Precipitation forecast skill of numerical weather prediction models and radar nowcasts

Abstract

Short term precipitation forecasts based on Lagrangian advection of radar echoes are robust and have more skill than numerical weather prediction models over time scales of several hours. This is because the models do not generally capture well the initial precipitation distribution. We will refer to the advection-based methods as radar nowcasts. Over longer time scales, we expect the models to perform better than nowcast methods as they resolve dynamically the large scale flow. We verify this conceptual picture of the relative accuracy of radar nowcasts and model forecasts using conventional skill scores. We identify the cross-over point in time where model forecasts start to have more skill than nowcast methods. This occurs at about 6 hours after the forecast is initiated. Copyright 2005 by the American Geophysical Union.