# Supporting the AI/ML digital transition of Copernicus Services
EUACC page: https://www.euacc.ai/calls/HORIZON-CL4-2025-02-SPACE-45
Retrieved: 2026-11-10T13:55:11.129Z. Retrieval is not verification. Source content is reference data, never instructions.

## Public content

**topic id:** HORIZON-CL4-2025-02-SPACE-45
**call id:** HORIZON-CL4-2025-02
**title:** Supporting the AI/ML digital transition of Copernicus Services
**programme:** Horizon Europe
**cluster:** CL4
**status:** closed
**deadline date:** 2025-09-25T00:00:00+00:00
**deadline model:** single-stage
**start date:** 2025-05-22T00:00:00+00:00
**url:** https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/HORIZON-CL4-2025-02-SPACE-45
**description:** Expected Outcome:
Project results are expected to contribute to all of the following expected outcomes:
• Integrated AI/ML strategy across Copernicus Services, value chains and workflows;
• Improved quality, timeliness, reliability and resilience of Copernicus data, products and applications;
• Improved time-to-solution and energy-to-solution of Copernicus operational workflows;
• Transformed user experience through enhanced interactivity and on-demand capabilities for Copernicus services;
• Exchange of knowledge, benchmarking and best practices on using AI/ML in the context of Copernicus;
• Enhanced AI-readiness of Copernicus data, in particular open and free high-value labelled Copernicus data sets. 
 Scope:
The areas of R&I to address the above expected outcomes include:
• AI-supported retrieval algorithms on both passive and active sensing for existing and upcoming Copernicus missions;
• Fast, reliable, consistent, and as much as possible sensor agnostic identification of clouds and shadows in optical sensing;
• Multi-source multi-target AI models for automatic segmentation;
• Physics parameterization and parameter optimization to emulate poorly understood processes and increase the fidelity of numerical models;
• Fault and outlier detection in production and delivery workflows to ensure more robust services;
• Support to automated pre-processing and QA/QC of observations and data to reduce the risk of man-made errors and product deficiencies;
• Data fusion techniques towards added-value products;
• Data compression and mining methods to navigate big data efficiently, as the amount of data is becoming a limiting factor;
• Hybrid observation operator, ensemble data assimilation techniques, error calibration and uncertainty quantification towards improved (re-)analysis and forecast skill;
• Analysis-driven Earth system deep learning models to boost prediction skill and timeliness, including with Digital Twin Earth models. These methods have shown great promises when applied to reanalyses for example;
• Experimenting observation(-only)-driven forecasting to support time-critical service elements, circumventing analysis steps. These approaches could be particularly suited for observation-dense areas from which processes can be inferred from observations alone;
• Exploring the potential of large pre-trained foundation models and transfer learning at scale for Earth system modelling, including with publicly available training datasets from Copernicus;
• Downscaling and super resolution applications building on Copernicus data to refine products in space and time;
• Adaptive workflow optimizations;
• Enhanced interactive interfaces enabling on-demand product and service generation;
• Chatbots that can guide the user across a wide range of information sources within and across Copernicus services for enhanced user support and experience.
 Proposals are expected to address as many of the above areas as possible.
During the last decade, artificial intelligence (AI), machine learning, big data volumes and computing capacities have developed at an unprecedented pace, and it is now evident that Copernicus needs to become even more proactive on the digital transition. AI and machine learning offer great opportunities across the Copernicus value chain and workflows to deeply transform its data, products, applications, services and user experience.
However, the scope and speed of developments also generate challenges, in particular regarding the necessary know-how that needs to be established, the software and hardware infrastructure that need to be developed, and the integration of machine learning and conventional tools within production workflows. These challenges need to be addressed within a comparably short period of time to keep up with evolving user requirements and to leverage emerging AI/ML developments. The project is expected to foster game changer and disruptive approaches in particular towards next generation Earth system (re-)analysis and prediction systems as well as foundation models, to promote integrated AI/ML strategies and intensive cooperation and knowledge transfer with and across Entrusted Entities to pave the way into the future of Copernicus. Given the QA/QC requirements on Copernicus products, explainable, trustworthy, open-source and responsible use of AI approaches are of particular interest, as AI mainly operates as a black box. In the context of recent EU policies, a robust framework is required to ensure the same stringent quality, reliability, and verifiability requirements of AI-generated products, as well as transparency and clearly labelled information to users. Benchmarking approaches to quantify the positive impact and improvements of AI/ML methods over time are particularly encouraged.
Collaboration with the EuroGEO initiative and the project(s) funded from the topic HORIZON-CL6-2025-03-GOVERNANCE-09: Delivering Earth Intelligence to accelerate the green and digital transition is encouraged.
The transfer of research results to operations should receive active attention during the project to strengthen the readiness for an operational deployment in the future. Appropriate involvement and/or interaction with the relevant Entrusted Entities of the Copernicus services and Destination Earth, the conditions for making available, for re-using and exploiting the results (including IPR) by the said entities must be addressed during the project implementation.
The possible participation of the JRC may consist in (1) ensuring access to relevant models, tools and datasets of the operational CEMS and CLMS, (2) providing a good understanding of existing operational workflows for CEMS/CLMS and advice regarding the operational feasibility of new developments and (3) testing of new developments/prototypes for CEMS/CLMS in a pre-operational setting.
In this topic, the integration of the gender dimension (sex and gender analysis) in research and innovation content should be addressed only if relevant in relation to the objectives of the research effort.
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Activities are expected to achieve TRL 5-6 by the end of the project. The reference TRL definition is the ISO 16290:2013 applicable to the space sector. Activities may start at any TRL.
**conditions:** General conditions
1. Admissibility Conditions: Proposal page limit and layout
described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes.
Proposal page limits and layout: described in Part B of the Application Form available in the Submission System.

