摘要
围绕“地球系统与全球变化”重点专项项目“中国极端天气气候事件的形成机理及其预测和归因”2024年度主要进展,从极端事件变化的观测事实、环流特征与动力学机理,海洋关键过程与海气相互作用机理,海洋过程对极端天气气候的影响,陆面过程及其影响研究,极端事件模拟与预测等5个方面介绍了项目的最新研究成果。1)揭示了变暖趋势对中国近40年破纪录高温事件的影响,基于通用热气候指数分析了中国区域极端高温事件的时空变化特征,探讨了不同增暖期中国东部极端降水的演变规律,阐明了长江中下游极端热浪事件的热、动力学特征,并归因了人类活动对亚洲热点区域极端温度事件的影响。2)量化了前期冬季北太平洋涛动对后期ENSO发展的作用,指出热带太平洋年际-年代际变率在超长La Nina事件形成有重要贡献;揭示了La Nina纬向位置对印度洋偶极子的调制机理,发现ENSO对东海-黑潮区域海温的影响存在季节性反转;开展了黑潮延伸体区域SST异常和海洋热浪的季节可预报性研究,阐明了非线性过程对大气季节内振荡的作用,探讨了多因子影响北大西洋多年代际变化的物理机制。3)揭示了ENSO对晚冬“暖北极-冷欧亚”模态的非对称影响,发现了其与中国东部前、后冬降水模态及黑潮反气旋的联系,并阐释了对东海-黑潮区海温和东亚降水的季节性变化机理;指出Mega-ENSO与西北太平洋台风生成区域的向极移动存在密切联系,揭示了热带跨洋盆海气相互作用对台风生成位置和频次的影响过程;发现南极变暖驱动南大西洋变暖是2022年东亚高温热浪的重要成因,热带北大西洋变率显著调控我国东北森林野火。4)揭示了欧亚大陆土壤湿度次季节变化对我国北方群发性极端降水事件的影响机制,评估了积雪覆盖对温度次季节变化及预测的影响;开展了陆面因子与陆气耦合过程影响干旱的归因与预估研究;阐明了陆面过程与海陆协同影响中国夏季降水和超级梅雨、极端降水的物理机制;评估了华北夏季灌溉对降水日循环和区域水循环的影响及城市化对珠三角暖季中尺度对流系统和强降水的影响。5)系统评估了CMIP6模式对“暖北极-冷欧亚”模态前后冬次季节反转的模拟能力,构建了中国东南区域复合极端湿热事件的季节预测模型;利用年际增量方法构建了华北盛夏强降水频次的物理统计预测模型,基于深度学习方法改进长江中下游流域夏季极端降水动力模式的预测性能;同步开展了动力模式的发展及预测应用研究。最后,展望了面临的挑战和需要进一步加强研究的相关问题,以期为推动我国极端天气气候领域的研究提供一定参考。
The article reviews the progress made in 2024 under China's National Key R&D Program for Earth System and Global Change.It highlights key research findings across five areas:observational facts and circulation characteristics of extreme event changes,key oceanic processes and air-sea interaction mechanisms,the influence of oceanic processes on extreme weather and climate,land surface processes and their impacts,and the simulation and prediction of extreme events.Significant advances in 2024 include the following:1)Our study examined the impact of long-term warming trends on record-breaking high-temperature in China events over the past 40 years.Using the Universal Thermal Climate Index(UTCI),we characterized the spatial distribution and long-term trends of extreme high-temperature events.Observational evidence was provided for changes in hourly and daily extreme precipitation across eastern China during different warming periods.Additionally,regional differences in the duration of summer heatwaves and their associated large-scale circulation anomalies were identified.The dynamic and thermal characteristics of extreme heatwaves in the middle and lower reaches of the Yangtze River were analyzed,and attribution studies assessed the influence of human activities on extreme temperature events in Asian hotspots.2)We quantified the role of the winter North Pacific Oscillation(NPO)in shaping subsequent ENSO events,emphasizing the contribution of tropical Pacific interannual-decadal variability to prolonged La Nina events.Our research also proposed a modulation mechanism whereby La Nina's zonal position influences the Indian Ocean Dipole(IOD)and identified seasonal reversals in ENSO's impact on sea surface temperature(SST)in the East China Sea-Kuroshio Region.Furthermore,we investigated the seasonal predictability of SST anomalies and marine heatwaves in the Kuroshio Extension Region,highlighting the role of nonlinear processes in the amplitude evolution of the Madden-Julian Oscillation(MJO)and extreme MJO formation.Additionally,pathways linking anthropogenic forcing,natural variability,and internal climate fluctuations to multidecadal changes in the North Atlantic were explored.3)Our findings revealed asymmetric ENSO influences on the late-winter“Warm Arctic-Cold Eurasia”pattern and identified links between ENSO and precipitation patterns in eastern China during early and late winter.The connection between ENSO and the Kuroshio anticyclone was also examined.Seasonal mechanisms linking ENSO to SST