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NOS Coastal Ocean Operational Forecast Systems

Presented By: Patrick Burke (NOS/CO-OPS)Contributors: Aijun Zhang (CO-OPS), Peter Stone (CO-OPS),

Edward Myers (CSDL), Frank Aikman (CSDL)

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Operational System Attribute(s)

System Name Acronym Areal Coverage Horz Res

Cycle Freq

Fcst Length

(hr)

Estuarine/Bay models

ROMS: CBOFS, DBOFS, TBOFS FVCOM: SFBOFS SELFE: CREOFS

U.S. major ports and coastal waters

50m-5km

Every 6 hours

48 hrs (2 days)

Coastal/Shelf models NGOFS (FVCOM) Gulf of Mexico

100m-10km

Every 6 hours

48 hrs (2 days)

Great Lakes GLOFS (POM) 5 Great Lakes 5km-10km*

Every 6 hours

60 hrs (2.5 days)

System Data Assimilation or Initialization TechniqueAll existing NOS OFS do not use data assimilation techniques. However, the future West Coast OFS (under development) uses 4DVAR data assimilation method. Current cycle run is initialized from the restart file generated from previous cycle nowcast run for all NOS OFS (no adjustments)

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Why System(s) are Operational

Primary stakeholders and requirement drivers• Safe and efficient marine transportation (ports managers, pilots)• Emergency response for emergency managers, U.S. Coast Guard; NOS/ORR;

NWS/WFO, state and local coastal managers• Ecosystem forecasting (NOAA Eco-forecasting Roadmap)

What products are the models contributing to?• Provide high-resolution forecast guidance of total water levels, currents,

water temperature and salinity • Integration of hydrodynamic and atmospheric forecasts (Tampa WFO pilot

project)• Guidance to develop ecosystem forecasts (HAB, hypoxia, pathogens)

What product aspects are you trying to improve with your development plans? • Complete national coverage (CONUS)• Salinity and temperature (density) forecasts• Ice and biogeochemical forecasting• Mean water level bias in upper estuary (e.g. Columbia River)• Coastal contributions to Total Water Prediction efforts (linking rivers to the

coasts; coupling wave models with OFS)

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Why System(s) are Operational

Top 3 System Performance Strengths• Operate under a shared common framework (COMF) to facilitate O&M and

updates• Leverage modeling advances by using standard community ocean models• Modeling infrastructure (national backbone capability) for other types of

forecasts

Top 3 System Performance Challenges • Availability of real-time observations in data tank to support data assimilation• Availability of standard river forecast products for riverine boundary conditions• Frequent WCOSS Outage for maintenance and system upgrades

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System Evolution Over the Next 5 Years

Major forcing factors• Complete geographic coverage to head of tide meet requests from navigation

stakeholders (Precision Navigation), emergency responders and coastal managers

• Emerging requirements from Eco-forecasting Roadmap and Total Water Prediction initiatives

Science and development priorities• Improve density forecasts and stratification in coastal waters• Adequately resolve physical phenomena for both deeper shelf areas and

shallow estuaries within same model domain (e.g. eddies inside bays)• Improve forcing conditions of freshwater (river forecasts), precipitation and

surface heat flux inputs (bulk flux algorithm for high wind events)

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System Evolution Over the Next 5 Years

What are you top challenges to evolving the system(s) to meet stakeholder requirements?• Provide accurate water temperature and salinity forecasts to meet requirements

from ecological forecasting communities• Lack of real-time observations within shallow coastal waters for data

assimilation and model skill assessment

Potential opportunities for simplification going forward• Coupling hydrodynamic model with atmospheric, wave, watershed and

ecological models• Regional approach - a single domain to cover both shelf and estuary (5-year

plan)

COVERAGE OF NOS OFSNOS 5-year plan (regional approach)

>FY21

>FY21FY19

FY18

FY16FY21

FY20

FY20

FY21

FY19

FY21FY19

>FY21

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Top 3 Things You Need From the UMAC

1. Knowledge transfer in using a comprehensive single model grid (lessons learned, best practices)

2. Recommended approaches to improve temperature and salinity forecasts

3. Perspective in using either ensemble or probabilistic approach to improve coastal ocean forecasts within a competitive system resource environment