On the spatial distribution of rainfall nowcasting errors due to orographic forcing

Abstract

ABSTRACTThe goal of this research is to study the effect of orography on the spatial distribution of rainfall nowcasting errors. Twenty months of forecasts of hourly rainfall accumulations from the short‐term ensemble prediction system (STEPS) for the weather radar composite over eastern Victoria, Australia, were verified against radar observations. The verification was stratified according to six different flow regimes derived by applying a k‐means clustering algorithm on the archive of motion fields. STEPS biases were found to have a strong flow‐regime dependence, which appears as an underestimation of rainfall on the windward side of terrain features followed by an overestimation on the leeward side. In the regions characterized by strong orographic forcing, the relative contribution of the bias to the root mean square error (RMSE) of the nowcast is locally important. The results also highlighted areas where the errors in the radar rainfall estimates contributed a significant fraction of the observed forecast error. These promising results open ways to integrate flow‐dependent and spatially inhomogeneous growth and decay mechanisms in the stochastic simulation of radar rainfall fields performed by STEPS.