A novel statistically-based approach to regionalize extreme precipitation events using temperature data

Melanie Meis (), Mariela Sued, Ramiro I. Saurral and Patricia Menéndez
Additional contact information
Melanie Meis: Universidad de Buenos Aires
Mariela Sued: Universidad de Buenos Aires
Ramiro I. Saurral: Universidad de Buenos Aires
Patricia Menéndez: The University of Melbourne

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 15, No 42, 14785-14807

Abstract: Abstract Extreme precipitation events have been increasing and intensifying over the past few decades, posing challenges for modeling and prediction, as well as for policy and decision making. While traditional approaches often focus solely on studying the precipitation process, recent studies advocate for considering multiple processes and variables to better understand the drivers and anomalies of precipitation. This is especially underexplored in South America. To address this, we propose a novel approach that combines time series modeling and quantile regression to estimate the extreme quantiles of precipitation based on maximum daily temperatures. This methodology helps in understanding the relationships between these processes and contributes to identifying gauge stations with coherent climatic covariability, offering valuable insights into the regionalization of extreme events.

Keywords: Climate; Statistical modelling for extreme events; Bivariate relationship; Covariability (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-024-06805-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:120:y:2024:i:15:d:10.1007_s11069-024-06805-9

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-024-06805-9

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().