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Thomas Hengstebeck, Kathrin Wapler, Dirk Heizenreder, and Paul Joe

Abstract

The radar network of the German Weather Service [Deutscher Wetterdienst (DWD)] provides 3D Doppler data in high spatial and temporal resolution, supporting the identification and tracking of dynamic small-scale weather phenomena. The software framework Polarimetric Radar Algorithms (POLARA) has been developed at DWD to better exploit the capabilities of the existing remote sensing data. The data processing and quality assurance implemented in POLARA include a dual-PRF dealiasing algorithm with error correction. Azimuthal shear information is derived and processed in the mesocyclone detection algorithm (MCD). Low- and midlevel azimuthal shear and track products are available as composite (multiradar) products. Azimuthal shear may be considered as a proxy for rotation. The MCD results and azimuthal shear products are part of the severe weather detection algorithms of DWD and are provided to the forecaster on the NinJo meteorological workstation system. The forecaster analyzes potentially severe cells by combining near-storm environment data with the MCD product as well as with the instantaneous azimuthal shear products (mid- and low level) and their tracks. These products and tracks are used to diagnose threat potential by means of azimuthal shear intensity and track longevity. Feedback from forecasters has shown the utility of the algorithms to analyze and diagnose severe convective cells in Germany and in adjacent Europe. In this paper, the abovementioned algorithms and products are presented in detail and case studies illustrating usability and performance are shown.

Open access
Paul M. James, Bernhard K. Reichert, and Dirk Heizenreder

Abstract

NowCastMIX is the core nowcasting guidance system at the German Weather Service. It automatically monitors several systems to capture rapidly developing high-impact mesoscale convective events, including 3D radar volume scanning, radar-based cell tracking and extrapolation, lightning detection, calibrated precipitation extrapolations, NWP, and live surface station reports. Within the context of the larger warning decision support process AutoWARN, NowCastMIX integrates the input data into a high-resolution analysis, based on a fuzzy logic approach for thunderstorm categorization and extrapolation, to provide an optimized warning solution with a 5-min update cycle for lead times of up to 1 h. Feature tracking is undertaken to optimize the direction of warning polygons, allowing individual, tangentially moving cells or cell clusters to be tracked explicitly. An adaptive ensemble clustering is deployed to reduce the spatial complexity of the resulting warning fields and smooth noisy temporal variations to a manageable level for duty forecasters. Further specialized outputs for civil aviation and for a public mobile phone warning app are generated. Now in its eighth year of operation, a comprehensive and complete set of thunderstorm analyses and nowcasts over Germany has been created, which is of unique value for ongoing research and development efforts for improving the system, as well as for addressing climatological aspects of severe convection. Verification has shown that NowCastMIX has helped to significantly improve the quality of the official warnings for severe convective weather events when used within the AutoWARN process.

Open access