variability in the East China Sea-Kuroshio Region and its influence on East Asian precipitation were clarified.We found a strong association between Mega-ENSO and the poleward shift of typhoon genesis locations in the western North Pacific,while trans-basin tropical air-sea interactions were shown to affect typhoon formation frequency.Furthermore,we identified Antarctic warming-induced South Atlantic warming as a key driver to the 2022 East Asian heatwaves and demonstrated that tropical North Atlantic variability modulates forest wildfire activity in Northeast China.4)We investigated the role of Eurasian soil moisture variability in triggering clustered extreme precipitation events in northern China and evaluated the influence of snow cover on subseasonal temperature variability and predictability.Attribution and projection studies examined drought patterns influenced by land surface factors and land-atmosphere coupling.The physical mechanisms linking land surface processes and land-sea interactions to summer precipitation,extreme Meiyu events,and heavy rainfall in China were further elucidated.Additionally,we assessed the impact of summer irrigation in North China on the diurnal cycle of precipitation and regional water cycles,as well as the effects of urbanization on mesoscale convective systems and heavy rainfall in the Pearl River Delta during warm seasons.5)The simulation capabilities of CMIP6 models in representing the subseasonal reversal of the“Warm Arctic-Cold Eurasia”pattern were systematically evaluated.A seasonal prediction model for compound extreme heat-humidity events in southeastern China was developed.Using an interannual increment approach,a physical-statistical prediction model for summer heavy precipitation days(HPDs)in North China was established.Additionally,deep learning techniques were employed to enhance dynamical model predictions of summer extreme precipitation in the middle and lower Yangtze River basin.Further advancements in dynamical model development and their predictive applications were explored.Finally,this article outlines key challenges and research priorities for future studies,aiming to advance understanding of extreme weather and climate in China.
作者
陈海山
张耀存
张文君
尹志聪
陈国森
华文剑
黄丹青
况雪源
刘芸芸
马红云
施宁
孙善磊
魏江峰
赵海坤
张杰
韩婷婷
李文铠
桑英涵
王润
CHEN Haishan;ZHANG Yaocun;ZHANG Wenjun;YIN Zhicong;CHEN Guosen;HUA Wenjian;HUANG Danqing;KUANG Xueyuan;LIU Yunyun;MA Hongyun;SHI Ning;SUN Shanlei;WEI Jiangfeng;ZHAO Haikun;ZHANG Jie;HAN Tingting;LI Wenkai;SANG Yinghan;WANG Run(State Key Laboratory of Climate System Prediction and Risk Management(CPRM)/Key Laboratory of Meteorological Disaster,Ministry of Education(KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD),Nanjing University of Information Science and Technology,Nanjing 210044,China;School of Atmospheric Sciences,Nanjing University of Information Science and Technology,Nanjing 210044,China;School of Atmospheric Sciences,Nanjing University,Nanjing 210093,China;State Key Laboratory of Climate System Prediction and Risk Management/China Meteorological Administration Key Laboratory for Climate Prediction Studies,National Climate Center,Beijing 100081,China;State Key Laboratory of Disaster Weather Science and Technology/Institute of Tibetan Plateau Meteorology,Chinese Academy of Meteorological Sciences,Beijing 100081,China)
出处
《大气科学学报》
北大核心
2025年第2期177-206,共30页
Transactions of Atmospheric Sciences
基金
国家重点研发计划项目(2022YFF0801600)。
关键词
极端天气气候事件
海气相互作用
陆面过程
机理
预测
extreme weather and climate events
air-sea interaction
land surface process
mechanism
prediction
