Adaptation to climate change requires in-depth understanding of climate change driven risks, including their determinants (hazards, exposure and vulnerabilities) and impacts to human, production and natural systems. Integrated Research Infrastructure Services for Climate Change Risks (IRISCC) is a consortium of diverse and complementary leading research infrastructures (RIs) covering disciplines from natural sciences to social sciences, across different domains and sectors. IRISCC provides scientific and knowledge services to foster cutting-edge research and evidence-based policymaking to improve Europe's resilience to climate change. IRISCC ensures a “one-stop-shop” for various user communities on climate change risk related RI services by setting up a dedicated Catalogue of services and related access management system both for granting transnational (onsite and remote) and offering virtual access. The Catalogue of services will be built through three consecutive releases, each delivering increasingly integrated services to its user communities. The IRISCC service integration will include Service Design Labs employing co-design and transdisciplinary action, and Service Demonstrators benchmarking the integrated cross-RI services. In addition to services aimed towards the scientific community, IRISCC will offer knowledge services aimed towards policymakers and other stakeholders. This is done together with risk management platforms. The research enabled by IRISCC contributes to future reports on climate change effects (IPCC, IPBES) as well as policy- and decision-making to meet the targets of climate adaptation strategies. IRISCC contributes to training a new generation of scientists to efficiently use RI services and for data stewardship. Data from IRISCC will be open and made available in compliance with FAIR principles and linked to European initiatives such as EOSC. Strong links will be created between IRISCC and current and future efforts under Horizon Europe.

Earth system models (ESM) show diverging estimates of ecosystem carbon (C) uptake which drives persistent uncertainty about future climate and limits the realization of policy mitigation goals. The CONCERTO project aims to strengthen the European research ecosystem by creating an innovative scientific collaborative framework that enhances our understanding, monitoring, and modelling of the terrestrial cycle (CC), and leads to reduced uncertainty and ESM convergence. This framework has three main elements: the exploitation of novel Earth Observation (EO) data, the innovation of process models fed by these data, and Data Assimilation (DA) and Machine Learning (ML) techniques. The consortium includes European experts and institutes active in these areas. CONCERTO will advance the representation of land cover, leaf area index (LAI) and management intensity through new maps of high resolution with layers relevant for the CC. The new management map will enhance the creation of a new biomass production map. Further, CONCERTO will prepare for the ingestion of FLEX data in land surface models (LSM) through DA, and exploit Sentinel-5P/TROPOMI HCHO indicative of biogenic volatile organic compound (VOC) emissions. As step towards moving away from prior (static) parameterizations, the novel P model will be used to ingest these new data sources. This will enhance understanding of ecosystems responses to climate extremes, fires, and vegetation recovery from them, and the parameterization of LSMs included in ESMs. Novel representations of the underrepresented processes of lateral carbon fluxes through outgassing of CO2 from rivers will be developed. Dedicated seasonal and climate experiments will demonstrate how improved representation of land surface processes benefit the accuracy and trustworthiness of global Earth System simulation. This will lead to better predictability of the influence of land management on the CC and underpin avenues towards carbon neutrality

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.

“Today, one third of the world’s people, mainly in least developed countries and small island developing states, are still not covered by early warning systems... This is unacceptable, particularly with climate impacts sure to get even worse. Early warnings and action save lives. To that end, today I announce the United Nations will spearhead new action to ensure every person on Earth is protected by early warning systems within five years.” - UN Secretary-General António Guterres on World Meteorological Day 2022/03/23 The ambition of the Strengthening Extreme Events Detection for Floods and Droughts (SEED-FD) project proposal is to give Europe, with the Copernicus Emergency Management Service, a leading position with this regard by breaking the current limitations of hydrological simulation accuracy and reliability and providing skillful floods and droughts forecasts available anywhere in the world, including in the global south for lower and middle-income countries, typically the most impacted by extreme hydrological events but also where the current knowledge gap in hydrological simulation and forecasting is highest. Combining state-of-the-art science with crucial advances in EO and non-EO technologies, the project's global objective is to enhance the quality and portfolio of the CEMS EWS for floods and droughts and improve the reliability of predictions all over the world. SEED-FD will target every critical part of the CEMS Hydrological Forecasting Modelling chain by applying state-of-the-art science to transform new observational information into high-quality hydrometeo extreme event forecast products. It will invest in better representing hydrological processes and parameterisation techniques of the CEMS core hydrological engine (LISFLOOD) and combine the model enhancements with innovative techniques to integrate EO and non-EO data with the near real-time hydrological processing chain for reducing hydrological forecasting errors.