from the latest Sixth Phase of the Couple Model Intercomparison Project.The annual mean precipitation is projected to increase by 7.4%-21.6%under five SSPs with a stronger change in the northern TP by the end of the 21st century relative to the present climatology.Changes in the TP precipitation at seasonal scales show a similar moistening trend to that of annual mean precipitation,except for the drying trend in winter precipitation along the southern edges of the TP.Weighting generally suggests a slightly stronger increase in TP precipitation with reduced model uncertainty compared to equally-weighted projections.The effect of weighting exhibits spatial and seasonal differences.Seasonally,weighting leads to a prevailing enhancement of increase in spring precipitation over the TP.Spatially,the influence of weighting is more remarkable over the northwestern TP regarding the annual,summer and autumn precipitation.Differences between weighted and original MMEs can give us more confidence in a stronger increase in precipitation over the TP,especially for the season of spring and the region of the northwestern TP,which requires additional attention in decision making.
基金funded by the National Key Research and development Program of China (Grant No. 2017YFA0604004)the National Natural Science Foundation of China (Grant Nos. 91737306, U1811464, 41530426, 91837101, 41730963, and 91637312)
文摘The outputs of the Chinese Academy of Sciences(CAS) Flexible Global Ocean–Atmosphere–Land System(FGOALS-f3-L) model for the baseline experiment of the Atmospheric Model Intercomparison Project simulation in the Diagnostic,Evaluation and Characterization of Klima common experiments of phase 6 of the Coupled Model Intercomparison Project(CMIP6) are described in this paper. The CAS FGOALS-f3-L model, experiment settings, and outputs are all given. In total,there are three ensemble experiments over the period 1979–2014, which are performed with different initial states. The model outputs contain a total of 37 variables and include the required three-hourly mean, six-hourly transient, daily and monthly mean datasets. The baseline performances of the model are validated at different time scales. The preliminary evaluation suggests that the CAS FGOALS-f3-L model can capture the basic patterns of atmospheric circulation and precipitation well, including the propagation of the Madden–Julian Oscillation, activities of tropical cyclones, and the characterization of extreme precipitation. These datasets contribute to the benchmark of current model behaviors for the desired continuity of CMIP.
基金supported by the National Key R&D Program for Developing Basic Sciences (Grant Nos. 2016YFC1401401 and 2016YFC1401601)the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDC01000000)the National Natural Science Foundation of China (Grants Nos. 41576026, 41576025, 41776030, 41931183 and 41976026)
文摘The datasets of two Ocean Model Intercomparison Project(OMIP)simulation experiments from the LASG/IAP Climate Ocean Model,version 3(LICOM3),forced by two different sets of atmospheric surface data,are described in this paper.The experiment forced by CORE-II(Co-ordinated Ocean–Ice Reference Experiments,Phase II)data(1948–2009)is called OMIP1,and that forced by JRA55-do(surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis)data(1958–2018)is called OMIP2.First,the improvement of LICOM from CMIP5 to CMIP6 and the configurations of the two experiments are described.Second,the basic performances of the two experiments are validated using the climatological-mean and interannual time scales from observation.We find that the mean states,interannual variabilities,and long-term linear trends can be reproduced well by the two experiments.The differences between the two datasets are also discussed.Finally,the usage of these data is described.These datasets are helpful toward understanding the origin system bias of the fully coupled model.
基金jointly supported by the National Natural Science Foundation of China(Grant No.41991285)the National Key Research and Development Program of China(2017YFA0605004)the Program for Distinguished Professors of Jiangsu。
文摘Based on 20 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),this article explored possible reasons for differences in simulation biases and projected changes in precipitation in northern China among the allmodel ensemble(AMME),“highest-ranked”model ensemble(BMME),and“lowest-ranked”model ensemble(WMME),from the perspective of atmospheric circulations and moisture budgets.The results show that the BMME and AMME reproduce the East Asian winter circulations better than the WMME.Compared with the AMME and WMME,the BMME reduces the overestimation of evaporation,thereby improving the simulation of winter precipitation.The three ensemble simulated biases for the East Asian summer circulations are generally similar,characterized by a stronger zonal pressure gradient between the mid-latitudes of the North Pacific and East Asia and a northward displacement of the East Asian westerly jet.However,the simulated vertical moisture advection is improved in the BMME,contributing to the slightly higher performance of the BMME than the AMME and WMME on summer precipitation in North and Northeast China.Compared to the AMME and WMME,the BMME projects larger increases in precipitation in northern China during both seasons by the end of the 21st century under the Shared Socioeconomic Pathway 5-8.5(SSP5-8.5).One of the reasons is that the increase in evaporation projected by the BMME is larger.The projection of a greater dynamic contribution by the BMME also plays a role.In addition,larger changes in the nonlinear components in the BMME projection contribute to a larger increase in winter precipitation in northern China.