The DOI displayed 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

Version 2 - 2023-11-22 Version 1 - 2023-07-03

Usage statistics

Categories

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

Keywords

climate change extreme precipitation global domain reanalysis relative entropy seasonality

Geolocation

Time coverage

1959-2021

Licence

CC BY 4.0

Interoperability

• RO-Crate Metadata

Export as...

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

History

• 2023-07-03 first online

• 2023-11-23 published, posted

Publisher

4TU.ResearchData

Format

netcdf, python

Derived from

• ERA5 reanalysis dataset

Funding

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

Organizations

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