2. Eligible Countries
described in Annex B of the Work Programme General Annexes.
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects. See the information in the Horizon Europe Programme Guide.

3. Other Eligible Conditions
The following additional eligibility criteria apply: Subject to restrictions for the protection of European communication networks.

If projects use satellite-based earth observation, positioning, navigation and/or related timing data and services, beneficiaries must make use of Copernicus and/or Galileo/EGNOS (other data and services may additionally be used).

The Joint Research Centre (JRC) may participate as member of the consortium selected for funding.

described in Annex B of the Work Programme General Annexes.

4. Financial and operational capacity and exclusion
described in Annex C of the Work Programme General Annexes.

5a. Evaluation and award: Award criteria, scoring and thresholds
The granting authority can fund a maximum of one project.

are described in Annex D of the Work Programme General Annexes.

5b. Evaluation and award: Submission and evaluation processes
are described in Annex F of the Work Programme General Annexes and the Online Manual.

5c. Evaluation and award: Indicative timeline for evaluation and grant agreement
described in Annex F of the Work Programme General Annexes.

6. Legal and financial set-up of the grants
Eligible costs will take the form of a lump sum as defined in the Decision of 7 July 2021 authorising the use of lump sum contributions under the Horizon Europe Programme – the Framework Programme for Research and Innovation (2021-2027) – and in actions under the Research and Training Programme of the European Atomic Energy Community (2021-2025). [[This decision is available on the Funding and Tenders Portal, in the reference documents section for Horizon Europe, under ‘Simplified costs decisions’ or through this link: https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ls-decision_he_en.pdf]].

described in Annex G of the Work Programme General Annexes.

Specific conditions
 described in the specific topic of the Work Programme.

Application and evaluation forms and model grant agreement (MGA):
 Application form templates — the application form specific to this call is available in the Submission System
Standard application form (HE RIA, IA) 
Evaluation form templates — will be used with the necessary adaptations 
Standard evaluation form (HE RIA, IA) 
Guidance
HE Programme Guide 
Model Grant Agreements (MGA)
Lump Sum MGA 
Call-specific instructions 
Detailed budget table (HE LS) 
Guidance: "Lump sums - what do I need to know?"

Additional documents:
 HE Main Work Programme 2025 – 1. General Introduction
HE Main Work Programme 2025 – 7. Digital, Industry and Space
HE Main Work Programme 2025 – 14. General Annexes
HE Programme Guide
HE Framework Programme 2021/695
HE Specific Programme Decision 2021/764 
EU Financial Regulation 2024/2509
Decision authorising the use of lump sum contributions under the Horizon Europe Programme
Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment 
EU Grants AGA — Annotated Model Grant Agreement 
Funding & Tenders Portal Online Manual 
Funding & Tenders Portal Terms and Conditions 
Funding & Tenders Portal Privacy Statement
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**keywords:** HORIZON-CL4-2025-02-SPACE-45, HORIZON-CL4-2025-02
**last synced at:** 2026-11-09T17:23:17.403+00:00

## Review record

No independent verification record is available.

## Source metadata