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A Spatiotemporal Classification of the Peruvian Precipitations Between 1990 and 2015

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Abstract

Precipitation and its variations have great importance in water resource management and sustainable development. In this study, the Peruvian precipitations between January 1990 to October 2015, were used. The precipitations were classified under spatial, temporal, and spatiotemporal classes. For this aim, properties of the precipitation time series including the monthly mean, monthly standard deviation, and principal components at monthly and annual scale were evaluated. Results were projected on a map using the Kriging method. Later, the double mass curves of the monthly precipitation time series were used to classify the temporal changes in the precipitations. Thereafter, the Spearman rank-order correlation was used to evaluate the spatiotemporal changes in monthly and annual precipitation time series by projected t-values on the Peruvian map. Finally, precipitations time series were plotted against Köppen–Geiger climate class of each station and several large scale oscillations namely North Atlantic Oscillation (NAO), El Niño/Southern Oscillation (ENSO), Atlantic Multi-decadal Oscillation (AMO), and Pacific Decadal Oscillation (PDO) simultaneously. It was concluded that there are at least three major climatic regions in the country. Spatial classes, depicts that the Andes Ranges is a major role player in the climate of the country while the ENSO and PDO are the main drivers of the precipitation extremes. Results also indicated to an ascending changes in the amount of precipitation from west to east, while a descending changes were observed at Amazon forest near San Ramon.

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Acknowledgements

The author appreciates the Republic of Peru’s National Service of Meteorology and Hydrology (SENAMHI) for providing the required data for this study.

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  1. Department of Civil Engineering, Bursa Technical University, Bursa, Turkey

    Babak Vaheddoost

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Correspondence to Babak Vaheddoost.

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Vaheddoost, B. A Spatiotemporal Classification of the Peruvian Precipitations Between 1990 and 2015. Pure Appl. Geophys. 177, 4509–4520 (2020). https://doi.org/10.1007/s00024-020-02454-8

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