Month: September 2025

Source: Hong Kong Government special administrative region

     To gather views from the market, the Transport and Logistics Bureau (TLB), together with the Highways Department (HyD), today (September 5) invites parties in the industry who are interested in participating in the Hong Kong section of the Hong Kong-Shenzhen Western Rail Link (Hung Shui Kiu-Qianhai) (HSWRL) project to submit expressions of interest (EOI) for the project.
 
     A spokesman for the TLB said, “The construction of the HSWRL is a crucial initiative in support of the thorough implementation of the Outline Development Plan for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). It enhances infrastructure connectivity in the GBA and facilitates Hong Kong’s better integration into national development. Coupled with the co-location customs clearance arrangement, the HSWRL will connect the metro networks in the western regions of Hong Kong and Shenzhen. A trip from Hung Shui Kiu to Qianhai will only take approximately 15 minutes, which will help foster the “one-hour living circle” in the GBA. The HSWRL is also an important transport infrastructure promoting the development of the Northern Metropolis, catering to the local travel demand in the Hung Shui Kiu/Ha Tsuen New Development Area as well as the Lau Fau Shan, Tsim Bei Tsui and Pak Nai areas.”
 
     The Government plans to implement the Hong Kong section of the HSWRL through open tender. The HyD commenced the investigation and design work for the Hong Kong section of the HSWRL in mid-2025 including statutory processes such as the environmental impact assessment and gazettal. The target is to have the Hong Kong section of the HSWRL ready for tendering in 2027 and to strive for completion of the construction works in 2034, followed immediately by integrated testing and commissioning to realise the common goal of the governments of Hong Kong and Shenzhen to commission the HSWRL in 2035.
 
     The spokesman said, “The HyD held briefing sessions earlier on July 25, August 1 and August 7 in Shenzhen, Guangzhou and Hong Kong respectively to introduce details of the Hong Kong section of the HSWRL and matters relating to the invitation for EOI from the industry. We are thankful for the enthusiastic participation from the industry. More than 160 organisations from the industry participated in the three aforementioned briefing sessions and provided valuable perspectives and suggestions. We now formally invite the industry to submit EOI for the Hong Kong section of the HSWRL to provide further comments on various aspects including project scheme, procurement arrangement, financial arrangement, and implementation timetable. The feedback gathered from the EOI will allow the Government to have a better understanding of the market’s views on the construction and operation of the Hong Kong section of the HSWRL to formulate more appropriate tender terms and details.”
 
     The deadline for submission of EOI is noon on October 31, 2025 (Friday). The HyD will conduct an online briefing session for exchanges of views with industry organisations interested in submitting an EOI. Details of the EOI invitation and briefing session can be found on the webpage of the Hong Kong section of the HSWRL project (hswrl.hk/).
 
     The HSWRL is approximately 18.1 kilometres long, with the Hong Kong section and the Shenzhen section being about 7.3km long and 10.8km long respectively. The alignment will start from the west of Hung Shui Kiu Station under construction on the Tuen Ma Line, passing through Ha Tsuen and Lau Fau Shan, crossing Deep Bay and connecting to Qianhai via Shenzhen Bay Port. It is an underground railway line comprising a total of five stations, with a depot located in Ha Tsuen. To enhance the convenience of border crossing and travel experience, and fully leverage the attractiveness and efficiency of the cross-boundary railway, the governments of Hong Kong and Shenzhen have agreed to establish the co-location of the immigration and customs facilities in Shenzhen, with no immigration and customs facilities in Hong Kong.

Source: Hong Kong Government special administrative region

Source: Hong Kong Government special administrative region

Source: Hong Kong Government special administrative region

Source: Hong Kong Government special administrative region

The Transport Department (TD) today (September 5) reminded members of the public that to facilitate the holding of horse race meetings at the Happy Valley Racecourse during the 2025/2026 Season, the following special traffic and transport arrangements will be implemented in phases on the race dates from next Wednesday (September 10) in the vicinity of the Happy Valley Racecourse.
 
Special traffic arrangements
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1. From 50 minutes prior to the start of the first race (day meetings) or from 6pm (night meetings), the section of Wong Nai Chung Road southbound between Queen’s Road East and the slip road leading to the Aberdeen Tunnel will be temporarily closed to all vehicular traffic (except for vehicles heading for the Aberdeen Tunnel). Meanwhile, the section of Wong Nai Chung Road southbound between Village Road and the slip road leading to the Aberdeen Tunnel will be converted to one-way northbound until all the horse races end and when it is safe to reopen the roads to normal vehicular traffic.
 
