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  5. Role of large-scale climate oscillations in precipitation extremes associated with atmospheric rivers: nonstationary framework

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Article
English
2023

Role of large-scale climate oscillations in precipitation extremes associated with atmospheric rivers: nonstationary framework

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English
2023
Hydrological Sciences Journal
Vol 68 (3)
DOI: 10.1080/02626667.2022.2159412

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Manish Kumar Goyal
Manish Kumar Goyal

Indian Institute Of Technology Indorethe Institution

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Shivam Singh
Manish Kumar Goyal
Srinidhi Jha

Abstract

Atmospheric rivers (ARs) are filamentary regions of high-water vapour flux in the lower troposphere that contribute significantly to poleward moisture movement in mid-latitude regions. Key characteristics (frequency, duration, and intensity) of ARs have been explored to recognize the regions vulnerable to AR-flood. To investigate the association of ARs with large-scale climate oscillations (LSCOs), precipitation extremes (PEs) maximum 1-day precipitation (Rx1day), maximum consecutive 5-day precipitation (Rx5day), precipitation amount from very wet days (R95pTOT) are explored in a non-stationary framework of generalized extreme value distribution, taking the Arctic Oscillation, North Atlantic Oscillation, El Niño Southern Oscillation, and Pacific Decadal Oscillation (PDO) as covariates. In almost 30% of regions around the globe, May-June-July-August-September (MJJAS) season PDO was found to be the relatively most influential covariate for capturing PEs. The west coast of North America and of Europe, southernmost South America, central East Asia, New Zealand, and Australia have been identified as the most critical regions associated with AR linked with PE-associated LSCOs.

How to cite this publication

Shivam Singh, Manish Kumar Goyal, Srinidhi Jha (2023). Role of large-scale climate oscillations in precipitation extremes associated with atmospheric rivers: nonstationary framework. Hydrological Sciences Journal, 68(3), pp. 395-411, DOI: 10.1080/02626667.2022.2159412.

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Publication Details

Type

Article

Year

2023

Authors

3

Datasets

0

Total Files

0

Language

English

Journal

Hydrological Sciences Journal

DOI

10.1080/02626667.2022.2159412

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