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

KONG Yunqi; DENG Yujiao; HU Xiaoming

doi:10.16032/j.issn.1004-4965.2026.007

Abstract：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.