Advancements in Automated Convective Cell Detection and Nowcasting at Deutscher Wetterdienst (DWD)

At DWD, a semi-automated process is currently used to warn the public about thunderstorm-related hazards such as large hail, strong wind gusts, and heavy rainfall. Human forecasters are supported by algorithms and meteorological products that integrate information from various data sources.A key component of this infrastructure is KONRAD3D, a tool designed for the detection, tracking, and nowcasting of convective cells, particularly thunderstorms. KONRAD3D uses three-dimensional, quality-controlled radar reflectivity data from DWD’s radar network as its primary data source. It generates warning indicators for hail, heavy rainfall, and wind gust threats.In addition, the algorithm incorporates various supplementary data sources, including lightning data (LINET), DWD’s dual-polarization hydrometeor classification (to assess hail potential), grid-based, range-gauge-adjusted quantitative precipitation estimates (QPE) for evaluating heavy rainfall, and DWD’s mesocyclone detection for supporting wind gust warnings.Furthermore, numerical weather prediction (NWP) data are used to derive the most unstable vertical trajectories, from which meteorological quantities such as CAPE, CIN, vertical wind shear, and helicities are calculated. Cell-based vertically integrated ice (VII) and VII density are also now provided. Finally, cloud top height information derived from satellite data has been integrated.An evaluation of KONRAD3D’s cell detections and nowcasts against lightning observations has been conducted. However, assessing false alarms is non-trivial, as cell detections without lightning are permissible—early detection is a key objective. Therefore, we analyze cell tracks rather than individual cells in order to identify very short-lived, non-lightning tracks as potential false alarms.This contribution presents the basic functionality and recent enhancements of KONRAD3D, outlines its integration into DWD’s warning infrastructure, and summarizes the statistical results that assess its performance.

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Published
2025-08-08
DOI
https://doi.org/10.5194/ecss2025-308
Primary Topic
Meteorological Phenomena and Simulations
Type
article
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article

Advancements in Automated Convective Cell Detection and Nowcasting at Deutscher Wetterdienst (DWD)

Lukas Josipovic, Cornelia Strube, Christian Berndt, Robert Feger et al.
Meteorological Phenomena and Simulations
article

Advancements in Automated Convective Cell Detection and Nowcasting at Deutscher Wetterdienst (DWD)

Lukas Josipovic, Cornelia Strube, Christian Berndt, Robert Feger, Manuel Werner
article en

Abstract

At DWD, a semi-automated process is currently used to warn the public about thunderstorm-related hazards such as large hail, strong wind gusts, and heavy rainfall. Human forecasters are supported by algorithms and meteorological products that integrate information from various data sources.A key component of this infrastructure is KONRAD3D, a tool designed for the detection, tracking, and nowcasting of convective cells, particularly thunderstorms. KONRAD3D uses three-dimensional, quality-controlled radar reflectivity data from DWD’s radar network as its primary data source. It generates warning indicators for hail, heavy rainfall, and wind gust threats.In addition, the algorithm incorporates various supplementary data sources, including lightning data (LINET), DWD’s dual-polarization hydrometeor classification (to assess hail potential), grid-based, range-gauge-adjusted quantitative precipitation estimates (QPE) for evaluating heavy rainfall, and DWD’s mesocyclone detection for supporting wind gust warnings.Furthermore, numerical weather prediction (NWP) data are used to derive the most unstable vertical trajectories, from which meteorological quantities such as CAPE, CIN, vertical wind shear, and helicities are calculated. Cell-based vertically integrated ice (VII) and VII density are also now provided. Finally, cloud top height information derived from satellite data has been integrated.An evaluation of KONRAD3D’s cell detections and nowcasts against lightning observations has been conducted. However, assessing false alarms is non-trivial, as cell detections without lightning are permissible—early detection is a key objective. Therefore, we analyze cell tracks rather than individual cells in order to identify very short-lived, non-lightning tracks as potential false alarms.This contribution presents the basic functionality and recent enhancements of KONRAD3D, outlines its integration into DWD’s warning infrastructure, and summarizes the statistical results that assess its performance.

Deutscher Wetterdienst (DE)
Industry, innovation and infrastructure
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Meteorological Phenomena and Simulations
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Advancements in Automated Convective Cell Detection and Nowcasting at Deutscher Wetterdienst (DWD) — Lukas Josipovic, Cornelia Strube, et al. · (2025) | TGRS Research Map | TGRS