A workflow for the Climate Digital Twin

Abstract

The escalating intricacy of climate models and the demand for high-resolution temporal and spatial data need the development of advanced workflows to effectively manage the complexities associated with a Climate Digital Twin. The designed workflow, tailored to meet these challenges, is model-agnostic, allowing for simulations across various models, such as IFS-NEMO, IFS-FESOM, and ICON. Notably, its adaptability extends to diverse High-Performance Computing environments, facilitated by the containerization of data consumers. A user-friendly configuration structure is implemented, providing scientists with a simplified interface that conceals the inherent complexity of the model during simulations. Additionally, the workflow includes immediate and continuous data processing, promoting scalability in temporal and spatial resolution. This approach ensures the efficient handling of intricate climate models, meeting the demands for high-resolution temporal and spatial data, while enhancing user accessibility and adaptability across different computational environments. Furthermore, the workflow, which uses Autosubmit as the workflow manager, ensures the traceability and reproducibility of the experiments, allowing for the tracking of processes and ensuring the ability to reproduce results accurately. Finally, the workflow allows for the aggregation of tasks into larger jobs, reducing queue times on shared machines and optimizing resource usage.