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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/nhess-2020-10
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-10
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  09 Mar 2020

09 Mar 2020

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A revised version of this preprint was accepted for the journal NHESS and is expected to appear here in due course.

Predictive modeling of hourly probabilities for weather-related road accidents

Nico Becker1,2, Henning W. Rust1,2, and Uwe Ulbrich1 Nico Becker et al.
  • 1Institut für Meteorologie, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
  • 2Hans-Ertel-Centre for Weather Research, Berlin, Germany

Abstract. An impact of weather on road accidents has been identified in several studies with a focus mainly on monthly or daily accident counts. We study hourly probabilities of road accidents caused by adverse weather conditions in Germany on the spatial scale of administrative districts. Meteorological predictor variables from radar-based precipitation estimates, high-resolution reanalysis and weather forecasts are used in logistic regression models. Models taking into account temperature and hourly precipitation sums reach the best predictive skill according to different metrics. By introducing meteorological variables, the models hit rate is increased from 0.3 to 0.7, while keeping the false alarm rate constant at 0.2. Accident probability has a non-linear relationship with precipitation. Given an hourly precipitation sum of 1 mm, accident probabilities are about 5 times larger at negative temperatures compared to positive temperatures. Based on ensemble weather forecasts skilful predictions of accident probabilities of up to 21 hours are possible; the loss of skill compared to a model using radar and reanalysis data is negligible. The findings are relevant in the context of impact based warnings for both road users, road maintenance and traffic management authorities, as well as rescue forces.

Nico Becker et al.

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Nico Becker et al.

Nico Becker et al.

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Latest update: 29 Sep 2020
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Short summary
A set of models is developed to forecast hourly probabilities of weather-related road accidents in Germany on the spatial scale of administrative districts. If information about precipitation and temperature is provided to the model, it produces the best results. Based on weather forecasts we show that skilful predictions of accident probabilities of up to 21 hours are possible. The findings are relevant in the context of impact based warnings for road users and authorities.
A set of models is developed to forecast hourly probabilities of weather-related road accidents...
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