Improving fog simulation in East China: The role of soil moisture constraint and meteorological observation nudging

Soil moisture plays a crucial role in fog formation and duration, yet its impact has not been sufficiently assessed in fog numerical simulations. This study evaluates the impact of soil moisture constraints (SMC) on fog simulation over East China using the WRF-Chem model, incorporating a series of soil moisture observation data from the China Meteorological Administration and reanalysis products. Additionally, the study assesses the improvements achieved through the meteorological observation nudging (MON) assimilation scheme. Results indicate that the MON scheme significantly improves the simulation accuracy of fog coverage, with the threat score (TS) improving from 65.1 % to 71.2 %, alongside better simulation of key meteorological variables. When combined with MON, SMC derived from observational data further enhances accuracy of fog area simulation, achieving a TS of 72.3 %. Notably, SMC derived from observational soil moisture (Obs-SMC) data outperforms SMC from reanalysis products (ERA5-SMC and FNL-SMC) in overall fog simulation. For RH, MON raised the average index of agreement (IOA) from 0.67 to 0.69 and reduced the normalized mean error (NME) from 24.4 % to 21.7 %. With Obs-SMC, the IOA further increased to 0.83, and the NME dropped to 14.3 %, demonstrating notable improvements in simulation performance. Process analysis suggests that the Obs-SMC further enhances surface evaporation, facilitating near-surface fog condensation and increasing the regional mean liquid water content (LWC) by approximately 0.01 g/kg. Our findings highlight the critical role of accurate soil moisture data in improving fog simulation, implicating a valuable approach for enhancing fog forecasting accuracy.