Articles | Volume 24, issue 6
https://doi.org/10.5194/nhess-24-1929-2024
https://doi.org/10.5194/nhess-24-1929-2024
Brief communication
 | 
11 Jun 2024
Brief communication |  | 11 Jun 2024

Brief communication: SWM – stochastic weather model for precipitation-related hazard assessments using ERA5-Land data

Melody Gwyneth Whitehead and Mark Stephen Bebbington

Related subject area

Hydrological Hazards
Text mining uncovers the unique dynamics of socio-economic impacts of the 2018–2022 multi-year drought in Germany
Jan Sodoge, Christian Kuhlicke, Miguel D. Mahecha, and Mariana Madruga de Brito
Nat. Hazards Earth Syst. Sci., 24, 1757–1777, https://doi.org/10.5194/nhess-24-1757-2024,https://doi.org/10.5194/nhess-24-1757-2024, 2024
Short summary
The value of multi-source data for improved flood damage modelling with explicit input data uncertainty treatment: INSYDE 2.0
Mario Di Bacco, Daniela Molinari, and Anna Rita Scorzini
Nat. Hazards Earth Syst. Sci., 24, 1681–1696, https://doi.org/10.5194/nhess-24-1681-2024,https://doi.org/10.5194/nhess-24-1681-2024, 2024
Short summary
Limited effect of the confluence angle and tributary gradient on Alpine confluence morphodynamics under intense sediment loads
Théo St. Pierre Ostrander, Thomé Kraus, Bruno Mazzorana, Johannes Holzner, Andrea Andreoli, Francesco Comiti, and Bernhard Gems
Nat. Hazards Earth Syst. Sci., 24, 1607–1634, https://doi.org/10.5194/nhess-24-1607-2024,https://doi.org/10.5194/nhess-24-1607-2024, 2024
Short summary
Does a convection-permitting regional climate model bring new perspectives on the projection of Mediterranean floods?
Nils Poncet, Philippe Lucas-Picher, Yves Tramblay, Guillaume Thirel, Humberto Vergara, Jonathan Gourley, and Antoinette Alias
Nat. Hazards Earth Syst. Sci., 24, 1163–1183, https://doi.org/10.5194/nhess-24-1163-2024,https://doi.org/10.5194/nhess-24-1163-2024, 2024
Short summary
Added value of seasonal hindcasts to create UK hydrological drought storylines
Wilson C. H. Chan, Nigel W. Arnell, Geoff Darch, Katie Facer-Childs, Theodore G. Shepherd, and Maliko Tanguy
Nat. Hazards Earth Syst. Sci., 24, 1065–1078, https://doi.org/10.5194/nhess-24-1065-2024,https://doi.org/10.5194/nhess-24-1065-2024, 2024
Short summary

Cited articles

Arnaud, P., Bouvier, C., Cisneros, L., and Dominguez, R.: Influence of rainfall spatial variability on flood prediction, J. Hydrol., 260, 216–230, https://doi.org/10.1016/S0022-1694(01)00611-4, 2002. 
Burton, A., Kilsby, C., Fowler, H., Cowpertwait, P., and O'Connell, P.: RainSim: A spatial–temporal stochastic rainfall modelling system, Environ. Modell. Softw., 23, 1356–1369, https://doi.org/10.1016/j.envsoft.2008.04.003, 2008. 
Chappell, P. R.: The climate and weather of Bay of Plenty, 3rd edn., NIWA Science and Technology Series, Number 62, https://niwa.co.nz/static/BOP ClimateWEB.pdf (last access: 23 August 2023), 2013. 
DiCiccio, T. and Efron, B.: Bootstrap Confidence Intervals, Stat. Sci., 11, 189–212, https://www.jstor.org/stable/2246110 (last access: 5 June 2024), 1996. 
Fox, J. and Weisberg, S.: An R Companion to Applied Regression, 3rd edn., Sage Publications, Thousand Oaks CA, USA, 576 pp., https://socialsciences.mcmaster.ca/jfox/Books/Companion/ (last access: 5 June 2024), 2019. 
Download
Short summary
Precipitation-driven hazards including floods, landslides, and lahars can be catastrophic and difficult to forecast due to high uncertainty around future weather patterns. This work presents a stochastic weather model that produces statistically similar (realistic) rainfall over long time periods at minimal computational cost. These data provide much-needed inputs for hazard simulations to support long-term, time and spatially varying risk assessments.
Altmetrics
Final-revised paper
Preprint