Vol.:(0123456789) Natural Hazards https://doi.org/10.1007/s11069-020-04011-x 1 3 ORIGINAL PAPER A principal component analysis approach to assess CHIRPS precipitation dataset for the study of climate variability of the La Plata Basin, Southern South America Wilmar Loaiza Cerón 1,2  · Jorge Molina‑Carpio 3  · Irma Ayes Rivera 2  · Rita Valeria Andreoli 4  · Mary Toshie Kayano 5  · Teresita Canchala 6 Received: 8 May 2019 / Accepted: 25 April 2020 © Springer Nature B.V. 2020 Abstract This article assesses the consistency of the satellite precipitation estimate CHIRPS v.2 to describe the spatiotemporal rainfall variability in the La Plata Basin (LPB), the second largest hydrographic basin in South America, by (a) pixel-to-point comparison of CHIRPS data with 167 observed monthly precipitation time series using three pairwise metrics (coefcient of correlation, bias and root mean square error) and (b) principal component analysis (PCA) to evaluate the large-scale coherence between CHIRPS and rain gauge data. The pairwise metrics indicate that CHIRPS better represents the rainfall in the coastal, northeastern and southeastern parts of the basin than in the Andean region to the west. The PCA shows that CHIRPS describes most of the observed rainfall variability in the LPB, but contains more variability, especially during December–February and March–May sea- sons. The two major modes observed are highly correlated spatially (empirical orthogonal functions—EOFs) and temporally (principal components—PCs) with the corresponding CHIRPS modes. The PCA allows the determination of the main rainfall variability modes and their possible relations with climate variability modes. Besides, the analyses of the precipitation anomaly modes show that the El Niño Southern Oscillation explains the frst EOF modes of datasets. The PCA provides an alternative and efective means of assessing the consistency of CHIRPS data in representing spatial and temporal rainfall variability in the LPB. Keywords CHIRPS · Satellite precipitation estimate · Performance metrics · Principal component analysis · La Plata Basin 1 Introduction A common difculty when studying extreme climatic events associated with rainfall vari- ability, such as droughts and foods, is the lack of timely and reliable information. This is especially true for regions where the gauge networks are sparse and unevenly distributed, * Wilmar Loaiza Cerón wilmar.ceron@correounivalle.edu.co; wiloce16@gmail.com Extended author information available on the last page of the article