ESiWACE focuses on the community's support to reach a higher readiness level regarding exascale supercomputing and knowledge transfer between the different Earth System modeling centers and teams across Europe. The project focuses on three main pillars:
the transfer and establishment of knowledge and technology for efficient and scalable simulations of weather and climate across the Earth system modeling community,
closing common technology knowledge gaps and providing toolboxes for high-resolution Earth system modeling via joint developments and
serve as a sustainable community hub for training, communication, and dissemination of high-performance computing for weather and climate modeling in Europe.
ESiWACE brings the various approaches to address these challenges from the different modeling groups together to transfer knowledge across the weather and climate domain, generate synergies between the local efforts, provide targeted support to modeling groups via customized high-performance computing services, and provide training to educate the next generation of researchers.
EC-Earth is coupled Earth System Model for climate simulations developed by a European consortium of national meteorological services and research institutes.
NEMO (Nucleus for European Modelling of the Ocean) is a state-of-the-art modeling framework. It is used for research activities and forecasting services in ocean and climate sciences. NEMO is developed by a European consortium with the objective of ensuring long-term reliability and sustainability.
ICON is coupled Earth System Model for climate simulations based on the ICON (ICOsahedral Non-hydrostatic) framework with its unstructured, icosahedral grid concept.
IFS is an atmospheric model for weather simulations, which includes a sophisticated data assimilation system and a global numerical model of the Earth system.
HPCW is a set of weather and climate benchmarks that isolates key elements in the workflow of weather and climate prediction systems to improve performance and allow a detailed performance comparison for different hardware.
Increase the efficiency of weather and climate simulations on state-of-the-art supercomputers.
Design tools to close technology gaps for high-performance computing.
Develop tools to tackle the data challenge of high-resolution weather and climate modeling.
Support the wider weather and climate modeling community using state-of-the-art supercomputers via targeted services, training, and capacity building.
Build a well-connected and inclusive community for high-resolution Earth System modeling across Earth system science and HPC.