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基于CMIP6多模式的和田河流域未来气候变化预估

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地学前缘 2023年第3期30卷 515-528页

作者：何朝飞骆成彦陈伏龙龙爱华唐豪石河子大学水利建筑工程学院新疆石河子832000 生态水利工程兵团寒旱区重点实验室新疆石河子832000 新疆水利水电勘测设计研究院有限公司新疆乌鲁木齐830000 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室北京100038

气候系统模式是对历史和未来气候模拟最广泛有效的工具,但存在一定的不足和局限性,使其无法直接用以预估未来气候变化。本文采用基于分位数映射的日偏差校正(DBC)、多模式集合(MME)平均和基于皮尔逊r相关系数的加权集合(r-MME)平均方法,... 详细信息

气候系统模式是对历史和未来气候模拟最广泛有效的工具,但存在一定的不足和局限性,使其无法直接用以预估未来气候变化。本文采用基于分位数映射的日偏差校正(DBC)、多模式集合(MME)平均和基于皮尔逊r相关系数的加权集合(r-MME)平均方法,以1971—2000年为基准期,评估6种气候模式在和田河流域的适用性;运用r-MME方法对未来SSP1-2.6、SSP2-4.5和SSP5-8.5情景下各模式的偏差校正结果进行集合,分析未来近期(2021—2050年)、远期(2061—2090年)日最高、最低气温以及降水的时空演变特征。结果表明:基于DBC的r-MME融合方法能够综合考虑各模式的优势,可大幅提高气候模式模拟的精度,年均最高气温、最低气温和降水量与实测序列的相关系数分别达到0.918、0.821和0.878;3种情景下的气温和降水均呈现增加趋势,其中低强迫SSP1-2.6情景下的增幅最小,远期年最高气温、最低气温和降水的平均增量分别为2.830、2.523℃和46.412 mm,高强迫SSP5-8.5情景下的增幅最大,远期年最高气温、最低气温和降水的平均增量为5.697、6.452℃和93.206 mm;同时,未来温差的逐渐减少使得流域“暖湿化”现象更加明显。该研究结果可为未来气候变化下和田河流域经济发展和生态文明建设,以及水资源预测提供重要的理论依据。

关键词：和田河流域 CMIP6 模式评估偏差校正气候变化

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基于CMIP6的全球及干旱带干旱时空演变

水资源保护 2023年第2期39卷 40-49页

作者：杨肖丽马慧君吴凡张梦如张林燕崔周宇任立良袁山水河海大学水文水资源与水利工程科学国家重点实验室江苏南京210098 河海大学水文水资源学院江苏南京210098 河海大学长江保护与绿色发展研究院江苏南京210098

针对全球范围内极端气候事件频繁发生的问题,采用等距离分位数方法,构建CMIP6模式高精度降水、气温数据库,耦合帕默尔干旱指数(PDSI)预估未来情景(SSP1-2.6、SSP2-4.5、SSP3-7.0、SSP5-8.5)下全球及干旱带干旱特征时空演变趋势。结果表... 详细信息

针对全球范围内极端气候事件频繁发生的问题,采用等距离分位数方法,构建CMIP6模式高精度降水、气温数据库,耦合帕默尔干旱指数(PDSI)预估未来情景(SSP1-2.6、SSP2-4.5、SSP3-7.0、SSP5-8.5)下全球及干旱带干旱特征时空演变趋势。结果表明:经过偏差校正的CMIP6模拟精度明显提高;基准期(1979—2014年)全球干旱频次变化较小,干旱历时较长,干旱烈度较强,干旱带的干旱烈度较弱;预测期(2025—2060年)全球干旱特征在时空分布上差异性显著,干旱频次较高,平均干旱历时增加,平均干旱烈度增强;预测期干旱带干旱频次、干旱历时和干旱烈度均呈现增加趋势,热带/亚热带干旱带和温带干旱带变旱趋势较显著。

