Articles | Volume 16, issue 11
https://doi.org/10.5194/nhess-16-2391-2016
https://doi.org/10.5194/nhess-16-2391-2016
Research article
 | 
21 Nov 2016
Research article |  | 21 Nov 2016

An analysis of uncertainties and skill in forecasts of winter storm losses

Tobias Pardowitz, Robert Osinski, Tim Kruschke, and Uwe Ulbrich

Related authors

A statistical model to estimate the local vulnerability to severe weather
Tobias Pardowitz
Nat. Hazards Earth Syst. Sci., 18, 1617–1631, https://doi.org/10.5194/nhess-18-1617-2018,https://doi.org/10.5194/nhess-18-1617-2018, 2018
Short summary

Related subject area

Atmospheric, Meteorological and Climatological Hazards
The risk of synoptic-scale Arctic cyclones to shipping
Alexander Frank Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Nat. Hazards Earth Syst. Sci., 24, 2115–2132, https://doi.org/10.5194/nhess-24-2115-2024,https://doi.org/10.5194/nhess-24-2115-2024, 2024
Short summary
Estimation of future rainfall extreme values by temperature-dependent disaggregation of climate model data
Niklas Ebers, Kai Schröter, and Hannes Müller-Thomy
Nat. Hazards Earth Syst. Sci., 24, 2025–2043, https://doi.org/10.5194/nhess-24-2025-2024,https://doi.org/10.5194/nhess-24-2025-2024, 2024
Short summary
Climatic characteristics of the Jianghuai cyclone and its linkage with precipitation during the Meiyu period from 1961 to 2020
Ran Zhu and Lei Chen
Nat. Hazards Earth Syst. Sci., 24, 1937–1950, https://doi.org/10.5194/nhess-24-1937-2024,https://doi.org/10.5194/nhess-24-1937-2024, 2024
Short summary
Application of the teaching–learning-based optimization algorithm to an analytical model of thunderstorm outflows to analyze the variability of the downburst kinematic and geometric parameters
Andi Xhelaj and Massimiliano Burlando
Nat. Hazards Earth Syst. Sci., 24, 1657–1679, https://doi.org/10.5194/nhess-24-1657-2024,https://doi.org/10.5194/nhess-24-1657-2024, 2024
Short summary
Projections and uncertainties of winter windstorm damage in Europe in a changing climate
Luca G. Severino, Chahan M. Kropf, Hilla Afargan-Gerstman, Christopher Fairless, Andries Jan de Vries, Daniela I. V. Domeisen, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 1555–1578, https://doi.org/10.5194/nhess-24-1555-2024,https://doi.org/10.5194/nhess-24-1555-2024, 2024
Short summary

Cited articles

Bröcker, J. and Smith, L.: From ensemble forecasts to predictive distribution functions, Tellus A, 60, 663–678, https://doi.org/10.1111/j.1600-0870.2008.00333.x, 2008.
Buizza, R., Miller, M., and Palmer, T. N.: Stochastic representation of model uncertainties in the ECMWF ensemble prediction system, Q. J. Roy. Meteorol. Soc., 125, 2887–2908, https://doi.org/10.1002/qj.49712556006, 1999.
Doms, G.: A Description of the Nonhydrostatic Regional COSMO-Model – Part I: Dynamics and Numerics Consortium for Small-Scale Modelling, Deutscher Wetterdienst, Offenbach, Germany, 2011.
Donat, M. G., Pardowitz, T., Leckebusch, G. C., Ulbrich, U., and Burghoff, O.: High-resolution refinement of a storm loss model and estimation of return periods of loss-intensive storms over Germany, Nat. Hazards Earth Syst. Sci., 11, 2821–2833, https://doi.org/10.5194/nhess-11-2821-2011, 2011.
ECMWF: Operational archive for the Ensemble prediction system, available at: http://apps.ecmwf.int/archive-catalogue/?class=od&stream=enfo&expver=1 (last access: 1 April 2016), 2016.
Download
Short summary
This paper describes an approach to derive probabilistic predictions of local winter storm damage occurrences. Such predictions are subject to large uncertainty due to meteorological forecast uncertainty and uncertainties in modelling weather impacts. The paper aims to quantify these uncertainties and demonstrate that valuable predictions can be made on the district level several days ahead.
Altmetrics
Final-revised paper
Preprint