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  Spatiotemporal dynamics of moisture influx and their role in precipitation extremes: A study of December 2023 in Kayalpattinam

Ganapathiraju, S. A., Kanth, U., V., M. S. L., Rathinasamy, M., Kumar, K. N., Vallejo-Bernal, S. M., Marwan, N., Kaur, S. (2025 online): Spatiotemporal dynamics of moisture influx and their role in precipitation extremes: A study of December 2023 in Kayalpattinam. - Atmospheric Research, 331, 108680.
https://doi.org/10.1016/j.atmosres.2025.108680

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https://zenodo.org/records/15235584 (Ergänzendes Material)
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 Urheber:
Ganapathiraju, Sree Anusha1, Autor
Kanth, Utkarsh2, Autor
V., Madhuri Sai Latha2, Autor
Rathinasamy, Maheswaran1, Autor
Kumar, Kondapalli Niranjan2, Autor
Vallejo-Bernal, Sara M.1, Autor
Marwan, Norbert1, Autor                 
Kaur, Sukhwinder2, Autor
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Zusammenfassung: In 2023, the coastal town of Kayalpattinam in Tamil Nadu recorded an extraordinary rainfall exceeding 950 mm on December 17 and 18, resulting in severe flash floods and devastation to livelihoods in the community. This study critically examines the physical mechanisms driving this event across scales. Employing regional reanalysis datasets, we elucidate the localized characteristics responsible for extreme precipitation and systematically address the associated uncertainties. The investigation revealed that the spatiotemporal dynamics of moisture transport played a vital role in the increased moisture influx over the region. In particular, the local convection combined with heightened atmospheric instability and intensified advection in the surrounding areas played a pivotal role in the formation of significant mid-tropospheric cyclones. These developed atmospheric phenomena are rarely observed in this region, which typically experiences tropical cyclones and depressions more frequently. This study emphasizes the necessity of conducting meticulous investigations to improve risk assessments and preparedness for future climatological phenomena of similar magnitude.

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Sprache(n): eng - English
 Datum: 2025-12-042025-12-17
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: MDB-ID: No MDB - stored outside PIK (see locators/paper)
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Working Group: Development of advanced time series analysis techniques
Research topic keyword: Atmosphere
Research topic keyword: Extremes
Research topic keyword: Monsoon
Research topic keyword: Weather
Regional keyword: Asia
Model / method: Quantitative Methods
Model / method: Nonlinear Data Analysis
DOI: 10.1016/j.atmosres.2025.108680
 Art des Abschluß: -

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Titel: Atmospheric Research
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
 Urheber:
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 331 Artikelnummer: 108680 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/1501191
Publisher: Springer