Performance Evaluation of Version 5 (V05) of Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) over the Tianshan Mountains of China

Abstract

This study evaluated the performance of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) version 5 (V05) Early-run and Final-run (IMERG-E and IMERG-F, respectively) products over the Tianshan Mountains. For comparison, the accuracies of two Tropical Rainfall Measuring Mission (TRMM) products (3B42RT and 3B42V7) were also analyzed. Performance of the satellite-based precipitation products (SPPs) was analyzed at daily to annual scales from April 2014 to October 2017. Results showed that: (1) IMERG-F and 3B42V7 performed better than IMERG-E and 3B42RT in the characterization of spatiotemporal variability of precipitation; (2) Precipitation estimates from IMERG-F were in the best overall agreement with the gauge-based data, followed by IMERG-E and 3B42V7 on all temporal scales; (3) IMERG-E and 3B42RT products were failed to provide accurate precipitation amounts, whereas IMERG-F and 3B42V7 were able to provide accurate precipitation estimates with the lowest relative biases (4.98% and −1.71%, respectively) and RMSE (0.58 mm/day and 0.76 mm/day, respectively); (4) The enhancement from the IMERG Early-run to the Final-run to capture the moderate to heavy precipitation events was not evident; (5) On seasonal scale, IMEGR-F performed better than all other SPPs, particularly during the spring season with negligible bias (0.28%). It was deduced that IMERG-F was capable of replacing TRMM products.

Assessment of IMERG-V06 Precipitation Product over Different Hydro-Climatic Regimes in the Tianshan Mountains, North-Western China

“…Gauge-based records showed a gradual decrease in the average daily precipitation amounts from the northwest to the southeast. Similar distributions of average daily precipitation in the Tianshan Mountains were found in a previous study [41]. Generally, all SPPs were able to capture the spatial distribution of precipitation, albeit SPPs showed considerable overestimation/underestimation of precipitation amounts at different stations.…”

“…The Chinese National Meteorological Information Centre had ensured the high quality of daily time-series data of the selected gauging stations. Moreover, many recent hydrological and climatological studies have successfully utilized the precipitation data of the considered gauging stations [5,41,44,48]. Considering the availability and quality of the gauge-based observations, this study was designed for the period from June 2014 to December 2017.…”

“…Although several previous studies have reported the performance of satellite-based precipitation products (including GPM-and TRMM-based products) in central Asia [41][42][43][44], the error characteristics and enhancements in the latest version of IMERG- V06 have not yet been reported. Comparative evaluations of this newly released precipitation product in different topographic conditions and climatic systems are very important for further enhancements in algorithms, and for hydrological, meteorological, agricultural, environmental, and ecological studies.…”

Nine-Year Systematic Evaluation of the GPM and TRMM Precipitation Products in the Shuaishui River Basin in East-Central China

“…With their annual CC and RB values exceeding the good performance thresholds, both IMERG_F and 3B42 can be regarded as reliable sources of monthly precipitation in the SRB. Similar to our study, previous studies have also observed satisfactory performance of IMERG_F and 3B42 in monthly rainfall estimation [43,44]. Figure 3 compares the spatial distribution of the four annual continuous evaluation metrics among the SPPs at the monthly scale.…”

Assessment of PERSIANN-CCS, PERSIANN-CDR, SM2RAIN-ASCAT, and CHIRPS-2.0 Rainfall Products over a Semi-Arid Subtropical Climatic Region

“…Recent advancements in satellite-mounted rainfall detection sensors and data retrieval algorithms have enabled researchers and other data users to utilize rainfall data at fine spatial and temporal scales. The satellite-based rainfall products (SRPs) can provide continuous information on rainfall's occurrence, intensity, and quantity [6,7]. Generally, these SRPs provide rainfall estimates based on data from passive microwave (MW) sensors, infrared (IR) sensors, or a combination of the two datasets.…”