Journal Article

The Destination Earth digital twin for climate change adaptation

Müller, Sebastian, Nurisso, Matteo, Quintino, Tiago, Van Thielen, Ginka, Nazarova, Natalia, Rocha Monteiro, Nuno, Hearne, Shane, Kegel, Jessica, Pelletier, Charles, Kontkanen, Jenni, Willner, Sven, Kelbling, Matthias, Klocke, Daniel, Manninen, Pekka, Grayson, Katherine, Sidorenko, Dmitry, Räisänen, Jouni, Reuter, Balthasar, Frauen, Claudia, Tuomenvirta, Heikki, Doblas-Reyes, Francisco J, Ghosh, Supriyo, Medvedev, Alexey, Sharma, Tanvi, Sievi-Korte, Outi, Streffing, Jan, Vitali, Emanuele, Kosukhin, Sergey, Naryanappa, Devaraju, Redler, René, Zimmermann, Janos, Jung, Thomas, Griffith, Matthew, Alsina-Ferrer, Ivan, Davini, Paolo, Bretonnière, Pierre-Antoine, Pradhan, Himansu Kesari, Sandu, Irina, Jiménez, Bernat, Ghinassi, Paolo, Batlle Martín, Marc, Schnur, Reiner, Tuppi, Lauri, Kornblueh, Luis, Hartick, Carl, Järvinen, Heikki, Castrillo, Miguel, Milinski, Sebastian, Nortamo, Henrik, Bockelmann, Hendryk, Enkovaara, Jussi, Niraula, Bimochan, Steger, Christian, Soret, Albert, Beltrán, Daniel, Früh, Barbara, Bauer, Peter, Danovaro, Emanuele, Hadade, Ioan, Ghosh, Rohit, Thober, Stephan, Al Turjmam, Mohammed Hus

2026

Overview

The Climate Change Adaptation Digital Twin (Climate DT), developed as part of the European Commission's Destination Earth (DestinE) initiative, sets up an operational system for producing multi-decadal, multi-model global climate projections and translating climate data into climate impact information to support adaptation efforts. This system delivers data with local granularity at spatial resolutions of 5–10 km and hourly outputs, leading to globally consistent information at scales that matter for decision-making. It also enables the testing of what-if scenarios such as high-resolution storylines, which are physically consistent global simulations of extreme events under different climate conditions and provide contextual insights to support concrete adaptation decisions. They support the generation of more equitable (understood as accessible and relevant across regions) climate information. The Climate DT is built on cutting-edge infrastructure, expert collaboration, and digital innovation. It is designed to support on-demand responses to policy questions, with quantified uncertainty. It will foster interactivity by allowing users to influence simulation design, model output portfolios, and application integration through co-design. AI-based tools, including emulators and chatbots, are being developed in parallel to enhance climate information access. Sector-specific applications are embedded in the system to synchronously translate climate data into tailored climate-impact indicators, with examples provided for energy, water, and forest management. The applications have been co-designed with informed users. A unified, cross-platform workflow defines the orchestration of all components, which is handled by a single workflow manager and relies on containerised components, facilitating automation, portability, maintainability, and traceability. Data management is unified using standard grids (HEALPix), ensuring consistency and easing data usability under a strict governance policy. Streaming enables real-time data use by the data consumers and unlocks access to the unprecedented data wealth produced by the high-resolution simulations. Monitoring tools provide real-time quality control of data and model outputs and enable continuous assessment of the realism of the climate simulations during Climate DT operation. The compute-intensive system is powered by world-class supercomputing capabilities through a strategic partnership with the European High Performance Computing Joint Undertaking (EuroHPC). Despite high computational demands, the Climate DT sets a new benchmark for delivering equitable, credible, and actionable climate information. It complements existing initiatives like CMIP, CORDEX, and national and European climate services, and aligns with global climate science goals to support climate adaptation.

• Publisher: Copernicus GmbH
• Subject: Adaptation / Artificial intelligence / Automation / Climate adaptation / Climate change / Climate change adaptation / Climate models / Climate science / Climatic conditions / Climatic data / Co-design / Data management / Decision making / Digital twins / Forest management / Global climate / High resolution / Maintainability / Quality control / Real time / Workflow