scholarly journals Suitability of TRMM Products with Different Temporal Resolution (3-Hourly, Daily, and Monthly) for Rainfall Erosivity Estimation

2020 ◽  
Vol 12 (23) ◽  
pp. 3924
Author(s):  
Xianghu Li ◽  
Zhen Li ◽  
Yaling Lin

Rainfall erosivity (RE) is a significant indicator of erosion capacity. The application of Tropical Rainfall Measuring Mission (TRMM) rainfall products to deal with RE estimation has not received much attention. It is not clear which temporal resolution of TRMM data is most suitable. This study quantified the RE in the Poyang Lake basin, China, based on TRMM 3B42 3-hourly, daily, and 3B43 monthly rainfall data, and investigated their suitability for estimating RE. The results showed that TRMM 3-hourly product had a significant systematic underestimation of monthly RE, especially during the period of April–June for the large values. The TRMM 3B42 daily product seems to have better performance with the relative bias of 3.0% in summer. At the annual scale, TRMM 3B42 daily and 3B43 monthly data had acceptable accuracy, with mean error of 1858 and −85 MJ∙mm/ha∙h and relative bias of 18.3% and −0.85%, respectively. A spatial performance analysis showed that all three TRMM products generally captured the overall spatial patterns of RE, while the TRMM 3B43 product was more suitable in depicting the spatial characteristics of annual RE. This study provides valuable information for the application of TRMM products in mapping RE and risk assessment of soil erosion.

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Guanghua Wei ◽  
Haishen Lü ◽  
Wade T. Crow ◽  
Yonghua Zhu ◽  
Jianqun Wang ◽  
...  

The comprehensive assessment of the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) V05B is important for benchmarking the product’s continued improvement and future development. The performance of IMERG V05B precipitation products was systematically evaluated using 542 precipitation gauges at multiple spatiotemporal scales from March 2014 to February 2017 over China. Moreover, IMERG V05B was compared with IMERG V04A, the Tropical Rainfall Measuring Mission (TRMM) 3B42, and the Climate Prediction Center Morphing technique (CMORPH)-CRT in this study. Categorical verification techniques and statistical methods are used to quantify their performance. Results illustrate the following. (1) Except for IMERG V04A’s severe underestimation over the Tibetan Plateau (TP) and Xinjiang (XJ) with high negative relative biases (RBs) and CMORPH-CRT’s overestimation over XJ with high positive RB, the four satellite-based precipitation products generally capture the same spatial patterns of precipitation over China. (2) At the annual scale over China, the IMERG products do not show an advantage over its predecessor (TRMM 3B42) in terms of RMSEs, RRMSEs, and Rs; meanwhile, the performance of IMERG products is worse than TRMM 3B42 in spring and summer according to the RMSE, RRMSE, and R metrics. Between the two IMERG products, IMERG V05B shows the anticipated improvement (over IMERG V04A) with a decrease in RMSE from 0.4496 to 0.4097 mm/day, a decrease of RRMSE from 16.95% to 15.44%, and an increase of R from 0.9689 to 0.9759 during the whole study period. Similar results are obtained at the seasonal scale. Among the four satellite products, CMORPH-CRT shows the worst seasonal performance with the highest RMSE (0.6247 mm/day), RRMSE (23.55%), and lowest R (0.9343) over China. (3) Over XJ and TP, IMERG V05B clearly improves the strong underestimation of precipitation in IMERG V04A with the RBs of 5.2% vs. −21.8% over XJ, and 2.78% vs. −46% over TP. Results at the annual scale are similar to those obtained at the seasonal scale, except for summer results over XJ. While, over the remaining subregions, the two IMERG products have a close performance; meanwhile, IMERG V04A slightly improves IMERG V05B’s overestimation according to RBs (except for HN) at the annual scale. However, all four products are unreliable over XJ at both an annual and seasonal scale. (4) Across all products, TRMM 3B42 best reproduces the probability density function (PDF) of daily precipitation intensity. (5) According to the categorical verification technique in this study, both IMERG products yield better results for the detection of precipitation events on the basis of probability of detection (POD) and critical success index (CSI) categorical evaluations compared to TRMM 3B42 and CMORPH-CRT over China and across most of the subregions. However, all four products have room for further improvement, especially in high-latitude and dry climate regions. These findings provide valuable feedback for both IMERG algorithm developers and data set users.


