Co‐Occurring Atmospheric Features and Their Contributions to Precipitation Extremes

Abstract Object‐based identification algorithms for atmospheric features are commonly utilized to attribute global precipitation. This study employs a systematic approach to examine feature co‐occurrences and their relationships to mean and extreme precipitation. Four features are identified using existing data sets for atmospheric rivers (ARs), mesoscale convective systems (MCSs), low‐pressure systems (LPSs), and fronts (FTs). Often, a single atmospheric phenomenon satisfies the criteria set by multiple feature identification algorithms, yielding an association between precipitation and multiple features. Over the extra‐tropics, the number of features attributed to a single event typically increases with precipitation intensity. Over two‐thirds of the precipitation is from co‐occurring features, with a considerable fraction related to AR‐FT co‐occurrences. Over the tropics, about one‐quarter of precipitation is associated with co‐occurring features, with LPS‐MCS co‐occurrences contributing substantially in monsoon regions. MCSs are the leading single‐feature contributors over tropical land and oceans. In the extra‐tropics, FTs, ARs, and their co‐occurrences account for over half of the total precipitation over oceans. AR‐FT‐MCS and FT‐MCS co‐occurrences contribute to extremes (precipitation exceeding the 95th percentile) over both oceans (over 30%) and land (over 20%). Any combination of features involving MCSs shows a larger contribution to high percentiles of precipitation intensity. A case analysis indicates that AR‐FT‐MCS co‐occurrences exhibit convective instability and deep vertical motion, suggesting that the feature trackers and reanalysis are capturing physics relevant to both convective and frontal systems. The results here emphasize the need for simultaneous identifications of multiple features when attributing precipitation to atmospheric phenomena.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2025-02-28
DOI
https://doi.org/10.1029/2024jd041687
Citations
4
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
4.42
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article

Co‐Occurring Atmospheric Features and Their Contributions to Precipitation Extremes

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4 citations
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Climate variability and models
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article

Co‐Occurring Atmospheric Features and Their Contributions to Precipitation Extremes

Jennifer L. Catto, Zhe Feng, Paul Ullrich, Fiaz Ahmed, D. L. Suhas, William R. Boos, J. David Neelin, Travis O’Brien, Suqin Q. Duan, Lai-Yung Ruby Leung, Yang Zhou, Wu-Yang Tsai
article en
4 citations

Abstract

Abstract Object‐based identification algorithms for atmospheric features are commonly utilized to attribute global precipitation. This study employs a systematic approach to examine feature co‐occurrences and their relationships to mean and extreme precipitation. Four features are identified using existing data sets for atmospheric rivers (ARs), mesoscale convective systems (MCSs), low‐pressure systems (LPSs), and fronts (FTs). Often, a single atmospheric phenomenon satisfies the criteria set by multiple feature identification algorithms, yielding an association between precipitation and multiple features. Over the extra‐tropics, the number of features attributed to a single event typically increases with precipitation intensity. Over two‐thirds of the precipitation is from co‐occurring features, with a considerable fraction related to AR‐FT co‐occurrences. Over the tropics, about one‐quarter of precipitation is associated with co‐occurring features, with LPS‐MCS co‐occurrences contributing substantially in monsoon regions. MCSs are the leading single‐feature contributors over tropical land and oceans. In the extra‐tropics, FTs, ARs, and their co‐occurrences account for over half of the total precipitation over oceans. AR‐FT‐MCS and FT‐MCS co‐occurrences contribute to extremes (precipitation exceeding the 95th percentile) over both oceans (over 30%) and land (over 20%). Any combination of features involving MCSs shows a larger contribution to high percentiles of precipitation intensity. A case analysis indicates that AR‐FT‐MCS co‐occurrences exhibit convective instability and deep vertical motion, suggesting that the feature trackers and reanalysis are capturing physics relevant to both convective and frontal systems. The results here emphasize the need for simultaneous identifications of multiple features when attributing precipitation to atmospheric phenomena.

Journal of Geophysical Research AtmospheresVol. 130(5)
Lawrence Livermore National Laboratory (US), Planetary Science Institute (US), Pacific Northwest National Laboratory (US), Lawrence Berkeley National Laboratory (US), University of California, Los Angeles (US), University of Exeter (GB), Indiana University Bloomington (US), University of California, Davis (US), University of California, Berkeley (US)
Openalex Percentile: Top 7%
Climate variability and models
4.42
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