2. From about 35 minutes before the start of the last race, the following road sections will be closed to all vehicular traffic until the closed road sections reopen:
(i) the slip road connecting Wong Nai Chung Road and the Aberdeen Tunnel;
(ii) the section of Wong Nai Chung Road southbound between Queen’s Road East and the slip road connecting Wong Nai Chung Road and the Aberdeen Tunnel;
(iii) the section of Wong Nai Chung Road southbound between Village Road and near Parsee Cemetery;
(iv) the section of Leighton Road westbound between Wong Nai Chung Road and Canal Road East; and
(v) the section of Morrison Hill Road southbound between Leighton Road and Queen’s Road East.

Public transport service arrangements
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1. In connection with the above road closure and traffic diversion arrangements, franchised bus and green minibus routes operating in the affected areas will be temporarily diverted from about 35 minutes before the start of the last race. Meanwhile, the bus stops on Leighton Road eastbound near Matheson Street, Morrison Hill Road southbound near Sports Road and at the junction of Leighton Road westbound and Wong Nai Chung Road will also be temporarily suspended;
 
2. The tram stop on Wong Nai Chung Road outside the Hong Kong Cemetery will be suspended from about one hour prior to the start of the last race; and
 
3. In connection with the horse race meeting arrangements at the Happy Valley Racecourse, the taxi stand on Sung Tak Street and on-street parking spaces on Wong Nai Chung Road southbound between Sports Road and Blue Pool Road will be temporarily suspended in the following periods:
(i) day meetings – from 11am to 7pm; and
(ii) night meetings – from 5pm to 11.59pm
 
The TD anticipates that the traffic in the vicinity of affected areas will be very congested during the horse race meetings. Motorists are advised to avoid driving to the affected areas as far as possible. Members of the public planning to go to the affected areas are advised to use public transport services as far as possible. The TD and the Police will closely monitor the traffic situation and implement appropriate measures whenever necessary.
 
For details of the special traffic and public transport arrangements, members of the public may visit the TD’s website (www.td.gov.hk), mobile application “HKeMobility” or passenger notices issued by the relevant public transport operators.

Source: Government of Singapore

CAWRAS to implement $25 million Weather Science Research Programme under the Research, Innovation and Enterprise 2025 Plan

JOINT NEWS RELEASE BETWEEN NEA, A*STAR, NTU SINGAPORE AND NUS

Singapore, 05 September 2025 – The Climate and Weather Research Alliance Singapore (CAWRAS) was established today as a national research platform to advance tropical climate and weather research for Singapore and Southeast Asia and to nurture local talent pipeline in weather and climate science. CAWRAS is jointly established by the National Environment Agency (NEA), Agency for Science, Technology and Research (A*STAR), Nanyang Technological University, Singapore (NTU Singapore), and the National University of Singapore (NUS).

2          As a start, CAWRAS will implement the $25 million Weather Science Research Programme (WSRP) funded under the Research, Innovation and Enterprise 2025 Plan announced earlier this year. Led by the Centre for Climate Research Singapore (CCRS) [1], CAWRAS brings together leading research institutions to expand weather science capabilities at the national level. This coordinated effort comes at a time when advances in technology, such as high-resolution modelling, artificial intelligence (AI), and enhanced observational networks, present new opportunities to improve weather prediction. The research alliance will expand its scope to include climate research on longer timescales in future.

3            Ten research projects [2] have been awarded under the WSRP, focusing on four key areas: improving the use of weather observations, developing next-generation weather/climate models, performing a detailed historical weather re-analysis over recent decades for Southeast Asia, and enhancing weather prediction accuracy through advanced post-processing techniques.

4          In one of the projects, researchers will use AI to develop more skilful predictions of convective hazards, potentially enhancing forecasts of heavy rainfall and strong winds. The programme will also develop advanced weather prediction systems that consider how local weather is affected by ocean and land conditions, which could improve our ability to forecast weather phenomena like Sumatra squalls. Scientists will also develop a high-resolution modelling system for better representation of fine-scale urban weather phenomena and leverage AI to capture nuanced patterns that traditional physical models might miss. These projects will be supported by a new Climate and Weather Research and Evaluation Testbed (CAWRET) that provides researchers access to extensive observation datasets, advanced modelling capabilities and supercomputing resources [3].

