Validation of CHIRPS estimated precipitation in a semi-arid region of Argentina
Keywords:
CHIRPS, gridded data, validation, precipitationAbstract
Gridded data of precipitation are a valuable tool in scarce-observational data contexts. Validation through statistical analysis is essential for its use. This work aims to validate the Climate Hazards Infrared Precipitation with Stations (CHIRPS) database for the southwest of Buenos Aires province (1990-2020). This dataset has adequate spatio-temporal coverage to study rainfall variability. For validation purposes, Pearson's correlation coefficient (r-Pearson), mean absolute error (mae), root mean squared error (rmse) and percent bias (pbias) were applied in the R environment using the hydroGOF package. CHIRPS shows a correlation between 0.68 and 0.84 for observed data on both monthly and annual scales. It also tends to overestimate rainfall between 2 and 4%, except in the northwestern sector, where it underestimates between 4 and 11%. It is concluded that CHIRPS is applicable for rainfall variability studies in the analyzed region, where the lack of data is a recurrent problem, considering the spatial errors detected.
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