The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation.

Temporally clustered precipitation extremes can have catastrophic impacts. Therefore, understanding their drivers is paramount for risk assessment in current and future climates. Here, we model for each season 3-week extreme precipitation event counts with Poisson Generalized Linear Models and nine...

Full description

Bibliographic Details
Published in:iScience
Main Authors: Tuel, Alexandre, Martius, Olivia
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2022
Subjects:
Online Access:https://boris.unibe.ch/166033/1/1-s2.0-S2589004222001250-main.pdf
https://boris.unibe.ch/166033/
id ftunivbern:oai:boris.unibe.ch:166033
record_format openpolar
spelling ftunivbern:oai:boris.unibe.ch:166033 2023-08-20T04:06:55+02:00 The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation. Tuel, Alexandre Martius, Olivia 2022-03-18 application/pdf https://boris.unibe.ch/166033/1/1-s2.0-S2589004222001250-main.pdf https://boris.unibe.ch/166033/ eng eng Elsevier https://boris.unibe.ch/166033/ info:eu-repo/semantics/openAccess Tuel, Alexandre; Martius, Olivia (2022). The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation. iScience, 25(3), p. 103855. Elsevier 10.1016/j.isci.2022.103855 <http://dx.doi.org/10.1016/j.isci.2022.103855> 910 Geography & travel 550 Earth sciences & geology info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion PeerReviewed 2022 ftunivbern https://doi.org/10.1016/j.isci.2022.103855 2023-07-31T22:12:17Z Temporally clustered precipitation extremes can have catastrophic impacts. Therefore, understanding their drivers is paramount for risk assessment in current and future climates. Here, we model for each season 3-week extreme precipitation event counts with Poisson Generalized Linear Models and nine major modes of climate variability as covariates. Model goodness-of-fit is highest in the tropics, particularly over the equatorial Pacific, the Maritime Continent, and East Africa, where ENSO, the Indian Ocean Dipole (IOD) and the MJO are the major drivers of sub-seasonal temporal clustering of extreme precipitation. The IOD and MJO also matter over Southwest Asia during boreal fall and winter. In the Northern Hemisphere, the North Atlantic Oscillation impacts clustering west of the Iberian Peninsula and over Scandinavia and Greenland, and the Pacific North American pattern matters over the central/northern Pacific Ocean. Finally, our models show very little skill in the Southern Hemisphere, where temporal clustering is also less frequent. Article in Journal/Newspaper Greenland North Atlantic North Atlantic oscillation BORIS (Bern Open Repository and Information System, University of Bern) Greenland Indian Pacific iScience 25 3 103855
institution Open Polar
collection BORIS (Bern Open Repository and Information System, University of Bern)
op_collection_id ftunivbern
language English
topic 910 Geography & travel
550 Earth sciences & geology
spellingShingle 910 Geography & travel
550 Earth sciences & geology
Tuel, Alexandre
Martius, Olivia
The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation.
topic_facet 910 Geography & travel
550 Earth sciences & geology
description Temporally clustered precipitation extremes can have catastrophic impacts. Therefore, understanding their drivers is paramount for risk assessment in current and future climates. Here, we model for each season 3-week extreme precipitation event counts with Poisson Generalized Linear Models and nine major modes of climate variability as covariates. Model goodness-of-fit is highest in the tropics, particularly over the equatorial Pacific, the Maritime Continent, and East Africa, where ENSO, the Indian Ocean Dipole (IOD) and the MJO are the major drivers of sub-seasonal temporal clustering of extreme precipitation. The IOD and MJO also matter over Southwest Asia during boreal fall and winter. In the Northern Hemisphere, the North Atlantic Oscillation impacts clustering west of the Iberian Peninsula and over Scandinavia and Greenland, and the Pacific North American pattern matters over the central/northern Pacific Ocean. Finally, our models show very little skill in the Southern Hemisphere, where temporal clustering is also less frequent.
format Article in Journal/Newspaper
author Tuel, Alexandre
Martius, Olivia
author_facet Tuel, Alexandre
Martius, Olivia
author_sort Tuel, Alexandre
title The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation.
title_short The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation.
title_full The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation.
title_fullStr The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation.
title_full_unstemmed The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation.
title_sort influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation.
publisher Elsevier
publishDate 2022
url https://boris.unibe.ch/166033/1/1-s2.0-S2589004222001250-main.pdf
https://boris.unibe.ch/166033/
geographic Greenland
Indian
Pacific
geographic_facet Greenland
Indian
Pacific
genre Greenland
North Atlantic
North Atlantic oscillation
genre_facet Greenland
North Atlantic
North Atlantic oscillation
op_source Tuel, Alexandre; Martius, Olivia (2022). The influence of modes of climate variability on the sub-seasonal temporal clustering of extreme precipitation. iScience, 25(3), p. 103855. Elsevier 10.1016/j.isci.2022.103855 <http://dx.doi.org/10.1016/j.isci.2022.103855>
op_relation https://boris.unibe.ch/166033/
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1016/j.isci.2022.103855
container_title iScience
container_volume 25
container_issue 3
container_start_page 103855
_version_ 1774718286323253248