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

Journal metrics

IF value: 3.102
IF3.102
IF 5-year value: 3.284
IF 5-year
3.284
CiteScore value: 5.1
CiteScore
5.1
SNIP value: 1.37
SNIP1.37
IPP value: 3.21
IPP3.21
SJR value: 1.005
SJR1.005
Scimago H <br class='widget-line-break'>index value: 90
Scimago H
index
90
h5-index value: 42
h5-index42
NHESS | Articles | Volume 20, issue 10
Nat. Hazards Earth Syst. Sci., 20, 2857–2871, 2020
https://doi.org/10.5194/nhess-20-2857-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Nat. Hazards Earth Syst. Sci., 20, 2857–2871, 2020
https://doi.org/10.5194/nhess-20-2857-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 29 Oct 2020

Research article | 29 Oct 2020

Predictive modeling of hourly probabilities for weather-related road accidents

Nico Becker et al.

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (26 Jun 2020) by Joaquim G. Pinto
AR by Nico Becker on behalf of the Authors (31 Jul 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (08 Aug 2020) by Joaquim G. Pinto
RR by Anonymous Referee #1 (10 Aug 2020)
RR by Anonymous Referee #3 (12 Aug 2020)
ED: Publish subject to technical corrections (09 Sep 2020) by Joaquim G. Pinto
AR by Nico Becker on behalf of the Authors (10 Sep 2020)  Author's response    Manuscript
Publications Copernicus
Download
Short summary
A set of models is developed to forecast hourly probabilities of weather-related road accidents in Germany at the spatial scale of administrative districts. Model verification shows that using precipitation and temperature data leads to the best accident forecasts. Based on weather forecast data we show that skilful predictions of accident probabilities of up to 21 h ahead are possible. The models can be used to issue impact-based warnings, which are relevant for road users and authorities.
A set of models is developed to forecast hourly probabilities of weather-related road accidents...
Citation
Altmetrics
Final-revised paper
Preprint