The MidAtlantic Coastal Ocean Observing Regional Association includes:

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MACOORA gt MARCOOS Demonstration of Integrated
Modeling, Observation and Analysis for Applied
Coastal Ocean Prediction
http//www.macoora.orghttp//marcoos.us

• The Mid-Atlantic Coastal Ocean Observing Regional
  Association includes
• Chesapeake Bay
• Delaware Bay
• New York Bight Harbor
• Long Island Sound, and
• Massachusetts and Rhode
• Island Bays and Shelf

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Existing Mid-Atlantic Sub-regional Observing
Systems - 2003
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RU Endurance Line glider transect May 18-24, 2006
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Regional Theme 1 Maritime Safety Search And
Rescue
MARCOOS HF Radar Network
Before
Coast Guard SAROPS
USCG
Weatherflow
After
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Regional Theme 2 Ecological Decision Support -
Fisheries
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• Theme 1 Maritime Safety Coast Guard Search And
  Rescue
• Weather Surface Winds
• Integrate Weatherflow network into NWS WFO
  validation datastreams
• Transition WRF modeling capability to WFOs
• Validate real-time WRF capability for ocean
  forecasters
• HF Radar Surface Currents
• Upgrade full network to readily sustainable
  status
• Implement community designed QA/QC
• Evaluate with Coast Guard drifters
• Provide real time data to ocean forecasters
  EDS
• Statistical Surface Current Forecast
• Run real time forecasts for inclusion in EDS
• Evaluate with Coast Guard drifters
• Dynamical Surface Current Forecasts
• Run test forecasts for inclusion in EDS

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• Theme 2 Ecological Decision Support Fisheries
• Satellite Imagery
• Sustain activities to provide real-time imagery
  
• to fishing community via world wide web
• Provide real-time data to the ocean forecasters
• Underwater Gliders
• Operate the growing glider network as a
• regional asset
• Implement community recommended QA/QC
• Provide real time data to ocean forecasters
• Dynamical 3-D Forecasts
• 3-D assimilation based feedback to glider
  sampling
• Data Management
• Install tools to share satellite imagery and
  glider data with ocean forecasters

Courtesy Hank Lobe
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Northeast shelf ROMS nested in GODAE HYCOM North
Atlantic model (operational and OPeNDAP
accessible)
CODAR surface currents coastal
meteorology
glider T,S, optics along paths
Satellite SST, color, mesoscale and coastal
altimetry plus ship XBT, surface T/S, and ADCP,
NDBC buoys, and Argo CTD (all broadcast on GTS)

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UMass HOPS
Rutgers ROMS
Stevens Tech NYHOPS
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Individual satellite SST passes
LaTTE ROMS model domain and observations for
reanalysis and forecasting with 4DVAR assimilation
Scaling down Larger domain models with data
assimilation set the far field context for
smaller domain local and regional ocean weather
applications.
depth (m)
CODAR
Glider and ship (EcoShuttle) tracks
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Scaling up IOOSOOI physics and biogeochemical
observations, coupled modeling, to regional /
global carbon climate processes
Hofmann, E. E., et al. (2008), Eastern U.S.
Continental Shelf Carbon Budget Integrating
Models, Data Assimilation, and Analysis,
Oceanography, vol 21, no. 1, in press.
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MARCOOS Time line for developments in Modeling,
Analysis and Data Assimilation

• 0-12 months
• Work with MARCOOS partners on data streams for
  assimilation and data quality control
• CODAR QC and uncertainty estimates
• Satellites
• SST from Coastwatch PFEG, JHU jpeg format, RU
  COOL
• Seek site to match http//oceanwatch.pfeg.noaa.gov
  8081/thredds
• SST LAC extract from Rutgers Weogeo via OPeNDAP
• Gliders revise format used in SW06 format
  (KKYY-to-netcdf?)
• XBT-CTD AOML GTS feed for VOS XBT, Argo, NDBC
  time series
• WRF/MM5 (Mt.Holly/Colle) to OPeNDAP or via GRIB
• interoperability with existing model feeds
• Assimilation methodology development (all groups)

• 6-18 months
• Drifter evaluation 2006/2007
• SMLDB comparisons with respective prototype
  modeling systems
• drifter dispersion algorithm development
• skill metrics (including position uncertainty
  estimates and ensembles)
• Formulate quantitative skill metrics for all
  fields (u,v,T,S,z)
• Model intercomparison
• RMSE/Taylor/target/NOAA (emphasis on forecast
  skill metric)
• Model interoperability
• 12-24 months
• Gather to MARCOOS CF-conventions OPeNDAP server
• Ingest subsets to EDS
• MapServer interface
• 24 months
• Real-time ready
• Multi-model ensemble

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• MACOORA/MARCOOS Coastal Ocean Modeling and
  Prediction in 2008-2011
• Operational MAB modeling
• Comparison of Kalman Filer and 4D-Variational
  assimilation of all observing system data
• gliders, CODAR, cabled observatory, satellites,
  floats, ships
• Bio-optics, ecosystem, carbon cycle, sediment
  transport, and watershed coupling for
  applications/users
• Synchronous physics coupling to waves and
  atmosphere
• Nesting (2-way) to larger and smaller domains
  (upscaling and downscaling)
• Cyberinfrastructure for data transport, metadata
  descriptions, data and model output discovery
  (catalogs) and model interoperability
• Contribute to observing system design (through
  OSSEs) and operation (adaptive sampling)

Coastal Ocean Modeling and Prediction
grouphttp//www.myroms.org
jwilkin_at_rutgers.edu
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• Model-based reanalysis and prediction requires
  near and far field observations the network must
  combine basin scale (Argo, satellite) to
  shelf-wide (long glider missions, CODAR) to
  regional (Pioneer) to local/intense (LaTTE,
  SW06)
• Ready access to data and operational models
  facilitates local to regional scale operational
  ocean weather applications (in analogy to
  national scale weather analyses from NCEP
  underpinning regional forecasts at local NWS
  offices or research projects)
• Cyberinfrastructure needs include
• (1) getting ALL data to modelers (as super-users)
  to inject modeling into the analysis steps (as in
  numerical weather prediction)
• (2) while maintaining metadata and implementing
  quality control, and
• (3) ensuring model-based analysis gets out to
  users
• Integrated modeling/observations studies and new
  model development (e.g. carbon cyclebio-optics)
  enable us to tackle societal problems on large
  scales
• Models have the capability to quantitatively
  inform observing system design and real-time
  operation

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ROMS Operational Modeling workflow

• During t lt ti acquire over networkAll data
  for model forcingObserved river flow (e.g.
  USGS), Meteorology surface air temperature,
  pressure, humidity, vector wind, rain, shortwave,
  long-wave radiation (e.g NOMADS/NCEP), Ocean
  open boundary conditions (e.g. Hycom N. Atlantic,
  mercator-ocean.fr)All possible observations of
  ocean state for assimilation CODAR, satellite
  (SST, altimetry, color), moorings, gliders,
  AUVs, NDBC buoys, tide gauges, research/VOS
  underway obs

Requirements/tasks in forcing data
acquisitionInterpolation from data to model
gridsAccommodate data source failures - switch
to alternate service (redundancy) or product
(fall-back)Requirements/tasks in assimilation
data pre-processingQuality control
Filtering/interpolationMelding data streams
into model observations file