虽然第六次耦合模式比较计划(Coupled Model Intercomparison Project 6,CMIP6)能很好地预测大尺度气候要素,但是其在预测流域尺度方面的效果与实测数据仍有差别,尤其是在青藏高原这种高海拔、地形复杂地区,气候模式所产生的误差更大。...虽然第六次耦合模式比较计划(Coupled Model Intercomparison Project 6,CMIP6)能很好地预测大尺度气候要素,但是其在预测流域尺度方面的效果与实测数据仍有差别,尤其是在青藏高原这种高海拔、地形复杂地区,气候模式所产生的误差更大。基于最新一代高分辨率CMIP6模式历史情景和SSP126、SSP245、SSP370、SSP585等多种未来气候排放情景,研究使用包括偏差校正、KNN、SDSM等多种统计降尺度方法进行降尺度分析,并对各自的预测性能进行了评估,在此基础上使用性能最佳的统计降尺度方式预估青藏高原地区的未来降水,对最终得到的预估降水的时空演变特征进行了详细的分析,并与青藏高原的历史降水情况进行了对比。结果表明,3种统计降尺度在青藏高原的适用性差异较大,线性回归降尺度方法的性能最佳,其次为偏差校正方法,最差为KNN类比方法。从未来降水预估情况分析,青藏高原未来80 a平均降水、降水极值等总体呈上升趋势但上升幅度较小,且空间分布情况变化不大。研究结果可为青藏高原水资源评价及规划与管理提供科学依据。展开更多
借助第五次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)多模式集合数据及英国气候研究所(Climatic Research Unit Time-Series version 4.0,CRU TSv4.0)的格点降水资料,分析了多模式集合平均降水在亚...借助第五次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)多模式集合数据及英国气候研究所(Climatic Research Unit Time-Series version 4.0,CRU TSv4.0)的格点降水资料,分析了多模式集合平均降水在亚洲的偏差分布特征,检验了三种偏差订正统计方法,并且预估了2021~2050年亚洲降水的可能变化。结果表明,在CMIP5历史气候模拟中,多模式集合降水在亚洲存在明显偏差,北方降水偏多,南方偏少,其中在青藏高原、内蒙古、蒙古国等地明显偏多达30%~40%,南亚偏少30%~40%,在越南和华南沿海偏少20%~30%等。2006~2015年预估降水偏差型与历史气候模拟相似,具有准定常性,可以通过二者之差将其消去。偏差订正检验表明,单纯除去模式气候漂移后的降水距平太小,尽管距平符号一致率较高。在暖季(5~10月),一元对数回归偏差订正结果在北方略优于一元差分回归,在冷季(11月至次年4月)与此相反,二者结合可以构成区域组合回归偏差订正法。最后,用组合订正法订正了RCP4.5情景下20个CMIP5模式集合2021~2050年亚洲降水预估偏差,又利用某些区域的去除模式漂移后的订正结果对其盲区进行了补充订正。结果表明,相对于1976~2005年气候平均,在暖季,中国南方、南亚东北部、中亚南部、阿拉伯半岛东北部等地降水可能减少10%~20%;从中国的三江源区到淮河流域带降水会增加约20%,东北南部的降水会增加约10%;新疆北部降水增加约10%,南部约20%;华北和东北大部降水减少约10%~20%;中南半岛北部降水增加约10%;亚洲高纬度地带降水也略有增加。在冷季,亚洲降水呈现北方增加,南方减少的格局,其中南亚降水减少最明显,达-10%左右,中国西南部减少约-5%;中国西部降水增加幅度为20%~40%,华北和东北增加约5%;亚洲高纬度降水增加约为10%~40%。因此,随着气候暖化,未来30年中国的淮河流域、长江和黄河上游可能降水增多,而西南地区的旱情可能会持续,建议有关部门提前做好应对部署。展开更多
使用日本气象研究所(Meteorological Research Institute,MRI)大气环流模式在20 km分辨率下的国际大气模式比较计划(Atmospheric Model Intercomparison Project,AMIP)试验结果以及A1B温室气体排放情景下(简称A1B情景)的预估试验数据,...使用日本气象研究所(Meteorological Research Institute,MRI)大气环流模式在20 km分辨率下的国际大气模式比较计划(Atmospheric Model Intercomparison Project,AMIP)试验结果以及A1B温室气体排放情景下(简称A1B情景)的预估试验数据,预估了青藏高原夏季(6—8月)降水的变化,并讨论了降水变化的可能原因。在A1B情景下,青藏高原夏季降水量显著增加,中心位于青藏高原东南部,主要归因于来自印度洋和孟加拉湾的西南水汽,经90°E—100°E附近进入高原的水汽输送显著增加。同时,整个青藏高原夏季强降水出现概率增加,降水频率南部减少,北部增加。高原南部(北部)降水频率的减少(增加)是因为该地区降水强度的增加速率快(慢)于降水量的增加速率。高分辨率MRI模式预估的青藏高原夏季降水变化与较低分辨率的耦合模式预估结果基本一致,但提供了更详细的局地变化信息。展开更多
Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assesse...Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.展开更多
Recently, a new high-resolution daily downscaled data-set derived from 21 CMIP5 model simulations has been released by NASA, called ＇NASA Earth Exchange Global Daily Downscaled Projections＇ （NEX-GDDP）. In this stu...Recently, a new high-resolution daily downscaled data-set derived from 21 CMIP5 model simulations has been released by NASA, called ＇NASA Earth Exchange Global Daily Downscaled Projections＇ （NEX-GDDP）. In this study, the performance of this data-set in simulating precipitation extremes and long-term climate changes across China are evaluated and compared with CMIP5 GCMs. The results indicate that NEX-GDDP can successfully reproduce the spatial patterns of precipitation extremes over China, showing results that are much closer to observations than the GCMs, with increased Pearson correlation coefficients and decreased model relative error for most models. Furthermore, NEX-GDDP shows that precipitation extremes are projected to occur more frequently, with increased intensity, across China in the future. Especially at regional to local scales, more information for the projection of future changes in precipitation extremes can be obtained from this high-resolution data-set. Most importantly, the uncertainties of these projections at the regional scale present significant decreases compared with the GCMs, making the projections by NEX-GDDP much more reliable. Therefore, the authors believe that this high-resolution data-set will be popular and widely used in the future, particularly for climate change impact studies in areas where a finer scale is required.展开更多
