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Articles

Comprehensive comparison of daily IMERG and GSMaP satellite precipitation products in Ardabil Province, Iran

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Pages 3139-3153 | Received 27 Mar 2018, Accepted 20 Aug 2018, Published online: 08 Nov 2018
 

ABSTRACT

The measurement of precipitation is essential for most environmental studies such as drought monitoring, watershed operations, water hazard management, etc. Development of satellite products has improved their applicability in environmental modelling and could proffer an alternative to gauge-based precipitation data, particularly in areas where there is no sufficient number of gauges or poor gauge distribution but they should be evaluated in different areas using ground-based data as references. In the present study, daily Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM- IMERG- Final (Version 5)) and Global Satellite Mapping of Precipitation-Moving Vector with Kalman filter (GSMaP-MVK (Version 7)) precipitation products were evaluated in comparison with gauges observations in Ardabil province, north-west of Iran, from 1 January 2016 to 21 October 2017. Several statistical indices including linear correlation coefficient, Bias (B), Multiplicative Bias (Bm), Relative Bias (Br), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Probability of Detection (POD), False Alarm Ratio (FAR) and Critical Success Index (CSI) were used for evaluation. The results showed that the correlation between GSMaP estimates and gauge observations is higher than that of IMERG (0.42 and 0.33, respectively). On the other hand, GSMaP tends to overestimate precipitation substantially, while IMERG is involved in both under and overestimation slightly. Although these products could not show very high accuracy in precipitation estimation, the estimated precipitation values by IMERG were relatively closer to gauge records and can be used as a replacement for gauge observation in the study area where there is lack of weather stations.

Acknowledgments

We acknowledge NASA and JAXA which provide IMERG and GSMaP data, respectively, and develop and compute their algorithms and make them accessible online. We acknowledge Ardabil Province Meteorological Organization (MO) and Ghasem Hozabrpoor (MO data officer) for providing the gauge-based data. Moreover, Mohamed Saber (Assistant Professor, Assiut University, Egypt) who helped in improving the article after the review process is appreciated.

Disclosure statement

No potential conflict of interest was reported by the authors.

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