SINGV – the Convective-Scale Numerical Weather Prediction System for Singapore

Q4 Environmental Science Asean Journal on Science and Technology for Development Pub Date : 2019-12-27 DOI:10.29037/ajstd.581

Xiangyu Huang, D. Barker, S. Webster, A. Dipankar, A. Lock, M. Mittermaier, Xiangming Sun, R. North, Rob Darvell, D. F. Boyd, J. C. Lo, Jianyu Liu, B. Macpherson, P. Heng, A. Maycock, Laura Pitcher, R. Tubbs, M. McMillan, Sijin Zhang, S. Hagelin, A. Porson, G. Song, Becky Beckett, W. Cheong, A. Semple, C. Gordon

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引用次数: 15

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.

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新加坡对流尺度数值天气预报系统

极端降雨是新加坡以及其他热带地区的主要气象灾害之一，它可能导致严重的局部洪水。自2013年以来，新加坡气象局(MSS)和英国气象局(UKMO)一直在合作开发一个名为SINGV的对流尺度数值天气预报(NWP)系统。它的主要目的是为新加坡及周边地区提供改进的天气预报，重点是改进局部强降雨的短期预报。本文介绍了SINGV的发展概况、MSS最新的NWP能力以及一些关键的评估结果。本文描述了与任何适合热带深处的千米尺度NWP发展相关的科学进展，并对局部数据同化的影响和集合预测的效用提供了一些见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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