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Explaining monthly precipitation anomalies in northwestern South America by integrating vertical dynamics and energetics

Explaining monthly precipitation anomalies in northwestern South America by integrating vertical dynamics and energetics

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Authors

Jose Obregon-Yataco 

Abstract

Northwestern South America (NWSA), a region critically important for monitoring coastal El Niño and La Niña events, receives its maximum cumulative precipitation in February-March. Thermodynamic indices alone, often fail to explain observed precipitation anomalies because they neglect the influence of large-scale environmental dynamics. To bridge this gap, a low-frequency climate index called Buoyancy Work Rate (BWR) is proposed, which quantifies the rate of conversion from potential to kinetic energy by coupling local thermodynamic instability with vertical motion (ω) forced by large-scale dynamics. The BWR is calculated by vertically integrating the product of parcel buoyancy (ΔT) and ω from the surface to the 100 hPa level. Statistical evaluation between 1981 and 2024 demonstrates that BWR outperforms established indices in spatial correlation, RMSE, and F1-scores, particularly for extreme precipitation events. Physically, the index explains how variations in vertical motion profiles modulate precipitation outcomes across events with similar instability, effectively explaining the contrasting impacts of the 2016, 2017, and 2023 El Niño events. Furthermore, since BWR capture primarily on large-scale vertical motions, which typically exhibit higher predictability in climate models than vertical humidity profiles, the BWR emerges as a robust candidate for future forecasting applications.

DOI

https://doi.org/10.31223/X57X7J

Subjects

Oceanography and Atmospheric Sciences and Meteorology

Keywords

climate index, Precipitation, South America, El Niño, thermodynamic

Dates

Published: 2026-01-07 08:42

Last Updated: 2026-01-08 06:10

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License

CC BY Attribution 4.0 International

Additional Metadata

Data Availability (Reason not available):
PISCO V2.1 dataset is available at https://iridl.ldeo.columbia.edu/SOURCES/.SENAMHI/.HSR/.PISCO/index.html; RAIN4PE at https://datapub.gfz-potsdam.de/download/10.5880.PIK.2020.010enouiv/; ERA5 reanalysis data at https://cds.climate.copernicus.eu/datasets

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