Postdoctoral Researcher – UrbaNE: Urban Numerical Weather Prediction Expedited

Job title:

Postdoctoral Researcher – UrbaNE: Urban Numerical Weather Prediction Expedited

Company

University of Reading

Job description

To undertake research within the URBANE (Urban Numerical Weather Prediction Expedited) project. This project focuses on services and forecasts for people and infrastructure in urban environments, supporting both ECMWF and the Met Office in their drives towards better representation of urban environments within numerical weather prediction (NWP) and climate models. The key contribution of this project will be evaluating urban NWP with observations, taking better advantage of high resolution thermal remote sensing), field campaign data and radiative transfer modelling.By enhancing our capabilities in global data assimilation, simulation and analysis, AFESP will deliver a new class of accurate, reliable and usable forecasts, aiming to re-define the medium-range predictability limit from two to at least four weeks, enabling a wide range of new scientific and societal applications. Within that, URBANE focuses on services and forecasts for people and infrastructure in urban environments, to improve services supporting health, infrastructure risk, and climate-change resilience. This requires representing urban environments better and at appropriate scales within models. The key contribution will be evaluating urban NWP with observations.Main duties and responsibilities:
Working with ECMWF, Met Office, NCEO, ERC urbisphere and NERC ASSURE researchers the candidate will undertake collaborative research and make significant contributions to the following activities:

• Research on processes and process chains that help increasing skill in the extended NWP range, with a focus on scales at which new observations and state-of-the art numerical simulation are more directly comparable.
• Develop and test new approaches in numerical simulation that target increased process fidelity, including enhanced resolution, new parametrisations suitable for km-scale, including alternative methods such as machine learning. Prioritise use of unexplored observations, both for verification and as candidates for additional data assimilation.
• Research on developing new data assimilation techniques that are capable of handling dense data, as well as increased coupling between Earth System components
• Attend, contribute to, and organise relevant project meetings.
• Report on progress and results of the research through appropriate methods, including papers for submission to scientific journals, presentation of results at conferences and workshops, etc.
• Maintain awareness of current progress in relevant research areas to ensure that the research remains at the cutting edge.
• Liaise with collaborators from other parts of the programme on a regular basis, including travel to visit project partners as required.

URBANE is part of the Advancing the Frontiers of Earth System Prediction (AFESP) research programme, a 15-year investment by the University of Reading, in partnership with ECMWF, Met Office and NCAS. AFESP will deliver tackle some of far-term (10-15 year) and difficult (high-risk, high-reward) research challenges in global Earth System prediction.Closing Date: 6 June 2024Interview Date: TBCInformal contact details:
Contact role: Professor of Urban Meteorology
Contact name: Professor Sue Grimmond
Contact email:Alternative informal contact details:
Contact role: Professor of Climate System Science & Climate Hazards and Director of University of Reading – ECMWF Research Collaboration
Contact name: Professor Pier Luigi Vidale
Contact email:Applications from job seekers who require sponsorship to work in the UK are welcome & will be considered alongside all other applications. By reference to the applicable SOC code for this role, sponsorship may be possible under the Skilled Worker Route. Applicants should ensure that they are able to meet the points requirement under the PBS. There is further information about this on the .£33,966 to £44,263 per annum

Expected salary

£33966 – 44263 per year

Location

England

Job date

Wed, 15 May 2024 00:50:33 GMT

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