关键词：气候变化全球干旱带 CMIP6 PDSI 干旱特征

Changes in the ground surface temperature in permafrost regions along the Qinghaie-Tibet engineering corridor from 1900 to 2014:A modified assessment of CMIP6

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Advances in Climate Change Research 2023年第1期14卷 85-96页

作者： Zan-Pin XING Lin ZHAO Lei FAN Guo-Jie HU De-Fu ZOU Chong WANG Shu-Ci LIU Er-Ji DU Yao XIAO Ren LI Guang-Yue LIU Yong-Ping QIAO Jian-Zong SHI Cryosphere Research Station on the QinghaieTibet Plateau State Key Laboratory of Cryospheric ScienceNorthwest Institute of Eco-Environment and ResourceChinese Academy of SciencesLanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China School of Geographical Sciences Nanjing University of Information Science&TechnologyNanjing 210044China Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station School of Geographical SciencesSouthwest UniversityChongqing 400715China Department of Environment and Science Queensland GovernmentBrisbaneQLD 4102Australia

Numerous studies were published in the last two decades to evaluate and project the permafrost changes in its thermal state,mainly based on the soil temperature datasets from the Coupled Model Intercomparison Project(cmip),and discuss the impacts of permafrost changes on regional hydrological,ecological and climatic systems and even carbon cycles.However,limited monitored soil temperature data are available to validate the cmip outputs,resulting in the over-projection of future permafrost changes in cmip3 and cmip5.Moreover,future permafrost changes in CMIP6,particularly over the QinghaieTibet Plateau(QTP),where permafrost covers more than 40%of its territory,are still unknown.To address this gap,we evaluated and calibrated the monthly ground surface temperature(GST;5 cm below the ground surface),which was often used as the upper boundary to simulate and project permafrost changes derived from 19 CMIP6 Earth System Models(ESMs)against in situ measurements over the QTP.We generated the monthly GST series from 1900 to 2014 for five sites based on the linear calibration models and validated them through the three other sites using the same calibration methods.Results showed that all of the ESMs could capture the dynamics of in situ GST with high correlations(r>0.90).However,large errors were detected with a broad range of centred root-mean-square errors(1.14-4.98℃).The Top 5 model ensembles(MME5)performed better than most individual ESMs and averaged multi-model ensembles(MME19).The calibrated GST performed better than the GST obtained from MME5.Both annual and seasonal GSTs exhibited warming trends with an average annual rate of 0.04℃ per decade in the annual GST.The average seasonal warming rate was highest in winter and spring and lowest in summer.This reconstructed GST data series could be used to simulate the long-term permafrost temperature over the QTP.

关键词： Ground surface temperature CMIP6 Cold bias Permafrost Qinghaie-Tibet engineering corridor

The Subsurface and Surface Indian Ocean Dipoles and Their Association with ENSO in CMIP6 models

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Advances in Atmospheric Sciences 2023年第6期40卷 975-987页

作者： Ge SONG Rongcai REN State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044China University of Chinese Academy of Sciences Beijing 100049China

This study assesses the reproducibility of 31 historical simulations from 1850 to 2014 in the Coupled Model Intercomparison Project phase 6(CMIP6) for the subsurface(Sub-IOD) and surface Indian Ocean Dipole(IOD) and their association with El Ni?o-Southern Oscillation(ENSO). Most CMIP6 models can reproduce the leading east-west dipole oscillation mode of heat content anomalies in the tropical Indian Ocean(TIO) but largely overestimate the amplitude and the dominant period of the Sub-IOD. Associated with the much steeper west-to-east thermocline tilt of the TIO, the vertical coupling between the Sub-IOD and IOD is overly strong in most CMIP6 models compared to that in the Ocean Reanalysis System 4(ORAS4). Related to this, most models also show a much tighter association of Sub-IOD and IOD events with the canonical ENSO than observations. This explains the more(less) regular Sub-IOD and IOD events in autumn in those models with stronger(weaker) surface-subsurface coupling in TIO. Though all model simulations feature a consistently low bias regarding the percentage of the winter–spring Sub-IOD events co-occurring with a Central Pacific(CP) ENSO, the linkage between a westward-centered CP-ENSO and the Sub-IOD that occurs in winter–spring, independent of the IOD, is well reproduced.

