Science & Engineering Challenges/Advances

S&E Challenges I-WRF Framework Goals S&E Advances
WRF container limited to single node computing New I-WRF container will enable multi-node WRF Container-based modeling that scales
Limited visualization capabilities New tools will be integrated with the Analysis/Visualization Container such as ParaView Seamless data analysis experience with enhanced visualization capabilities
Community confidence in research results Containerized METplus tools will be optimized for I-WRF framework Faster access to verifcation tools and refinement of workflows
Difficulty compiling and configuring WRF Standard multi-node capable containers will be built, tested, and ready to use Rapid application deployment
Target systems with specialized hardware and/or limited container capabilities Easy to modify features. Extendable design. Platform portability to desktop, cloud/edge, and HPC for research flexibility
Consistent execution environment Reusable and repeatable framework Reproducible scientific results
Automated container deployment, scaling, and management Scripted Kubernetes orchestration via Terraform solution will be created for WRF Reliable container orchestration
Difficulty developing new containers from scratch I-WRF use case scripts, build files, etc. will be shared with sample data and storage configurations Creating I-WRF container framework will spur community development of new containers and science apps
~50% students have difficulty configuring their machines to start WRF training exercises Turnkey container for easier education of students and early career scientists Increased student recruitment from all relevant domains; bigger pipeline to close the diversity gap
Lack of CI technical support skills, and/or time available I-WRF will reduce need for CI support; 24x7 virtual workshop training available. NCAR committed to sustaining I-WRF. Researchers can get started with multi-node WRF without CI staff support, lowering the bar for less resource rich institutions