1. Data Analysis of GPM Constellation Satellites-IMERG and ERA-Interim Precipitation Products over West of Iran Ehsan Sharifi 1, Reinhold Steinacker 1, and Bahram Saghafian 2 1 Department of Meteorology and Geophysics, University of Vienna, Vienna (Austria) 2 Department of Technical and Engineering, Science and Research Branch, Islamic Azad University, Tehran (Iran) Contact: Ehsan Sharifi University of Vienna Department of Meteorology and Geophysics Althanstraße 14 / UZA II, 1090 Vienna, Austria ehsansharifi83@gmail.com References Sharifi, E.; Steinacker, R.; Saghafian, B. Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results. Remote Sens. 2016, 8, 135. NASA. “GPM_3IMERGHH 03”. Available online: http://disc.sci.gsfc.nasa.gov/SSW/ (accessed on 6 June 2015). European Centre for Medium-Range Weather Forecasts (ECMWF). “ERA Interim, Daily”. Available online: http://apps.ecmwf.int/datasets/data/interim-full-daily/ (accessed on 1 July 2015). Precipitation is a critical component of the Earth's hydrological cycle. The primary requirement in precipitation measurement is to know where and how much precipitation is falling at any given time. Especially in data sparse regions with insufficient radar coverage, satellite information can provide a spatial and temporal context. Nonetheless, evaluation of satellite precipitation is essential prior to operational use. Accurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to hazards. In situ observations over mountainous areas are mostly limited, but currently available satellite precipitation products can potentially provide the precipitation estimation needed for meteorological and hydrological applications. One of the newest and blended methods that use multi-satellites and multi-sensors has been developed for estimating global precipitation. The considered data set known as Integrated Multi-satellitE Retrievals (IMERG) for GPM (Global Precipitation Measurement) is routinely produced by the GPM constellation satellites. As a result, this study aims to assess the accuracy of the new generation of satellite precipitation products (IMERG final run) over West of Iran (Kermanshah). Introduction Results Conclusion Methods IMERG, 3B42 and ERA-Interim yield underestimate the observed values while IMERG underestimated slightly and performed better. Furthermore, with respect to evaluation of probability of detection (POD), critical success index (CSI) and false alarm ratio (FAR), IMERG yields a better value of POD, CSI and FAR in comparison to 3B42 and era-Interim in daily scale. Overall, ERA- Interim product produced fewer robust results when compared to IMERG. ERA- Interim yields weak results of POD, FAR and CSI for precipitation above 5 mm/day over West of Iran while IMERG is far superior to the other products. At present, the IMERG data are available from 12 March 2014 to present, thus providing IMERG-V03D final run data for March 2014 to February 2015 period. Acknowledgments The 3B42 and IMERG data were provided by the NASA/Goddard Space Flight Center’s and PPS, which develop and compute the 3B42 and IMERG as a contribution to TMPA and GPM constellation satellites. We acknowledge the ECMWF-ERA-Interim datasets from the Meteorological Archiving System (MARS) of the European Centre for Medium Range Weather Forecasts (ECMWF). Kermanshah situated in West of Iran. Most of the surface of this region lies within the Zagros Mountains. The climate of the highlands is mild in summer and cold in winter, with heavy snowfall; only the province’s western strip belongs to the warm climate. The average temperatures in Kermanshah City are approximately 0⁰ C in January and 26⁰ C in July. The winds blowing from the Mediterranean Sea carry rainclouds, with an annual precipitation of up to 700mm in the highlands and about 400mm at Kermanshah City. Precipitation DataRain-GaugesIdentify of daily rainfall events Obtain amount of rain-gauges’ rainfall corresponding to their pixel Evaluate precipitation estimation products using RMSE, MAE, Bias, Mbias, Rbias, CC, POD, FAR and CSI IMERG, 3B42 and ERA- Interim products Extract daily precipitation Extract rainfall products in order to pixel forming of our area interest Fig. 1. Flowchart of research procedure. RMSEMAEBiasMbiasRbiasCC IMERG7.14.91-0.720.88-0.120.52 3B-427.725.39-1.590.75-0.250.42 ERA-Interim7.354.31-3.330.52-0.480.38 PODFARCSI IMERG0.680.420.47 3B420.510.570.30 ERA-Interim0.630.460.42 Table 2. Statistical indices of daily precipitation events (mid-March 2014 to February 2015) Table 3. Spatially averaged POD, FAR and CSI metrics for all precipitation range Satellite NoYes Rain GaugeNoCorrect negative (d)False alarms (b) YesMisses (c)Hits (a) ProductsTemporal resolutionSpatial resolutionRegions Availability Period IMERGhalf-hourly0.1 degree60⁰N - 60⁰S March 2014 – present 3B423-hourly0.25 degree50⁰N - 50⁰S 1997 - present ERA-INTERIMdaily0.125 degree90⁰N - 90⁰S 1979-present Table 2. Characteristics of Satellite/Model Precipitation Products Table 1. Contingency table Study Area Fig. 4. Spatial distribution of POD, FAR and CSI for all precipitation range PODFARCSI IMERG0.600.440.38 3B420.450.590.26 ERA-Interim0.270.520.21 Table 3. Spatially averaged POD, FAR and CSI metrics for precipitation above 5 mm/day