Examination of Forecast Errors and the Impact of Assimilating High-Density Observations at Convective Scale in Context of the Ensemble Kalman Filter

Radar data has been assimilated to improve the quantitative precipitation forecast at the convective scale, and many studies have shown the positive impact of it. This study examines the short-term forecast error at convective scale and explains the impact of assimilating radial wind and reflectivity. In addition, by using the Ensemble Kalman filter system, one investigate that if it is possible to reduce the assimilation window for cycling process by providing additional high density observations such as temperature and humidity measurement.