The 1st International and 4th National Congress on Iranian Irrigation and Drainage, Urmia, Iran, 13 - 14 November 2019
Uncertainty estimation of precipitation products estimated from different platforms are essential for many hydrological and agricultural applications that use these datasets. Among the precipitation retrieval products satellite- and model-based estimates have the advantage of providing consistent and continuous precipitation records. This study evaluates a satellite-based product (TMPA 3B42V7) and a model-based product (ECMWF 1 daily deterministic forecast) by using 16 ground-based gauges data as reference in the West Azarbayjan province of Iran for a period of January 2007 to May 2015. Precipitation estimates are evaluated for their accuracy, intensity-frequency, and different temporal components (climatology and anomaly). The results show the errors of the products are more governed by the anomaly component than the climatology component, where anomaly component is primarily used for many extreme event analysis like drought. Overall, the ECMWF and TMPA long term biases are 7 mm/mon and -0.25 mm/mon, respectively. On average, ECMWF product show marginally better monthly correlation with observed data than TMPA: for TMPA and ECMWF the correlations are 0.79 and 0.83 respectively for the complete datasets, 0.88 and 0.86 respectively for the climatology components, 0.66 and 0.77 respectively for the anomaly components. TMPA has similar precipitation frequency with the gauge particularly for precipitation events having less than 20mm/day, while ECMWF tends to overestimate the precipitation frequency for events between 1mm/day and 20mm/day. The results show both ECMWF and TMPA products are of good quality for use in different applications over the study region investigated here.