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Dynamic Adaptation in Mesoscale Weather Forecasting Systems: LEAD Project Insights

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25 diapositives · 287 Views · Jan 02, 2020

Explore the LEAD Project's self-managing systems for adaptive weather forecasting, showcasing Ensemble Forecasting, Adaptive Cyberinfrastructure, and Evolutionary Workflow Solutions. Learn from the challenges faced and lessons learned for building similar infrastructures.

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  1. LEAD Project Discussion Presented by: Emma Buneci for CPS 296.2: Self-Managing Systems Source for many slides: Kelvin Droegemeier, Year 2 site visit presentation.

  2. Mesoscale Weather

  3. What Weather & IT Today Do …

  4. Radars Do Not Adaptively Scan

  5. The Case for Dynamic Adaptation • Adaptation in Time • Adaptation in Space • Ensemble Forecasting • Adaptive Observing Systems • Adaptive Cyber-infrastructure • Managing Forecast and Simulation Process

  6. Adaptation in Time

  7. Adaptation in Space

  8. Ensemble Forecasting

  9. Adaptive Observing Systems

  10. Adaptive Cyberinfrastructure

  11. Managing the Forecast & Simulation Process • Current State: 50,000 lines of Perl code. • In Progress: LEAD Workflow Environment

  12. LEAD Service Oriented Architecture Desktop Applications • IDV • WRF Configuration GUI User Interface LEAD Portal Crosscutting Services Why A Service-Oriented Architecture? • Flexible and malleable • Platform independence (emphasis on protocols, not platforms) • Loose integration via modularity • Evolvable and re-usable (e.g. Java) • Interoperable by use of standards robustness Control Education Browse Workflow Visualization Portlets MyLEAD Monitor Control Query Ontology Client Interface Workflow Monitor Application Resource Broker (Scheduler) Stream Service Control Service Authorization Workflow Services Workflow Engine/Factories Ontology Service Query Service Application & Configuration Services Configuration and Execution Services Data Services Execution Description Host Environment Authentication Decoder/Resolver Service Transcoder Service/ ESML VO Catalog Application Description Application Host Catalog Services WRF, ADaM, IDV, ADAS THREDDS GPIR Geo-Reference GUI Monitoring Resource Access Services OPenDAP Scheduler Grid FTP Generic Ingest Service OGSA-DAI RLS LDM SSH GRAM Notification Observations • Streams • Static • Archived Data Bases Distributed Resources Steerable Instruments Specialized Applications Computation Storage Source: LEAD Team

  13. Some Discussion Points • Complexity of the infrastructure to support LEAD • Lesson learned: viable solution where small number of services are persistent; remaining are on-demand • Challenges for the system administrators • Large scale networks, supercomputers; different for sys. Admins in industry setting? • What lessons from this experiment will apply to building similar infrastructures in other domains • Future impact of LEAD