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
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
The diurnal temperature range(DTR)serves as a vital indicator reflecting both natural climate variability and anthropogenic climate change.This study investigates the historical and projected multitemporal DTR variati...The diurnal temperature range(DTR)serves as a vital indicator reflecting both natural climate variability and anthropogenic climate change.This study investigates the historical and projected multitemporal DTR variations over the Tibetan Plateau.It assesses 23 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6)using CN05.1 observational data as validation,evaluating their ability to simulate DTR over the Tibetan Plateau.Then,the evolution of DTR over the Tibetan Plateau under different shared socioeconomic pathway(SSP)scenarios for the near,middle,and long term of future projection are analyzed using 11 selected robustly performing models.Key findings reveal:(1)Among the models examined,BCC-CSM2-MR,EC-Earth3,EC-Earth3-CC,EC-Earth3-Veg,EC-Earth3-Veg-LR,FGOALS-g3,FIO-ESM-2-0,GFDL-ESM4,MPI-ESM1-2-HR,MPI-ESM1-2-LR,and INM-CM5-0 exhibit superior integrated simulation capability for capturing the spatiotemporal variability of DTR over the Tibetan Plateau.(2)Projection indicates a slightly increasing trend in DTR on the Tibetan Plateau in the SSP1-2.6 scenario,and decreasing trends in the SSP2-4.5,SSP3-7.0,and SPP5-8.5 scenarios.In certain areas,such as the southeastern edge of the Tibetan Plateau,western hinterland of the Tibetan Plateau,southern Kunlun,and the Qaidam basins,the changes in DTR are relatively large.(3)Notably,the warming rate of maximum temperature under SSP2-4.5,SSP3-7.0,and SPP5-8.5 is slower compared to that of minimum temperature,and it emerges as the primary contributor to the projected decrease in DTR over the Tibetan Plateau in the future.展开更多
利用第六次国际耦合模式比较计划(CMIP6)中的18个模式,基于欧洲中期天气预报中心第五代再分析资料(ERA5)再分析数据对青藏高原夏季降水数据进行了偏差校正,并从平均降水和极端降水两方面评估了校正前后的CMIP6数据以及单个模式在1979-2...利用第六次国际耦合模式比较计划(CMIP6)中的18个模式,基于欧洲中期天气预报中心第五代再分析资料(ERA5)再分析数据对青藏高原夏季降水数据进行了偏差校正,并从平均降水和极端降水两方面评估了校正前后的CMIP6数据以及单个模式在1979-2014年的表现。研究结果表明,该校正方法高度依赖于用于偏差校正的ERA5再分析数据在研究区域的质量,尽管偏差校正后的青藏高原夏季平均降水的误差和误差率上有所改善,但在年际时间变化特征方面却不如偏差校正前的数据。大多数CMIP6模式能够较好地模拟1979-2014年青藏高原上由西北至东南逐渐递增的平均降水空间变化特征。偏差校正前的降水数据在高原上会出现显著的高估,误差率为60.4%,经过偏差校正后的数据相对观测数据误差降低,误差率为-13.9%,并且偏差校正后的数据与ERA5的平均误差仅为0.003 mm·d^(-1),与ERA5的空间相关性高达0.999。空间趋势方面,观测数据表明青藏高原大部分地区夏季降水在1979-2014年呈现轻微增加的趋势,只有东缘出现明显降低的趋势。偏差校正前后的数据都能够大致刻画出这一空间分布特征,然而,未经偏差校正的大多数单个CMIP6模式与ERA5的空间相关系数未超过0.5。与由独立观测降水数据的年际变化特征相比,偏差校正前的数据高估了高原上的降水量,而偏差校正后的数据相比观测结果则偏低。通过确定95%分位阈值选取了极端降水个例,其集合平均极端降水空间分布与年平均降水类似,也呈西北向东南递增的趋势。部分CMIP6模式较好地模拟了这一特征,如MRI-ESM2-0(The Meteorological Research Institute Earth System Model version 2.0)和ACCESSCM2(Australian Community Climate and Earth System Simulator Climate Model Version 2),与观测结果的空间相关系数分别为0.851和0.821。但偏差校正后的数据在空间相关性方面下降,由偏差校正前的0.861降为0.730,未能准确刻画高原极端降水阶梯式递增的特点。偏差校正后的极端降水数据误差分布与偏差校正前相似,偏低区域主要集中在高原南部腹地和东部。进一步的极端降水贡献率分析结果表明,观测结果与CMIP6降水数据均显示1979-2014年期间极端降水贡献率变化趋势不明显。单个CMIP6模式中,EC-Earth3-Veg(European Community Earth-Vegetation model version 3)和EC-Earth3(European Community Earth Model version 3)及CanESM5(The Canadian Earth System Model version 5)在多个统计评估指标上排名靠前,展示出较好的模拟能力;IPSL-CM6A-LR(Institut Pierre-Simon Laplace Climate Model 6A Low Resolution)在平均降水误差和极端降水的误差指标上表现出色。展开更多
