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Cloudy with a chance of fish
Tiffany C. Vance
NMFS/Alaska Fisheries Science Center Stephen Sontag and Kyle Wilcox RPS/Applied Science Associates
We’re not in California anymore
Participants and Research Subjects
• Fisheries biologists, biological and physical oceanographers studying fisheries recruitment in the Gulf of Alaska, Bering Sea and Arctic Ocean
• Walleye pollock and Pacific salmon • Early life history in relation to recruitment • Field and laboratory research, modeling • GIS and IT in the cloud/server
Sample and Data Types
• Oceanographic data – CTD, water chemistry, nutrients
• Biological data – zooplankton and ichthyo- plankton samples, age-0 and age-1 fish, diet studies
• Modeling – currents, temperature, salinity, particle-tracking
• Ancillary data – station location, weather conditions, sample information
Walleye Pollock and Pacific Salmon
EcoDAAT and LarvaMap
• EcoDAAT – ArcServer/Oracle based data discovery and display
• LarvaMap – Amazon cloud based modeling of larval dissemination
EcoDAAT Goals and Process
• Design single Oracle database • Load data from existing Access databases • Prototype front-end created in ArcServer • Flex viewer, user authentication • Link to ArcGIS for further analyses • Tiered data access • Test deployment on an Amazon cloud hosted
instance of ArcServer
EcoDAAT Architecture
Main Interface
• LDAP authentication • ArcServer security as an option
Forms-based Data Selection
Map-based Data Selection
Results
Querying and Exporting Data
Spatial Analyses
LarvaMap: Particle Tracking 101 • Atmospheric and oceanographic applications § Volcanic plumes § Hazmat releases § Sediment § Larval fish
• Circulation model output • Particle tracking model • Visualization of results
• Circulation model output, e.g. ROMS • 4D - velocities at each grid point • May also have water properties such as temperature • DAP server – THREDDS, Hyrax
Particle Tracking Model • Behaviors of particles
• Particle transport model – frequently parallelized
• Run locally or remotely
• Data management
Complete System • Behavior library to create, catalog, and share larva
behaviors: http://bit.ly/WFiZjK
• Fate and transport model written as a python library: http://bit.ly/WFjz17
• LarvaService implementing the transport library in a cloud architecture
• Web client interacting with LarvaService through REST API: http://bit.ly/14aZinD
LarvaMap Web Client
LarvaMap Web Service
Run Queue
Transport Model Transport Model
Transport Model Transport Model
Transport Model Transport Model Remote Datasets
(THREDDS)
Workflow
1.) User configures run
2.) Run request sent to service and validated
3. ) Run request is put onto queue
4. ) Configured Amazon instance picks up run from queue
5. ) Raw data are returned to service
6. ) Service generates output formats and visualizations
7. ) User downloads results
Remote dataset Local “cached” copy
Data Extent Data Extent
• Data requested “as needed” from remote DAP endpoint • Particles use local cached copy in forcing algorithms
Remote Data Request
Remote dataset Local “cached” copy
Data Extent
Particle reaches extent of cache and requests new data be collected
“DataController” gathers remote data and adds to local cache
Remote Data Request
Remote dataset Local “cached” copy
Data Extent
Particles continue to run and the process is repeated
Remote Data Request
Remote dataset Local “cached” copy
Data Extent Data Extent
Particle reaches extent of cache and requests new data be collected
“DataController” gathers remote data and adds to local cache
Remote Data Request
Remote dataset Local “cached” copy
Data Extent Data Extent
Particles continue to run and the process is repeated
Remote Data Request
Remote dataset Local “cached” copy
Data Extent
Eventually…
Remote Data Request
Net CDF and Shapefile Particle Output
• Direct import into ArcGIS • Foundation for 2D mapping visualizations • netCDF complies with CF1.6 Discrete Sampling Geometries • Use of compliance checker for CF • Compliant units and standard names where applicable • Foundation for movie/animation visualizations
Case Study – Pollock Larval Transport
• Field data suggest transport both into Shelikof Strait and along the shelf • Testing release (spawning) off Kenai Peninsula • 10 – 100 particles • Released May 15th
• Model run for 100 days • Took 1:32 to run
Results
Stress Testing LarvaMap as a teaching tool – WHOI class using it this fall – excellent stress testing
Future Possibilities
• Linking LarvaMap and EcoDAAT – start a model run and automatically gather any associated in situ data for display with model results
• Store model runs in EcoDAAT • Very large scale model outputs (100,000
particles, 1 year, 300GB) and how to display and visualize in ArcGIS
