Articles | Volume 16, issue 11
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,,, 2018
Short summary

Related subject area

Atmospheric, Meteorological and Climatological Hazards
The climatology and nature of warm-season convective cells in cold-frontal environments over Germany
George Pacey, Stephan Pfahl, Lisa Schielicke, and Kathrin Wapler
Nat. Hazards Earth Syst. Sci., 23, 3703–3721,,, 2023
Short summary
Forecasting large hail and lightning using additive logistic regression models and the ECMWF reforecasts
Francesco Battaglioli, Pieter Groenemeijer, Ivan Tsonevsky, and Tomàš Púčik
Nat. Hazards Earth Syst. Sci., 23, 3651–3669,,, 2023
Short summary
The impact of global navigation satellite system (GNSS) zenith total delay data assimilation on the short-term precipitable water vapor and precipitation forecast over Italy using the Weather Research and Forecasting (WRF) model
Rosa Claudia Torcasio, Alessandra Mascitelli, Eugenio Realini, Stefano Barindelli, Giulio Tagliaferro, Silvia Puca, Stefano Dietrich, and Stefano Federico
Nat. Hazards Earth Syst. Sci., 23, 3319–3336,,, 2023
Short summary
Shallow and deep learning of extreme rainfall events from convective atmospheres
Gerd Bürger and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 3065–3077,,, 2023
Short summary
Linking reported drought impacts with drought indices, water scarcity and aridity: the case of Kenya
Marleen R. Lam, Alessia Matanó, Anne F. Van Loon, Rhoda A. Odongo, Aklilu D. Teklesadik, Charles N. Wamucii, Marc J. C. van den Homberg, Shamton Waruru, and Adriaan J. Teuling
Nat. Hazards Earth Syst. Sci., 23, 2915–2936,,, 2023
Short summary

Cited articles

Bröcker, J. and Smith, L.: From ensemble forecasts to predictive distribution functions, Tellus A, 60, 663–678,, 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,, 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,, 2011.
ECMWF: Operational archive for the Ensemble prediction system, available at: (last access: 1 April 2016), 2016.
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.
Final-revised paper