Enhancements of Singapore’s Convective Rainfall Prediction
This project explores the application of advanced technologies and methodologies to boost the speed and accuracy at which PUB, Singapore’s National Water Agency, predicts heavy rainfall.
Research Goals
- Advance understanding of dynamic and thermodynamic processes that influence extreme convective storms in urban areas.
- Boost computational capabilities for high-resolution, convection-permitting simulations to support inland flood modelling.
- Leverage machine learning (ML) and weather generators to improve real-time forecasting of convective storms and rainfall extremes.
Why This Matters
- Provides Singapore with high-resolution rainfall re-analysis products, merging all available data for improved accuracy and detail.
- Enables the development of algorithms incorporating microwave links and CCTV footage into near real-time gridded rainfall products.
- Generates insights on how climate change and urbanisation affect convective rainfall patterns, supporting policy and planning.
- Refines hydrological models using physics-informed ML approaches for hyperlocal rainfall representation, enhancing flood response and management.
Latest Research Highlights
- Developed a 5-minute, high-resolution gauge–radar rainfall dataset combining radar coverage with in-situ accuracy for urban-scale storm analysis.
- Conducted a quantitative study showing that Singapore storms are typically localised and short-lived.
- Enhanced capabilities for detecting and forecasting convective storms, supporting national flood and coastal resilience efforts.
Meet the Team
Meet the team behind the Enhancements of Singapore’s Convective Rainfall Prediction project.
Principal Investigator (PI):
Professor Vladan Babovic
National University of Singapore
Scientist:
Wenhao Fu
Agency for Science, Technology and Research (A*STAR)
Co-Principal Investigator (Co-PI):
Professor Simone
Fatichi
National University of Singapore
Student:
Du Haoliang
National University of Singapore
Senior Scientist:
Dr. Ronald Chan
Agency for Science, Technology and Research (A*STAR)
Student:
Lim Chin Seng
National University of Singapore
Research Fellow (RF):
Dr. Qi Zhuang
National University of Singapore
Student:
Naila Matin
National University of Singapore
Scientist:
Kannan Sundaravadivelu
Agency for Science, Technology and Research (A*STAR)
Student:
Xu Chengcheng
National University of Singapore
More Projects from the H2 Domain
Discover research initiatives under the Monitoring, Prediction and Digitalisation of Coastal Environment domain that harness data and digital technologies to enhance Singapore’s resilience to sea-level rise, extreme weather, and coastal flooding.
Download CFI's project booklet for more information on each project
CFI Singapore Tranche 1 and 2
If you wish to reach out regarding a specific project, please email CFI Singapore at cfisg@nus.edu.sg