1. Applied Physics Laboratory
APL MURI Kickoff
1/3/2019
Applied Physics Laboratory

2. Applied Physics Laboratory
APL MURI TEAM
Bob Miyamoto
David Jones
Jim Pitton
Keith Kerr
Mark Krueger
1/3/2019
Applied Physics Laboratory

3. Key Strengths of the Team
Navy/domain experience
Related research projects
MHSII
EVIS
DRI
Visualization, Intelligent Agents, Engineering Statistics
1/3/2019
Applied Physics Laboratory

4. Applied Physics Laboratory
APL Role in MURI Team
Provide relevance to Navy needs
Coordinate interaction w/ Navy Orgs.
Develop task-based visualizations
Integrate component research efforts
Facilitate interaction among MURI participants
1/3/2019
Applied Physics Laboratory

5. Navy METOC & Uncertainty
“Model of the Day?”
Tropical Cyclone forecasts
EFS at FNMOC
Ship Routing
Long Range Temp Forecast
1/3/2019
Applied Physics Laboratory

6. Navy METOC & Uncertainty
Based on my experience as the Operations Officer at FNMOC
Forecasters have limited understanding
Confusing products
Not designed for forecaster
Great potential still not fully realized
1/3/2019
Applied Physics Laboratory

7. Examples of Navy Uncertainty Products
1/3/2019
Applied Physics Laboratory

8. FNMOC Ensemble Temp Mean
1/3/2019
Applied Physics Laboratory

9. Applied Physics Laboratory
FNMOC 2m Temp Plume
1/3/2019
Applied Physics Laboratory

10. FNMOC Gale Probability
1/3/2019
Applied Physics Laboratory

11. Applied Physics Laboratory
Areas to investigate
How forecasters deal with uncertainty
Uses of uncertainty information by METOC customers
Easier ways to create uncertainty products
Better visualization techniques
Verification
1/3/2019
Applied Physics Laboratory

12. Applied Physics Laboratory
FNMOC COAMPS
1/3/2019
Applied Physics Laboratory

13. Applied Physics Laboratory
UW Ensemble Mean
1/3/2019
Applied Physics Laboratory

14. Applied Physics Laboratory
Next Steps
Cognitive Task Analysis at
Whidbey Island
Norfolk
Collaborative work with NPMOC, NLMOC, NPMOF, & FNMOC
Visualization research >>>
1/3/2019
Applied Physics Laboratory

15. Exploratory Software Prototype
Requirements
Design
Prototype Development
Iterative Refinement
Implementation Analysis
1/3/2019
Applied Physics Laboratory

16. Tentative Requirements
User-based framework
Analytic & Geospatial visualization tools
Collaborative, interactive exploration
Cross-platform availability
Easy extensibility
Suitable for broad range of expertise
1/3/2019
Applied Physics Laboratory

17. Implementation Tools (1)
Java Language
Cross-platform
Sophisticated network (web) model
Can “wrap” models in other languages
Inference Engine
Easy to tailor level of expertise
Can both bound and sequence operations
1/3/2019
Applied Physics Laboratory

18. Implementation Tools (2)
VisAD for Visualization
Model-View-Controller architecture
Remote display and collaboration
Sophisticated data model
High-level scripting language (Jython)
Supports specialized “toolkit” development
Currently used within meteorological community
1/3/2019
Applied Physics Laboratory

19. VisAD Creations (courtesy VMET) Terrain and Wind Vectors
1/3/2019
Applied Physics Laboratory

20. VisAD Creations (Courtesy VMET) Time Series Wind Fields
1/3/2019
Applied Physics Laboratory

21. VisAD Creations (courtesy VMET) MM5 output – wind and temp fields
1/3/2019
Applied Physics Laboratory