The Copernicus Climate Change Service Evolution (CERISE) project will address the requirements of the two research topics of the call. The scope of CERISE is to enhance the quality of the C3S reanalysis and seasonal forecast portfolio, with a focus on land-atmosphere coupling. It will support the evolution of C3S, over the timescale of three years and beyond, by improving the C3S climate reanalysis and the seasonal prediction systems and products towards enhanced integrity and coherence of the C3S Earth system ECVs. CERISE will develop new and innovative ensemble-based coupled land-atmosphere data assimilation approaches and land surface initialisation techniques to pave the way for the next generations of the C3S reanalysis and seasonal prediction systems. These developments will be combined with innovative work on observation operator developments integrating Artificial Intelligence (AI) to ensure optimal data fusion fully integrated in coupled assimilation systems. They will drastically enhance the exploitation of past, current, and future Earth system observations over land surfaces, including from the Copernicus Sentinels and from the European Space Agency (ESA) Earth Explorer missions, moving towards an all-sky and all-surface approach.
The CERISE outputs, aim at medium to long-term upgrades of the C3S systems with targeted progressive implementation in the next three years and beyond. CERISE will improve the quality and consistency of the C3S reanalysis and multi-system seasonal prediction, directly addressing the evolving user needs for improved and more consistent C3S Earth system.
CERISE has the following key objectives:
- Develop unified multivariate ensemble-based land data assimilation systems for global and regional reanalysis systems;
- Develop methodologies for coupled surface-atmosphere data assimilation and improve the exploitation of Earth system interface observations;
- Investigate innovative balanced land-atmosphere initialisation methodologies for seasonal prediction with a focus on the consistency between retrospective forecasts (reforecasts) and real-time land surface initial conditions;
- Create and assess a consistent extension of slow-varying surface variables for Land Cover (LC), Leaf Area Index (LAI) and lake cover, data back to 1925 for reanalysis;
- Deliver prototype coupled Earth systems and land surface reanalysis systems datasets at global and regional scales;
- Deliver multi-system seasonal forecast demonstrator datasets integrating novel land initialisation methods;
- Develop innovative diagnostic methods to assess quality in reanalysis prototypes and seasonal forecast demonstrators;
- Provide recommendations for operational implementation in the Copernicus Climate Change Service
Overarching objectives of CERISE to support the evolution, with a focus on land-atmosphere consistency, of C3S Earth system reanalyses and seasonal prediction systems and the provision of the proof of concept for future integration in C3S.