Preprints
https://doi.org/10.5194/hess-2022-233
https://doi.org/10.5194/hess-2022-233
 
01 Jul 2022
01 Jul 2022
Status: this preprint is currently under review for the journal HESS.

A principal component based strategy for regionalisation of precipitation intensity-duration-frequency (IDF) statistics

Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz Kajsa Maria Parding et al.
  • Norwegian Meteorological Institute

Abstract. Intensity-duration-frequency (IDF) statistics describing extreme rainfall intensities in Norway were analysed with the purpose of investigating how the shape of the curves is influenced by geographical conditions and local climate characteristics. To this end, principal component analysis (PCA) was used to quantify salient information about the IDF curves and a Bayesian linear regression was used to study the dependency of the shapes on climatological and geographical information. Our analysis indicated that the shapes of IDF curves in Norway are influenced by both geographical conditions and 24-hr precipitation statistics. Based on this analysis, an empirical model was constructed to predict IDF curves in locations with insufficient sub-hourly rain gauge data and for the future using downscaled data from global climate models. Our new method was also compared with a recently proposed formula for estimating sub-daily rainfall intensity based on 24-hr rain gauge data. We found that a Bayesian inference of a PCA representation of IDF curves provides a promising strategy for estimating sub-daily return levels for rainfall.

Kajsa Maria Parding et al.

Status: open (until 26 Aug 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2022-233', Anonymous Referee #1, 12 Aug 2022 reply

Kajsa Maria Parding et al.

Kajsa Maria Parding et al.

Viewed

Total article views: 345 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
278 61 6 345 27 4 5
  • HTML: 278
  • PDF: 61
  • XML: 6
  • Total: 345
  • Supplement: 27
  • BibTeX: 4
  • EndNote: 5
Views and downloads (calculated since 01 Jul 2022)
Cumulative views and downloads (calculated since 01 Jul 2022)

Viewed (geographical distribution)

Total article views: 272 (including HTML, PDF, and XML) Thereof 272 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 12 Aug 2022
Download
Short summary
Intensity-Duration-Frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, e.g., for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.