ASEAN Journal on Science and Technology for Development
Abstract
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.
Publication Date
12-27-2019
Recommended Citation
Xiang-Yu, Huang; Dale, Barker; Stuart, Webster; Anurag, Dipankar; Adrian, Lock; Marion, Mittermaier; Xiangming, Sun; North; Rob, Darvell; Douglas, Boyd; Jeff, Lo; Jianyu, Liu; Bruce, Macpherson; Peter, Heng; Adam, Maycock; Laura, Pitcher; Robert, Tubbs; Martin, McMillan; Sijin, Zhang; Susanna, Hagelin; Aurore, Porson; Guiting, Song; Becky, Beckett; Kiong, Cheong Wee; Allison, Semple; and Chris, Gordon
(2019)
"SINGV – the Convective-Scale Numerical Weather Prediction System for Singapore,"
ASEAN Journal on Science and Technology for Development: Vol. 36:
No.
3, Article 2.
DOI: https://doi.org/10.29037/ajstd.581
Available at:
https://ajstd.ubd.edu.bn/journal/vol36/iss3/2