Evaluation of IMERG V07 Precipitation Datasets at Hourly and Daily Scales in Texas, USA

This study evaluates the performance of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) version 7 (IMERG v07) datasets (IMERG-Early, IMERG-Late, and IMERG-Final) in estimating precipitation at hourly and daily scales using PIERS station data from Texas collected from October 2023 to September 2025. Four stations were analyzed to evaluate precipitation occurrence, total precipitation, mean precipitation, 99th percentile extreme precipitation, and precipitation intensity. Model performance was assessed using both categorical and continuous statistical metrics, along with probability density function (PDF) and cumulative distribution function (CDF) analyses. IMERG datasets detected 53–75% of hourly precipitation events and 71–87% of daily precipitation events. IMERG-Late and IMERG-Final exhibited comparable performance in detecting precipitation events at the hourly timescale, whereas IMERG-Late performed better at the daily timescale across most stations and performance metrics. The ability of IMERG products to simulate precipitation totals was station-specific and depended on the temporal resolution level. At the hourly scale, IMERG-Final performed best at PIERS0035 and PIERS0034; IMERG-Early performed best at PIERS0030, and IMERG-Early and IMERG-Late performed equally well at PIERS0032. On the daily scale, IMERG-Early provided the best results at PIERS0030 and PIERS0032, whereas IMERG-Final performed better at PIERS0035 and PIERS0034. The performance of the IMERG datasets also varied across stations and temporal scales in simulating mean precipitation and different precipitation percentiles. Overall, although IMERG-Final is the calibrated dataset and is generally recommended for research applications, this study found that IMERG-Early and IMERG-Late outperformed IMERG-Final at specific temporal scales, for certain precipitation metrics, and at particular stations. The results further demonstrate that IMERG dataset performance varies across temporal scales, precipitation metrics, and observation sites.