Please use this identifier to cite or link to this item:
https://doi.org/10.29037/ajstd.581
DC Field | Value | |
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dc.title | SINGV – the Convective-Scale Numerical Weather Prediction System for Singapore | |
dc.contributor.author | Huang, Xiang-Yu | |
dc.contributor.author | Barker, Dale | |
dc.contributor.author | Webster, Stuart | |
dc.contributor.author | Dipankar, Anurag | |
dc.contributor.author | Lock, Adrian | |
dc.contributor.author | Mittermaier, Marion | |
dc.contributor.author | Sun, Xiangming | |
dc.contributor.author | North, Rachel | |
dc.contributor.author | Darvell, Rob | |
dc.contributor.author | Boyd, Douglas | |
dc.contributor.author | Lo, Jeff | |
dc.contributor.author | Liu, Jianyu | |
dc.contributor.author | Macpherson, Bruce | |
dc.contributor.author | Heng, Peter | |
dc.contributor.author | Maycock, Adam | |
dc.contributor.author | Pitcher, Laura | |
dc.contributor.author | Tubbs, Robert | |
dc.contributor.author | McMillan, Martin | |
dc.contributor.author | Zhang, Sijin | |
dc.contributor.author | Hagelin, Susanna | |
dc.contributor.author | Porson, Aurore | |
dc.contributor.author | Song, Guiting | |
dc.contributor.author | Beckett, Becky | |
dc.contributor.author | Cheong, Wee Kiong | |
dc.contributor.author | Semple, Allison | |
dc.contributor.author | Gordon, Chris | |
dc.date.accessioned | 2022-07-06T03:52:15Z | |
dc.date.available | 2022-07-06T03:52:15Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Huang, Xiang-Yu, Barker, Dale, Webster, Stuart, Dipankar, Anurag, Lock, Adrian, Mittermaier, Marion, Sun, Xiangming, North, Rachel, Darvell, Rob, Boyd, Douglas, Lo, Jeff, Liu, Jianyu, Macpherson, Bruce, Heng, Peter, Maycock, Adam, Pitcher, Laura, Tubbs, Robert, McMillan, Martin, Zhang, Sijin, Hagelin, Susanna, Porson, Aurore, Song, Guiting, Beckett, Becky, Cheong, Wee Kiong, Semple, Allison, Gordon, Chris (2019). SINGV – the Convective-Scale Numerical Weather Prediction System for Singapore. ASEAN Journal on Science and Technology for Development 36 (3). ScholarBank@NUS Repository. https://doi.org/10.29037/ajstd.581 | |
dc.identifier.issn | 02175460 | |
dc.identifier.issn | 22249028 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/227962 | |
dc.description.abstract | <jats:p>Extreme rainfall is one of the primary meteorological hazards in Singapore, as well as elsewhere in the deep tropics, and it can lead to significant local flooding. Since 2013, the Meteorological Service Singapore (MSS) and the United Kingdom Met Office (UKMO) have been collaborating to develop a convective-scale Numerical Weather Prediction (NWP) system, called SINGV. Its primary aim is to provide improved weather forecasts for Singapore and the surrounding region, with a focus on improved short-range prediction of localized heavy rainfall. This paper provides an overview of the SINGV development, the latest NWP capabilities at MSS and some key results of evaluation. The paper describes science advances relevant to the development of any km-scale NWP suitable for the deep tropics and provides some insights into the impact of local data assimilation and utility of ensemble predictions.</jats:p> | |
dc.publisher | UGM Press | |
dc.source | Elements | |
dc.type | Article | |
dc.date.updated | 2022-07-06T02:36:47Z | |
dc.contributor.department | COMPUTATIONAL SCIENCE | |
dc.contributor.department | S'PORE NUCLEAR RSCH & SAFETY INITIATIVE | |
dc.description.doi | 10.29037/ajstd.581 | |
dc.description.sourcetitle | ASEAN Journal on Science and Technology for Development | |
dc.description.volume | 36 | |
dc.description.issue | 3 | |
dc.published.state | Unpublished | |
Appears in Collections: | Staff Publications Elements |
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