Hydrological Utility and Uncertainty of Multi-Satellite Precipitation Products in the Mountainous Region of South Korea

Kim, Jong Pil; Jung, Il‐Won; Park, Kyung Won; Yoon, Sun‐Kwon; Lee, Dong-Hee

doi:10.3390/rs8070608

Cited by 40 publications

(25 citation statements)

References 53 publications

(84 reference statements)

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“…We found higher correlation coefficients with TRMM (r = 0.7, Figure 6a) and lower coefficients with Hydroe (r = 0.51, Figure 6b) than those reported by Jiang et al [19] (r = 0.66). However, our results were slightly lower than those of Kim et al [21], who identified …”

Section: Discussioncontrasting

confidence: 56%

“…The Sapucaí watershed has an average annual rainfall of 1200 mm, while Paraíba state, which is located in the semiarid region, varies from 300 to 1000 mm. Studies conducted in the mountainous regions of South Korea [21] and China [19] showed different r values. We found higher correlation coefficients with TRMM (r = 0.7, Figure 6a) and lower coefficients with Hydroe (r = 0.51, Figure 6b) than those reported by Jiang et al [19] (r = 0.66).…”

Section: Discussionmentioning

confidence: 99%

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Validation of Satellite Rainfall Products over a Mountainous Watershed in a Humid Subtropical Climate Region of Brazil

2017

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Abstract:Remote sensing allows for the continuous and repetitive measurement of rainfall values. Satellite rainfall products such as Tropical Rainfall Measurement Mission (TRMM) 3B42 and the Hydroestimator (Hydroe) can be potential sources of data for hydrologic applications, mainly in areas with irregular and sparse spatial distributions of traditional rain gauge stations. However, the accuracy of these satellite rainfall products over different spatial and temporal scales is unknown. In this study, we examined the potential of the TRMM 3B42 and Hydroe rainfall products to provide reliable rainfall estimates for a mountainous watershed in a humid subtropical climate region of Brazil. The purpose was to develop useful guidelines for future hydrologic studies on the potential and uncertainties of the rainfall products at different spatial and temporal resolutions. We compared the satellite products to reference rainfall data collected at 11 rain gauge stations irregularly distributed in the area. The results showed different levels of accuracy for each temporal scale evaluated. TRMM 3B42 performed better at the daily, monthly, and seasonal scales than Hydroe, while Hydroe presented a better correlation at the annual scale. In general, TRMM 3B42 overestimated the rainfall over the watershed at all evaluated temporal scales, whereas Hydroe underestimated it except for June-August at the seasonal scale. An evaluation based on contingency tables indicated that TRM 3B42 was better able to represent the local rainfall than Hydroe. The findings of this study indicate that satellite rainfall products are better suited for applications at the monthly and annual scales rather than the daily scale.

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Section: Discussioncontrasting

confidence: 56%

Section: Discussionmentioning

confidence: 99%

Validation of Satellite Rainfall Products over a Mountainous Watershed in a Humid Subtropical Climate Region of Brazil

2017

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“…GSMaP provides a series of precipitation estimates with different latencies, such as near-real-time product (GSMaP-NRT), post-real-time product with MW-IR reanalysis (GSMaP-MVK), and gauge-corrected post-real-time product (GSMaP-GAUGE). These products have been used for hydrological applications, such as flash flood simulations in the Nile River basin in Egypt [51], the Huong River basin in Vietnam [52], the Karpuz River basin in Turkey [10], and the Jhelum, Chenab, and upper Indus River basins in Pakistan [53,54]; flood inundation modeling in the Thua Thien Hue Province in Vietnam [55] and the Mundeni Aru River basin in Sri Lanka [9]; daily streamflow simulations in the Tocantins-Araguaia basin in Brazil [7], the Soyang dam basin in South Korea [56], and the Biliu basin in China [8]; annual runoff analysis in West Africa [57]; and global surface runoff mapping [58]. However, most of these studies [7][8][9][10][51][52][53][54][55][56][57] mainly adopted TRMM-era GSMaP SPPs (e.g., GSMaP versions 04 and 05) for hydrological evaluations or applications, and the hydrological assessment of GPM-era GSMaP SPPs (e.g., versions 06 and 07) was rarely reported.…”

