The Centre for Climate Research Singapore (CCRS) is the research division of the Meteorological Service Singapore (MSS), with a vision is to be a world leading centre in tropical climate and weather research focussing on the Southeast Asia region. With approximately fifty staff, CCRS’ mission is to advance scientific understanding of tropical climate variability and change and its associated weather systems affecting Singapore and the wider Southeast Asia region, so that the knowledge and expertise can benefit decision makers and the community.
Within CCRS, the Department of Weather Research (DWR) is responsible for research and development supporting CCRS’ core ‘seamless’ ‘SINGV’ modelling system, used in both Numerical Weather Prediction (NWP) and regional climate projection applications e.g. Singapore’s ‘V3’ 3rd National Climate Study launched in January 2024. DWR also oversees research in AI-based rainfall nowcasting, forecast verification, the transition to operations of NWP science upgrades, and the development of customised products to support MSS weather services and other stakeholders. DWR works closely with CCRS’ High Performance Computing Branch, local universities and has bilateral research partnerships with several major international weather/climate organisations including the UK Met Office, Australian Bureau of Meteorology, and US National Center for Atmospheric Research (NCAR). CCRS is a core member of the multinational Momentum (formerly Unified Model) Partnership, with a focus on tropical urban weather/climate.
A new Data Assimilation and Ensembles (DAE) branch has recently been created within DWR to expand CCRS’ research activities in high-resolution (km-scale and higher) ensemble data assimilation (DA). A number of positions are now available in the new branch, at various levels ranging from research scientist to branch head.
[What you will be working on]
• Keeping abreast of the latest research in high-resolution atmospheric DA and ensemble prediction.
• Developing innovative DA algorithms suitable for km-scale tropical NWP and regional reanalysis applications.
• Performing impact studies of novel surface- and space-based observations e.g. ground-based radar, hyperspectral sounders, cubesats, etc.
• Exploring the role of AI in observation preprocessing and data assimilation.
• Supporting the translation of ensemble DA system development into operations.
• Working in collaboration with CCRS’ local and international strategic partners to leverage DA research and development in the wider community for MSS/CCRS applications.
• Publishing research outcomes in peer-reviewed publications and presenting findings at international meetings.
• (Branch Head): Providing science leadership, and project/staff management for a team of 4-5 DAE staff.
The job might be for you if you possess the following:
• Masters or PhD degree (or equivalent) in meteorology, data science, mathematics or a related field.
• At least 3 years research experience/publications in developing and/or applying data assimilation/science tools in physical science applications.
• Medium-High level of proficiency in scientific computing.
• Familiarity with NWP systems and data assimilation algorithms (e.g. JEDI, WRFDA, etc) is desirable.
• (Branch Head): Previous experience leading a science team and/or major project is desirable.
• Ability to work effectively to deadlines on individual projects and as part of a diverse team.
• Interest and passion to deliver relevant R&D for societal benefits.
• Ability to network effectively with the local and international research community.
• Ability to engage and communicate with scientists and stakeholders from diverse communities.
• Candidates with more years of experience will be considered for the Branch Head position.
As part of the shortlisting process for this role, you may be required to complete a medical declaration and/or undergo further assessment.
To apply, please proceed to Careers@gov at https://sggovterp.wd102.myworkdayjobs.com/PublicServiceCareers/job/NATIONAL-ENVIRONMENT-AGENCY/Deputy-Principal--Snr---Research-Scientist--Data-Assimilation---Ensembles-Branch-_JR-10000033884