Evaluating Orographic Enhanced Precipitation Associated with Landfalling Atmospheric Rivers over California

Atmospheric rivers (AR) have provided historical rainfall to California. The primary effort in this study was on the improvement of short-range precipitation forecasts among several primary watersheds in California, with a focus on the influence of AR landfalling paths on the rainfall distribution over mountain ranges and the associated dynamics using the Atmospheric River Analysis and Forecast System (AR-AFS). In this study, AR events were compared during the 2022-2023 water year with the model’s efficiency and accuracy for the following AR types: weak, moderate, and strong cases. Thus, ARs were categorized with their associated orographic precipitation patterns and characteristics. Results from the AR-AFS model were analyzed to understand the dynamics of formation and propagation of precipitation for individual AR events. In addition, a series of high-resolution models using the Weather Research and Forecasting (WRF) model were compared to verify the findings from the AR-AFS real-case simulations. These simulations included 4D-VAR data assimilation of the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) satellite and the Next Generation Weather Radar (NEXRAD) radar data. Sensitivities of orographic enhanced precipitation were investigated by analyzing results from Multi-Radar/Multi-Sensor (MRMS) machine learning (ML) parameters to further evaluate the efficiency of the current AR-AFS model microphysics.