Validation of chirps gauge – satellite based rainfall dataset over Nicaragua, 2011 - 2021

Rainfall is a key input for many weather and climate numerical models. Therefore the strong need to have a dense enough monitoring network for this parameter. Satellite-based rainfall products have emerged in recent decades as an alternative to the more expensive gauge stations. However, a proper validation of such satellite-based products against gauge data must be performed before using their data. This study presents a validation of CHIRPS dataset against gauge data for 17 stations across Nicaragua. The performance of the product was validated at different temporal scales (daily, pentadal, monthly and annual) by different error metrics. A total of six quantitative error metrics was assessed: Bias Percentage (PBIAS), Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Pearson’s r and Nash Stucliffe Efficiency (NSE). A total three categorical indices were assessed at daily time scale: Probability of Detection (POD), False Alarm Ratio (FAR) and Critical Success Index (CSI). The results showed that CHIRPS dataset have better performance at monthly and annual time scales, while it is not capable of adequately represent the daily variability.