CLAIMA

About the project

CLAIMA (Climate AI Modelling and Analysis) is a four-year Horizon Europe project working to establish a European AI-driven Digital Twin Platform for Climate. The platform combines generative AI, foundation models, climate emulators, learned downscaling and scalable computing into an open, modular and interoperable research infrastructure that serves both climate science and evidence-based decision-making. By integrating and rigorously validating cutting-edge AI climate models within a standards-based environment, CLAIMA will make climate simulations orders of magnitude faster, deliver high-resolution climate information, and enable seamless weather-to-climate projections, all while safeguarding the scientific robustness and reproducibility that credible climate research demands.

The platform is designed for deployment on European HPC and AI Factory infrastructures and sits in close alignment with wider initiatives such as Destination Earth, offering pre-operational AI capabilities that research groups, industry and public services can pick up and use. Its impact will be demonstrated through a set of flagship applications spanning Earth system science, climate-resilient shipping, energy infrastructure planning and climate-related health risks. This is a deliberate choice to prove, in real settings, that AI-enabled climate modelling can accelerate discovery and support adaptation and resilience across Europe.
Coordinated by the Alfred-Wegener-Institut, Helmholtz Centre for Polar and Marine Research (Germany), CLAIMA runs from September 2026 to August 2030 and unites a consortium of European partners spanning climate science, AI research, high-performance computing, and communication. 

Trust-IT role in CLAIMA

Trust-IT contributes to CLAIMA as the partner responsible for communication, dissemination and stakeholder engagement. The team's remit is to translate CLAIMA's scientific and technical progress into content, campaigns and conversations that reach the audiences who matter most: the wider climate research community, policy-makers, industry adopters, and citizens with a stake in Europe's climate future.

In practice, Trust-IT oversees the design and roll-out of the project's Communication and Dissemination Plan, curates CLAIMA's brand and visual identity, and runs its website and social media presence. The team also supports internal coordination across the consortium, manages editorial planning and press relations, and shapes the outward-facing narrative that will accompany CLAIMA's flagship demonstrations and public deliverables, making sure that a highly technical project speaks clearly, and to the right people, at every stage of its life.

Expected impact and outcomes

CLAIMA sets out to change what is possible in climate modelling. By placing AI at the core of the next generation of climate models, and by validating those models under rigorous scientific standards, the project aims to make credible high-resolution climate information available on timescales that today's approaches simply cannot match.
The expected outcomes reach well beyond the technical. Faster, finer and more reliable climate simulations translate into better-informed adaptation strategies for coastal cities, more resilient energy infrastructure planning, safer shipping routes across a changing Arctic, and stronger public-health responses to climate-driven risks. By feeding its results into European infrastructures such as Destination Earth, and by keeping the platform open and interoperable by design, CLAIMA will leave behind a shared European capability rather than a closed prototype, an infrastructure that researchers, public services and industry can continue to build on well after the project ends.

In doing so, CLAIMA also contributes to Europe's wider ambition of technological sovereignty in climate science: a homegrown, trustworthy AI stack for one of the defining challenges of our times. 
 

The project is funded by the European Union's Horizon Europe research and innovation programme under Grant Agreement No. 101290971.