The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/21293760

Gruendemann, Gaby; Zorzetto, Enrico; Beck, Hylke; Schleiss, Marc; Nick van de Giesen et. al. (2023): Scripts for creating the figures of "Extreme precipitation return levels for multiple durations on a global scale". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21293760.v1

Dataset

• Civil Engineering
• Natural Hazards
• Environmental Engineering
• Atmosphere and Weather
• Other Earth Sciences
• Earth Sciences
• Engineering
• Environment

GPEX dataset, journal of hydrology, python scripts

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Gaby Gründemann , Enrico Zorzetto, Hylke Beck, Marc Schleiss, Nick van de Giesen, Marco Marani, Ruud van der Ent

This contains the python scripts in order to recreate the figures of the manuscript: Gründemann, G. J., Zorzetto, E., Beck, H. E., Schleiss, M., Van de Giesen, N., Marani, M., & van der Ent, R. J. (2023). Extreme precipitation return levels for multiple durations on a global scale. Journal of Hydrology, 621, 129558.

• 2023-05-22 first online, published, posted

4TU.ResearchData

python script

Extreme precipitation return levels for multiple durations on a global scale

https://doi.org/10.4121/12764429

• Transforming Weather Water data into value-added Information services for sustainable Growth in Africa (grant code 776691) [more info...] European Commission
• European Climate Prediction system (grant code 776613) [more info...] European Commission
• Unravelling the moisture sources in precipitation extremes worldwide (grant code 016.Veni.181.015) [more info...] Dutch Research Council

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Water Management;
Centre for Hydrology, University of Saskatchewan, Canada;
Program in Atmospheric and Oceanic Sciences, Princeton University, USA;
King Abdullah University of Science and Technology (KAUST), Saudi Arabia;
TU Delft, Faculty of Civil Engineering and Geosciences, Department of Geoscience and Remote Sensing;
Dipartimento di Ingegneria Civile, Edile ed Ambientale, Universita’ degli Studi di Padova, Italy;
Water Research Centre, School of Civil and Environmental Engineering, University of New South Wales, Sydney, Australia