Abstract
The Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) products have been widely used, but their error and uncertainty characteristics over diverse climate regimes still need to be quantified. In this study, we focused on a systematic evaluation of TMPA’s error characteristics over mainland China, with an improved error-component analysis procedure. We performed the analysis for both the TMPA real-time and research product suite at a daily scale and 0.25° × 0.25° resolution. Our results show that, in general, the error components in TMPA exhibit rather strong regional and seasonal differences. For humid regions, hit bias and missed precipitation are the two leading error sources in summer, whereas missed precipitation dominates the total errors in winter. For semi-humid and semi-arid regions, the error components of two real-time TMPA products show an evident topographic dependency. Furthermore, the missed and false precipitation components have the similar seasonal variation but they counter each other, which result in a smaller total error than the individual components. For arid regions, false precipitation is the main problem in retrievals, especially during winter. On the other hand, we examined the two gauge-correction schemes, i.e., climatological calibration algorithm (CCA) for real-time TMPA and gauge-based adjustment (GA) for post-real-time TMPA. Overall, our results indicate that the upward adjustments of CCA alleviate the TMPA’s systematic underestimation over humid region but, meanwhile, unfavorably increased the original positive biases over the Tibetan plateau and Tianshan Mountains. In contrast, the GA technique could substantially improve the error components for local areas. Additionally, our improved error-component analysis found that both CCA and GA actually also affect the hit bias at lower rain rates (particularly for non-humid regions), as well as at higher ones. Finally, this study recommends that future efforts should focus on improving hit bias of humid regions, false error of arid regions, and missed snow events in winter.
Highlights
In China, flood and drought are two primary natural hazards, often causing heavy property damages and human casualties [1,2,3]
The 0.25 ̋ dataset was developed from 2419 rainfall gauges over mainland China from April 2008 to present, while the other 0.5 ̋ product was based on 756 national standard meteorological stations with longer time series that can date back to 1955
For winter, the underestimation of satellite precipitation over humid regions is mainly determined by missed precipitation, while the overestimation over arid and semi-arid regions mostly comes from false precipitation
Summary
In China, flood and drought are two primary natural hazards, often causing heavy property damages and human casualties [1,2,3]. 60 ̋ N–60 ̋ S and the gauge-adjusted, post-real-time 3B42V7 for research purposes (hereafter “V7”; two months latency) with spatial coverage of 50 ̋ N–50 ̋ S [5,6] These two quasi-global satellite precipitation products have been widely utilized in various hydrological and meteorological applications in China [7,8,9,10,11,12,13]. The error-component analysis technique treats these error sources separately, which in turn track the error sources better than the conventional approaches This helps both algorithm developers and data users to better understand the error features of satellite precipitation and their generation mechanisms. The goal of this paper is to systematically evaluate the Version-7 TMPA products over the entirety of mainland China, with the error-component analysis technique.
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