Site-specific precipitation estimate from TRMM data using bilinear weighted interpolation technique: An example from Kuwait

Din, Saif Ud; Al-Dousari, Ali; Ramdan, Asep Muhammad; Ghadban, A. Al

doi:10.1016/j.jaridenv.2007.12.013

Cited by 27 publications

(18 citation statements)

References 14 publications

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“…Another potential use of this information could be the improvement of the current rainfall monitoring network, by supplementing data within the high variability areas or even to supply information at unmonitored sites (Uddin et al. ). This could be of great help for the proper management and conservation of water at the SRB.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin, Mexico

Ávila-Carrasco

Júnez-Ferreira

Gowda

et al. 2018

J American Water Resour Assoc

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Assessment of water resources requires reliable rainfall data, and rain gauge networks may not provide adequate spatial representation due to limited point measurements. The Tropical Rainfall Measuring Mission (TRMM) provides rainfall data at global scale, and has been used with good results. However, TRMM data are an indirect measurement of rainfall, and therefore must be validated for its proper use. In this work, a validation scheme was designed and implemented to compare the TRMM Version 7 (V7) monthly rainfall product at different time frames with data measured in two hydrologic subregions of the Santiago River Basin (SRB) in Mexico: Río Alto Santiago and Río Bajo Santiago (RBS). Additionally, three physio‐climatic regions provide an assessment of the interplay of topography, distance from coastal regions, and seasonal weather patterns on the correspondence between both datasets. The TRMM V7 rainfall product exhibited good agreement with the rain gauge data particularly for the RBS and for the whole SRB during wettest summer and autumn seasons. However, strong regional dependence was observed due to differences in climate and topography. Overall, in spite of some noted underestimations, the monthly TRMM V7 rainfall product was found to provide useful information that can be used to complement limited monitoring as is the case of RBS. An improved combined rainfall product could be generated and thus gaining the most benefits from both data sources.

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Section: Discussionmentioning

confidence: 99%

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin, Mexico

Ávila-Carrasco

Júnez-Ferreira

Gowda

et al. 2018

J American Water Resour Assoc

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“…The applicability of the BWI method to derive precipitation information at any spatial location has been recommended to reduce the space mismatch errors when direct measurements are unavailable. Uddin et al () found good agreement between the computed TRMM precipitation data using the BWI method and the measured data. Zhang, He, Ma, & Pang () used three interpolation methods, including inverse distance‐weighted, bilinear interpolation and the nearest point, to compute precipitation over the locations of rain gauge stations from satellite precipitation products and found that the results of the bilinear interpolation method fit well with the gauge values at daily and monthly scales.…”

Section: Introductionmentioning

confidence: 90%

“…This could be due to the complex topography, harsh natural environment, and sparsely distributed rain gauges in the TP, which is likely to bring uncertainty and spatial mismatch errors to the results when interpolating ground‐based data. To improve the interpolation accuracy, the grid‐to‐point method has been adopted, in Mount Kilimanjaro (Haque, Maskey, Uhlenbrook, & Mul, ) and Kuwait (Uddin, Aldousari, Ramadan, & Alghadban, ), for example. The similarities in topography and mean precipitation between the TP and Mount Kilimanjaro imply that it is possible to improve the reliability of the TP precipitation data obtained from TRMM through the grid‐to‐point method.…”

Section: Introductionmentioning

confidence: 99%

“…Two grid‐to‐point techniques, including nearest neighbour (NN) and bilinear weighted interpolation (BWI), are available to extract the daily TRMM precipitation value at any spatial location, with limited or even no ground rain gauge station data (Uddin et al, ). The applicability of the BWI method to derive precipitation information at any spatial location has been recommended to reduce the space mismatch errors when direct measurements are unavailable.…”

Section: Introductionmentioning

confidence: 99%

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Effects of temporal scales and space mismatches on the TRMM 3B42 v7 precipitation product in a remote mountainous area

Ebrahimi

Chen

et al. 2017

Hydrological Processes

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The accurate measurement of precipitation is essential to understanding regional hydrological processes and hydrological cycling. Quantification of precipitation over remote regions such as the Tibetan Plateau is highly unreliable because of the scarcity of rain gauges. The objective of this study is to evaluate the performance of the satellite precipitation product of tropical rainfall measuring mission (TRMM) 3B42 v7 at daily, weekly, monthly, and seasonal scales. Comparison between TRMM grid precipitation and point-based rain gauge precipitation was conducted using nearest neighbour and bilinear weighted interpolation methods. The results showed that the TRMM product could not capture daily precipitation well due to some rainfall events being missed at short time scales but provided reasonably good precipitation data at weekly, monthly, and seasonal scales. TRMM tended to underestimate the precipitation of small rainfall events (less than 1 mm/day), while it overestimated the precipitation of large rainfall events (greater than 20 mm/day). Consequently, TRMM showed better performance in the summer monsoon season than in the winter season. Through comparison, it was also found that the bilinear weighted interpolation method performs better than the nearest neighbour method in TRMM precipitation extraction.

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“…Accadia et al [14] showed that the application of the bilinear interpolation to precipitation fields with spatial resolution of about 10 km may introduce bias since it does not conserve total precipitation and results in smoothing of the precipitation field by increasing the minima and reducing the maxima. However, this interpolation method has been satisfactorily used in previous studies [15,16].…”

Section: Evaluation Proceduresmentioning

confidence: 99%

Evaluation of Error in IMERG Precipitation Estimates under Different Topographic Conditions and Temporal Scales over Mexico

et al. 2017

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This study evaluates the precipitation product of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) over the Mexican region during the period between April 2014 and October 2015 using three different time scales for cumulative precipitation (hourly, daily and seasonal). Also, the IMERG data have been analyzed as a function of elevation given the rain gauges from the automatic meteorological stations network, located within the area of study, which are used as a reference. In the present study, continuous and categorical statistics are used to evaluate IMERG. It was found that IMERG showed better performance at the daily and seasonal time scale resolutions. While hourly precipitation estimates reached a mean correlation coefficient of 0.35, the daily and seasonal precipitation estimates achieved correlations over 0.51. In addition, the IMERG precipitation product was able to reproduce the diurnal and daily cycles of the average precipitation with a trend towards overestimating rain gauges. However, extreme precipitation events were highly underestimated, as shown by relative biases of −61% and −46% for the hourly and daily precipitation analysis, respectively. It was also found that IMERG tends to improve precipitation detection and to decrease magnitude errors over the higher terrain elevations of Mexico.

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Site-specific precipitation estimate from TRMM data using bilinear weighted interpolation technique: An example from Kuwait

Cited by 27 publications

References 14 publications

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin, Mexico

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin, Mexico

Effects of temporal scales and space mismatches on the TRMM 3B42 v7 precipitation product in a remote mountainous area

Evaluation of Error in IMERG Precipitation Estimates under Different Topographic Conditions and Temporal Scales over Mexico

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