Statistical and Hydrological Comparisons between TRMM and GPM Level-3 Products over a Midlatitude Basin: Is Day-1 IMERG a Good Successor for TMPA 3B42V7?

Abstract

The goal of this study is to quantitatively intercompare the standard products of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) and its successor, the Global Precipitation Measurement (GPM) mission Integrated Multisatellite Retrievals for GPM (IMERG), with a dense gauge network over the midlatitude Ganjiang River basin in southeast China. In general, direct comparisons of the TMPA 3B42V7, 3B42RT, and GPM Day-1 IMERG estimates with gauge observations over an extended period of the rainy season (from May through September 2014) at 0.25° and daily resolutions show that all three products demonstrate similarly acceptable (~0.63) and high (0.87) correlation at grid and basin scales, respectively, although 3B42RT shows much higher overestimation. Both of the post-real-time corrections effectively reduce the bias of Day-1 IMERG and 3B42V7 to single digits of underestimation from 20+% overestimation of 3B42RT. The Taylor diagram shows that Day-1 IMERG and 3B42V7 are comparable at grid and basin scales. Hydrologic assessment with the Coupled Routing and Excess Storage (CREST) hydrologic model indicates that the Day-1 IMERG product performs comparably to gauge reference data. In many cases, the IMERG product outperforms TMPA standard products, suggesting a promising prospect of hydrologic utility and a desirable hydrologic continuity from TRMM-era product heritages to GPM-era IMERG products. Overall, this early study highlights that the Day-1 IMERG product can adequately substitute TMPA products both statistically and hydrologically, even with its limited data availability to date, in this well-gauged midlatitude basin. As more IMERG data are released, more studies to explore the potential of GPM-era IMERG in water, weather, and climate research are urgently needed.

Multiscale Comparative Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products from 2015 to 2017 over a Climate Transition Area of China

“…PDF emphasizes lighter rainfall rates, making it more suitable for evaluating the ability of satellite precipitation to detect light precipitation [14]. The PDF of satellite precipitation shown in Figure 8a was consistent with that of gauge observations for the rainfall rate greater than 0.5 mm/day and tended to underestimate the gauge precipitation in this study.…”

Assessment of the Latest GPM-Era High-Resolution Satellite Precipitation Products by Comparison with Observation Gauge Data over the Chinese Mainland

“…Tang et al found that GPM IMERG performed well in hydrological modeling simulation in the mid-latitude Ganjiang River basin in southeast China, outperforming its predecessor TRMM 3B42 [40]. W. Qi et al applied GSMap-MVK data to perform discharge simulations in the Biliu basin located in northwestern China, and results showed that GSMap-MVK had a huge advantage over TRMM 3B42 for discharge simulations, especially at the monthly and inter-annual scales [18]. The two studies cited above also found that good discharge simulation depended on the appropriate match between the hydrological model and precipitation product, as a better precipitation product did not necessarily guarantee a better discharge simulation.…”

“…Additionally, for most developing countries, such as China, with insufficient spatial coverage of in-situ data, long time delays for data processing and availability, and the absence of data sharing across disciplines, the application of satellite-derived precipitation data has shown significant advantages. However, the sources of inherent error associated with these products, which stem from indirect physical estimates of rainfall, have not been well understood to date, especially for the latest HRPP grid data, and would have a significant influence on their application [18]. Therefore, it is essential to evaluate their accuracy and error characteristics by comparing them against observations from precipitation gauges before various applications are utilized.…”

Assessment of GPM and TRMM Multi-Satellite Precipitation Products in Streamflow Simulations in a Data-Sparse Mountainous Watershed in Myanmar

“…Several previous studies [31][32][33][34][35][36][37] found that, although 3B42V7 and IMERG products effectively capture the spatiotemporal variations of precipitation in different regions around the world, these estimates still contain considerable errors when compared with ground observations. Given that precipitation inputs are among the most dominant uncertainty sources for hydrological models, satellite precipitation products must be bias-corrected when adopted as the input of a hydrological model for streamflow simulations.…”