This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6(CMIP6)in simulating marine heatwaves(MHWs)in the South China Sea(SCS)during the historical period(1982−2...This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6(CMIP6)in simulating marine heatwaves(MHWs)in the South China Sea(SCS)during the historical period(1982−2014),and also investigates future changes in SCS MHWs based on simulations from three shared socioeconomic pathway(SSP)scenarios(SSP126,SSP245,and SSP585)using CMIP6 models.Results demonstrate that the CMIP6 models perform well in simulating the spatial-temporal distribution and intensity of SCS MHWs,with their multi-model ensemble(MME)results showing the best performance.The reasonable agreement between the observations and CMIP6 MME reveals that the increasing trends of SCS MHWs are attributed to the warming sea surface temperature trend.Under various SSP scenarios,the year 2040 emerges as pivotal juncture for future shifts in SCS MHWs,marked by distinct variations in changing rate and amplitudes.This is characterized by an accelerated decrease in MHWs frequency and a notably heightened increase in mean intensity,duration,and total days after 2040.Furthermore,the projection results for SCS MHWs suggest that the spatial pattern of MHWs remains consistent across future periods.However,the intensity shows higher consistency only during the near-term period(2021−2050),while notable inconsistencies are observed during the medium-term(2041−2070)and long-term(2071−2100)periods under the three SSP scenarios.During the nearterm period,the SCS MHWs are characterized by moderate and strong events with high frequencies and relatively shorter durations.In contrast,during the medium-term period,MHWs are also characterized by moderate and strong events,but with longer-lasting and more intense events under the SSP245 and SSP585 scenarios.However,in the long-term period,extreme MHWs become the dominant feature under the SSP585 scenario,indicating a substantial intensification of SCS MHWs,effectively establishing a near-permanent state.展开更多
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 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supported by The Second Tibetan Plateau Scientific Expedition and Research(STEP)program(Grant No.2019QZKK0102)the National Natural Science Foundation of China(Grant No.41975135)+1 种基金the Natural Science Foundation of Sichuan,China(Grant No.2022NSFSC1092)funded by the China Scholarship Council。
文摘The diurnal temperature range(DTR)serves as a vital indicator reflecting both natural climate variability and anthropogenic climate change.This study investigates the historical and projected multitemporal DTR variations over the Tibetan Plateau.It assesses 23 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6)using CN05.1 observational data as validation,evaluating their ability to simulate DTR over the Tibetan Plateau.Then,the evolution of DTR over the Tibetan Plateau under different shared socioeconomic pathway(SSP)scenarios for the near,middle,and long term of future projection are analyzed using 11 selected robustly performing models.Key findings reveal:(1)Among the models examined,BCC-CSM2-MR,EC-Earth3,EC-Earth3-CC,EC-Earth3-Veg,EC-Earth3-Veg-LR,FGOALS-g3,FIO-ESM-2-0,GFDL-ESM4,MPI-ESM1-2-HR,MPI-ESM1-2-LR,and INM-CM5-0 exhibit superior integrated simulation capability for capturing the spatiotemporal variability of DTR over the Tibetan Plateau.(2)Projection indicates a slightly increasing trend in DTR on the Tibetan Plateau in the SSP1-2.6 scenario,and decreasing trends in the SSP2-4.5,SSP3-7.0,and SPP5-8.5 scenarios.In certain areas,such as the southeastern edge of the Tibetan Plateau,western hinterland of the Tibetan Plateau,southern Kunlun,and the Qaidam basins,the changes in DTR are relatively large.(3)Notably,the warming rate of maximum temperature under SSP2-4.5,SSP3-7.0,and SPP5-8.5 is slower compared to that of minimum temperature,and it emerges as the primary contributor to the projected decrease in DTR over the Tibetan Plateau in the future.
