Testing and Evaluation of an Atmospheric River Prediction Model

An atmospheric river analysis and forecast system (AR-AFS) is being developed by NOAA’s Environmental Modeling Center to better understand and predict the extreme precipitation events induced by atmospheric rivers (ARs).  This system is a limited-area version of NOAA’s Unified Forecast System, with 3-km horizontal resolution.  As part of a community effort to optimize the system’s performance, we are currently evaluating the impact of different physics parameterizations on the system’s quantitative precipitation forecast (QPF) along the US West Coast. 

To a large degree, the accuracy of the precipitation forecast for a landfalling AR is determined by synoptic-scale, dynamical forcing; however, the parameterized physical processes in the model also play an important role.  The factors contributing to errors in QPF are multiscale in nature, and vary in their sensitivity to the model representation of both dynamical and physical processes.  Using precipitation observations as well as meteorological analyses, we present an evaluation of the impact of different physics parameterizations on the model performance.