Towards a radar- and observation-based hail climatology for Germany

In the German Strategy for Adaptation to Climate Change hail is identified as one of the major subjects of concern regarding transport infrastructure. Moreover hailstorms are a major threat to e.g. agriculture and the automobile industry causing significant economical damages and losses. Despite the...

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Main Authors: Thomas Junghänel, Christoph Brendel, Tanja Winterrath, Andreas Walter
Format: Article
Language:English
Published: Borntraeger 2016-09-01
Series:Meteorologische Zeitschrift
Subjects:
Online Access:http://dx.doi.org/10.1127/metz/2016/0734
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spelling doaj-40a9c5190c1d4514a7d7d1fbcd88d75c2020-11-24T22:15:48ZengBorntraegerMeteorologische Zeitschrift0941-29482016-09-0125443544510.1127/metz/2016/073485525Towards a radar- and observation-based hail climatology for GermanyThomas JunghänelChristoph BrendelTanja WinterrathAndreas WalterIn the German Strategy for Adaptation to Climate Change hail is identified as one of the major subjects of concern regarding transport infrastructure. Moreover hailstorms are a major threat to e.g. agriculture and the automobile industry causing significant economical damages and losses. Despite these significant hail-related meteorological risks no comprehensive observation-based hail climatology for Germany exists. In this study we present a new approach to this task, combining radar data with different kinds of hail reports, such as ground observation and agricultural insurance data. Preprocessing ensures the applicability of the radar data for the presented climatological analysis. In this sense a number of detection methods are applied to filter artefacts, especially clutter pixels and spokes that disrupt radar measurements. To construct a reliable hail climatology for Germany we process all information into a 10‑year based annual average number of hail days on a 1km×1km$1\,\text{km}\times1\,\text{km}$ grid using a two-path hail criterion. While the first path combines a threshold of 50 dBZ with a hail report, the second path is based on a 55 dBZ threshold only. By adding radar data we increase the spatial representativity of the ground based hail reports and gain additional information in regions which lack observational data. Overall, the results are mainly determined by events derived from the first path (68 %). A validation of our dataset at 65 stations of Deutscher Wetterdienst shows that the method slightly underestimates the number of hail days, especially for mountainous regions. This results in a better adaption of the hail criterion to lowlands. The resulting hail frequency map shows an increase in the average number of hail days per year from north to south. In particular, hailstorms occur less frequently in the Central North German Plain and the Mecklenburg Coastal Lowland, whereas the highest number of hail days occurs mostly in the uplands of the Black Forest and the Swabian Jura, but also in the Rhenish Massif, the Alpine Foreland and the Lower Rhine Plain. Moreover, the Feldberg region in the Southern Black Forest shows the highest number of hail days per year.http://dx.doi.org/10.1127/metz/2016/0734weather radarhailclimatologyinsurance
collection DOAJ
language English
format Article
sources DOAJ
author Thomas Junghänel
Christoph Brendel
Tanja Winterrath
Andreas Walter
spellingShingle Thomas Junghänel
Christoph Brendel
Tanja Winterrath
Andreas Walter
Towards a radar- and observation-based hail climatology for Germany
Meteorologische Zeitschrift
weather radar
hail
climatology
insurance
author_facet Thomas Junghänel
Christoph Brendel
Tanja Winterrath
Andreas Walter
author_sort Thomas Junghänel
title Towards a radar- and observation-based hail climatology for Germany
title_short Towards a radar- and observation-based hail climatology for Germany
title_full Towards a radar- and observation-based hail climatology for Germany
title_fullStr Towards a radar- and observation-based hail climatology for Germany
title_full_unstemmed Towards a radar- and observation-based hail climatology for Germany
title_sort towards a radar- and observation-based hail climatology for germany
publisher Borntraeger
series Meteorologische Zeitschrift
issn 0941-2948
publishDate 2016-09-01
description In the German Strategy for Adaptation to Climate Change hail is identified as one of the major subjects of concern regarding transport infrastructure. Moreover hailstorms are a major threat to e.g. agriculture and the automobile industry causing significant economical damages and losses. Despite these significant hail-related meteorological risks no comprehensive observation-based hail climatology for Germany exists. In this study we present a new approach to this task, combining radar data with different kinds of hail reports, such as ground observation and agricultural insurance data. Preprocessing ensures the applicability of the radar data for the presented climatological analysis. In this sense a number of detection methods are applied to filter artefacts, especially clutter pixels and spokes that disrupt radar measurements. To construct a reliable hail climatology for Germany we process all information into a 10‑year based annual average number of hail days on a 1km×1km$1\,\text{km}\times1\,\text{km}$ grid using a two-path hail criterion. While the first path combines a threshold of 50 dBZ with a hail report, the second path is based on a 55 dBZ threshold only. By adding radar data we increase the spatial representativity of the ground based hail reports and gain additional information in regions which lack observational data. Overall, the results are mainly determined by events derived from the first path (68 %). A validation of our dataset at 65 stations of Deutscher Wetterdienst shows that the method slightly underestimates the number of hail days, especially for mountainous regions. This results in a better adaption of the hail criterion to lowlands. The resulting hail frequency map shows an increase in the average number of hail days per year from north to south. In particular, hailstorms occur less frequently in the Central North German Plain and the Mecklenburg Coastal Lowland, whereas the highest number of hail days occurs mostly in the uplands of the Black Forest and the Swabian Jura, but also in the Rhenish Massif, the Alpine Foreland and the Lower Rhine Plain. Moreover, the Feldberg region in the Southern Black Forest shows the highest number of hail days per year.
topic weather radar
hail
climatology
insurance
url http://dx.doi.org/10.1127/metz/2016/0734
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