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.
Authors
- Jennifer L. Catto (ORCID: https://orcid.org/0000-0002-8662-1398)
- Zhe Feng (ORCID: https://orcid.org/0000-0002-7540-9017)
- Paul Ullrich (ORCID: https://orcid.org/0000-0003-4118-4590)
- Fiaz Ahmed (ORCID: https://orcid.org/0000-0003-4194-895X)
- D. L. Suhas (ORCID: https://orcid.org/0000-0001-7453-867X)
- William R. Boos (ORCID: https://orcid.org/0000-0001-9076-3551)
- J. David Neelin (ORCID: https://orcid.org/0000-0001-9414-9962)
- Travis O’Brien (ORCID: https://orcid.org/0000-0002-6643-1175)
- Suqin Q. Duan (ORCID: https://orcid.org/0000-0001-6951-119X)
- Lai-Yung Ruby Leung (ORCID: https://orcid.org/0000-0002-3221-9467)
- Yang Zhou (ORCID: https://orcid.org/0000-0003-2835-4081)
- Wu-Yang Tsai
Institutions
- 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)
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