BURGER - A bottom-up regionalization approach for global sub-daily intensity-duration-frequency data
Authors/Creators
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Hoch, Jannis
(Project leader)1
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Probyn, Izzy
(Project member)1
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Marra, Francesco
(Researcher)2
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Lucas, Chris
(Project member)3
- Bates, Joe (Data collector)1
- Cooper, Anthony (Project member)1
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Prof. Dr. Hayley J. Fowler
(Researcher)
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Hatchard, Simbidzayi
(Project member)4
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Lewis, Elizabeth
(Researcher)5
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Savage, James
(Project member)1
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Addor, Nans
(Project member)1, 6
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Sampson, Christopher
(Sponsor)1
- 1. Fathom
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2.
University of Padua
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3.
Fathom (United Kingdom)
- 4. Fathom Global
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5.
University of Manchester
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6.
University of Exeter
Description
Description
Intensity-duration-frequency (IDF) curves require accurate observations which are not available everywhere. To provide globally consistent IDF maps, we harness the accuracy of Global Sub-Daily Rainfall (GSDR) gauge observations and combine this with the power of a random forest regression model to regionalise the parameters of a the SMEV (Simplified Metastatistical Extreme Value) distribution. After regionalisation, it is possible to compute intensities for any combination of return period and durations up to 24 hours. These regionalised intensities are named BURGER, the ”Bottom Up Regionalised Global Extreme Rainfall dataset”.
The BURGER dataset here provided contains rainfall intensities [mm/hr] for selected return periods ranging from 2 to 10,000 years and durations 1, 3, 6, 12, and 24 hours. The spatial resolution is 0.1 degree. The horizontal reference system is WGS84 (EPSG 4326).
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Additional details
Related works
- Is described by
- Publication: 10.1029/2024WR039773 (DOI)
Software
- Development Status
- Active