Studies of Optimal Land Surface Conditions Most Favorable for Heat Wave Onsets Over the Yangtze River Valley

Abstract Heat waves (HWs) cause severe impacts on society and the economy. Early warning is crucial for disaster risk management about HW onsets. Land surface conditions are key to HW onsets. However, few studies have investigated which specific land surface features are more likely to cause HW onsets. Here, we investigate this issue by exploring the land surface conditions more favorable for HW onsets over the Yangtze River Valley using the conditional nonlinear optimal perturbation related to parameters (CNOP‐P) approach. The numerical results indicate that CNOP‐P type land surface conditions are the most favorable for HW onsets compared to random types. Surface energy partitioning is primarily influenced by CNOP‐P type surface conditions, which lead to more energy release in the form of sensible heat fluxes. Vegetation is a key factor influencing HW occurrence, as it significantly affects surface energy partitioning by regulating vegetation transpiration. In addition, individual results also show that soil evaporation processes also have an important role in HW onsets. More importantly, the increase in shortwave radiative fluxes due to reduced cloudiness and increased 500 hPa geopotential height provide more favorable conditions for HW onsets. Compared to CNOP‐P type conditions, RP type conditions have less influence on surface energy, moisture, and atmospheric circulation, making it difficult to create conditions conducive to HW onsets. This study explores the identification of land surface conditions that are more favorable for HW onsets, further deepens our understanding of HW onsets, and provides some insights into the development of early warning systems.