Cloud computing and high-performance computing (HPC) have become essential infrastructures for processing large-scale Earth Observation (EO) and Earth System modeling data. The convergence of these paradigms—combined with containerization, AI/ML frameworks, and cloud-native storage—is reshaping how we manage, analyze, and share geoscientific information.
Pangeo (pangeo.io) is a global open community developing scalable, interoperable workflows using tools such as Xarray, Dask, Zarr, and Jupyter. Discrete Global Grid Systems (DGGS) offer a complementary paradigm: equal-area, multi-resolution indexing that enables seamless integration across domains and scales. Together, these approaches support FAIR (Findable, Accessible, Interoperable, Reusable) data management and reproducible, transdisciplinary research.
We invite contributions that explore Cloud and HPC workflows for Earth science, including but not limited to:
• Big data platforms, cloud federations, and interoperable infrastructures (IaaS, PaaS, SaaS)
• Cloud-HPC convergence for EO and modeling workloads
• DGGS-based data organization, indexing, and multi-resolution analysis
• Cloud-native AI/ML applications for geoscientific data
• Reproducible workflows and executable notebooks using Pangeo tools
• Cloud storage solutions, data lakes, and FAIR data management
• Sustainable and green computing practices
We welcome case studies, technical developments, and community-driven initiatives that advance open, scalable, and interoperable Earth data science.
HPC and Cloud workflows for Earth Observation and Modeling data and Pangeo and DGGS, Enabling FAIR, Open, and Reusable Workflows for Transdisciplinary Earth Science
Convener:
Vasileios Baousis
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Co-conveners:
Tina Odaka,
Anne Fouilloux,
Marica Antonacci,
Max Jones,
Stathes Hadjiefthymiades,
Mohanad Albughdadi