The arctic knowledge-based system: Science gateway integration for petascale arctic data processing and geospatial feature prediction

Science gateways have become essential platforms that integrate computational resources, data services, and workflows for domain researchers, enabling artificial intelligence-driven (AI) analyses at scale. Building on this paradigm, we introduce the Science Gateway component of the Arctic Knowledge-Based System (A-KBS), designed to advance AI-assisted modeling of permafrost dynamics and other Arctic geospatial processes. The A-KBS provides researchers with a unified portal to configure and execute multi-horizon prediction tools for active layer thickness, ground deformation, wildfire occurrence, freeze/thaw states, soil and air temperature analyses, and to run global scale geospatial HPC workflows leveraging data from across the circumpolar Arctic. This system orchestrates workloads through Kubernetes-based (K8s) containerized environments, Globus Data Transfer/Compute services, and distributed computing tools such as Slurm, ParSL, and Ray.io. Its web portal is deployed on the University of North Dakota’s (UND) virtualized, load-balanced K8s cluster with cloud migration enabled by Rancher, while Python-based AI functions authored in JupyterHub are executed on remote systems through Globus Compute Endpoints. Current development has integrated the A-KBS with the UND high-performance computing (HPC) Talon cluster and Amazon Web Services-managed K8s resources, with a roadmap in place to extend this integration to other HPC environments including the San Diego Supercomputer Center’s Expanse System. By coupling scalable infrastructure with a suite of existing AI-driven workflows for environmental prediction tasks, the A-KBS accelerates Arctic science, strengthens cryospheric research, and supports decision-making through its integration with cyberinfrastructure surrounding the DRP (Defense Resiliency Platform Against Extreme Cold Weather) initiative. • The Arctic Knowledge-Based System (A-KBS) Science Gateway is introduced for AI-assisted Arctic research. • Deployment on a Kubernetes-based architecture validated the platform’s stability, scalability, and interoperability. • Integration of Globus and JupyterHub streamlined remote computing and eliminated user-side infrastructure complexity. • Unified authentication, secure data management, and automated monitoring ensured reliable operation for Arctic workflows.