文摘利用第六次国际耦合模式比较计划(CMIP6)中的18个模式,基于欧洲中期天气预报中心第五代再分析资料(ERA5)再分析数据对青藏高原夏季降水数据进行了偏差校正,并从平均降水和极端降水两方面评估了校正前后的CMIP6数据以及单个模式在1979-2014年的表现。研究结果表明,该校正方法高度依赖于用于偏差校正的ERA5再分析数据在研究区域的质量,尽管偏差校正后的青藏高原夏季平均降水的误差和误差率上有所改善,但在年际时间变化特征方面却不如偏差校正前的数据。大多数CMIP6模式能够较好地模拟1979-2014年青藏高原上由西北至东南逐渐递增的平均降水空间变化特征。偏差校正前的降水数据在高原上会出现显著的高估,误差率为60.4%,经过偏差校正后的数据相对观测数据误差降低,误差率为-13.9%,并且偏差校正后的数据与ERA5的平均误差仅为0.003 mm·d^(-1),与ERA5的空间相关性高达0.999。空间趋势方面,观测数据表明青藏高原大部分地区夏季降水在1979-2014年呈现轻微增加的趋势,只有东缘出现明显降低的趋势。偏差校正前后的数据都能够大致刻画出这一空间分布特征,然而,未经偏差校正的大多数单个CMIP6模式与ERA5的空间相关系数未超过0.5。与由独立观测降水数据的年际变化特征相比,偏差校正前的数据高估了高原上的降水量,而偏差校正后的数据相比观测结果则偏低。通过确定95%分位阈值选取了极端降水个例,其集合平均极端降水空间分布与年平均降水类似,也呈西北向东南递增的趋势。部分CMIP6模式较好地模拟了这一特征,如MRI-ESM2-0(The Meteorological Research Institute Earth System Model version 2.0)和ACCESSCM2(Australian Community Climate and Earth System Simulator Climate Model Version 2),与观测结果的空间相关系数分别为0.851和0.821。但偏差校正后的数据在空间相关性方面下降,由偏差校正前的0.861降为0.730,未能准确刻画高原极端降水阶梯式递增的特点。偏差校正后的极端降水数据误差分布与偏差校正前相似,偏低区域主要集中在高原南部腹地和东部。进一步的极端降水贡献率分析结果表明,观测结果与CMIP6降水数据均显示1979-2014年期间极端降水贡献率变化趋势不明显。单个CMIP6模式中,EC-Earth3-Veg(European Community Earth-Vegetation model version 3)和EC-Earth3(European Community Earth Model version 3)及CanESM5(The Canadian Earth System Model version 5)在多个统计评估指标上排名靠前,展示出较好的模拟能力;IPSL-CM6A-LR(Institut Pierre-Simon Laplace Climate Model 6A Low Resolution)在平均降水误差和极端降水的误差指标上表现出色。
基金The National Natural Science Foundation of China under contract Nos 42275024 and 42105040the Key R&D Program of China under contract No.2022YFE0203500+3 种基金the Guangdong Basic and Applied Basic Research Foundation under contract Nos 2023B1515020009 and 2024B1515040024the Youth Innovation Promotion Association CAS under contract No.2020340the Special Fund of South China Sea Institute of Oceanology of the Chinese Academy of Sciences under contract No.SCSIO2023QY01the Science and Technology Planning Project of Guangzhou under contract No.2024A04J6275.
文摘This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6(CMIP6)in simulating marine heatwaves(MHWs)in the South China Sea(SCS)during the historical period(1982−2014),and also investigates future changes in SCS MHWs based on simulations from three shared socioeconomic pathway(SSP)scenarios(SSP126,SSP245,and SSP585)using CMIP6 models.Results demonstrate that the CMIP6 models perform well in simulating the spatial-temporal distribution and intensity of SCS MHWs,with their multi-model ensemble(MME)results showing the best performance.The reasonable agreement between the observations and CMIP6 MME reveals that the increasing trends of SCS MHWs are attributed to the warming sea surface temperature trend.Under various SSP scenarios,the year 2040 emerges as pivotal juncture for future shifts in SCS MHWs,marked by distinct variations in changing rate and amplitudes.This is characterized by an accelerated decrease in MHWs frequency and a notably heightened increase in mean intensity,duration,and total days after 2040.Furthermore,the projection results for SCS MHWs suggest that the spatial pattern of MHWs remains consistent across future periods.However,the intensity shows higher consistency only during the near-term period(2021−2050),while notable inconsistencies are observed during the medium-term(2041−2070)and long-term(2071−2100)periods under the three SSP scenarios.During the nearterm period,the SCS MHWs are characterized by moderate and strong events with high frequencies and relatively shorter durations.In contrast,during the medium-term period,MHWs are also characterized by moderate and strong events,but with longer-lasting and more intense events under the SSP245 and SSP585 scenarios.However,in the long-term period,extreme MHWs become the dominant feature under the SSP585 scenario,indicating a substantial intensification of SCS MHWs,effectively establishing a near-permanent state.
