Evaluation of the Tropical Rainfall Measuring Mission 3B43 product over an inland area in Brazil and the effects of satellite boost on rainfall estimates

Curtarelli, Marcelo; Rennó, Camilo Daleles; Alcântara, Enner

doi:10.1117/1.jrs.8.083589

Cited by 21 publications

(14 citation statements)

References 19 publications

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“…Larger RMSE values were found during the wet season (e.g., SON and DJF) because of the scaling up effect of the precipitation rate from an hourly to monthly scale. The findings are consistent with other studies that found overestimation of TRMM products in the estimation of total precipitation amount [47,48]. The bias-corrected TMPA-3B43 product is generated using multiple satellite images and algorithms, as well as the GPCC product.…”

Section: Spatial Assessmentsupporting

confidence: 79%

Evaluation of TRMM Product for Monitoring Drought in the Kelantan River Basin, Malaysia

Tan

Chua

et al. 2017

Water

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Assessment of satellite precipitation products' capability for monitoring drought is relatively new in tropical regions. The purpose of this paper is to evaluate the reliability of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B43 product in estimating the standardized precipitation index (SPI) in the Kelantan River Basin, Malaysia from 1998 to 2014, by comparing it with data from 42 rain gauges. Overall, the TMPA-3B43 performed well in the monthly precipitation estimation, but performed moderately in the seasonal scale. Better performance was found in the northeast monsoon (wet season) than in the southwest monsoon (dry season). The product is more reliable in the northern and north-eastern regions (coastal zone) compared to the central, southern and south-eastern regions (mountainous area). For drought assessment, the correlations between the TMPA-3B43 and ground observations are moderate at various time-scales (one to twelve months), with better performance at shorter time-scales. The TMPA-3B43 shows similar temporal drought behavior by capturing most of the drought events at various time-scales, except for the 2008-2009 drought. These findings show that the TMPA-3B43 is not suitable to be used directly for SPI estimation in this basin. More bias correction and algorithm improvement work are needed to improve the accuracy of the TMPA-3B43 in drought monitoring.

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Section: Spatial Assessmentsupporting

confidence: 79%

Evaluation of TRMM Product for Monitoring Drought in the Kelantan River Basin, Malaysia

Tan

Chua

et al. 2017

Water

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“…Curtarelli et al [18] evaluated the effects of the TRMM orbital change on the monthly rainfall measurements. They showed that the increased error does not preclude the use of the TRMM 3B43 product for estimating the areal rainfall over the Itumbiara Reservoir drainage area [18]. However, only data after the boost was included in the analysis of the present study.…”

Section: Trmm Multisatellite Precipitation Analysismentioning

confidence: 99%

“…The satellite rainfall estimates were evaluated through analyses of the error (P 3B42 − P rain gauge for TRMM data and P Hydroe − P rain gauge for Hydroe data), linear correlation coefficient (r), bias, mean absolute error (MAE), and root mean square error (RMSE) based on the work of Curtarelli et al [18] and Duan and Bastiaanssen [10]. To facilitate the comparison and discussion with published results, the relative value of each statistical indicator was also calculated based on the mean rainfall estimated by the reference data for all temporal scales.…”

Section: Evaluation Of the Satellite Rainfall Productsmentioning

confidence: 99%

“…To obtain the mean rainfall based on reference data over the watershed, we chose the Thiessen polygon method, which considers the non-uniformity in the spatial distribution of the rain gauge stations, where it simply assumes a linear variation of rainfall between stations [8,18]. This method defines the area of influence for each station within the watershed, where the mean rainfall is calculated by weighting the rainfall values of each station for its area of influence [8].…”

Section: Preparation Of Reference Datamentioning

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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“…The TRMM data, with a spatial resolution of 0.25 × 0.25 degrees, was subset to both the CRB and the larger, surrounding watersheds to gain insight into the influence of local precipitation patterns on flooding area. TRMM precipitation data has proven successful in previous studies, such as Curtarelli et al [34], which showed the TRMM 3B43 data to be in sound agreement with reference data collected at rain gauge stations. Even in studies that show TRMM data to be somewhat unreliable, the southern region of Africa indicates a lower bias than other regions and the 3B43 product was shown to be the most reliable [35].…”

Section: Precipitationmentioning

confidence: 67%

Thermal Imagery-Derived Surface Inundation Modeling to Assess Flood Risk in a Flood-Pulsed Savannah Watershed in Botswana and Namibia

2016

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Abstract:The Chobe River Basin (CRB), a sub-basin of the Upper Zambezi Basin shared by Namibia and Botswana, is a complex hydrologic system that lies at the center of the world's largest transfrontier conservation area. Despite its regional importance for livelihoods and biodiversity, its hydrology, controlled by the timing and relative contributions of water from two regional rivers, remains poorly understood. An increase in the magnitude of flooding in this region since 2009 has resulted in significant displacements of rural communities. We use an innovative approach that employs time-series of thermal imagery and station discharge data to model seasonal flooding patterns, identify the driving forces that control the magnitude of flooding and the high population density areas that are most at risk of high magnitude floods throughout the watershed. Spatio-temporal changes in surface inundation determined using NASA Moderate-resolution Imaging Spectroradiometer (MODIS) thermal imagery (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) revealed that flooding extent in the CRB is extremely variable, ranging from 401 km 2 to 5779 km 2 over the last 15 years. A multiple regression model of lagged discharge of surface contributor basins and flooding extent in the CRB indicated that the best predictor of flooding in this region is the discharge of the Zambezi River 64 days prior to flooding. The seasonal floods have increased drastically in magnitude since 2008 causing large populations to be displaced. Over 46,000 people (53% of Zambezi Region population) are living in high magnitude flood risk areas, making the need for resettlement planning and mitigation strategies increasingly important.

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Evaluation of the Tropical Rainfall Measuring Mission 3B43 product over an inland area in Brazil and the effects of satellite boost on rainfall estimates

Cited by 21 publications

References 19 publications

Evaluation of TRMM Product for Monitoring Drought in the Kelantan River Basin, Malaysia

Evaluation of TRMM Product for Monitoring Drought in the Kelantan River Basin, Malaysia

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

Thermal Imagery-Derived Surface Inundation Modeling to Assess Flood Risk in a Flood-Pulsed Savannah Watershed in Botswana and Namibia

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