PNNL

Abstract

Convection-permitting models (CPMs) offer a substantial improvement over coarser-resolution models in simulating deep convection and mesoscale convective systems (MCSs). Despite these advancements, CPMs continue to exhibit persistent biases, notably the overestimation of precipitation intensity and cloud depth with underestimation of stratiform precipitation area. This study introduces a novel parameterization for sub-grid scale circulation by applying a small rotation to the grid-scale flow to account for under-resolved convective drafts in km-scale models. This parameterized anomalous circulation is then applied to the advection of moisture, hydrometeors, and momentum, thereby enhancing the exchange of these variables between convective drafts and their environment. The scheme is implemented in the Weather Research and Forecasting (WRF) model and optimized for improved representation of precipitation statistics. Evaluation through month-long simulations at 4-km and 1-km grid spacings over the Amazon of the optimized advection scheme (OAS) shows improved representation of precipitation rates, outgoing longwave radiation, characteristics of MCSs and surface temperature. This study highlights the potential of physically justified parameterization of sub-grid scale circulations to improve the fidelity of CPM simulations.