Preprints
https://doi.org/10.5194/amt-2022-190
https://doi.org/10.5194/amt-2022-190
 
05 Jul 2022
05 Jul 2022
Status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

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

Mathias Gergely1, Maximilian Schaper1, Matthias Toussaint2, and Michael Frech1 Mathias Gergely et al.
  • 1German Meteorological Service (Deutscher Wetterdienst, DWD), Observatorium Hohenpeißenberg, Hohenpeißenberg, Germany
  • 2GAMIC Weather Radar and Signal Processing, Aachen, Germany

Abstract. This study explores the potential of using Doppler (power) spectra from vertically pointing C-band radar birdbath scans to investigate precipitating clouds above the radar. First, the novel birdbath scan strategy for the network of dual-polarization C-band radars operated by the German Meteorological Service (Deutscher Wetterdienst, DWD) is outlined, and a newly developed spectral postprocessing and analysis method is presented. The postprocessing algorithm isolates the weather signal from non-meteorological contributions in the radar output based on polarimetric attributes, identifies the statistically significant precipitation modes contained in each Doppler spectrum, and calculates characteristics of every precipitation mode as well as multimodal properties that describe the relation among different modes when more than a single mode is identified. To achieve a high degree of automation and flexibility, the postprocessing chain combines classical signal processing with clustering algorithms. Uncertainties in the calculated modal and multimodal properties are estimated from the small variations associated with smoothing the measured radar signal.

The analysis of five birdbath scans recorded at different radar sites and for various precipitation conditions delivers reliable profiles of the derived modal and multimodal properties for two snowfall cases and for stratiform precipitation above and below the melting layer. To help identify the dominant precipitation growth mechanism, Doppler spectra from DWD's birdbath scans can be used to retrieve the typical degree of riming for individual snow modes. Here, the automatically identified snow modes span a wide range of riming conditions with estimated rime mass fractions of up to RMF > 0.5. The evaluation of Doppler spectra inside the melting layer and for an intense frontal shower, with observed radar reflectivities of up to about 40 dBZ, occasionally shows erroneously identified precipitation modes and spurious results for the calculated higher-order Doppler moments of skewness and kurtosis. Nonetheless, the Doppler spectra from DWD's operational C-band radar birdbath scan provide a detailed view into the precipitating clouds and allow for calculating a high-resolution profile of radar reflectivity, mean Doppler velocity, and spectral width even in intense frontal precipitation.

Mathias Gergely et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-190', Anonymous Referee #1, 01 Aug 2022
    • AC1: 'Reply on RC1', Mathias Gergely, 26 Oct 2022
  • RC2: 'Comment on amt-2022-190', Anonymous Referee #2, 08 Sep 2022
    • AC2: 'Reply on RC2', Mathias Gergely, 26 Oct 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-190', Anonymous Referee #1, 01 Aug 2022
    • AC1: 'Reply on RC1', Mathias Gergely, 26 Oct 2022
  • RC2: 'Comment on amt-2022-190', Anonymous Referee #2, 08 Sep 2022
    • AC2: 'Reply on RC2', Mathias Gergely, 26 Oct 2022

Mathias Gergely et al.

Mathias Gergely et al.

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Short summary
This study presents the novel vertically pointing birdbath scan of the German C-band radar network, which provides high-resolution profiles of precipitating clouds above all DWD weather radars since spring 2021. Our AI based postprocessing method for filtering and analyzing the recorded radar data offers a unique quantitative view into a wide range of precipitation events from snowfall over stratiform rain to intense frontal showers and will be used to complement DWD’s operational services.