Articles | Volume 15, issue 8
https://doi.org/10.5194/nhess-15-1757-2015
https://doi.org/10.5194/nhess-15-1757-2015
Brief communication
 | 
11 Aug 2015
Brief communication |  | 11 Aug 2015

Statistical detection and modeling of the over-dispersion of winter storm occurrence

M. Raschke

Related authors

About the return period of a catastrophe
Mathias Raschke
Nat. Hazards Earth Syst. Sci., 22, 245–263, https://doi.org/10.5194/nhess-22-245-2022,https://doi.org/10.5194/nhess-22-245-2022, 2022
Short summary

Related subject area

Atmospheric, Meteorological and Climatological Hazards
On the potential of using smartphone sensors for wildfire hazard estimation through citizen science
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024,https://doi.org/10.5194/nhess-24-3035-2024, 2024
Short summary
Global estimates of 100-year return values of daily precipitation from ensemble weather prediction data
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024,https://doi.org/10.5194/nhess-24-2939-2024, 2024
Short summary
Exploring the sensitivity of extreme event attribution of two recent extreme weather events in Sweden using long-running meteorological observations
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024,https://doi.org/10.5194/nhess-24-2875-2024, 2024
Short summary
Probabilistic short-range forecasts of high-precipitation events: optimal decision thresholds and predictability limits
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024,https://doi.org/10.5194/nhess-24-2793-2024, 2024
Short summary
Surprise floods: the role of our imagination in preparing for disasters
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024,https://doi.org/10.5194/nhess-24-2633-2024, 2024
Short summary

Cited articles

Claeskens, G. and Hjort, N. L.: Model selection and model averaging, in: Cambridge Series in Statistical and Probabilistic Mathematics, Cambridge University Press, Cambridge, 2008.
Coles, S.: An introduction to statistical modeling of extreme values, Springer, London, 2001.
Consul, P. C. and Jain, G. C.: A generalization of the Poisson distribution, Technometrics, 15, 791–799, 1973.
Consul, P. C. and Shoukri, M. M.: Maximum likelihood estimation for the generalized Poisson distribution, Commun. Stat. Theory Meth., 10, 977–991, 1984.
Fahrmeir, L., Kneib, T., Lang, S., and Marx, B.: Regression – models, methods and applications, Springer, Heidelberg, Germany, 2013.
Download
Short summary
Here, I discuss and improve the detection and modeling of the over-dispersion of winter storm occurrence using the example of Germany. For this purpose, the generalized Poisson distribution and criteria for the model selection are introduced. Correct statistical model selection ensures the statistical significance of the model, including an over-dispersion. The relation between expectation and variance of a thinned inhomogeneous Poisson process is derived. This is also applied to data.
Altmetrics
Final-revised paper
Preprint