Subseasonal-to-seasonal (S2S) prediction of atmospheric rivers in the Northern Winter

Atmospheric rivers (ARs) are characterized by intense lower tropospheric plumes of moisture transport that are frequently responsible for midlatitude wind and precipitation extremes. The prediction of ARs at subseasonal-to-seasonal (S2S) timescales is currently at a low level of skill, reflecting a need to improve our understanding of their underlying sources of predictability. Based on 20 year hindcast experiments from the Geophysical Fluid Dynamics Laboratory’s SPEAR S2S forecast system, we evaluate the S2S prediction skill of AR activities in the northern winter. Higher forecast skill is detected for high-frequency AR activities (3–7 days/week) compared to low-frequency AR activities (1–2 days/week), even though the occurrence rate of high-frequency ARs exceeds that of low-frequency ARs. For the first time, we have applied the Average Predictability Time technique to the SPEAR system to identify the three most predictable modes of AR in the North Pacific sector. These modes can be attributed to the influences of the El Niño–Southern Oscillation, the Pacific North American pattern, and the Arctic Oscillation. S2S AR forecast skill in western United States is modulated by various phases of large-scale variability. This study highlights potential windows of opportunity for operational S2S AR forecasting.

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Publication Details

Journal
npj Climate and Atmospheric Science
Published
2024-11-07
DOI
https://doi.org/10.1038/s41612-024-00827-7
Citations
4
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.13

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article

Subseasonal-to-seasonal (S2S) prediction of atmospheric rivers in the Northern Winter

Lucas Harris, Nathaniel C. Johnson, Kai‐Chih Tseng, Ben P. Kirtman et al.
4 citations
npj Climate and Atmospheric Science
Climate variability and models
1.13
article

Subseasonal-to-seasonal (S2S) prediction of atmospheric rivers in the Northern Winter

Lucas Harris, Nathaniel C. Johnson, Kai‐Chih Tseng, Ben P. Kirtman, Baoqiang Xiang, Thomas L. Delworth, Wei Zhang
article en
4 citations

Abstract

Atmospheric rivers (ARs) are characterized by intense lower tropospheric plumes of moisture transport that are frequently responsible for midlatitude wind and precipitation extremes. The prediction of ARs at subseasonal-to-seasonal (S2S) timescales is currently at a low level of skill, reflecting a need to improve our understanding of their underlying sources of predictability. Based on 20 year hindcast experiments from the Geophysical Fluid Dynamics Laboratory’s SPEAR S2S forecast system, we evaluate the S2S prediction skill of AR activities in the northern winter. Higher forecast skill is detected for high-frequency AR activities (3–7 days/week) compared to low-frequency AR activities (1–2 days/week), even though the occurrence rate of high-frequency ARs exceeds that of low-frequency ARs. For the first time, we have applied the Average Predictability Time technique to the SPEAR system to identify the three most predictable modes of AR in the North Pacific sector. These modes can be attributed to the influences of the El Niño–Southern Oscillation, the Pacific North American pattern, and the Arctic Oscillation. S2S AR forecast skill in western United States is modulated by various phases of large-scale variability. This study highlights potential windows of opportunity for operational S2S AR forecasting.

npj Climate and Atmospheric ScienceVol. 7(1)
University of Miami (US), National Taiwan University of Science and Technology (TW), Cooperative Institute for Research in Environmental Sciences (US), National Taiwan University (TW), NOAA Geophysical Fluid Dynamics Laboratory (US), Princeton University (US), University Corporation for Atmospheric Research (US), American Orchid Society (US), National Taipei University (TW)
Center for Sponsored Coastal Ocean Research
Life below water
Openalex Percentile: Top 22%
Climate variability and models
1.13
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