Abstract
Satellite-based precipitation products are becoming available at very high temporal and spatial resolutions, which has accelerated their use in various hydro-meteorological and hydro-climatological applications. Because the quantitative accuracy of such products is affected by numerous factors related to atmospheric and terrain properties, validating them over different regions and environments is needed. This study investigated the performance of two high-resolution global satellite-based precipitation products: the climate prediction center MORPHing technique (CMORPH) and the latest version of the Integrated Multi-SatellitE Retrievals for the Global Precipitation Mission (GPM) algorithm (IMERG), V06, over the United Arab Emirates from 2010 through 2018. The estimates of the products and that of 71 in situ rain gauges distributed across the country were compared by employing several common quantitative, categorical, and graphical statistical measures at daily, event-duration, and annual temporal scales, and at the station and study area spatial scales. Both products perform quite well in rainfall detection (above 70%), but report rainfall not observed by the rain gauges at an alarming rate (more than 30%), especially for light rain (lower quartile). However, for moderate and intense (upper quartiles) rainfall rates, performance is much better. Because both products are highly correlated with rain gauge observations (mostly above 0.7), the satellite rainfall estimates can probably be significantly improved by removing the bias. Overall, the CMORPH and IMERG estimates demonstrate great potential for filling spatial gaps in rainfall observations, in addition to improving the temporal resolution. However, further improvement is required, regarding the overestimation and underestimation of small and large rainfall amounts, respectively.
Highlights
As a vital component of the hydrologic cycle, precipitation is characterized by its chaotic nature, the short time scale over which it can occur and evolve, and high variability in the temporal and spatial domains [1,2]
Precipitation rates and accumulations can be measured directly at the ground level by using sensors, for instance, rain gauges and disdrometers, or such information can be inferred from measurements of remote sensing instruments such as ground-based and airborne radar, as well as microwave and infrared (IR) sensors aboard satellites [3,4]
Satellite-based precipitation products provide the means for timely near-global precipitation estimates
Summary
As a vital component of the hydrologic cycle, precipitation is characterized by its chaotic nature, the short time scale over which it can occur and evolve, and high variability in the temporal and spatial domains [1,2]. Rainfall measurements by remote sensors provide large areal coverage and are available at high spatial and temporal resolutions; their accuracy is limited because of different sources of systematic and random errors. Ground-based weather radars estimate precipitation at very high spatial and temporal resolutions, with real-time monitoring over a large area (relative to rain gauges) [13,14]. Realizing the huge potential of satellite-based precipitation products, researchers across the world have conducted significant studies to verify and validate them [5,16,17,18,19,20,21,22,23,24] Their performance must be further verified, in arid and semi-arid regions and regions with complex terrain [23]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
