A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023

• Autores: Canziani, Pablo O.; Lakkis, S. Gabriela See "Lakkis, Susan Gabriela"; Yuchechen, Adrian E.
• Año de publicación: 2025
• Idioma: inglés
• Tipo de recurso: artículo
• Fuente: Atmosphere 2025, 16 (914)
• Materia: METEREOLOGIA; PRECIPITACIONES; Argentina
• Institución: Pontificia Universidad Católica Argentina

Fil: Canziani, Pablo O. Universidad Tecnológica Nacional; Argentina
Fil: Lakkis, Susan Gabriela. CONICET; Argentina
Fil: Yuchechen, Adrian E. Pontificia Universidad Católica Argentina, Facultad de Ingeniería y Ciencias Agrarias; Argentina
This study investigates the long-term variability and extremes of monthly precipitation during 150 years or more at 4 locations in Argentina: Corrientes, Córdoba, Buenos Aires, and Bahía Blanca. Annual and seasonal trends, extreme dry and wet months over the whole period, and the relationships between large-scale climate drivers and monthly rainfall are considered. Results show that, except for Córdoba, the complete anomaly timeseries trend analysis for all other stations yielded null trends over the centennial study period. Considerable month-to-month variability is observed for all locations together with the existence of low-frequency decadal to interdecadal variability, both for monthly precipitation anomalies and for statistically significant excess and deficit months. Linear fits considering oceanic climate indicators as drivers of variability yield significant differences between locations, while not between full records and seasonally sampled. Issues regarding the use of linear analysis to quantify variability, the dispersion along the timeline of record extreme rainy months at each location, together with the evidence of severe daily precipitation events not necessarily coinciding with the ranking of the rainiest months at each location, highlights the challenges of understanding the drivers of variability of both monthly and severe daily precipitation and the need of using extended centennial timeseries whenever possible.