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CO2强迫下广东地表气温响应及其不确定性归因OA

Surface Temperature Response to CO2 Forcing in Guangdong:A Quantitative Attribution of Uncertainties

中文摘要英文摘要

基于第六次耦合模式比较计划(Coupled Model Intercomparison Project Phase 6,简称CMIP6)的18个气候模式模拟数据,采用了控制试验(piControl)作为稳定气候状态的参考,使用突然4倍CO2 强迫试验(abrupt-4×CO2)来模拟极端温室气体排放情景下的气候响应,并利用气候反馈响应分析方法(CFRAM),定量评估了外强迫、各辐射反馈过程和非辐射过程对广东省增暖及其不确定性的贡献.结果显示,广东省的增暖幅度在不同模式间存在差异,增暖范围为3.71~7.07℃,集中在4.42~5.40℃之间,且增暖在西部和北部最显著.对于多模式集合平均的增暖进行了定量归因分析,气候反馈响应分析表明,水汽反馈和二氧化碳强迫是主要的增暖驱动力,分别贡献了4.92℃和2.42℃.地表热存储和云反馈也对增暖有显著正贡献,而地表感热通量和潜热通量则表现出降温效应.在不确定性分析中,云短波辐射效应、地表感热通量和地表热存储是主要的不确定性来源,这些不确定性主要来自模式在云层物理、地表能量平衡和热量再分配方面的差异,未来研究应重点关注这些过程以提高区域气候变化预估的准确性.

Based on simulations from 18 climate models participating in the Coupled Model Intercomparison Project Phase 6(CMIP6),this study uses the piControl experiment as a reference for a base climate state and the abrup-4×CO2 experiment to simulate the climate response under an extreme greenhouse gas forcing scenario.The Climate Feedback Response Analysis Method(CFRAM)was employed to quantitatively evaluate the contributions of external forcings,various radiative feedback processes,and non-radiative processes to the warming over Guangdong Province and the associated uncertainties.The results show that the projected warming over Guangdong varies across models with an estimated range of 3.71℃to 7.07℃,and a robust estimate centered between 4.42℃and 5.40℃.The warming is most pronounced in the western and northern regions of the province.A quantitative attribution analysis of the multi-model ensemble mean indicates that water vapor feedback and CO2 forcing are the primary drivers of the projected warming,contributing 4.92℃and 2.42℃,respectively.Surface heat storage and cloud feedback also provide significant positive contributions to the warming,while surface sensible heat flux and latent heat flux contribute to a cooling effect.Uncertainty analysis reveals that cloud shortwave radiative effects,surface sensible heat flux,and surface heat storage are the main sources of uncertainty,stemming primarily from differences in model representations of cloud physics,surface energy balance,and heat redistribution.Future research to improve the accuracy of regional climate projections should focus on better constraining these key processes.

孔蕴淇;邓玉娇;胡晓明

广东省生态气象中心,广东 广州 510641广东省生态气象中心,广东 广州 510641中山大学大气科学学院,广东 珠海 519000

天文与地球科学

二氧化碳地表气温气候反馈CMIP6不确定性

carbon dioxidesurface temperatureclimate feedbackCMIP6uncertainty

《热带气象学报》 2026 (1)

83-93,11

广东省基础与应用基础研究基金项目(2024A1515510009)广东省气象局科学技术项目(GRMC2023Q01)共同资助

10.16032/j.issn.1004-4965.2026.007

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