Canziani et al. (2025) A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023

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Identification

• Journal: Atmosphere
• Year: 2025
• Date: 2025-07-29
• Authors: Pablo O. Canziani, Susan Gabriela Lakkis, Adrián E. Yuchechen
• DOI: 10.3390/atmos16080914

Research Groups

Not specified in the provided text.

Short Summary

This study analyzes over 150 years of monthly precipitation at four Argentine locations to evaluate long-term trends and the influence of large-scale climate drivers. The results indicate generally null long-term trends but significant decadal variability and a disconnect between monthly precipitation rankings and severe daily events.

Objective

• To investigate the long-term variability, extremes, and the relationship between large-scale climate drivers and monthly precipitation at four specific locations in Argentina.

Study Configuration

• Spatial Scale: Local scale (four stations: Corrientes, Córdoba, Buenos Aires, and Bahía Blanca, Argentina).
• Temporal Scale: Centennial scale ($\ge 150$ years).

Methodology and Data

• Models used: Trend analysis and linear regression (linear fits) using oceanic climate indicators.
• Data sources: Long-term monthly precipitation observational records.

Main Results

• Trends: Null trends were found for Corrientes, Buenos Aires, and Bahía Blanca over the centennial period, while Córdoba exhibited a trend.
• Variability: Significant month-to-month variability and low-frequency decadal to interdecadal variability were observed in precipitation anomalies and extreme months.
• Climate Drivers: Linear relationships between oceanic climate indicators and rainfall varied significantly by location.
• Extremes: Severe daily precipitation events did not necessarily coincide with the months ranked as the rainiest, highlighting a discrepancy between monthly totals and daily extremes.

Contributions

• Highlights the limitations of using linear analysis to quantify precipitation variability.
• Underscores the necessity of utilizing extended centennial timeseries to accurately understand the drivers of both monthly and severe daily precipitation.

Funding

Not specified in the provided text.

Citation

@article{Canziani2025Study,
  author = {Canziani, Pablo O. and Lakkis, Susan Gabriela and Yuchechen, Adrián E.},
  title = {A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023},
  journal = {Atmosphere},
  year = {2025},
  doi = {10.3390/atmos16080914},
  url = {https://doi.org/10.3390/atmos16080914}
}