In its second phase, ESiWACE advanced European weather and climate models towards exascale computing, preparing them to exploit the performance and data capabilities of pre-exascale supercomputers.

ESiWACE2 focused on:

1. Improving the performance and scalability of weather and climate models on next-generation supercomputers.

2. Exploring innovative technologies, including machine learning and heterogeneous computing architectures.

3. Improving data processing and management for large-scale simulations.

4. Strengthening HPC services, training and collaboration across the European weather and climate modelling community.

In its first funding phase, ESiWACE aimed to improve the efficiency and productivity of weather and climate simulations on high-performance computing (HPC) systems, enabling increasingly realistic, high-resolution simulations.

ESiWACE1 focused on:

1. Improving the scalability of models, tools and data management on state-of-the-art supercomputers.

2. Enhancing the usability and deployment of weather and climate models across the European HPC ecosystem.

3. Developing solutions to manage and exploit the vast amounts of data generated by high-resolution simulations.

4. A key objective was to demonstrate global, kilometre-scale weather and climate simulations, helping identify and overcome performance bottlenecks in community-driven models.