Author(s): Mahdi Alemi; Rodrigo Maia

Linked Author(s): Rodrigo Maia

Keywords: Precipitation; Satellite product; PERSIANN-CCS-CDR; Bias adjustment

Abstract: The study aims to propose and evaluate a simple approach to adjust daily satellite gridded data by considering ground-based data (i.e., from rain gauges). The corresponding algorithms were written in Python and a model was developed for that aim. The model can analyze any gridded satellite data over any geographic region of the world, this study presenting the application and evaluation of the model for mainland Portugal. Moreover, the recently-released (late 2020) PERSIANN-CCS-CDR product was selected for the study, having in attention that the referred satellite product provides relatively long-term precipitation records (1983-present) with high spatiotemporal resolution (0.04o x 0.04o spatial and 3-hourly temporal). The present comparison study was performed at both pixel (0.04o) and watershed scales. Regarding the latter spatial scale, three watersheds in mainland Portugal were chosen for the corresponding analysis. Overall, the satellite and the rain gauge datasets agree well at the monthly time level. The obtained results show differences between the two datasets at the daily time level, but the adjusted daily PERSIANN-CCS-CDR data are in good agreement with the corresponding rain-gauge data at both grid and watershed scales.

DOI: https://doi.org/10.3850/IAHR-39WC2521711920221314

Year: 2022