# Performance Evaluation of IMERG GPM Products during Tropical Storm Imelda
## 1 Introduction
Obtaining reliable and accurate precipitation data has been a challenge for scientists and users, even though precipitation data is vital for many environmental and hydrological analyses [12; 13]. To verify and enhance predictions, precipitation measurements are generally obtained through rain gauges, weather radars, and satellite sensors [14; 15]. All of these data sources provide measurements with specific spatiotemporal resolutions and are distinguished by their instrumental and environmental uncertainty. The difference in the spatiotemporal resolutions of the data introduces a novel challenge for the comparative evaluation of the measurements in hydrological modeling and analysis studies [16]. Historically, rain gauges have been the main source of precipitation data with variable temporal frequencies at ground level. Rain gauge measurements are considered to be ground-truth observations at the point level in comparison to radar and satellite sensors [17]. Conversely, the sparse distribution of rain gauges makes it harder to interpret the actual precipitation for coverage over larger areas [18; 19]. Spatial interpolation of the gauge data in mountainous regions is more challenging, considering the geography of the landscape [20]. The use of ground-based radar allows users to have a higher spatiotemporal resolution of the precipitation data and increases the understanding of storm structures and precipitation estimates. However, the acquisition of radar data is sometimes limited in mountainous regions, as the terrain complexity and radar beam obstruction effects distort the measurements [21; 22; 23; 24; 25; 26; 27; 28]. Moreover, the construction and maintenance of radar systems in difficult terrain is expensive and unfeasible for almost every country [29]. Combining the strengths and weaknesses of both measurement systems, methods such as Bayesian combination or conditional merging, ordinary kriging correction, and mean bias correction have been developed for better precipitation estimates [30; 31; 32; 33]. The Global Precipitation Measurement (GPM) mission, a successor of the Tropical Rainfall Measuring Mission (TRMM), has been providing precipitation estimates since 2014 [29]. Precipitation estimates using the GPM satellite constellation have major advantages over the other previous satellite precipitation products in terms of global spatial coverage and temporal and spatial resolution [29]. After the introduction of the Integrated Multi-Satellite Retrievals for the Global Precipitation Mission (IMERG) products in 2014, the use of satellite-based precipitation estimates in hydrologic applications has seen great interest from researchers. Researchers have validated the IMERG products using ground-based observations (radar and rain gauges) and found an overall improvement in precipitation estimates over previous similar products, such as TRMM, PERSIANN, CMORPH, GSMAP, and MSWEP [34; 35]. Stage-IV radar data have been widely used as a validation dataset to evaluate the performance of the IMERG products, as researchers aim to improve the algorithm of the IMERG products [36; 37; 38; 39]. Data acquisition from the satellite-based measurements can be almost real-time, with only a 4-hr latency between capture and acquisition and 3.5 months latency for the availability of post-real-time research data. IMERG GPM precipitation product estimates overcome the limitations of both gauge and radar systems by warranting real-time data and global spatial coverage [29]. These products are less affected by localized weather or terrain conditions during weather events such as storms, tornadoes, and flooding, and by other technical issues, than measurements obtained with ground-based radar instruments. Although these products provide precipitation estimates with near-global spatial coverage, especially valuable for mountainous regions, the spatial resolution is still rather coarse [40; 41; 42; 43].