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Title: Predictability of Extreme Precipitation in Western U.S. Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration

Abstract

In this study, we quantified the relationship between atmospheric rivers (ARs) and occurrence and magnitude of extreme precipitation in western U.S. watersheds, using AR tracking results of Atmospheric River Tracking Method Intercomparison Project and precipitation from a high-resolution regional climate simulation. Our analysis indicates that ARs have the potential of predicting extreme precipitation events at daily scale, with Gilbert Skill Score of ~0.2, and monthly extreme precipitation amount in the west coast watershed is closely related to AR intensity, with correlation coefficients of up to 0.6. The relationship between ARs and precipitation is most significant in the Pacific Northwest and California. Lastly, using K-means clustering algorithm, AR events can be classified into three categories with distinct features: weak ARs, flash ARs, and prolonged ARs. Flash ARs and prolonged ARs, though accounting for less than 50% of total AR events, are more important in controlling regional extreme precipitation patterns, and should be prioritized for future studies of hydrological extreme events.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [1];  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ocean University of China, Qingdao (China)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1489284
Alternate Identifier(s):
OSTI ID: 1481425
Report Number(s):
PNNL-SA-136740
Journal ID: ISSN 0094-8276
Grant/Contract Number:  
AC05-76RL01830; AC02‐05CH11231; AC06-76RL01830; AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Geophysical Research Letters
Additional Journal Information:
Journal Volume: 45; Journal Issue: 21; Journal ID: ISSN 0094-8276
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; precipitation; atmospheric river; extreme events; machine learning; prediction

Citation Formats

Chen, Xiaodong, Leung, L. Ruby, Gao, Yang, Liu, Ying, Wigmosta, Mark, and Richmond, Marshall. Predictability of Extreme Precipitation in Western U.S. Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration. United States: N. p., 2018. Web. doi:10.1029/2018GL079831.
Chen, Xiaodong, Leung, L. Ruby, Gao, Yang, Liu, Ying, Wigmosta, Mark, & Richmond, Marshall. Predictability of Extreme Precipitation in Western U.S. Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration. United States. doi:10.1029/2018GL079831.
Chen, Xiaodong, Leung, L. Ruby, Gao, Yang, Liu, Ying, Wigmosta, Mark, and Richmond, Marshall. Wed . "Predictability of Extreme Precipitation in Western U.S. Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration". United States. doi:10.1029/2018GL079831.
@article{osti_1489284,
title = {Predictability of Extreme Precipitation in Western U.S. Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration},
author = {Chen, Xiaodong and Leung, L. Ruby and Gao, Yang and Liu, Ying and Wigmosta, Mark and Richmond, Marshall},
abstractNote = {In this study, we quantified the relationship between atmospheric rivers (ARs) and occurrence and magnitude of extreme precipitation in western U.S. watersheds, using AR tracking results of Atmospheric River Tracking Method Intercomparison Project and precipitation from a high-resolution regional climate simulation. Our analysis indicates that ARs have the potential of predicting extreme precipitation events at daily scale, with Gilbert Skill Score of ~0.2, and monthly extreme precipitation amount in the west coast watershed is closely related to AR intensity, with correlation coefficients of up to 0.6. The relationship between ARs and precipitation is most significant in the Pacific Northwest and California. Lastly, using K-means clustering algorithm, AR events can be classified into three categories with distinct features: weak ARs, flash ARs, and prolonged ARs. Flash ARs and prolonged ARs, though accounting for less than 50% of total AR events, are more important in controlling regional extreme precipitation patterns, and should be prioritized for future studies of hydrological extreme events.},
doi = {10.1029/2018GL079831},
journal = {Geophysical Research Letters},
issn = {0094-8276},
number = 21,
volume = 45,
place = {United States},
year = {2018},
month = {10}
}

Journal Article:
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