Soil Organic Matter Reduces Persistent Nighttime Surface Warm Bias in Convection-Permitting U.S. Simulations

Convection-permitting modeling has become a cornerstone for improving representation of land-atmosphere processes, predicting weather extremes, and creating long-term hydrometeorological data sets. The convection-permitting Weather Research and Forecasting (WRF) modeling with the NoahMP land-surface scheme is widely used for kilometer-scale hydroclimatic applications. We identify persistent large warm biases (up to ∼8°C) in daily minimum surface air temperature (T_min) in convection-permitting WRF/NoahMP simulations across the western, central, and southeastern US. Motivated by the potential of soil organic matter (SOM) to mitigate nighttime warm bias, we implement a physical representation of this previously missing component and assess its effects on land-surface fluxes and surface air temperature. Including SOM significantly changes surface soil thermal properties and reduces T_min warm bias (by 75%) by mitigating the overestimated diurnal amplitude of ground heat flux (by 29%). This offers a physics-based pathway to improve future kilometer-scale simulations.