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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 [Deutscher Wetterdienst (DWD)] 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 parameterizes the microphysical processes in the lower troposphere based on the appropriate thermodynamical profile that 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. Significance Statement: For a national weather service and its customers, the separation of precipitation types into solid and liquid is a key issue for improving weather forecasts and warnings. We combined measurements from weather radars and weather stations together with output of numerical weather prediction models and developed a method of estimating the precipitation type at a height of 2 m. Previous studies of the hydrometeor classification field concentrate on warm season weather conditions using "radar observations only" or apply a hybrid combination of radar observations with model information. The uniqueness of our work is the additional introduction of surface observations with high temporal and spatial resolution for a better estimation of the thermodynamical profiles to improve the "all season alignment." [ABSTRACT FROM AUTHOR]

Doppler spectra measured by vertically pointing radars are inherently linked to raindrop size distributions (DSDs). But accurate estimation of DSDs remains challenging because raindrop spectra are broadened by atmospheric turbulence and shifted by vertical air motions. This paper presents a novel method to estimate vertical air motions in which there is no need to assume a model for DSD at each range gate. The theory of the new method is that the spectral difference between the adjacent range gates is contributed by vertical air motions and the variability of DSDs. The contribution of the change of DSDs is estimated by looking up the prepared tables [lookup tables (LUTs)] of raindrop velocity difference and shape function difference. Then the vertical air motions can be estimated by minimizing the cost function of the two spectra between the adjacent range gates. The retrieval algorithm is applied to three cases including a stratiform case and two convective cases observed by a C-band vertically pointing radar in Longmen, Guangdong Province, China, in June 2016. Before that, the spectrum broadening effect is removed by the traditional deconvolution method with a wind profiler. The vertical profiles of precipitation parameters are also retrieved to investigate the microphysical process. The precipitation parameters retrieved near the surface are compared with the ground data collected by a two-dimensional video disdrometer (2DVD), and the results show good agreement. Significance Statement: Estimating vertical air motions and raindrop size distributions are of great help to improve precipitation forecasts and weather modification. This study developed a new method to estimate the vertical air motions using Doppler spectra measured by a vertically pointing radar. The advantage of the new method is that there is no need to assume models for raindrop size distributions. We applied the new method to a stratiform case and two convective cases, and the vertical profiles of precipitation parameters are retrieved. The results show that both the dynamic and microphysical processes in convective cases have larger variability than those in the stratiform case. In the future, the characteristics of more types of precipitation clouds will be investigated. [ABSTRACT FROM AUTHOR]