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:
-
[1];
[1];
[2];
[1];
[1];
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ocean University of China, Qingdao (China)
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
- 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:
- 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. https://doi.org/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. https://doi.org/10.1029/2018GL079831. https://www.osti.gov/servlets/purl/1489284.
@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},
number = 21,
volume = 45,
place = {United States},
year = {Wed Oct 24 00:00:00 EDT 2018},
month = {Wed Oct 24 00:00:00 EDT 2018}
}
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Figures / Tables:
Figure 1: AR-IDA calculation. This figure shows the integral at a given time step t. The red contour shows the spatial extent of the AR event at time t, and the colored grids show the IVT values of the AR over land. At each time step t, we integrate themore »
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