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
Against the backdrop of climate change,the activity of tropical cyclones(TCs)has captured widespread attention.Observational datasets indicate a declining trend in the genesis longitude of western North Pacific(WNP)TC...Against the backdrop of climate change,the activity of tropical cyclones(TCs)has captured widespread attention.Observational datasets indicate a declining trend in the genesis longitude of western North Pacific(WNP)TCs.This study investigates the zonal changes of WNP TCs with CMIP6-HighResMIP models.These models capture the genesis density of WNP TCs fairly well.The results reveal a westward shift in TC genesis longitude.This trend is associated with the significant reduction in the TC frequency over the southeastern WNP.The study also discusses changes in large-scale circulation patterns and the impact of the strengthening Pacific Walker circulation.展开更多
为探究汤旺河上游流域未来气温、降水及径流的变化情况,采用第六次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 6,CMIP6)中CanESM5模式下的3种情景(SSP1-2.6、SSP2-4.5、SSP5-8.5)数据,基于Delta降尺度方法对未...为探究汤旺河上游流域未来气温、降水及径流的变化情况,采用第六次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 6,CMIP6)中CanESM5模式下的3种情景(SSP1-2.6、SSP2-4.5、SSP5-8.5)数据,基于Delta降尺度方法对未来气温和降水进行处理,并结合SWAT(Soil and Water Assessment Tool)水文模型预估未来径流变化。未来整个时期(2015—2100年)最高、最低气温和降水均有所增加,但在不同情境下的增速不同,分别为0.65℃/10a、0.65℃/10a、12.23 mm/10a(SSP1-2.6),0.25℃/10a、0.39℃/10a、11.14 mm/10a(SSP2-4.5),0.81℃/10a、0.86℃/10a、23.57 mm/10a(SSP5-8.5);汤旺河上游流域未来径流在3种情境下有增加现象,增幅位于-2.12%~52.04%,且近期(2017—2050年)SSP1-2.6、SSP5-8.5和中期(2050—2100年)SSP1-2.6、SSP2-4.5、SSP5-8.5情境下流域内8、9月份峰值径流量高于基准期,最大增量为36.69 m^(3)/s。未来整个汤旺河上游流域可能出现暖湿现象,发生极端水文事件的风险可能变大。通过对未来气候进行模拟,分析汤旺河上游流域径流变化特征,可为区域水资源配置、水资源利用和预防旱涝灾害提供科学依据与理论支撑。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
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 a key project of the National Natural Science Foundation of China[grant number 42192563]。
文摘Against the backdrop of climate change,the activity of tropical cyclones(TCs)has captured widespread attention.Observational datasets indicate a declining trend in the genesis longitude of western North Pacific(WNP)TCs.This study investigates the zonal changes of WNP TCs with CMIP6-HighResMIP models.These models capture the genesis density of WNP TCs fairly well.The results reveal a westward shift in TC genesis longitude.This trend is associated with the significant reduction in the TC frequency over the southeastern WNP.The study also discusses changes in large-scale circulation patterns and the impact of the strengthening Pacific Walker circulation.
文摘为探究汤旺河上游流域未来气温、降水及径流的变化情况,采用第六次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 6,CMIP6)中CanESM5模式下的3种情景(SSP1-2.6、SSP2-4.5、SSP5-8.5)数据,基于Delta降尺度方法对未来气温和降水进行处理,并结合SWAT(Soil and Water Assessment Tool)水文模型预估未来径流变化。未来整个时期(2015—2100年)最高、最低气温和降水均有所增加,但在不同情境下的增速不同,分别为0.65℃/10a、0.65℃/10a、12.23 mm/10a(SSP1-2.6),0.25℃/10a、0.39℃/10a、11.14 mm/10a(SSP2-4.5),0.81℃/10a、0.86℃/10a、23.57 mm/10a(SSP5-8.5);汤旺河上游流域未来径流在3种情境下有增加现象,增幅位于-2.12%~52.04%,且近期(2017—2050年)SSP1-2.6、SSP5-8.5和中期(2050—2100年)SSP1-2.6、SSP2-4.5、SSP5-8.5情境下流域内8、9月份峰值径流量高于基准期,最大增量为36.69 m^(3)/s。未来整个汤旺河上游流域可能出现暖湿现象,发生极端水文事件的风险可能变大。通过对未来气候进行模拟,分析汤旺河上游流域径流变化特征,可为区域水资源配置、水资源利用和预防旱涝灾害提供科学依据与理论支撑。
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。
