Articles | Volume 17, issue 7
https://doi.org/10.5194/nhess-17-993-2017
https://doi.org/10.5194/nhess-17-993-2017
Research article
 | 
03 Jul 2017
Research article |  | 03 Jul 2017

Simple and approximate estimations of future precipitation return values

Rasmus E. Benestad, Kajsa M. Parding, Abdelkader Mezghani, and Anita V. Dyrrdal

Related authors

Downscaling the probability of heavy rainfall over the Nordic countries
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1463,https://doi.org/10.5194/egusphere-2024-1463, 2024
Short summary
Various ways of using empirical orthogonal functions for climate model evaluation
Rasmus E. Benestad, Abdelkader Mezghani, Julia Lutz, Andreas Dobler, Kajsa M. Parding, and Oskar A. Landgren
Geosci. Model Dev., 16, 2899–2913, https://doi.org/10.5194/gmd-16-2899-2023,https://doi.org/10.5194/gmd-16-2899-2023, 2023
Short summary
A Norwegian Approach to Downscaling
Rasmus E. Benestad
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-176,https://doi.org/10.5194/gmd-2021-176, 2021
Revised manuscript not accepted
Short summary
Downscaling probability of long heatwaves based on seasonal mean daily maximum temperatures
Rasmus E. Benestad, Bob van Oort, Flavio Justino, Frode Stordal, Kajsa M. Parding, Abdelkader Mezghani, Helene B. Erlandsen, Jana Sillmann, and Milton E. Pereira-Flores
Adv. Stat. Clim. Meteorol. Oceanogr., 4, 37–52, https://doi.org/10.5194/ascmo-4-37-2018,https://doi.org/10.5194/ascmo-4-37-2018, 2018
Short summary
The use of regression for assessing a seasonal forecast model experiment
Rasmus E. Benestad, Retish Senan, and Yvan Orsolini
Earth Syst. Dynam., 7, 851–861, https://doi.org/10.5194/esd-7-851-2016,https://doi.org/10.5194/esd-7-851-2016, 2016
Short summary

Related subject area

Atmospheric, Meteorological and Climatological Hazards
GTDI: a game-theory-based integrated drought index implying hazard-causing and hazard-bearing impact change
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci., 24, 3479–3495, https://doi.org/10.5194/nhess-24-3479-2024,https://doi.org/10.5194/nhess-24-3479-2024, 2024
Short summary
Insurance loss model vs. meteorological loss index – how comparable are their loss estimates for European windstorms?
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 24, 3445–3460, https://doi.org/10.5194/nhess-24-3445-2024,https://doi.org/10.5194/nhess-24-3445-2024, 2024
Short summary
Intense rains in Israel associated with the train effect
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci., 24, 3267–3277, https://doi.org/10.5194/nhess-24-3267-2024,https://doi.org/10.5194/nhess-24-3267-2024, 2024
Short summary
Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024,https://doi.org/10.5194/nhess-24-3225-2024, 2024
Short summary
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

Cited articles

Arkin, P. A., Joyce, R., and Janowiak, J. E.: The estimation of global monthly mean rainfall using infrared satellite data: The GOES precipitation index (GPI), Remote Sensing Reviews, 11, 107–124, https://doi.org/10.1080/02757259409532261, 1994.
Benestad, R.: Novel Methods for Inferring Future Changes in Extreme Rainfall over Northern Europe, Clim. Res., 34, 195–210, 2007.
Benestad, R. E.: Association between trends in daily rainfall percentiles and the global mean temperature, J. Geophys. Res.-Atmos., 118, 10802–10810, https://doi.org/10.1002/jgrd.50814, 2013.
Benestad, R. E.: A Mental Picture of the Greenhouse Effect: A Pedagogic Explanation, Theor. Appl. Climatol., 128, 679–688, https://doi.org/10.1007/s00704-016-1732-y, 2016.
Benestad, R. E.: Simple and approximate estimation of future precipitation return-values, https://doi.org/10.6084/m9.figshare.5047789.v1, 2017.
Download
Short summary
We propose a strategy for quantifying the maximum effect a temperature change has on heavy precipitation amounts, making use of the limited available sources of information: laws of physics, seasonal variations, mathematical estimation of probability, and s large number of climate model results. An upper bound is estimated rather than the most likely value.
Altmetrics
Final-revised paper
Preprint