The overall objective of Mopo is to develop a validated, user-friendly, feature-rich, innovative and well-performing energy system modelling toolset to serve public authorities, network operators, industry and academia to plan sustainable and resilient energy systems in a cost-effective manner. Mopo will include 1) component tools to produce all necessary energy system data; 2) system tool to manage data, scenarios and modelling workflows, to visualise data and to maintain datasets in multi-user environment without losing the track of changes; 3) planning tool to optimise all energy sectors in detail, including sector specific physics and highly flexible representation of temporal, spatial and technological aspects – user can choose how to model depending on the specific needs. The project is based on existing state-of-the-art tools including Spine Toolbox and SpineOpt. The advanced capabilities will be demonstrated through an industrial case (with detailed sector-specific physics) and Pan-European case (resilient pathways). The project will also produce an open access Pan-European dataset at hourly temporal resolution and high spatial resolution (NUTS2 capable). It can be fed into SpineOpt or used by other modelling groups. Mopo tools can recreate data at resolution required by the end-user – also for future climates. End-user requirements, feedback and tool validations will be important part of Mopo – the consortium includes representatives from all end-user categories. Partners will also have skills in user-interfaces, computational efficiency, data processing, code testing, community building and all aspects related to energy systems (technologies, sectors, resources). Mopo project aims to benefit 60% of network operators and public authorities within 2 years of the project end. The tools will be modular, which allows different organisations to adopt the parts that benefit their existing modelling systems.

Microbiomes have high potential to improve biobased processes. For example, in soil and groundwater they can degrade organic contaminants, a process called bioremediation. In Europe about 324,000 severely contaminated sites exist, which pose a risk to humans and the environment. Conventional remediation technologies to clean them are often too expensive and technically Microbiomes have a high potential to improve processes in the bio-based industry. Like the microbiome in the gut, that supports the body in the digestion of food, microbiomes in environmental compartments like soil and groundwater can produce enzymes that can degrade organic contaminants caused by human activities. In MIBIREM we will develop a TOOLBOX that helps to better develop applications for microbiomes. The TOOLBOX includes molecular methods for a better understand and monitoring, isolation and cultivation techniques as well as quality criteria for deposition of whole microbiomes and last, but not least methods that are applied to improve specific functions of microbiomes like microbiome evolution and enrichment cultures and microcosm tests. The TOOLBOX is developed for the environmental applications of microbiomes for ‘bioremediation’. For that purpose, three use-cases were selected. In these three use-cases the degradation of organic contaminants in soil and groundwater by active microbiomes is investigated and developed. The three groups of contaminants are cyanides, hexachlorocyclohexane (HCH) and petroleum hydrocarbons (PHC). The project starts with sampling of contaminated sites to isolate microbiomes active in degradation and to gain data for the development of a prediction tool that helps guide bioremediation. Isolated microbiomes and degrading strains will be deposited and will also be improved via laboratory evolution. Finally, the performance of the isolated microbiomes will be tested based on the gained knowledge about degrading microbiomes in pilot tests under real field conditions.

The European Climate Prediction system project (EUCP) has four objectives, all directly relevant to the work programme, and fully meet the challenge, scope and impact of the work programme. 1. Develop an innovative ensemble climate prediction system based on high-resolution climate models for Europe for the near-term (~1-40years), including improved methods used to characterise uncertainty in climate predictions, regional downscaling, and evaluation against observations. 2. Use the climate prediction system to produce consistent, authoritative and actionable climate information. This information will be co-designed with users to constitute a robust foundation for Europe-wide climate service activities to support climate-related risk assessments and climate change adaptation programmes. 3. Demonstrate the value of this climate prediction system through high impact extreme weather events in the near past and near future drawing on convection permitting regional climate models translated into risk information for, and with, targeted end users. 4. Develop, and publish, methodologies, good practice and guidance for producing and using authoritative climate predictions for 1-40year timescale. The system (objective1) will combine initialised climate predictions on the multi-annual timescale with longer-term climate projections and high resolution regional downscaling, using observations for evaluation. Methodologies will be developed to characterise uncertainty and to seamlessly blend the predictions and projections. Users will be engaged through active user groups. The system will be utilised (objective2) with users to co-produce information suitable for European climate service activities. A set of demonstrators will show the value of this information in real-world applications with user involvement (objective3). Key outputs will include disseminating and publishing the project’s methodologies, and user-relevant data and knowledge (objective4).

The path towards exascale computing holds enormous challenges for the community of weather and climate modelling regarding portability, scalability and data management that can hardly be faced by individual institutes. ESiWACE2 will therefore link, organise and enhance Europe's excellence in weather and climate modelling to (1) enable leading European weather and climate models to leverage the performance of pre-exascale systems with regard to both compute and data capacity as soon as possible and (2) prepare the weather and climate community to be able to make use of exascale systems when they become available. To achieve this goal, ESiWACE2 will (a) improve throughput and scalability of leading European weather and climate models and demonstrate the technical and scientific performance of the models in unprecedented resolution on pre-exascale EuroHPC systems, (b) evaluate and establish new technologies such as domain specific languages and machine learning for use in weather and climate modelling, (c) enhance HPC capacity via services to the weather and climate community to optimize code performance and allow model porting, (d) improve the data management tool chain from weather and climate simulations at scale, (e) foster co-design between model developers, HPC manufacturers and HPC centres, and (f) strengthen interactions of the community with the European HPC Eco-system. ESiWACE2 will deliver configurations of leading models that can make efficient use of the largest supercomputers in Europe and run at unprecedented resolution for high-quality weather and climate predictions. This will be a beacon for the community in Europe and around the world. ESiWACE2 will develop HPC benchmarks, increase flexibility to use heterogeneous hardware and co-design and provide targeted education and training for one of the most challenging applications to shape the future of HPC in Europe.

IS-ENES3 will deliver the third phase of the distributed e-infrastructure of the European Network for Earth System Modelling (ENES). IS-ENES3 will be initiated as the European climate modelling community faces the challenges of contributing to the next assessment report of the Intergovernmental Panel on Climate Change through the 6th phase of the Coupled Model Intercomparison Project. IS-ENES3 will address these challenges by developing, documenting and deploying new and advanced models and tools, standards and services to deal with unprecedented data volumes and model complexity. IS-ENES3 will stimulate collaboration, disseminate software and data, and further integrate the European climate science community. IS-ENES3 will support climate research, climate impact science, and the climate services industry. It will bring down barriers of access, and expand the community who can exploit the data and knowledge produced by state-of-the-art climate models. In doing so, it will find innovative ways of working with the Copernicus programme, other parts of the European data infrastructure, and with the high performance computing and data analytics industries. IS-ENES3 will be delivered by partners combining expertise in climate modelling, computational science, data management, climate impacts and climate services, with proven ability to increase the influence of European science internationally. It will deliver the European part of the Earth System Grid Federation and a central point of entry to services providing access to new data, software, models and tools. Joint research will support a new community sea ice model, promote efficient use of high-performance computing, improve the European common model evaluation framework, and develop and enhance services on data. Networking will grow the user base, increase the cohesion of the climate modelling community, promote innovation and prepare for a long term sustainable infrastructure in support of climate modelling.