5          Ms Koh Li-Na, Director-General of the Meteorological Service Singapore, NEA said, “CAWRAS is a strong commitment by our research institutions, working with the Centre for Climate Research Singapore, to collectively tackle the unique challenges of predicting weather in our tropical urban environment and enhance our understanding of climate change. We look forward to translating science to improved services to bolster Singapore’s resilience in the face of climate change.”

6          Professor Lim Keng Hui, Assistant Chief Executive (Science & Engineering Research Council) of A*STAR said, “A*STAR is proud to contribute to this national effort to improve Singapore’s weather research. Our expertise in high performance computing, artificial intelligence (AI), modelling and simulation will contribute to the development of the Climate and Weather Research & Evaluation Testbed (CAWRET) and support regional analysis. We look forward to working closely with our partners to translate scientific innovations into practical solutions that strengthen Singapore’s resilience to weather-related challenges, particularly in sectors in aviation, maritime, and urban planning.”

7          Professor Ernst Kuipers, Vice President (Research) of NTU Singapore said, “Leveraging NTU’s established track record in Earth and environmental sciences, supported by infrastructure like the Earth Observatory of Singapore, and our pioneering Climate Transformation Programme, we are uniquely positioned to combine AI, remote sensing, and advanced environmental modelling to forecast tropical weather with enhanced accuracy. Through interdisciplinary collaboration spanning fields like medicine, public health, environmental engineering, and urban resilience, NTU will contribute to Singapore’s role as a leading hub for tropical weather and climate science research in Southeast Asia.”

8          Professor Liu Bin, Deputy President (Research and Technology) of NUS said, “NUS welcomes this national research alliance as an integral part of our commitment to research and innovation in the areas of sustainability and climate change. Leveraging our research strengths such as urban climate modelling, hydroclimatology, artificial intelligence, and foundation modelling, we are excited to contribute significantly on a national level to Singapore’s weather prediction capabilities while nurturing the next generation of weather and climate scientists.”

 

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For more information, please submit your enquiries electronically via the Online Feedback Form or myENV mobile application.

ANNEX A

Awarded Projects under WSRP

Name of Proposal	Principal Investigator	Host Institute
Enhancing Next-Generation Numerical Weather Prediction Over Singapore with Radar Data Assimilation in the Joint Effort for Data Assimilation Integration (JEDI)	Dr Srivatsan V Raghavan	NUS
Novel Data Assimilation Methods for Tropical Weather Prediction	Associate Prof Wen Bihan	NTU
Representing the Complexity of Singapore’s Urban Environment and Understanding its Effects on our Weather, Including Extremes*	Prof Matthias Roth	NUS
Understanding the Effects of Multi-Scale Atmospheric Processes in the Prediction of Tropical Weather Systems*	Assistant Prof Wang Jingyu	NTU
Understanding the Effects of Air-Sea-Land Interactions on the Weather of the Maritime Continent	Dr Kaushik Sasmal	NUS
AI Foundation Models for Regional Weather Prediction in the Maritime Continent	Assistant Prof Zhu Lailai	NUS
Maritime Continent Atmospheric Regional Reanalysis (MCARR)*	Dr Koh Wee Shing	A*STAR
Predicting Convective Hazards in the Maritime Continent*	Dr Xiang Shili	A*STAR
Blending Weather Forecasts from Multiple Models	Dr Yin Yifang	A*STAR
Clustering Ensemble Realisations into Weather Scenarios with Uncertainty Estimates	Assistant Prof He Xiaogang	NUS
Climate and Weather Research and Evaluation Testbed (CAWRET)	Dr Koh Wee Shing	A*STAR

*Featured projects are elaborated in Annex B. Principal Investigators of these projects and Director of CCRS, Professor Dale Barker, will be available for doorstop interviews at the CAWRAS launch event on 5 September 2025.

