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This funding call focuses on the advancement of the Copernicus Climate Change Service (C3S) by developing innovative methods to process and pre-process Earth observation data, with a specific emphasis on reanalyses. Projects should aim to enhance data assimilation methods, improve climate records, and develop new reanalysis products, including centennial reanalyses and counterfactual datasets. The call encourages the integration of AI and machine learning techniques to accelerate reanalysis production while reducing the computational and environmental footprint. Collaborative efforts with European space agencies and integration of gender dimensions in research, if relevant, are expected. Open-licensed software is required, and active collaboration with Entrusted Entities of Copernicus services is emphasized to ensure operational readiness.
Opening: 03 Jun 2025
Deadline(s): 13 Nov 2025
Data provided by Sciencebusiness.net
This funding opportunity represents a pre-agreed draft that has not yet been officially approved by the European Commission. The final, approved version is expected to be published in the first quarter of 2025. This draft is provided for informational purposes and may be used to preliminarily form consortia and develop project ideas, but it is offered without any guarantees or warranties.
Expected Outcome
- Innovative methods for preparing observational input for reanalysis datasets.
- Enhanced data assimilation for climate sub-components in Copernicus products.
- Improved climate monitoring and extraction of historical data insights.
- Expanded reanalyses products, including centennial reanalyses and extreme event attribution datasets.
Scope
- Enhance Copernicus models to assimilate data from Copernicus Sentinel missions and other satellites.
- Develop innovative methods for data rescue and bias adjustment, particularly for historical observations.
- Improve the use of Sentinel data in reanalyses and coordinate developments in observational error characteristics.
- Explore AI and ML approaches to accelerate reanalysis updates and reduce computing energy demands.
- Strengthen operational readiness and ensure results are reusable by relevant Copernicus services.