Weather and climate extremes pose challenges for adaptation and mitigation policies as well as disaster risk management, emphasizing the value of Climate Services in supporting strategic decision-making. Today Climate Services can benefit from an unprecedented availability of data, in particular from the Copernicus Climate Change Service, and from recent advances in Artificial Intelligence (AI) to exploit the full potential of these data. The main objective of CLINT is the development of an AI framework composed of Machine Learning (ML) techniques and algorithms to process big climate datasets for improving Climate Science in the detection, causation and attribution of Extreme Events (EE), including tropical cyclones, heatwaves and warm nights, and extreme droughts, along with compound events and concurrent extremes. Specifically, the framework will support (1) the detection of spatial and temporal patterns, and evolutions of climatological fields associated with Extreme Events, (2) the validation of the physically based nature of causality discovered by ML algorithms, and (3) the attribution of past and future Extreme Events to emissions of greenhouse gases and other anthropogenic forcing. The framework will also cover the quantification of the Extreme Events impacts on a variety of socio-economic sectors under historical, forecasted and projected climate conditions by developing innovative and sectorial AI-enhanced Climate Services. These will be demonstrated across different spatial scales, from the pan European scale to support EU policies addressing the Water-Energy-Food Nexus to the local scale in three types of Climate Change Hotspots. Finally, these services will be operationalized into Web Processing Services, according to
COACCH (CO-designing the Assessment of Climate CHange costs) is a project funded by the European Union’s Horizon 2020 research and innovation programme and carried out by a consortium of 14 European organisations. COACCH will develop an innovative science-practice and integrated approach to co-design and co-deliver an improved downscaled assessment of the risks and costs of climate change in Europe, working with end users from research, business, investment, and policy making communities throughout the project.
The ETC/CCA is a Consortium of European institutions that supply thematic expertise to the European Environment Agency (EEA) working at the interface between science and policy, in support to policy development and implementation in the area of climate change impacts, vulnerability and adaptation across Europe.
GoNEXUS aims to develop a framework for designing and assessing innovative solutions for an efficient and sustainable coordinated governance of the water-energy-food-ecosystems (WEFE) nexus. Solutions will combine policy changes and soft path options with technical and infrastructure measures for a more resilient future. To achieve this objective, the project will build a powerful model toolbox and creative participatory Nexus Dialogues. The model toolbox will include forefront global/continental and river basin models, innovatively establishing a functional link between them. At global and continental scales, the toolbox will include the individual WEFE element models CAPRI (food, agri-environment), LISFLOOD-EPIC and PCR-GLOBWB (water), PRIMES and PROMETHEUS (energy), GLOBIO (environment), and GEM-E3 (macroeconomics), some of them used in EU policies. River basin models will include nested strategic WEFE management models (including behavioral modelling) and hydrological simulation models to expand the analysis of resilience at basin scale, including impacts on ecosystems. Nexus Dialogues will co- design scenarios, models, and solutions for a joint governance of the WEFE nexus. The solutions will be evaluated using the model toolbox through a set of novel nexus indicators and criteria (based on relevant SDGs metrics) to assess trade-offs between water status, and food and energy security. GoNEXUS will be applied at global and EU levels and to six river basins representing different features and WEFE challenges in Europe (Danube, Como, Jucar, Tagus-Segura) and Africa (Zambezi, Senegal). The innovative combination of models and Nexus Dialogues will provide more accurate evaluations of future scenarios, enabling knowledge sharing and brokerage, and improving WEFE
Through the use of High Performance Computing, HIGHLANDER will make it possible to process data and generating climate forecasts and projections to reduce the risks associated with climate change, for a more intelligent and sustainable management of natural resources and the territory.
Water, energy, food, and ecosystems (WEFE) are interconnected, comprising a coherent system (nexus) dominated by complexity and modulated by climatic and socio-economic drivers. Resource constraints, and their interconnectedness could hamper economic development, including optimal trade, market and policy solutions. NEXOGENESIS offers a coherent WEFE nexus framework for the assessment of potential impact pathways of implementing new policy objectives (WFD, RED, CAP, SDGs, Paris Agreement) in the nexus, including: (i) biophysical and socio-economic modelling; (ii) stakeholder engagement together with; (iii) validation of NEXOGENESIS outputs and; (iv) use of the latest artificial intelligence techniques.