气候系统预测:基础创新和集成应用
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国家自然科学基金资助项目(42088101)


Climate system prediction:fundamental innovations and integrated applications
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    摘要:

    随着全球变暖,极端天气气候事件增强,天气气候灾害造成的损失也愈发严重。当前气候预测的准确性远远不能满足社会需要,气候系统预测理论和方法面临着众多挑战性问题。为提档气候预测科学水平和准确率,由南京信息工程大学和中山大学承担的“气候系统预测研究中心”获得国家自然科学基金基础科学中心项目支持(2021年1月—2025年12月)。在该项目执行的前三年,项目团队开展了大量深入系统的研究,并取得了若干重要进展:1)揭示了气候系统的若干关键变化、驱动力和机制;2)剖析了海-陆-冰-气相互作用对我国重大极端气候事件的影响;3)在气候系统数值模式研发和预测系统集成方面取得重要进展;4)发展了延伸期-S2S-年代际的气候系统预测理论和方法。本文对这些进展作了扼要介绍,并针对气候与环境变化归因、古今气候环境研究融合、跨时空气候系统变异和极端气候、人工智能与气候科学、年代际预测和风险应对体系等关键科学问题做了展望。

    Abstract:

    Extreme weather and climate events are exacerbated by global warming,leading to increasingly severe losses from weather-related disasters.Despite progress,theories and methods of climate system prediction still face numerous challenges,and the precision of climate predictions remains inadequate for societal needs.To address these issues and enhance the scientific rigor and accuracy of climate prediction,the “Center for Climate System Prediction Research,” jointly led by Nanjing University of Information Science and Technology and Sun Yat-sen University,receive support from the National Natural Science Foundation of China (2021-01—2025-12).Over the initial three years of the project,the research team conducted extensive and systematic studies,resulting in several significant advances:(1) unveiling key changes,driving forces,and physical mechanisms of the climate system;(2) investigating the impacts of air-sea-land-ice interactions on extreme weather and climate events in China;(3) making substantial progress in developing numerical models for the climate system and integrating prediction systems;(4) advancing prediction theories and methods for the climate system across extended-range,subseasonal to seasonal (S2S),and decadal time scales.This study offers a brief overview of these advancements and identifies key scientific questions for future exploration,including climate and environmental change attribution,bridging paleoclimate with present climate studies,understanding climate system variability and extremes across time and space,the role of artificial intelligence in climate science,decadal prediction,and risk response systems.

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王会军,戴永久,杨崧,李天明,罗京佳,尹志聪,段明铿,周放,张艺佳,2024.气候系统预测:基础创新和集成应用[J].大气科学学报,47(2):161-172. WANG Huijun, DAI Yongjiu, YANG Song, LI Tim, LUO Jing-jia, YIN Zhicong, DUAN Mingkeng, ZHOU Fang, ZHANG Yijia,2024. Climate system prediction:fundamental innovations and integrated applications[J]. Trans Atmos Sci,47(2):161-172. DOI:10.13878/j. cnki. dqkxxb.20240303007

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  • 收稿日期:2024-03-03
  • 最后修改日期:2024-03-10
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  • 在线发布日期: 2024-05-22
  • 出版日期: 2024-03-28

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