Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 2.883 IF 2.883
  • IF 5-year value: 3.321 IF 5-year
    3.321
  • CiteScore value: 3.07 CiteScore
    3.07
  • SNIP value: 1.336 SNIP 1.336
  • IPP value: 2.80 IPP 2.80
  • SJR value: 1.024 SJR 1.024
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 81 Scimago H
    index 81
  • h5-index value: 43 h5-index 43
Discussion papers
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.

Submitted as: research article 09 Mar 2020

Submitted as: research article | 09 Mar 2020

Review status
This preprint is currently under review for the journal NHESS.

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.

Interactive discussion

Status: open (until 07 May 2020)
Status: open (until 07 May 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Nico Becker et al.

Nico Becker et al.

Viewed

Total article views: 147 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
119 27 1 147 0 1
  • HTML: 119
  • PDF: 27
  • XML: 1
  • Total: 147
  • BibTeX: 0
  • EndNote: 1
Views and downloads (calculated since 09 Mar 2020)
Cumulative views and downloads (calculated since 09 Mar 2020)

Viewed (geographical distribution)

Total article views: 106 (including HTML, PDF, and XML) Thereof 104 with geography defined and 2 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 05 Apr 2020
Publications Copernicus
Download
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...
Citation