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Validating CHIRPS ability to estimate rainfall amount and detect rainfall occurrences in the Philippines

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Abstract

The lack of sufficient rainfall data has been a common problem that hampers water resources planning in many developing countries with sparse weather monitoring networks. Satellite rainfall data requires validation to be considered adequate for any purpose it may serve. This study aimed to validate the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) ability to estimate monthly rainfall amounts and detect rainfall occurrences for various water resources planning over the four types of climate in the Philippines. It was validated using data from 68 rainfall stations. The results showed that CHIRPS performed best during the dry seasons, and its performance was well correlated with climate type. It was found that the best estimate of rainfall amount is in Climate Type I. The CHIRPS showed adequate performance in reproducing rainfall amount in Climate Types II and III. Its lowest performance was seen in Climate Type IV with 50% of the stations having adequate CHIRPS estimates of monthly rainfall amount. The CHIRPS had the best results at detecting rainfall occurrences during dry seasons when random chances are accounted for, otherwise, it detected better rainfall occurrence during wet seasons. It consistently over detected rainfall occurrences across climate types and seasons. The validation showed that CHIRPS data on the monthly time scale could be applied in water resources planning especially for drought assessments. The results may serve as a useful reference to many water managers and policy- and decision-makers as the country could only currently rely on a sparse weather monitoring network for observed rainfall data which are of utmost importance in water resources planning.

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Data availability

The CHIRPS satellite rainfall data is accessible at https://developers.google.com/earth-engine/datasets/catalog. The ground-based rainfall data is available upon request from the Philippine Atmospheric, Geophysical and Astronomical Services Administration of the Department of Science and Technology.

Code availability

Not applicable

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Funding

This research was funded and supported by the DOST–Engineering Research and Development for Technology and the DOST–Science Education Institute, the DOST–Philippine Council for Agriculture, Aquatic and Natural Resources Research and Development, and the Department of Agriculture–Bureau of Agricultural Research. The authors would also like to recognize the assistance of the DOST–Philippine Atmospheric, Geophysical and Astronomical Services Administration particularly the Impact Assessment and Applications Section of the Climatology and Agrometeorology Division for providing the ground-based rainfall data for free and Ms. Marissa Hernando-Valdez for proofreading this paper.

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Authors and Affiliations

  1. Department of Agricultural and Biosystems Engineering, College of Engineering, Isabela State University, 3309, Echague, Isabela, Philippines

    Lanie A. Alejo

  2. National Irrigation Administration, Magat River Integrated Irrigation System, Dam and Reservoir Division, 3309, Ramon, Isabela, Philippines

    Arlen S. Alejandro

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  1. Lanie A. Alejo
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  2. Arlen S. Alejandro
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Dr. Alejo conceived and designed the analysis, supervised the analysis, and wrote the paper. Engr. Alejandro collected the data, performed the analysis, and assisted in writing the paper.

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Correspondence to Lanie A. Alejo.

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Alejo, L.A., Alejandro, A.S. Validating CHIRPS ability to estimate rainfall amount and detect rainfall occurrences in the Philippines. Theor Appl Climatol 145, 967–977 (2021). https://doi.org/10.1007/s00704-021-03685-y

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