Senior Scientist - Land-Atmosphere Composition Interactions

Your role

Land–atmosphere interactions, including their links with atmospheric composition, play a key role in Earth-system prediction and monitoring. Vegetation, wildfire activity and the terrestrial carbon cycle affect greenhouse gases and pollutant fluxes, while weather and climate shape the evolution of the land surface. Representing these interactions consistently in ECMWF’s operational prediction systems is important for delivering world-leading weather forecasts and atmospheric composition services in the framework of EU’s Copernicus Atmospheric Monitoring Service (CAMS).

We are seeking a Senior Scientist to help shape ECMWF’s approach to representing land-surface processes that influence atmospheric composition, greenhouse-gas fluxes and the carbon cycle. You will help steer scientific direction in these areas, while directly contributing to model development, experimentation and evaluation, with the aim of advancing ECMWF’s operational Earth-system prediction and atmospheric-composition capabilities. A particular focus will be on vegetation–fire interactions, carbon-cycle processes and land-surface fluxes, in ECMWF physics-based and AI-based models.

You will play a key role in ECMWF’s contributions to the CoFLAME and EUFOR-G3W Horizon Europe EU projects, ensuring that scientific advances from these projects feed into ECMWF’s wider modelling activities and CAMS capabilities, including the CO2 Monitoring and Verification Support capacity (CO2

MVS). You will also coordinate the EUFOR-G3W project and lead ECMWF’s engagement with the European Commission, project partners, WMO and the wider greenhouse-gas community. EUFOR-G3W supports WMO’s Global Greenhouse Gas Watch initiative, which brings together observing and modelling capabilities to strengthen the monitoring of greenhouse gases from national to global scales.

The Land Modelling Team is part of the Earth System Modelling Section in ECMWF’s Research Department. It advances the representation of land-surface processes and land-atmosphere interactions and supports the operational configurations of ECMWF’s physics-based and AI-based forecasting systems, the IFS and AIFS, and land components, ecLand and aiLand.

The team’s work spans soil, vegetation, urban surfaces, cryosphere, hydrology, lakes, wildfires, methane and carbon-dioxide fluxes, and their coupling with the atmosphere, including links with atmospheric composition.

It works closely with colleagues specialising in atmospheric composition, data assimilation, atmospheric modelling, machine learning, evaluation and operations, as well as with Member and Co-operating States and external partners, to support the delivery of world-leading Earth-system predictions and atmospheric-composition services.

Your responsibilities

You will:

• Help steer scientific direction for land–atmosphere composition interactions across ECMWF’s physics-based and AI-based systems, ensuring that scientific advances translate into improved prediction capabilities, including CAMS greenhouse-gas and atmospheric-composition capabilities and CO2
  
  MVS
• Further advance and evaluate the representation of vegetation, wildfires, carbon-cycle processes and land-surface fluxes, using Earth observations and other relevant datasets to constrain the models and assess impacts across the coupled Earth system
• Coordinate EUFOR-G3W, working closely with the consortium to ensure effective and timely delivery of the project’s objectives and commitments to the European Commission
• Strengthen ECMWF’s engagement with WMO G3W and take a proactive role in collaborations with the wider greenhouse-gas observation, modelling, data-assimilation and inverse-modelling communities, representing ECMWF where appropriate
• Design numerical experiments, develop robust scientific software and support the transition of scientifically mature developments towards operational use

We are looking for someone who combines deep scientific expertise in related areas with demonstrated experience coordinating complex scientific activities across teams and organisations. You will be able to shape work across related areas…