2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Junzhi Liu ◽  
Zheng Duan ◽  
Jingchao Jiang ◽  
A-Xing Zhu

This study conducted a comprehensive evaluation of three satellite precipitation products (TRMM (Tropical Rainfall Measuring Mission) 3B42, CMORPH (the Climate Prediction Center (CPC) Morphing algorithm), and PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks)) using data from 52 rain gauge stations over the Meichuan watershed, which is a representative watershed of the Poyang Lake Basin in China. All the three products were compared and evaluated during a 9-year period at different spatial (grid and watershed) and temporal (daily, monthly, and annual) scales. The results showed that at daily scale, CMORPH had the best performance with coefficients of determination (R2) of 0.61 at grid scale and 0.74 at watershed scale. For precipitation intensities larger than or equal to 25 mm, RMSE% of CMORPH and TRMM 3B42 were less than 50%, indicating CMORPH and TRMM 3B42 might be useful for hydrological applications at daily scale. At monthly and annual temporal scales, TRMM 3B42 had the best performances, with highR2ranging from 0.93 to 0.99, and thus was deemed to be reliable and had good potential for hydrological applications at monthly and annual scales. PERSIANN had the worst performance among the three products at all cases.


2018 ◽  
Vol 136 (1-2) ◽  
pp. 15-30 ◽  
Author(s):  
Chaojun Gu ◽  
Xingmin Mu ◽  
Peng Gao ◽  
Guangju Zhao ◽  
Wenyi Sun ◽  
...  

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1380 ◽  
Author(s):  
Weilin Liu ◽  
Lina Liu

Global warming has resulted in unevenly distributed changes in precipitation and evapotranspiration, which has some influence on dry/wet conditions, thus exerting a tremendous impact on national life and the social economy, especially agricultural production. In order to characterize the dry/wet variations in the Poyang Lake basin during 1958–2013, based on the potential evapotranspiration (PET) estimated by the Thornthwaite (TH) and Penman–Monteith (PM) formulas, two types of Standardized Precipitation Evapotranspiration Index (SPEI), namely SPEI_th and SPEI_pm, were calculated in this study. The characteristic of dry/wet variations in the Poyang Lake basin was analyzed and a comparative analysis of two SPEIs was conducted. The results indicate that both SPEI series showed a wet trend in the Poyang Lake basin on an annual scale as well as seasonal scales during 1958–2013, except for spring and autumn. A drying trend was observed in spring, while in autumn, the dry and wet conditions in two SPEIs had opposite trends. However, all trends from two SPEIs were not significant, except for summer SPEI_pm. Meanwhile, significant positive correlations were detected between precipitation and two SPEIs, with the correlation coefficients above 0.95, whereas negative correlations were detected between PET and two SPEIs, with the correlation coefficients ranging from −0.17 to −0.85. This indicates that precipitation was the main climatic factor to determine change in dry/wet conditions in the Poyang Lake basin. Although there were obvious differences between the accumulated values of the Penman–Monteith-based PET (ET_pm) and Thornthwaite-based PET (ET_th), trends in the SPEI_pm series were generally consistent with those in the SPEI_th series, revealing that the method for PET calculation was not critical to the change in dry/wet conditions. Moreover, the results of the conditional probability of SPEI_pm and SPEI_th show that both SPEI_pm and SPEI_th could detect wet or dry events that were identified by SPEI_pm or SPEI_th.


Sign in / Sign up

Export Citation Format

Share Document