Evaluating Atmospheric River Impacts on Energy and Moisture Transport in the Arctic Using Different Detection Algorithms

Zhang, Chen, Cassano, John J., Seefeldt, Mark W., Tung, Wen-wen, Mahesh, Ankur and Collins, William D. ORCID: https://orcid.org/0000-0002-4463-9848 (2026) Evaluating Atmospheric River Impacts on Energy and Moisture Transport in the Arctic Using Different Detection Algorithms. Journal of Geophysical Research: Atmospheres, 131 (4). ISSN 2169-897X

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Abstract

Atmospheric rivers (ARs) significantly impact the Arctic climate system by enhancing atmospheric heat and moisture transport and altering the local energy budget. Developing AR detection tools (ARDTs) is critical yet challenging. This study evaluates 12 ARDTs in the Arctic to assess their performance in representing atmospheric heat (represented by moist static energy) and moisture transport, as well as surface downward longwave radiation (LWD) and precipitation impacts, spanning 2000 to 2019 using ERA5 reanalysis. We find that AR occurrence frequency in the Arctic varies widely, from less than 1% to over 13%, depending on the ARDT. This variability leads to differences in contributions to poleward atmospheric heat (<1%–33%) and moisture (<1%–49%) transport. The highest AR frequency, and corresponding contributions to atmospheric heat and moisture transport, occurs over the Atlantic sector during non-summer seasons for most ARDTs. This region aligns with the primary poleward moisture pathway and the end of climatological mid-latitude storm tracks, highlighting strong connections between Arctic ARs and mid-latitude cyclones. ARs induce significant LWD anomalies, largest in winter, smallest in summer, and also substantially contribute to the seasonal precipitation. Global ARDTs detect fewer ARs with larger anomalies (>100 W m−2 in higher Arctic), but contribute <1% to seasonal climatological LWD and precipitation. In contrast, polar-specific ARDTs detect higher AR occurrences and account for up to 16% of seasonal LWD and 41% precipitation. This suggests that algorithms emphasizing extreme events with large anomalies do not necessarily indicate a large climate radiative and precipitation impact.

Item Type: Article
Additional Information: Publisher Copyright: © 2026. The Author(s).
Uncontrolled Keywords: arctic climate,arctic surface energy budgets,atmospheric river,atmospheric river detection tools (ardt),moisture static energy,poleward moisture transport,geophysics,atmospheric science,space and planetary science,earth and planetary sciences (miscellaneous),sdg 13 - climate action ,/dk/atira/pure/subjectarea/asjc/1900/1908
Faculty \ School: Faculty of Science > School of Environmental Sciences
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Depositing User: LivePure Connector
Date Deposited: 08 Jul 2026 13:44
Last Modified: 12 Jul 2026 23:02
URI: https://ueaeprints.uea.ac.uk/id/eprint/103788
DOI: 10.1029/2025JD043335

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