Dynamic climate-agriculture intelligence for adaptive EU land management and cropping systems

TIPPING addresses the urgent need for climate-intelligent adaptation of European agriculture under shifting agroecological zones and increasing risks of extremes. The project aspires to design, develop, and release a comprehensive, operational, and transferable Agricultural Climate Intelligence Stack (ACIS) that integrates climate scenarios (WP2), socio-economic models, and behavioural simulation (WP3) into actionable decision-support tools for farmers, advisors, land managers, and policymakers. The integrated solution (WP4) combines dynamic AI-powered climate impact models, climate data tools (WP3), decision-support algorithms, and business models (WP6), enabling stakeholders across the agri-food value chain to understand the consequences of shifting climate zones, interact effectively with climate intelligence, and strengthen their capacity to decide what can be grown, where, and when. Grounded in a multi-actor co-design methodology (WP1) and inspired by the Data–Information–Knowledge–Wisdom (DIKW) model, TIPPING establishes five Climate Intelligence Hubs (CIHs) across Europe’s major agroclimatic zones (Atlantic, Boreal, Continental, Transitional, Mediterranean), serving as testbeds for validation, transferability, and stakeholder engagement (WP5). Importantly, TIPPING will support the strategic planning and evidence-based design of tailored climate adaptation plans on selected cropping systems facing diverse climate impacts. The consortium brings together 16 partners from 10 EU countries, spanning leading climate and Earth system scientists, agronomists, agricultural research institutes, AI/ML experts, farmer organisations, SMEs, and advisory networks. TIPPING will directly support the EU Adaptation Strategy, CAP, and the Mission on Climate Adaptation, strengthen the Destination Earth Climate Adaptation Digital Twin, and contribute to the FAIRification of agroclimatic data. JRC involvement is provisioned for support in WP2 Climate Data and Modelling Activities.