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Get Free AccessAtmospheric 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.
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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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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