TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms
On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of r...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2016
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| Online Access: | http://ir.unimas.my/id/eprint/15188/ http://ir.unimas.my/id/eprint/15188/2/TRMM%20Satellite%20-%20Copy.pdf |
| _version_ | 1848837801428123648 |
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| author | Marina, Patrick Mah, Yau Seng Putuhena, Frederik Josep Wang, Yin Chai Onni Suhaiza, Selaman |
| author_facet | Marina, Patrick Mah, Yau Seng Putuhena, Frederik Josep Wang, Yin Chai Onni Suhaiza, Selaman |
| author_sort | Marina, Patrick |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM) to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL). It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %); and good correlation (CC = 0.9). These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall. |
| first_indexed | 2025-11-15T06:45:26Z |
| format | Article |
| id | unimas-15188 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:45:26Z |
| publishDate | 2016 |
| publisher | EDP Sciences |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-151882022-05-30T08:37:00Z http://ir.unimas.my/id/eprint/15188/ TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms Marina, Patrick Mah, Yau Seng Putuhena, Frederik Josep Wang, Yin Chai Onni Suhaiza, Selaman TC Hydraulic engineering. Ocean engineering On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM) to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL). It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %); and good correlation (CC = 0.9). These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall. EDP Sciences 2016-12-12 Article PeerReviewed text en http://ir.unimas.my/id/eprint/15188/2/TRMM%20Satellite%20-%20Copy.pdf Marina, Patrick and Mah, Yau Seng and Putuhena, Frederik Josep and Wang, Yin Chai and Onni Suhaiza, Selaman (2016) TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms. MATEC Web of Conferences, 87. pp. 1-10. ISSN 2261236X https://www.matec-conferences.org/articles/matecconf/pdf/2017/01/matecconf_encon2017_01006.pdf DOI: 10.1051/matecconf/20178701006 |
| spellingShingle | TC Hydraulic engineering. Ocean engineering Marina, Patrick Mah, Yau Seng Putuhena, Frederik Josep Wang, Yin Chai Onni Suhaiza, Selaman TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms |
| title | TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms |
| title_full | TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms |
| title_fullStr | TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms |
| title_full_unstemmed | TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms |
| title_short | TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms |
| title_sort | trmm satellite algorithm estimates to represent the spatial distribution of rainstorms |
| topic | TC Hydraulic engineering. Ocean engineering |
| url | http://ir.unimas.my/id/eprint/15188/ http://ir.unimas.my/id/eprint/15188/ http://ir.unimas.my/id/eprint/15188/ http://ir.unimas.my/id/eprint/15188/2/TRMM%20Satellite%20-%20Copy.pdf |