Model Wind Field Forecast Verification Using Multiple-Doppler Syntheses from a National Radar Network

Model verification has traditionally relied upon in situ observations, which typically exist on a sparse network, making nonsurface model forecast verification difficult. Given increasing model resolution, supplemental observational datasets are needed. Multiple-Doppler wind retrievals using a national network of radars provide an opportunity to assess the accuracy of wind forecasts at multiple levels, as well as verification within a three-dimensional domain. Wind speed and direction verification results are presented for a 9-day period of forecasts from the French Application of Research to Operations at Mesoscale-Western Mediterranean (AROME-WMED) model using multiple-Doppler retrievals from the French Application Radar à la Météorologie Infrasynoptique (ARAMIS) network. For the analyzed period, relationships were found that suggest that errors are not only linked to forecasted evolution of meteorological phenomena, but are sensitive to terrain height below the analyzed level as well as mesoscale processes. The spatial distribution of errors at initialization and forecast times shows that biases are generally independent of location and terrain height at initialization, but that the impact of terrain below the analysis level affects the forecasted wind magnitude and direction over time. These comparisons illustrate that multiple-Doppler wind retrieval measurements accurately identify model error and can serve as an invaluable dataset for model verification.