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Singapore Launches Research Alliance To Strengthen Weather And Climate Science Capabilities
CAWRAS to implement $25 million Weather Science Research Programme under the Research, Innovation and Enterprise 2025 Plan
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).
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.
Ten research projects2 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.
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 resources3.
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.”
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.”
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.”
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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1 CCRS is the research arm of the Meteorological Service Singapore and part of NEA. It was launched in March 2013, with the vision to be a world leading centre in tropical climate and weather research focusing on the Southeast Asia region.
2 The awarded projects under the WSRP can be found in Annex A with several projects of note featured in Annex B.
3 A*STAR, as the host for CAWRET, will be working closely with the National Supercomputing Centre (NSCC) Singapore as a key partner to support the computational needs of weather and climate research under CAWRAS.
ANNEX A - Awarded Projects under WSRP
- 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, ASTAR
- 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 doorstep 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, ASTAR Institute of High Performance Computing (ASTAR 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, ASTAR Institute for Infocomm Research (ASTAR 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.
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