Articles | Volume 21, issue 12
https://doi.org/10.5194/hess-21-6501-2017
https://doi.org/10.5194/hess-21-6501-2017
Research article
 | 
20 Dec 2017
Research article |  | 20 Dec 2017

Precipitation extremes on multiple timescales – Bartlett–Lewis rectangular pulse model and intensity–duration–frequency curves

Christoph Ritschel, Uwe Ulbrich, Peter Névir, and Henning W. Rust

Related authors

Temporal dynamic vulnerability – impact of antecedent events on residential building losses to wind storm events in Germany
Andreas Trojand, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 25, 2331–2350, https://doi.org/10.5194/nhess-25-2331-2025,https://doi.org/10.5194/nhess-25-2331-2025, 2025
Short summary
Tree fall along railway lines: modelling the impact of wind and other meteorological factors
Rike Lorenz, Nico Becker, Barry Gardiner, Uwe Ulbrich, Marc Hanewinkel, and Benjamin Schmitz
Nat. Hazards Earth Syst. Sci., 25, 2179–2196, https://doi.org/10.5194/nhess-25-2179-2025,https://doi.org/10.5194/nhess-25-2179-2025, 2025
Short summary
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025,https://doi.org/10.5194/hess-29-1637-2025, 2025
Short summary
Extreme precipitation and flooding in Berlin under climate change and effects of selected grey and blue-green measures
Franziska Tügel, Katrin M. Nissen, Lennart Steffen, Yangwei Zhang, Uwe Ulbrich, and Reinhard Hinkelmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-445,https://doi.org/10.5194/egusphere-2025-445, 2025
Short summary
Decomposition of skill scores for conditional verification: impact of Atlantic Multidecadal Oscillation phases on the predictability of decadal temperature forecasts
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025,https://doi.org/10.5194/gmd-18-361-2025, 2025
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Stochastic approaches
Probabilistic Analysis of Future Drought Propagation, Persistence, and Spatial Concurrence in Monsoon-Dominant Asian Region under Climate Change
Dineshkumar Muthuvel and Xiaosheng Qin
EGUsphere, https://doi.org/10.5194/egusphere-2025-522,https://doi.org/10.5194/egusphere-2025-522, 2025
Short summary
Statistical estimation of probable maximum precipitation
Anne Martin, Elyse Fournier, and Jonathan Jalbert
EGUsphere, https://doi.org/10.5194/egusphere-2024-2594,https://doi.org/10.5194/egusphere-2024-2594, 2024
Short summary
Scientific logic and spatio-temporal dependence in analyzing extreme-precipitation frequency: negligible or neglected?
Francesco Serinaldi
Hydrol. Earth Syst. Sci., 28, 3191–3218, https://doi.org/10.5194/hess-28-3191-2024,https://doi.org/10.5194/hess-28-3191-2024, 2024
Short summary
Infilling of Missing Rainfall Radar Data with a Memory-Assisted Deep Learning Approach
Johannes Meuer, Laurens M. Bouwer, Frank Kaspar, Roman Lehmann, Wolfgang Karl, Thomas Ludwig, and Christopher Kadow
EGUsphere, https://doi.org/10.5194/egusphere-2024-1392,https://doi.org/10.5194/egusphere-2024-1392, 2024
Short summary
Estimation of radar-based Area-Depth-Duration-Frequency curves with special focus on spatial sampling problems
Golbarg Goshtasbpour and Uwe Haberlandt
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-177,https://doi.org/10.5194/hess-2024-177, 2024
Revised manuscript accepted for HESS
Short summary

Cited articles

Austin, P. and Houze, R.: Analysis of the structure of precipitation patterns in New England, J. Appl. Meteorol., 11, 926–935, 1972.
Bernard, M.: Formulas for rainfall intensities of long duration, T. Am. Soc. Civ. Eng., 96, 592–606, 1932.
Broyden, C.: The convergence of a class of double-rank minimization algorithms, J. I. Math. Appl., 6, 76–90, 1970.
Cameron, D., Beven, K., and Naden, P.: Flood frequency estimation by continuous simulation under climate change (with uncertainty), Hydrol. Earth Syst. Sci., 4, 393–405, https://doi.org/10.5194/hess-4-393-2000, 2000.
Cheng, L. and AghaKouchak, A.: Nonstationary precipitation Intensity-Duration-Frequency curves for infrastructure design in a changing climate, Sci. Rep.-UK, 4, 7093–7093, 2013.
Download
Short summary
A stochastic model for precipitation is used to simulate an observed precipitation series; it is compared to the original series in terms of intensity–duration frequency curves. Basis for the latter curves is a parametric model for the duration dependence of the underlying extreme value model allowing a consistent estimation of one single duration-dependent distribution using all duration series simultaneously. The stochastic model reproduces the curves except for very rare extreme events.
Share