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A Sub-Hourly Precipitation Dataset from a Pluviographic Network in Central Chile

Author

Listed:
  • Claudia Sangüesa

    (Cátedra UNESCO de Hidrología Superficial, Universidad de Talca, Talca 3467769, Chile
    Centro Nacional de Excelencia para la Industria de la Madera (CENAMAD), ANID BASAL FB210015, Pontificia Universidad Católica de Chile, Santiago 7810128, Chile)

  • Alfredo Ibañez

    (Cátedra UNESCO de Hidrología Superficial, Universidad de Talca, Talca 3467769, Chile
    Centro Nacional de Excelencia para la Industria de la Madera (CENAMAD), ANID BASAL FB210015, Pontificia Universidad Católica de Chile, Santiago 7810128, Chile)

  • Roberto Pizarro

    (Cátedra UNESCO de Hidrología Superficial, Universidad de Talca, Talca 3467769, Chile
    Centro Nacional de Excelencia para la Industria de la Madera (CENAMAD), ANID BASAL FB210015, Pontificia Universidad Católica de Chile, Santiago 7810128, Chile)

  • Cristian Vidal-Silva

    (Departamento de Visualización Interactiva y Realidad Virtual, Facultad de Ingeniería, Universidad de Talca, Talca 3467769, Chile)

  • Pablo Garcia-Chevesich

    (Department of Civil and Environmental Engineering, Colorado School of Mines, Golden, CO 80401, USA
    Intergubernamental Hydrological Programme, United Nations Educational, Scientific, and Cultural Organization (UNESCO), Montevideo 111000, Uruguay)

  • Romina Mendoza

    (Cátedra UNESCO de Hidrología Superficial, Universidad de Talca, Talca 3467769, Chile)

  • Cristóbal Toledo

    (Cátedra UNESCO de Hidrología Superficial, Universidad de Talca, Talca 3467769, Chile)

  • Juan Pino

    (Dirección de Transferencia Tecnológica, Universidad Tecnológica Metropolitana, Santiago 8330367, Chile)

  • Rodrigo Paredes

    (Facultad de Ingeniería, Universidad Finis Terrae, Providencia 7501014, Chile)

  • Ben Ingram

    (Departamento de Visualización Interactiva y Realidad Virtual, Facultad de Ingeniería, Universidad de Talca, Talca 3467769, Chile
    Faculty of Energy and Applied Sciences, Cranfield University, Cranfield MK43 0AL, UK)

Abstract

This data descriptor presents a unique high-resolution rainfall dataset derived from 14 pluviograph stations across central Chile’s Mediterranean region, covering variable periods starting from between 1969 and 1992, up to 2009. The dataset provides continuous precipitation records at a 5 min temporal resolution, obtained through the digitization and processing of pluviograph strip charts using specialized software. This high temporal resolution is unprecedented for the region and enables detailed analysis of rainfall intensity, duration, and frequency patterns critical for hydrological research, climate studies, and water resource management in general. Each station’s data was subjected to quality control procedures, including manual validation and correction of digitization errors to ensure data integrity. The dataset reveals the significant temporal variability of rainfall in central Chile, capturing both short-duration high-intensity events and longer precipitation patterns. By making this dataset publicly available, we provide researchers with a valuable resource for studying rainfall behavior in a Mediterranean climate zone subject to significant climate variability and change. The dataset supports various applications, including the development of intensity–duration–frequency curves, analysis of rainfall erosivity, calibration of hydrological models, and investigation of precipitation trends in the context of climate change.

Suggested Citation

  • Claudia Sangüesa & Alfredo Ibañez & Roberto Pizarro & Cristian Vidal-Silva & Pablo Garcia-Chevesich & Romina Mendoza & Cristóbal Toledo & Juan Pino & Rodrigo Paredes & Ben Ingram, 2025. "A Sub-Hourly Precipitation Dataset from a Pluviographic Network in Central Chile," Data, MDPI, vol. 10(7), pages 1-17, June.
    • Handle: RePEc:gam:jdataj:v:10:y:2025:i:7:p:95-:d:1684801
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    References listed on IDEAS

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    1. Feng He & Neda Mohamadzadeh & Mostafa Sadeghnejad & Ben Ingram & Yaser Ostovari, 2023. "Fractal Features of Soil Particles as an Index of Land Degradation under Different Land-Use Patterns and Slope-Aspects," Land, MDPI, vol. 12(3), pages 1-14, March.
    2. Selma B. Guerreiro & Hayley J. Fowler & Renaud Barbero & Seth Westra & Geert Lenderink & Stephen Blenkinsop & Elizabeth Lewis & Xiao-Feng Li, 2018. "Detection of continental-scale intensification of hourly rainfall extremes," Nature Climate Change, Nature, vol. 8(9), pages 803-807, September.
    3. Suman Ravuri & Karel Lenc & Matthew Willson & Dmitry Kangin & Remi Lam & Piotr Mirowski & Megan Fitzsimons & Maria Athanassiadou & Sheleem Kashem & Sam Madge & Rachel Prudden & Amol Mandhane & Aidan C, 2021. "Skilful precipitation nowcasting using deep generative models of radar," Nature, Nature, vol. 597(7878), pages 672-677, September.
    4. Julie Shortridge, 2019. "Observed trends in daily rainfall variability result in more severe climate change impacts to agriculture," Climatic Change, Springer, vol. 157(3), pages 429-444, December.
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