SINGV – the Convective-Scale Numerical Weather Prediction System for Singapore
| Autor: | Chris Gordon, Wee Kiong Cheong, Rachel North, Jeff Chun‐Fung Lo, Aurore Porson, Xiangming Sun, Laura Pitcher, Marion Mittermaier, Sijin Zhang, Dale Barker, Peter Heng, Rob Darvell, Anurag Dipankar, Becky Beckett, Stuart Webster, Bruce Macpherson, Xiang-Yu Huang, Allison Semple, Adrian Lock, Guiting Song, Adam Maycock, Jianyu Liu, Susanna Hagelin, Douglas F. A. Boyd, Martin McMillan, Robert Tubbs |
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| Rok vydání: | 2019 |
| Předmět: |
Atmospheric Science
deep tropics Science (General) 010504 meteorology & atmospheric sciences Meteorology convective-scale weather modelling 0208 environmental biotechnology Flooding (psychology) 02 engineering and technology Management Monitoring Policy and Law Oceanography Numerical weather prediction 01 natural sciences 020801 environmental engineering Q1-390 Data assimilation atmospheric data assimilation T1-995 Environmental science numerical weather prediction systems Scale (map) ensemble forecasts Waste Management and Disposal Technology (General) 0105 earth and related environmental sciences |
| Zdroj: | ASEAN Journal on Science and Technology for Development, Vol 36, Iss 3, Pp 81–90-81–90 (2019) |
| ISSN: | 2224-9028 0217-5460 |
| DOI: | 10.29037/ajstd.581 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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