Articles | Volume 26, issue 21
https://doi.org/10.5194/hess-26-5685-2022
https://doi.org/10.5194/hess-26-5685-2022
Technical note
 | 
11 Nov 2022
Technical note |  | 11 Nov 2022

Technical note: Modeling spatial fields of extreme precipitation – a hierarchical Bayesian approach

Bianca Rahill-Marier, Naresh Devineni, and Upmanu Lall

Viewed

Total article views: 2,168 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,528 557 83 2,168 49 59
  • HTML: 1,528
  • PDF: 557
  • XML: 83
  • Total: 2,168
  • BibTeX: 49
  • EndNote: 59
Views and downloads (calculated since 22 Mar 2022)
Cumulative views and downloads (calculated since 22 Mar 2022)

Viewed (geographical distribution)

Total article views: 2,168 (including HTML, PDF, and XML) Thereof 2,069 with geography defined and 99 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 01 Apr 2025
Download
Short summary
We present a new approach to modeling extreme regional rainfall by considering the spatial structure of extreme events. The developed models allow a probabilistic exploration of how the regional drainage network may respond to extreme rainfall events and provide a foundation for how future risks may be better estimated.
Share