文摘借助第五次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)多模式集合数据及英国气候研究所(Climatic Research Unit Time-Series version 4.0,CRU TSv4.0)的格点降水资料,分析了多模式集合平均降水在亚洲的偏差分布特征,检验了三种偏差订正统计方法,并且预估了2021~2050年亚洲降水的可能变化。结果表明,在CMIP5历史气候模拟中,多模式集合降水在亚洲存在明显偏差,北方降水偏多,南方偏少,其中在青藏高原、内蒙古、蒙古国等地明显偏多达30%~40%,南亚偏少30%~40%,在越南和华南沿海偏少20%~30%等。2006~2015年预估降水偏差型与历史气候模拟相似,具有准定常性,可以通过二者之差将其消去。偏差订正检验表明,单纯除去模式气候漂移后的降水距平太小,尽管距平符号一致率较高。在暖季(5~10月),一元对数回归偏差订正结果在北方略优于一元差分回归,在冷季(11月至次年4月)与此相反,二者结合可以构成区域组合回归偏差订正法。最后,用组合订正法订正了RCP4.5情景下20个CMIP5模式集合2021~2050年亚洲降水预估偏差,又利用某些区域的去除模式漂移后的订正结果对其盲区进行了补充订正。结果表明,相对于1976~2005年气候平均,在暖季,中国南方、南亚东北部、中亚南部、阿拉伯半岛东北部等地降水可能减少10%~20%;从中国的三江源区到淮河流域带降水会增加约20%,东北南部的降水会增加约10%;新疆北部降水增加约10%,南部约20%;华北和东北大部降水减少约10%~20%;中南半岛北部降水增加约10%;亚洲高纬度地带降水也略有增加。在冷季,亚洲降水呈现北方增加,南方减少的格局,其中南亚降水减少最明显,达-10%左右,中国西南部减少约-5%;中国西部降水增加幅度为20%~40%,华北和东北增加约5%;亚洲高纬度降水增加约为10%~40%。因此,随着气候暖化,未来30年中国的淮河流域、长江和黄河上游可能降水增多,而西南地区的旱情可能会持续,建议有关部门提前做好应对部署。
文摘使用日本气象研究所(Meteorological Research Institute,MRI)大气环流模式在20 km分辨率下的国际大气模式比较计划(Atmospheric Model Intercomparison Project,AMIP)试验结果以及A1B温室气体排放情景下(简称A1B情景)的预估试验数据,预估了青藏高原夏季(6—8月)降水的变化,并讨论了降水变化的可能原因。在A1B情景下,青藏高原夏季降水量显著增加,中心位于青藏高原东南部,主要归因于来自印度洋和孟加拉湾的西南水汽,经90°E—100°E附近进入高原的水汽输送显著增加。同时,整个青藏高原夏季强降水出现概率增加,降水频率南部减少,北部增加。高原南部(北部)降水频率的减少(增加)是因为该地区降水强度的增加速率快(慢)于降水量的增加速率。高分辨率MRI模式预估的青藏高原夏季降水变化与较低分辨率的耦合模式预估结果基本一致,但提供了更详细的局地变化信息。
基金supported by the Second Tibetan Plateau Scientific Expedition and Research(STEP)program[grant number 2019QZKK0102]the Chinese Academy of Sciences[grant number 060GJHZ2023079GC].
文摘Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.
基金supported by the Natural Science Foundation of Hubei Province of China[grant number 2020CFB331]the National Key Research and Development Program of China[grant number2018YFA0605602]the Strategic Project of the Chinese Academy of Sciences[grant number XDA19070402]。
基金jointly supported by the National Key Research and Development Program of China[grant number2016YFA0602401]the External Cooperation Program of Bureau of International Co-operation(BIC)+1 种基金Chinese Academy of Sciences[grant number 134111KYSB20150016]the National Natural Science Foundation of China[grant number 41421004]
文摘Recently, a new high-resolution daily downscaled data-set derived from 21 CMIP5 model simulations has been released by NASA, called ＇NASA Earth Exchange Global Daily Downscaled Projections＇ （NEX-GDDP）. In this study, the performance of this data-set in simulating precipitation extremes and long-term climate changes across China are evaluated and compared with CMIP5 GCMs. The results indicate that NEX-GDDP can successfully reproduce the spatial patterns of precipitation extremes over China, showing results that are much closer to observations than the GCMs, with increased Pearson correlation coefficients and decreased model relative error for most models. Furthermore, NEX-GDDP shows that precipitation extremes are projected to occur more frequently, with increased intensity, across China in the future. Especially at regional to local scales, more information for the projection of future changes in precipitation extremes can be obtained from this high-resolution data-set. Most importantly, the uncertainties of these projections at the regional scale present significant decreases compared with the GCMs, making the projections by NEX-GDDP much more reliable. Therefore, the authors believe that this high-resolution data-set will be popular and widely used in the future, particularly for climate change impact studies in areas where a finer scale is required.
