Evaluation of satellite-based precipitation products from GPM IMERG and GSMaP over the three-river headwaters region, China

Abstract

The three-river headwaters region (TRHR) is the birthplace of the Yangtze River, the Yellow River and the Lantsang River in China. Based on the grid surface precipitation data released by China Meteorological Administration (CMA), this paper evaluated the accuracy and error components of four near-real-time satellite precipitation products (GSMaP-NRT, GSMaP-MVK, IMERG-Early and IMERG-Late) in the era of a GPM (Global Precipitation Measurement) in TRHR. The conclusions are as follows: (1) The precipitation in TRHR is concentrated in the east and south, and the precipitation in the west is very low. IMERG (Early and Late) has a good spatial distribution of precipitation, while GSMaP has an obvious spatial smoothing of precipitation distribution, and does not better highlight the local precipitation characteristics. (2) The inversion accuracy of the satellite products is the best in the source region of the Lantsang River, followed by the source region of the Yellow River. The satellite products all show the lower correlation coefficient and serious underestimation of precipitation in the west of the TRHR. In addition, the closer to the west of the TRHR, the lower hit rate and the higher false alarm rate of the satellite products, especially the NRT and MVK products. In the eastern margin of the Yellow River headwater region and the Lantsang River headwater Region, RMSE and overestimated precipitation were higher in NRT and MVK, and FAR was higher in spite of higher POD and CSI. (3) The errors of GSMaP in the source region of the Yellow River and the Lantsang River are mainly caused by misreporting precipitation and overestimating the precipitation level, while the errors of GSMaP in the west of the TRHR are mainly caused by missing measurements of precipitation events. The underestimated precipitation of IMERG mainly comes from the missed measurement of precipitation and the underestimate of precipitation level, and there is no large false precipitation. (4) In addition, we found that the satellite products in the lake distribution area of the TRHR have serious missed precipitation errors, indicating that the GPM satellite products have the poor detection ability of precipitation near plateau lakes. On the whole, the precipitation inversion accuracy of IMERG (Early and Late) products is higher, which can better detect the occurrence of precipitation events, but the estimation of precipitation level is still not accurate. The precision of precipitation of satellite products near inland lakes on the plateau is poor, so the algorithm improvement of new products needs to be further solved in the future.

Advantages of GSMaP Data for Multi‐Timescale Precipitation Estimation in Luzon

“…The evidence supporting this finding is presented in Figure 11d that indicates that the errors of IMERG‐F in regard to underestimating rainfall over Luzon originally existed in IMERG‐L. Possible reasons for the underestimation of rainfall by IMERG‐L have been suggested in earlier studies (Bogerd et al., 2021; Wang et al., 2021) that indicate that IMERG‐L tends to miss shallow rainfall events, and this may lead to underestimation of rainfall. Additionally, we note from Figures 11d and 11e that GSMaP‐M is better than is IMERG‐L for assessing eastern Luzon but not for western Luzon.…”

A Preliminary Assessment of the GSMaP Version 08 Products over Indonesian Maritime Continent against Gauge Data

“…In addition, the correlation of daily GSMaP data and RG points is also very dependent on the number of gauges in grids used in validation (Satgé et al 2019). Several studies in China that compared GSMaP Grid data with RG points also found a moderate correlation (Lu and Yong 2018; An et al 2020;Zhou et al 2020;Wang et al 2021a). In addition, moderate correlation values were also found in Vietnam (Gummadi et al 2022) and Thailand (Trang et al 2020).…”

Moisture source anomalies connected to flood‐drought changes over the three‐rivers headwater region of Tibetan Plateau

“…The intensified atmospheric hydrological cycle exerts a significant effect on precipitation (Held & Soden, 2006;Immerzeel et al, 2010Immerzeel et al, , 2020Lan et al, 2016;Xi et al, 2018). Numerous studies demonstrated that the precipitation over TRHR manifested a variation on multiple scales, particularly featured by a significant increase during the last decades (Cao & Pan, 2014;Shi et al, 2016;Xi et al, 2018;Ma et al, 2018;Yiyang et al, 2020;Yan et al, 2020;Hua et al, 2021;Xianhong et al, 2022;Shang et al, 2021aShang et al, , 2022Li et al, 2022b;Guo et al, 2022) and a dry-to-wet shift in around the late 1980s in the context of global climate change (Zhang et al, 2017a;Sun & Wang, 2018;Ji et al, 2020;Shang et al, 2022).…”