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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) is a critical region for monitoring El Niño-driven hydroclimatic extremes, receiving its maximum cumulative precipitation in March. Thermodynamic indices alone often fail to explain observed precipitation anomalies in this region because they neglect the limiting role of large-scale environmental dynamics. To bridge this gap, a diagnostic proxy called the Buoyancy Work Rate (BWR) is proposed, which quantifies the rate of conversion from potential to kinetic energy by coupling local thermodynamic instability (ΔT) with vertical motion (ω) forced by large-scale dynamics. The BWR is calculated by vertically integrating the product $-\omega\Delta T$ from the surface to the 100 hPa level. Using the PCMCI+ causal discovery algorithm, this study empirically validates the classical thermodynamic energy balance mechanism, demonstrating that precipitation in the NWSA is dynamically controlled, with ω exerting a causal influence significantly stronger than local evaporation. Validation via Tail Dependence analysis (λu) reveals that the BWR achieves robust asymptotic dependence (λu ~0.8) during extreme events, effectively filtering out thermodynamic false positives (e.g., the 2016 event) by incorporating the vertical velocity constraint. Furthermore, autocorrelation analysis indicates that the inclusion of the thermodynamic component imparts significant signal persistence to the index, stabilizing the inherently chaotic nature of pure vertical velocity. Physically, the index explains how dynamic forcing modulates precipitation outcomes across events with similar instability, resolving the contrasting impacts of the 2016, 2017, and 2023 El Niño events. Consequently, the BWR emerges as a physically consistent tool that offers a longer predictability horizon for monitoring sub-seasonal hydroclimatic risks.

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 10:42

Last Updated: 2026-02-14 01:45

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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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