ANNEX B

Elaboration of Featured WSRP Projects

Project Title: Representing the Complexity of Singapore’s Urban Environment and Understanding its Effects on our Weather, Including Extremes

Principal Investigator: Prof Matthias Roth, Department of Geography, NUS

Synopsis: This project aims to implement and evaluate a new urban-scale prediction system that can better represent Singapore’s unique tropical urban environment. Using advanced modeling techniques and hybrid-AI approaches, the system will provide the underpinning atmosphere-land model configuration for high-resolution (100m) weather predictions of urban meteorological hazards for use in forecasts on timeframes of minutes to hours/days. The research will enhance our understanding of how Singapore’s dense urban landscape affects local weather patterns, including extreme events like intense rainfall and heat stress.

Key features of the project include:

• Implementation and evaluation of a sub-kilometer spatial resolution urban-scale environmental prediction system for Singapore

• Integration of three-dimensional urban canopy effects to better capture the impact of buildings and urban structures on local weather

• Evaluation using diverse urban observations, including new boundary layer measurements from strategically placed ceilometers
• Assessment of the feasibility/usefulness of the model for applications to flood operations and other urban weather-sensitive activities

This research will improve our ability to predict and respond to weather impacts in Singapore’s urban environment, contributing to enhanced weather services and urban resilience in the face of climate change.

 

Project Title: Understanding the Effects of Multi-Scale Atmospheric Processes in the Prediction of Tropical Weather Systems

Principal Investigator: Assistant Prof Wang Jingyu, National Institute of Education, NTU Singapore

Synopsis: This project aims to improve the prediction of tropical weather, which is particularly challenging due to the complex interaction of weather patterns occurring at different scales in our region.

Key features of the project include:

• Developing advanced modeling techniques that can simultaneously handle both large-scale tropical weather systems and local weather phenomena

• Improving high-resolution predictions of tropical weather while optimizing computational performance for next-generation supercomputers

• Enhancing representation of atmosphere and land processes, as well as their interactions in weather models to better capture extreme events

This project will advance our understanding of tropical weather systems and improve prediction capabilities for phenomena such as thunderstorms and heatwaves that are posing increasing risks to urban safety, infrastructure resilience, and public health across Southeast Asia and Singapore.

 

Project Title: Maritime Continent Atmospheric Regional Reanalysis (MCARR)

Principal Investigator: Dr Koh Wee Shing, A*STAR Institute of High Performance Computing (A*STAR IHPC)

Synopsis: This project aims to develop the first high-resolution regional weather reanalysis dataset for Singapore and Southeast Asia, covering the period from 1990s to 2025. By integrating sparse historical ground and satellite observations with next-generation numerical weather prediction (NWP) models and advanced data assimilation techniques, the project will produce a comprehensive and accurate historical weather record tailored for tropical climates.

Key features of the project include:

• Generation of a high-resolution (at least 4km) reanalysis dataset using cutting-edge NWP systems and ensemble-based data assimilation methods.

• Compilation and quality control of a regional historical observation datastore, encompassing both international and local data sources.

• Comprehensive scientific analysis of both observation and reanalysis datasets to validate accuracy, identify trends, and provide insights into regional climate dynamics.

• Development of a Regional Reanalysis Product Catalogue to support planning & operational decision-making in aviation, maritime, energy, and urban planning sectors.

This project will position Singapore as a regional leader in climate and weather science, enabling AI-powered forecasting and evidenced – based policymaking through robust historical climate data. It will also contribute to international collaboration and technological advancements in regional reanalysis.

 

Project Title: Predicting Convective Hazards in the Maritime Continent

Principal Investigator: Dr Xiang Shili, A*STAR Institute for Infocomm Research (A*STAR I2R)

Synopsis: This project aims to improve forecasts of hazardous weather events in Singapore and the surrounding region, such as heavy rainfall, strong winds, and lightning, using artificial intelligence (AI) and machine learning (ML) techniques. While there have been significant AI advances in global-scale weather forecasting, this project specifically addresses the unique challenges of predicting hazardous weather events in our equatorial region.

Key features of the project include:

• Adapting advanced AI and ML techniques to better predict hazardous weather events

• Combining diverse weather observations and model data to enhance forecast accuracy and improve interpretability for end users

• Creating more timely and actionable predictions of weather hazards affecting Singapore and the surrounding region

Through leveraging local observations, high-resolution model data and advanced AI/ML techniques, this project will improve our ability to forecast hazardous weather events that impact daily activities and operations in Singapore. This research will contribute to more accurate and timely weather warnings, helping to enhance Singapore’s weather resilience.

 

Source: Hong Kong Government special administrative region