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In this research work, the latest version 7 (V7) of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 product is evaluated over Greece, at five different temporal scales; 3, 6, 12, 24 and 48 hrs. Evaluation consists in assessing the performance of the product in reproducing observed, non-zero precipit...
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Evaluating the accuracy (ie, estimating the sensitivity and specificity) of new diagnostic tests without the presence of a gold standard is of practical meaning and has been the subject of intensive study for several decades. Existing methods use 2 or more diagnostic tests under several basic assumptions and then estimate the accuracy parameters vi...
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... However, as shown in Figures 6 and 7, except for prevailing afternoon precipitation, diurnal variation of precipitation in gauge observations was largely inconsistent with TRMM data, indicating that TRMM data can well capture prevailing afternoon precipitation but performs poorly at capturing hourly precipitation at other times. A study by Kotsifakis et al. [42] also pointed out that version 7 of the TRMM 3B42 precipitation data can hardly captain the characteristics of 3-hour, 6-hour, 12-hour, 24-hour, and 48-hour precipitation. ...
Diurnal variation of precipitation is a fundamental periodic signal of local climate. Comprehensive study of diurnal variation of precipitation is helpful in studying the formation of local climate and validating satellite precipitation products. In this study, a comparison is drawn between precipitation gauge observations and Tropical Rainfall Measuring Mission (TRMM) 3B42 data on diurnal variation of precipitation. First, using the K-means clustering algorithm, stations with gauge observations and pixels with TRMM data are divided into different groups according to the diurnal variation of precipitation, respectively. In each group, the stations have similar diurnal variation of precipitation. Then maps of diurnal variation of precipitation for gauge observations and TRMM data are obtained. According to these maps, the diurnal variation of precipitation over the contiguous United States (CONUS) presents seasonal variability in both gauge observations and TRMM data. In addition, the diurnal variation of precipitation shows clustered features in space. However, the spatial patterns of the obtained maps do not match, and the TRMM satellite data perform poorly in capturing the hourly precipitation event. Finally, the possible mechanism behind the prevailing nocturnal precipitation over the middle of the CONUS is discussed, with the prevailing nocturnal precipitation judged likely to be strongly related to the mountain-plains solenoid (MPS) circulation.
... The study also discovered an underestimation of TMPA 3B42 research version at a 3-h timescale. Another study [48] conducted in Greece evaluated TMPA 3B42 with rain gauge data at a high temporal resolution of 3 h and found a correlation coefficient value slightly less than 0.3 between both sources. Nevertheless, this correlation increased with aggregated time intervals, i.e., 6 h, 12 h, 24 h, and 48 h, and gained a peak value of 0.6 at a maximum aggregated interval. ...
... 0.65, 0.27, 0.52, 0.51, and 0.64, respectively. These scores are much better when compared to two erstwhile studies [48,52]. Categorical indices' scores at different rainfall intensities reveal that the TMPA products detect plenty of spurious rain events at light rain rates (rain rates <2 mm/h). ...
Flash floods which occur due to heavy rainfall in hilly and semi-hilly areas may prove deleterious when they hit urban centers. The prediction of such localized and heterogeneous phenomena is a challenge due to a scarcity of in-situ rainfall. A possible solution is the utilization of satellite-based precipitation products. The current study evaluates the efficacy of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) three-hourly products, i.e., 3B42 near-real-time (3B42RT) and 3B42 research version (3B42V7) at a sub-daily time scale. Various categorical indices have been used to assess the capability of products in the detection of rain/no-rain. Hourly rain rates are assessed by employing the most commonly used statistical measures, such as correlation coefficients (CC), mean bias error (MBE), mean absolute error (MAE), and root-mean-square error (RMSE). Further, a diurnal analysis is performed to authenticate TMPA’s performance in specific hours of the day. In general, the results show the good capability of both TMPA products in the detection of rain/no-rain events in all seasons except winter. Specifically, 3B42V7 performed better than 3B42RT. Moreover, both products detect a high number of rainy days falsely in light rain ranges. Regarding rainfall measurements, TMPA products exhibit an overall underestimation. Seasonally, 3B42V7 underestimates rainfall in monsoon and post-monsoon, and overestimates in winter and pre-monsoon. 3B42RT, on the other hand, underestimates rainfall in all seasons. A greater MBE and RMSE are found with both TMPA rain measurements in monsoon and post-monsoon seasons. Overall, a weak correlation and high MBE between the TMPA (3B42RT, 3B42V7) and reference gauge hourly rain rates are found at a three-hourly time scale (CC = 0.41, 0.38, MBE = −0.92, −0.70). The correlation is significant at decadal (CC = 0.79, 0.77) and monthly (CC = 0.91, 0,90) timescales. Furthermore, diurnal rainfall analysis indicates low credibility of 3B42RT to detect flash flooding. Within the parameters of this study, we conclude that the TMPA products are not the best choice at a three-hourly time scale in hilly/semi-hilly areas of Pakistan. However, both products can be used at daily, yet more reliably above daily, time scales, with 3B42V7 preferable due to its consistency.
