Abstract
Accurate estimation of precipitation is crucial for fundamental input to various hydrometeorological applications. Ground-based precipitation data suffer limitations associated with spatial resolution and coverage; hence, satellite precipitation products can be used to complement traditional rain gauge systems. However, the satellite precipitation data need to be validated before extensive use in the applications. Hence, we conducted a thorough validation of the Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals (IMERG) product for all of Iran. The study focused on investigating the performance of daily and monthly GPM IMERG (early, late, final, and monthly) products by comparing them with ground-based precipitation data at synoptic stations throughout the country (2014–2017). The spatial and temporal performance of the GPM IMERG was evaluated using eight statistical criteria considering the rainfall index at the country level. The rainfall detection ability index (POD) showed that the best IMERG product’s performance is for the spring season while the false alarm ratio (FAR) index indicated the inferior performance of the IMERG products for the summer season. The performance of the products generally increased from IMERG-Early to –Final according to the relative bias (rBIAS) results while, based on the quantile-quantile (Q-Q) plots, the IMERG-Final could not be suggested for the applications relying on extreme rainfall estimates compared to IMERG-Early and -Late. The results in this paper improve the understanding of IMERG product’s performance and open a door to future studies regarding hydrometeorological applications of these products in Iran.
Highlights
Precipitation plays a crucial role in the Earth’s hydrological cycle and is a fundamental input to a wide range of hydrological, meteorological, and climate model applications [1,2]
The performance of the products generally increased from Integrated Multi-satellite Retrievals for GPM (IMERG)-Early to –Final according to the relative bias results while, based on the quantile-quantile (Q-Q) plots, the IMERG-Final could not be suggested for the applications relying on extreme rainfall estimates compared to IMERG-Early and -Late
The study is one of the first IMERG Global Precipitation Measurement (GPM) product assessments at a country level taking into account temporal and geospatial properties
Summary
Precipitation plays a crucial role in the Earth’s hydrological cycle and is a fundamental input to a wide range of hydrological, meteorological, and climate model applications [1,2]. Accurate estimation of the precipitation amount and pattern is vital for improved prediction of water-related processes as well as reducing uncertainties for effective water resource management practices [3,4]. Ground-based measurements, i.e., rain gauges and weather radars, are considered a reliable source mainly at the local scale. At the regional and global scale, there are limitations for using ground-based measurements, in most developing countries [5]. Radar networks are often available where there is a coverage by rain gauges. Radars are Remote Sens. 2020, 12, 48; doi:10.3390/rs12010048 www.mdpi.com/journal/remotesensing
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