Spatial and temporal characteristics of rain intensity in the peninsular Malaysia using TRMM rain rate

Varikoden, Hamza; Samah, Azizan Abu; Babu, C. A.

doi:10.1016/j.jhydrol.2010.04.023

Cited by 83 publications

(48 citation statements)

References 24 publications

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“…With a maximum R 2 of 0.86 and 0.88, respectively, the 3B42RT and 3B42V7 appeared to have the best potential for analyzing abnormal precipitation events over Malaysia. Moreover, our results are in agreement with the findings of Varikoden et al [21], who evaluated the performance of previous version (V6) TRMM products at four rain gauges over south, east, west and highland areas of PM with R 2 ranging from 0.63 to 0.96, but better performances of version 7 than version 6 had been previously reported [65]. Our findings confirm that the 3B42V7 and 3B42RT are reliable and suitable for heavy precipitation estimation and monitoring (3B42RT is a real-time product) in Malaysia.…”

Section: /2007 Flood Event Assessmentsupporting

confidence: 94%

“…Varikoden et al [21] evaluated the daily precipitation from TRMM 3B42V6 data in Peninsular Malaysia, which covers only about 40% of the total area of Malaysia, using for validation only four precipitation gauges. Semire et al [22] validated the TRMM Microwave Imager (TMI) 2A12, 3B42V6, 3B43V6, and Global Precipitation Climatology Center (GPCC) with the monthly precipitation data collected over 10 years (2001-2010) from 22 precipitation gauges distributed over Malaysia.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

et al. 2015

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Satellite precipitation products (SPPs) potentially constitute an alternative to sparse rain gauge networks for assessing the spatial distribution of precipitation. However, applications of these products are still limited due to the lack of robust quality assessment. This study compares daily, monthly, seasonal, and annual rainfall amount at 342 rain gauges over Malaysia to estimations using five SPPs (3B42RT, 3B42V7, GPCP-1DD, PERSIANN-CDR, and CMORPH) and a ground-based precipitation product (APHRODITE). The performance of the precipitation products was evaluated from 2003 to 2007 using continuous (RMSE, R 2 , ME, MAE, and RB) and categorical (ACC, POD, FAR, CSI, and HSS) statistical approaches. Overall, 3B42V7 and APHRODITE performed the best, while the worst performance was shown by GPCP-1DD. 3B42RT, 3B42V7, and PERSIANN-CDR slightly overestimated observed precipitation by 2%, 4.7%, and 2.1%, respectively. By contrast, APHRODITE and CMORPH significantly underestimated precipitations by 19.7% and 13.2%, respectively, whereas GPCP-1DD only slightly underestimated by 2.8%. All six precipitation products performed better in the northeast monsoon than in the southwest OPEN ACCESSRemote Sens. 2015, 7 1505 monsoon. The better performances occurred in eastern and southern Peninsular Malaysia and in the north of East Malaysia, which receives higher rainfall during the northeast monsoon, whereas poor performances occurred in the western and dryer Peninsular Malaysia. All precipitation products underestimated the no/tiny (<1 mm/day) and extreme (≥20 mm/day) rainfall events, while they overestimated low (1-20 mm/day) rainfall events. 3B42RT and 3B42V7 showed the best ability to detect precipitation amounts with the highest HSS value (0.36). Precipitations during flood events such as those which occurred in late 2006 and early 2007 were estimated the best by 3B42RT and 3B42V7, as shown by an R 2 value ranging from 0.49 to 0.88 and 0.52 to 0.86, respectively. These results on SPPs' uncertainties and their potential controls might allow sensor and algorithm developers to deliver better products for improved rainfall estimation and thus improved water management.

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Section: /2007 Flood Event Assessmentsupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

et al. 2015

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“…The high intensity rainfall is absolutely absent during the SWM period except in the west coastal stations. The lowest monthly rainfall occurs in February, and the highest monthly rainfall in December (Varikoden et al, 2010). Fig.…”

Section: Investigation On Thementioning

confidence: 95%

Investigation on the Carbon Monoxide Pollution over Peninsular Malaysia Caused by Indonesia Forest Fires from AIRS Daily Measurement

Rajab¹,

Tan²,

Lim³

et al. 2011

Advanced Air Pollution

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“…A study carried out in Malaysia shows that TRMM is less sensitive towards low precipitation clouds than heavy precipitation clouds and the correlation obtained was better during the northeast monsoon [9]. The heaviest rainfall events occurred during the northeast monsoon and were mainly caused by the large-scale monsoon flows that contained heavy precipitation cloud [10]. The error can be explained by the presence of low versus heavy precipitation clouds in wet and dry seasons.…”

Section: Introductionmentioning

confidence: 98%

“…There are some uncertainties which makes the sensitivity of local-scale rainfall in a small region contentious [9]. These include the lack of TRMM precipitation algorithm sensitivity to low and high precipitation clouds [10,11], the effect of upscaling the rainfall rate to an effective temporal scale [12], and the coarse grid size of the TRMM data for solving local rainfall patterns [13].…”

Section: Introductionmentioning

confidence: 99%

Satellite Rainfall (TRMM 3B42-V7) Performance Assessment and Adjustment over Pahang River Basin, Malaysia

2018

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Abstract:The Tropical Rainfall Measuring Mission (TRMM) was the first Earth Science mission dedicated to studying tropical and subtropical rainfall. Up until now, there is still limited knowledge on the accuracy of the version 7 research product TRMM 3B42-V7 despite having the advantage of a high temporal resolution and large spatial coverage over oceans and land. This is particularly the case in tropical regions in Asia. The objective of this study is therefore to analyze the performance of rainfall estimation from TRMM 3B42-V7 (henceforth TRMM) using rain gauge data in Malaysia, specifically from the Pahang river basin as a case study, and using a set of performance indicators/scores. The results suggest that the altitude of the region affects the performances of the scores. Root Mean Squared Error (RMSE) is lower mostly at a higher altitude and mid-altitude. The correlation coefficient (CC) generally shows a positive but weak relationship between the rain gauge measurements and TRMM (0 < CC < 0.4), while the Nash-Sutcliffe Efficiency (NSE) scores are low (NSE < 0.1). The Percent Bias (PBIAS) shows that TRMM tends to overestimate the rainfall measurement by 26.95% on average. The Probability of Detection (POD) and Threat Score (TS) demonstrate that more than half of the pixel-point pairs have values smaller than 0.7. However, the Probability of False Detection (POFD) and False Alarm Rate (FAR) show that most of the pixel-point gauges have values lower than 0.55. The seasonal analysis shows that TRMM overestimates during the wet season and underestimates during the dry season. The bias adjustment shows that Mean Bias Correction (MBC) improved the scores better than Double-Kernel Residual Smoothing (DS) and Residual Inverse Distance Weighting (RIDW). The large errors imply that TRMM may not be suitable for applications in environmental, water resources, and ecological studies without prior correction.

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Spatial and temporal characteristics of rain intensity in the peninsular Malaysia using TRMM rain rate

Cited by 83 publications

References 24 publications

Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

Investigation on the Carbon Monoxide Pollution over Peninsular Malaysia Caused by Indonesia Forest Fires from AIRS Daily Measurement

Satellite Rainfall (TRMM 3B42-V7) Performance Assessment and Adjustment over Pahang River Basin, Malaysia

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