Abstract
Numerical prediction of precipitation associated with five cool-season atmospheric river events in northern California was analyzed and compared to observations. The model simulations were performed by using the Advanced Research Weather Research and Forecasting Model (ARW-WRF) with four different microphysical parameterizations. This was done as a part of the 2005–06 field phase of the Hydrometeorological Test Bed project, for which special profilers, soundings, and surface observations were implemented. Using these unique datasets, the meteorology of atmospheric river events was described in terms of dynamical processes and the microphysical structure of the cloud systems that produced most of the surface precipitation. Events were categorized as “bright band” (BB) or “nonbright band” (NBB), the differences being the presence of significant amounts of ice aloft (or lack thereof) and a signature of higher reflectivity collocated with the melting layer produced by frozen precipitating particles descending through the 0°C isotherm.
The model was reasonably successful at predicting the timing of surface fronts, the development and evolution of low-level jets associated with latent heating processes and terrain interaction, and wind flow signatures consistent with deep-layer thermal advection. However, the model showed the tendency to overestimate the duration and intensity of the impinging low-level winds. In general, all model configurations overestimated precipitation, especially in the case of BB events. Nonetheless, large differences in precipitation distribution and cloud structure among model runs using various microphysical parameterization schemes were noted.
How well were the early 2017 California Atmospheric River precipitation events captured by satellite products and ground‐based radars?