关键词： CMIP6 subsurface Indian Ocean Dipole surface Indian Ocean Dipole El Niño-Southern Oscillation

Assessing the Performance of CMIP6 Models in Simulating Droughts across Global Drylands

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Advances in Atmospheric Sciences 2024年第2期41卷 193-208页

作者： Xiaojing YU Lixia ZHANG Tianjun ZHOU Jianghua ZHENG LASG Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing 210044China University of Chinese Academy of Sciences Beijing 100049China College of Geography&Remote Sensing Sciences Xinjiang UniversityUrumqi 830046China

Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.

关键词： droughts hydrothermal conditions drylands CMIP6 model evaluation

How Well Do CMIP6 and cmip5 Models Simulate the Climatological Seasonal Variations in Ocean Salinity?

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Advances in Atmospheric Sciences 2022年第10期39卷 1650-1672,I0005-I0015页

作者： Yuanxin LIU Lijing CHENG Yuying PAN Zhetao TAN John ABRAHAM Bin ZHANG Jiang ZHU Junqiang SONG College of Meteorology and Oceanography College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China Center for Ocean Mega-Science Chinese Academy of SciencesQingdao 266071China University of Chinese Academy of Sciences Beijing 100049China School of Engineering University of St.Thomas2115 Summit Ave.St PaulMN 55105USA Marine Science Data Center Institute of OceanologyChinese Academy of SciencesQingdao 266071China

This paper includes a comprehensive assessment of 40 models from the Coupled Model Intercomparison Project phase 5(cmip5)and 33 models from the cmip phase 6(CMIP6)to determine the climatological and seasonal variation of ocean salinity from the surface to 2000 m.The general pattern of the ocean salinity climatology can be simulated by both the cmip5 and CMIP6 models from the surface to 2000-m depth.However,this study shows an increased fresh bias in the surface and subsurface salinity in the CMIP6 multimodel mean,with a global average of−0.44 g kg^(−1) for the sea surface salinity(SSS)and−0.26 g kg^(−1) for the 0-1000-m averaged salinity(S1000)compared with the cmip5 multimodel mean(−0.25 g kg^(−1) for the SSS and−0.07 g kg^(−1) for the S1000).In terms of the seasonal variation,both CMIP6 and cmip5 models show positive(negative)anomalies in the first(second)half of the year in the global average SSS and S1000.The model-simulated variation in SSS is consistent with the observations,but not for S1000,suggesting a substantial uncertainty in simulating and understanding the seasonal variation in subsurface salinity.The cmip5 and CMIP6 models overestimate the magnitude of the seasonal variation of the SSS in the tropics in the region 20°S-20°N but underestimate the magnitude of the seasonal change in S1000 in the Atlantic and Indian oceans.These assessments show new features of the model errors in simulating ocean salinity and support further studies of the global hydrological cycle.

关键词： salinity climatology seasonal cycle cmip5 CMIP6 upper ocean

FIO-ESM v2.0 CORE2-forced experiment for the CMIP6 Ocean Model Intercomparison Project

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Acta Oceanologica Sinica 2022年第10期41卷 22-31页

作者： Qi Shu Zhenya Song Ying Bao Xiaodan Yang Yajuan Song Xinfang Li Meng Wei Fangli Qiao First Institute of Oceanography and Key Laboratory of Marine Science and Numerical ModelingMinistry of Natural ResourcesQingdao266061China Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao266237China Shandong Key Laboratory of Marine Science and Numerical Modeling Qingdao266061China

