VALIDATION OF RAINFALL DATA ESTIMATED BY CHIRPS FOR THE SOUTHERN REGION OF ANGOLA

This work is to analyze the monthly rainfall estimation data from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) database and to verify their proximity in comparison with the data from four automatic meteorological stations (4) (EMA) of the National Institute of Meteorology and Geophysics (INAMET), which represent the Southern Region of Angola (RSA). The present study aims to validate the precipitation estimates of the CHIRPS product through analysis of statistical metrics, with the objective of subsidizing drought monitoring and water resources planning. In view of the scarcity and flaws in meteorological data in the RSA, which limit the production of scientific studies due to the insufficiency of time series covering the region, alternative data sources, such as reanalyses, are often used, which are the best option to fill these gaps. The analysis employs several statistical metrics including the Pearson correlation coefficient, the Spearman correlation coefficient, the Root Mean Square Error (RMSE), the Mean Absolute Error (MAE), and Bias - to assess the accuracy and reliability of CHIRPS under different climatic conditions. One of the main factors for this scarcity of data at RSA was the protracted civil war; currently, although there are public and private investments for the installation of new Automatic Weather Stations (EMAs), these are still insufficient to cover the entire southern region of Angola.