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/bac024f1-6c2e-4a09-bf0f-be78b6bbe21c

Gruendemann, Gaby; Zorzetto, Enrico; Nick van de Giesen; Ent, Ruud van der (2023): Scripts and data for "Historical shifts in seasonality and timing of extreme precipitation". Version 3. 4TU.ResearchData. dataset. https://doi.org/10.4121/bac024f1-6c2e-4a09-bf0f-be78b6bbe21c.v3

Dataset

x choose version: version 2 - 2023-11-22 version 1 - 2023-07-03

• Civil Engineering
• Natural Hazards
• Environmental Engineering
• Climate and Climate Change
• Atmosphere and Weather
• Engineering
• Environment

climate change, extreme precipitation, global domain, reanalysis, relative entropy, seasonality

1959-2021

CC BY 4.0

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

by Gaby Gründemann , Enrico Zorzetto, Nick van de Giesen, Ruud van der Ent

This dataset contains the python scripts and NetCDF data for the analyses and to recreate the figures of the manuscript: "Historical shifts in seasonality and timing of extreme precipitation" by Gaby Gründemann, Enrico Zorzetto, Nick van de Giesen, and Ruud van der Ent

• 2023-07-03 first online

• 2023-11-23 published, posted

4TU.ResearchData

netcdf, python

• ERA5 reanalysis dataset

• Transformative Environmental Monitoring to Boost Observations in Africa (grant code 101086209) [more info...] European Commission

Delft University of Technology, Faculty of Civil Engineering and Geosciences, Department of Water Management
University of Saskatchewan, Centre for Hydrology
Princeton University, Program in Atmospheric and Oceanic Sciences