Hymec: Surface Precipitation Type Estimation at the German Weather Service

Abstract

The analysis and forecast of precipitation characteristics is a key task for national meteorological services for providing high quality weather forecasts and warnings. Beside the precipitation amount, the precipitation type is essential to describe and evaluate the recent, ongoing and future weather situations.This paper introduces a new surface-based hybrid hydrometeor classification algorithm. The presented method combines polarimetric radar observations at radar beam height from the C-band dual-polarization weather radar network of the German Weather Service (DWD, Deutscher Wetterdienst) with corrected thermodynamical profiles of numerical weather prediction (NWP) model output and extrapolates the hydrometeor classes at radar beam height to a height of 2 m above ground level (AGL). The implemented technique parametrizes the microphysical processes in the lower troposphere based on the appropriate thermodynamical profile the hydrometeors have to pass along their way from the radar beam height to the surface. Due to errors in NWP output, the NWP vertical profiles of temperature and humidity are adjusted by using several types of surface stations with high spatial and temporal resolution.Verification results show considerable improvements in the hydrometeor classification near the ground compared to the radar sweep height. After an additional positive in-house evaluation, the presented method is integrated into DWD’s operational environment. The topic of this paper is to describe the processing steps for the computation of the near-surface precipitation type. In addition, example cases and a verification study complement the explanations.

Radio frequency interference detection and mitigation in the DWD C-band weather radar network

“…Data obtained by weather radars are a crucial element in today's forecasting and nowcasting tools (e.g. Besic et al, 2016;Steinert et al, 2021). Nowcasting applications and the analysis of local phenomena depend upon the high temporal and spatial resolution provided by weather radars.…”

Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes

“…For example, assigning general classes of precipitation particles, such as rain, light rain, dry snow, wet snow, graupel, and hail, to polarimetric radar data based on radar scattering calculations allows for identifying the dominant (in terms of the radar signature) precipitation particle type in each radar bin, called a hydrometeor classification (e.g. Marzano et al, 2007Marzano et al, , 2008Park et al, 2009;Dolan and Rutledge, 2009;Dolan et al, 2013;Al-Sakka et al, 2013;Bechini and Chandrasekar, 2014;Thompson et al, 2014;Frech and Steinert, 2015;Grazioli et al, 2015;Besic et al, 2016;Steinert et al, 2021). Furthermore, rain and snowfall rate or water content can be estimated from different combinations of measured polarimetric variables to improve quantitative precipitation estimates that were previously based only on measured radar reflectivity (e.g.…”

“…For DWD's C-band radars, for example, a birdbatch scan (where the radar antenna rotates a full 360°while pointing vertically upward, i.e. at a constant elevation angle of 90°) has been used routinely to monitor the calibration of the differential reflectivity (Frech and Hubbert, 2020), one of the polarimetric variables required as input for the 'Hymec' hydrometeor classification scheme at DWD (Steinert et al, 2021).…”

Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes

“…Polarimetric radar measurements of precipitating clouds provide crucial information both for fundamental research into precipitation processes and for operational weather services (Ryzhkov and Zrnic, 2019). For example, assigning general classes of precipitation particles, such as rain, light rain, dry snow, wet snow, graupel, and hail, to polarimetric radar data based on radar scattering calculations allows for identifying the dominant (in terms of the radar signature) precipitation particle type in each radar bin, called a hydrometeor classification (e.g., Marzano et al, 2007Marzano et al, , 2008Park et al, 2009;Dolan and Rutledge, 2009;Dolan et al, 2013;Al-Sakka et al, 2013;Bechini and Chandrasekar, 2014;Thompson et al, 2014;Frech and Steinert, 2015;Grazioli et al, 2015;Besic et al, 2016;Steinert et al, 2021). Furthermore, rain and snowfall rate or water content can be estimated from different combinations of measured polarimetric variables to improve quantitative precipitation estimates that were previously based only on measured radar reflectivity (e.g., Vivekanandan et al, 2004;Marzano et al, 2010;Bukovcic et al, 2018).…”

“…Some Cand S-band radar designs do not allow vertically pointing measurements; and where such observations are available, they are mostly used for quality control of polarimetric radar data. For DWD's C-band radars, for example, a birdbath scan (where the radar antenna rotates a full 360 • while pointing vertically upward, i.e., at a constant elevation angle of 90 • ) has been used routinely to monitor the calibration of the differential reflectivity (Frech and Hubbert, 2020), one of the polarimetric variables required as input for the Hymec hydrometeor classification scheme at the DWD (Steinert et al, 2021).…”