We introduced the Coupled Model Intercomparison Project Phase 6(CMIP6)Ocean Model Intercomparison Project CORE2-forced(OMIP-1)experiment by using the First Institute of Oceanography Earth System Model version 2.0(FIO-ESM v2.0),and comprehensively evaluated the simulation results.Unlike other OMIP models,FIO-ESM v2.0 includes a coupled ocean surface wave component model that takes into account non-breaking surface wave-induced vertical mixing in the ocean and effect of surface wave Stokes drift on air-sea momentum and heat fluxes in the climate system.A sub-layer sea surface temperature(SST)diurnal cycle parameterization was also employed to take into account effect of SST diurnal cycle on air-sea heat fluxes to improve simulations of air-sea interactions.Evaluations show that mean values and long-term trends of significant wave height were adequately reproduced in the FIO-ESM v2.0 OMIP-1 simulations,and there is a reasonable fit between the SST diurnal cycle obtained from in situ observations and that parameterized by FIO-ESM v2.0.Evaluations of model drift,temperature,salinity,mixed layer depth,and the Atlantic Meridional Overturning Circulation show that the model performs well in the FIO-ESM v2.0 OMIP-1 simulation.However,the summer sea ice extent of the Arctic and Antarctic is underestimated.

关键词： FIO-ESM OMIP CMIP6 OGCM

Simulations and Projections of Winter Sea Ice in the Barents Sea by CMIP6 Climate Models

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Advances in Atmospheric Sciences 2023年第12期40卷 2318-2330页

作者： Rongrong PAN Qi SHU Zhenya SONG Shizhu WANG Yan HE Fangli QIAO First Institute of Oceanography and Key Laboratory of Marine Science and Numerical ModelingMinistry of Natural ResourcesQingdao 266061China Shandong Key Laboratory of Marine Science and Numerical Modeling Qingdao 266061China

Dramatic changes in the sea ice characteristics in the Barents Sea have potential consequences for the weather and climate systems of mid-latitude continents,Arctic ecosystems,and fisheries,as well as Arctic maritime navigation.Simulations and projections of winter sea ice in the Barents Sea based on the latest 41 climate models from the Coupled Model Intercomparison Project Phase 6(CMIP6)are investigated in this study.Results show that most CMIP6 models overestimate winter sea ice in the Barents Sea and underestimate its decreasing trend.The discrepancy is mainly attributed to the simulation bias towards an overly weak ocean heat transport through the Barents Sea Opening and the underestimation of its increasing trend.The methods of observation-based model selection and emergent constraint were used to project future winter sea ice changes in the Barents Sea.Projections indicate that sea ice in the Barents Sea will continue to decline in a warming climate and that a winter ice-free Barents Sea will occur for the first time during 2042-2089 under the Shared Socioeconomic Pathway 585(SSP5-8.5).Even in the observation-based selected models,the sensitivity of winter sea ice in the Barents Sea to global warming is weaker than observed,indicating that a winter ice-free Barents Sea might occur earlier than projected by the CMIP6 simulations.

关键词： Arctic sea ice Barents Sea ocean heat transport sea ice projection CMIP6

The Arctic Sea Ice Thickness Change in CMIP6’s Historical Simulations

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Advances in Atmospheric Sciences 2023年第12期40卷 2331-2343页

作者： Lanying CHEN Renhao WU Qi SHU Chao MIN Qinghua YANG Bo HAN School of Atmospheric Sciences Sun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061China

This study assesses sea ice thickness(SIT)from the historical run of the Coupled Model Inter-comparison Project Phase 6(CMIP6).The SIT reanalysis from the Pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS)product is chosen as the validation reference data.Results show that most models can adequately reproduce the climatological mean,seasonal cycle,and long-term trend of Arctic Ocean SIT during 1979-2014,but significant inter-model spread exists.Differences in simulated SIT patterns among the CMIP6 models may be related to model resolution and sea ice model components.By comparing the climatological mean and trend for SIT among all models,the Arctic SIT change in different seas during 1979-2014 is evaluated.Under the scenario of historical radiative forcing,the Arctic SIT will probably exponentially decay at-18%(10 yr)-1 and plausibly reach its minimum(equilibrium)of 0.47 m since the 2070s.

关键词： sea ice thickness Arctic Ocean climate change historical simulation CMIP6