Evaluation of Satellite Rainfall Estimates over the Chinese Mainland

Abstract

Abstract:Benefiting from the high spatiotemporal resolution and near-global coverage, satellite-based precipitation products are applied in many research fields. However, the applications of these products may be limited due to lack of information on the uncertainties. To facilitate applications of these products, it is crucial to quantify and document their error characteristics. In this study, four satellite-based precipitation products (TRMM-3B42, TRMM-3B42RT, CMORPH, GSMaP) were evaluated using gauge-based rainfall analysis based on a high-density gauge network throughout the Chinese Mainland during [2003][2004][2005][2006]. To quantitatively evaluate satellite-based precipitation products, continuous (e.g., ME, RMSE, CC) and categorical (e.g., POD, FAR) verification statistics were used in this study. The results are as follows: (1) GSMaP and CMORPH underestimated precipitation (about −0.53 and −0.14 mm/day, respectively); TRMM-3B42RT overestimated precipitation (about 0.73 mm/day); TRMM-3B42, which is the only dataset corrected by gauges, had the best estimation of precipitation amongst all four products; (2) GSMaP, CMORPH and TRMM-3B42RT overestimated the frequency of low-intensity rainfall events; TRMM-3B42 underestimated the frequency of low-intensity rainfall events; GSMaP underestimated the frequency of high-intensity rainfall events; TRMM-3B42RT tended to overestimate the OPEN ACCESS Remote Sens. 2014, 6 11650 frequency of high-intensity rainfall events; TRMM-3B42 and CMORPH produced estimations of high-intensity rainfall frequency that best aligned with observations; (3) All four satellite-based precipitation products performed better in summer than in winter. They also had better performance over wet southern region than dry northern or high altitude regions. Overall, this study documented error characteristics of four satellite-based precipitation products over the Chinese Mainland. The results help to understand features of these datasets for users and improve algorithms for algorithm developers in the future.

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

“…Most of the low CC values for the two products were located in northern China, in regions of higher latitudes, and in arid northwestern China, which illustrates that the performance of satellite-based precipitation products is not good over northern arid and semi-arid China. This result is consistent with previous findings from Qin [33]. Overall, GSMap-Gauge exhibited the best correlation over most of China (almost 90% of CC values were greater than 0.6 and about half of them were greater than 0.8).…”

“…However, GSMap-Gauge underestimated precipitation by about 0.04 mm/day. Earlier work in China [33] found that the older GSMap product (GSMap-MVK version 4) also underestimated precipitation by about 0.53 mm/day over the period from 2003 to 2006. Although GSMap-Gauge was corrected by observational data in this study, it still resulted in negative ME values.…”

Evaluation of IMERG and TRMM 3B43 Monthly Precipitation Products over Mainland China

“…Obviously, IMERG products can provide many more spatial details related to precipitation than TRMM 3B43 products. In North China, TRMM 3B43 creates many isolated grid boxes of anomalous overestimation; Chen [25] reported similar findings based on the TRMM 3B42 dataset. As the interval of observation improved from 3 h for TRMM to 30 min for GPM, many more samples of precipitation were attained by IMERG, so many data can efficiently decrease the power of certain anomalous value.…”

“…In terms of QZ, the possible reason for this poor correlation is that most of this region stands at high elevations (over 4000 m). Many previous studies had revealed that TMPA products perform poorly in mountainous area [25,53,54]. These factors also lead to greater overestimation of annual precipitation across QZ and XJ than that in other regions.…”

“…This might be due to the fact that YG is located in the Yunnan-Guizhou Plateau, which has a higher elevation and more rugged terrain than the other two sub-regions (Figure 1). Many studies indicated complex topography might significantly influence the quality of satellite precipitation estimates [24,25,27].…”