Evaluation of satellite/reanalysis precipitation products over Iran

作者：Ehsan Taghizadeh, Farhang Ahmadi‐Givi, Luca Brocca, Ehsan Sharifi · 发表于：International Journal of Remote Sensing · 年份：2021 · DOI：10.1080/01431161.2021.1875508 · 被引用次数：35 · 研究领域：Precipitation Measurement and Analysis、Meteorological Phenomena and Simulations、Soil Moisture and Remote Sensing

This study aims to evaluate the satellite- and model-based precipitation products against a relatively dense station network of Iran Meteorological Organization (IRIMO) from January 2015 to June 2018 at daily timescale over Iran. The evaluations are carried out based on continuous and categorical statistical metrics. First, we employed daily satellite soil moisture (SM) observations from the Advanced Microwave Scanning Radiometer 2 (AMSR2) for estimating rainfall through the use of the relatively new SM2RAIN approach (SM2R-AMSR2). Next, we validated rainfall estimations from satellite/reanalysis products including version 05 daily Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG) Early (IMERG-DE), Late (IMERG-DL), and Final Daily (IMERG-DF) Runs and the European Centre for Medium-Range Weather Forecasts’ ReAnalysis Interim (ERA-Interim), ECMWF ReAnalysis 5th Generation (ERA5) and SM2R-AMSR2. Based on the probability density function (PDF), all satellite and model products capture more (less) precipitation events than the reference data set for precipitation under (upper) 5.0 mm day−1 threshold. Regarding the mean absolute error (MAE) and root-mean-square error (RMSE) quantities, the ERA5 product has the lowest error relative to other products. Also, the threat score (TS) indicates that this product has the highest accuracy. ERA-Interim and IMERG-DF had roughly similar performances. The results reveal the overall superiority of ERA5 d...