Section: Introductionmentioning

confidence: 99%

Applications of TRMM- and GPM-Era Multiple-Satellite Precipitation Products for Flood Simulations at Sub-Daily Scales in a Sparsely Gauged Watershed in Myanmar

et al. 2019

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Tropical Rainfall Measuring Mission (TRMM) and its successor, Global Precipitation Measurement (GPM), have provided hydrologists with important precipitation data sources for hydrological applications in sparsely gauged or ungauged basins. This study proposes a framework for statistical and hydrological assessment of the TRMM-and GPM-era satellite-based precipitation products (SPPs) in both near-and post-real-time versions at sub-daily temporal scales in a poorly gauged watershed in Myanmar. It evaluates six of the latest GPM-era SPPs: Integrated Multi-satellite Retrievals for GPM (IMERG) "Early", "Late", and "Final" run SPPs (IMERG-E, IMERG-L, and IMERG-F, respectively), and Global Satellite Mapping of Precipitation (GSMaP) near-real-time (GSMaP-NRT), standard version (GSMaP-MVK), and standard version with gauge-adjustment (GSMaP-GAUGE) SPPs, and two TRMM Multi-satellite Precipitation Analysis SPPs (3B42RT and 3B42V7). Statistical assessment at grid and basin scales shows that 3B42RT generally presents higher quality, followed by IMERG-F and 3B42V7. IMERG-E, IMERG-L, GSMaP-NRT, GSMaP-MVK, and GSMaP-GAUGE largely underestimate total precipitation, and the three GSMaP SPPs have the lowest accuracy. Given that 3B42RT demonstrates the best quality among the evaluated four near-real-time SPPs, 3B42RT obtains satisfactory hydrological performance in 3-hourly flood simulation, with a Nash-Sutcliffe model efficiency coefficient (NSE) of 0.868, and it is comparable with the rain-gauge-based precipitation data (NSE = 0.895). In terms of post-real-time SPPs, IMERG-F and 3B42V7 demonstrate acceptable hydrological utility, and IMERG-F (NSE = 0.840) slightly outperforms 3B42V7 (NSE = 0.828). This study found that IMERG-F demonstrates comparable or even slightly better accuracy in statistical and hydrological evaluations in comparison with its predecessor, 3B42V7, indicating that GPM-era IMERG-F is the reliable replacement for TRMM-era 3B42V7 in the study area. The GPM scientific community still needs to further refine precipitation retrieving algorithms and improve the accuracy of SPPs, particularly IMERG-E, IMERG-L, and GSMaP SPPs, because ungauged basins urgently require accurate and timely precipitation data for flood control and disaster mitigation.

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“…Since the launch of the TRMM satellite on 27 November 1997, TRMM-based satellite precipitation products have undergone a series of major revisions and widely used in hydrological applications [22][23][24][25]. After over 17 years of fruitful data gathering, the spacecraft was turned off and reentered the Earth's atmosphere on June 15, 2015.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Evaluation of GPM-IMERG, CMORPH, and TMPA Precipitation Products with Gauged Rainfall over Mainland China

Guang-hua

Lü

Crow

et al. 2018

Advances in Meteorology

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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-CRTshows 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. ese findings provide valuable feedback for both IMERG algorithm developers and data set users.

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Hydrological Utility and Uncertainty of Multi-Satellite Precipitation Products in the Mountainous Region of South Korea

Cited by 40 publications

References 53 publications

Validation of Satellite Rainfall Products over a Mountainous Watershed in a Humid Subtropical Climate Region of Brazil

Validation of Satellite Rainfall Products over a Mountainous Watershed in a Humid Subtropical Climate Region of Brazil

Applications of TRMM- and GPM-Era Multiple-Satellite Precipitation Products for Flood Simulations at Sub-Daily Scales in a Sparsely Gauged Watershed in Myanmar

Comprehensive Evaluation of GPM-IMERG, CMORPH, and TMPA Precipitation Products with Gauged Rainfall over Mainland China

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