Abstract
The influence of topographical characteristics and rainfall intensity on the accuracy of satellite precipitation estimates is of importance to the adoption of satellite data for hydrological applications. This study evaluates the three GPM IMERG V05B products over the arid country of Saudi Arabia. Statistical indices quantifying the performance of IMERG products were calculated under three evaluation techniques: seasonal-based, topographical, and rainfall intensity-based. Results indicated that IMERG products have the capability to detect seasons with the highest precipitation values (spring) and seasons with the lowest precipitation (summer). Moreover, results showed that IMERG products performed well under various rainfall intensities, particularly under light rain, which is the most common rainfall in arid regions. Furthermore, IMERG products exhibited high detection accuracy over moderate elevations, whereas it had poor performance over coastal and mountainous regions. Overall, the results confirmed that the performance of the final-run product surpassed the near-real-time products in terms of consistency and errors. IMERG products can improve temporal resolution and play a significant role in filling data gaps in poorly gauged regions. However, due to the errors in IMERG products, it is recommended to use sub-daily rain gauge data in satellite calibration for better rainfall estimation over arid and semiarid regions.
Highlights
Precipitation is one of the most complex natural process in the hydrological cycle that undergoes momentous variability at both the spatial and temporal scales
Passive microwave (PMW) measurements have demonstrated high performance at the global scale compared to algorithms that were based on IR and VI, while precipitation estimations that are based on IR have a higher temporal resolution than others [8,9]
A more recent study validated the IMERG products over Saudi Arabia, and the findings showed that the final-run product had a better performance than other products in detecting and estimating precipitation in the study area [4]
Summary
Precipitation is one of the most complex natural process in the hydrological cycle that undergoes momentous variability at both the spatial and temporal scales. Precipitation measurements at a high spatial and temporal resolution are crucial to properly simulate the hydrological states of natural systems. In the last three decades, meteorologists and hydrologists were attracted by advancements in satellite information technology; primarily their focus was on developing algorithms to retrieve precipitation data from information remotely collected by these satellites. These algorithms estimate precipitation amounts from the characteristics of clouds as interpreted from infrared (IR), visible (VI), and microwave (MW) satellite images [7].
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