Do extreme weather events affect human well-being? Dynamics and key factors from empirical evidence in China

Climate change-induced Extreme Weather (EW) poses cascading threats to Human Well-being (HWB). Yet, the complex spatial transmission mechanisms and the heterogeneous impacts of distinct climatic stressors remain understudied. To address this gap, this study develops a theoretical framework analyzing the cascading pathways from EW to HWB. By integrating spatial correlation analysis, the Spatial Durbin Model (SDM), and the Geographically Weighted Random Forest (GWRF) model, we empirically examine the spatiotemporal dynamics, spillover effects, and structural heterogeneity of four EW types—Extreme Low Temperature (LTD), High Temperature (HTD), Rainfall (ERD), and Drought (EDD)—across 184 Chinese cities from 2000 to 2022. Our results reveal four key insights: (1) Risk Interdependence: EW exerts a significant negative impact on HWB. Crucially, the negative spatial spillover effect exceeds the direct local effect, indicating that climate risks propagate through regional economic and social networks. (2) Structural Heterogeneity: The damage hierarchy follows LTD > HTD > EDD > ERD. LTD emerges as the most detrimental stressor, driven by an “adaptation deficit” in infrastructure against cold anomalies, particularly in less resilient regions. (3) Dynamic Evolution: The dominant climatic drivers of HWB are not spatially static but exhibit a distinct trajectory shift over time, migrating from Northern and Inland regions towards Southern and Coastal agglomerations. These findings underscore an urgent need to transition from atomistic adaptation strategies to coordinated regional governance to enhance collective climate resilience.