Comparison and evaluation of high resolution precipitation estimation products in Urmia Basin-Iran

•Analysis shows superiority of TMPA-V7 among corrected post real-time satellite products.•Between near-real time data sets, the PERSIANN has totally performed better than others.•Categorical analysis indicates that all products are much more reliable in rainfall detection than to estimate rain rates.•TMPA-V7 as the adjusted version of TMPA-RT is successfully modifying its real-time data set.•CMORPH-CRT as the adjusted version of CMORPH-RAW has totally worsened its estimations.

This study focuses on the comparison and evaluation of six daily 0.25° × 0.25° high resolution precipitation data sets (PERSIANN, CMORPH-RAW, CMORPH-CRT, TMPA-RT, TMPA-V7 and APHRODITE). The comparison is performed during years 2000 till 2011 in Urmia basin of Iran and the local daily rainfall gauge observations are considered as the reference data set. Several statistical, categorical and graphical evaluation techniques are used to compare and evaluate the product performances and quantify their biases from reference data. APHRODITE and TMPA-V7, by benefiting from gauge observations during their adjustment procedures present better estimations while among near real-time products, PERSIANN is able to remarkably outperform other estimations. Both CMORPH products has shown to have great overestimation (more than 200%) over the observations while PERSIANN and TMPA-RT tend to underestimate rainfall on average about 26% and 78% respectively. TMPA-V7 and APHRODITE also overestimate observations about 26 and 3 percentages. Compared to near real-time version of products, TMPA-V7 has succeeded to significantly improve TMPA-RT performance while CMORPH-CRT has completely unsuccessful in its mission. Although all rainfall estimation products are characterized by considerable biases in comparison to the gauge observations, detailed analysis indicate that some of them have the capability of becoming a valuable source of high resolution precipitation estimation data set, especially over purely gauged areas.