Taking place at the Royal Meteorological Institute of Belgium (RMIB), the ongoing 2-year PRECIP-TYPE project aims at improving the hydrometeor classification in Belgium through the use of dual-pol radar observations and Numerical Weather Prediction (NWP) model output. Combining these two sources of information in a fuzzy logic scheme yields an estimate of the precipitation type (rain, hail, snow,...) at the height of the measurement of the radar. This information is then further processed by using vertical temperature, humidity and pressure profiles from NWP output in order to account for the melting process that can occur before precipitation reaches the ground. The output of this precipitation type product is compared to the crowdsourced weather reports sent by the users of the RMIB smartphone app. Such user reports can include the precipitation type as well as the size of the hydrometeors. These reports are ingested in a database of the RMIB and undergo reliability checks that allow an easier discrimination between realistic and unrealistic observations.
We present the step-by-step methodology followed to obtain this first product version, including an extended clutter filtering, and we demonstrate its capabilities for a few challenging cases. We discuss the identified uncertainties and the remaining open questions. Regarding the perspectives, several possibilities are considered to further enhance this preliminary precipitation type product, such as the merging of dual-pol observations obtained from several radars, the comparison with alternative schemes of hydrometeor classification or the inclusion of the citizen observations (RMIB app) within the classification scheme. An overview of these lines of research will be presented.
How to cite: Watelet, S., Delobbe, L., and Reyniers, M.: Improving the hydrometeor classification at ground level in Belgium, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-641, https://doi.org/10.5194/ems2022-641, 2022.