Ecosystems Modeling for the Chesapeake Bay

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Ecosystems Modeling for the Chesapeake Bay

• David Green (NOAA / NWS)
• Mary Erickson (NOAA / NOS)
• Christopher Brown (NOAA / NESDIS)
• Howard Townsend (NOAA / NMFS)
• Raleigh Hood (UMCES Horn Point Laboratory)

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Ecological Forecasting in Chesapeake Bay Current
Capabilities

• Generate daily nowcasts and 3-day forecasts of
  sea nettles, the harmful algal bloom Karlodinium
  veneficum, and Vibrio cholerae in Chesapeake Bay
• Predictions created by identify the locations
  where ambient conditions coincide with the
  preferred environment ( habitat) of the organism
• Disseminate prototype predictions on WWW

Predicted chance of encountering sea nettle, C.
quinquecirrha, on August 17, 2007
Predicted relative abundance of Karlodinium
veneficum on August 17, 2007
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Sea Nettle Forecasting Procedure

• Estimate current surface salinity and temperature
  fields
• Georeference salinity and SST fields
• Apply habitat model
• Generate image illustrating the probable
  distribution of sea nettles
• Disseminate to users on WWW

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Transitioning Nettle Forecasts to Operations at
NWS

• Vision
• Use NOS-supplied Chesapeake Bay Operational
  Forecast System model
• Disseminate products through NWS
• Follow Operations and Service Improvement Process
• Assembling Integrated Working Team
• Writing Statement of Need
• Meet with Research Innovation Team

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Future Plans Chesapeake Bay Forecast System

• Objective
• Develop a fully integrated, ecosystem model of
  the Chesapeake Bay and its watershed that
  assimilates in-situ and satellite-derived data by
  adapting and coupling existing models
• Consists of a coupled air / land / coastal ocean
  modeling system
• System Components
• Air Atmosphere - Weather Research and
  Forecasting (WRF) Model
• Land Land - Soil and Water Assessment Tool
  (SWAT)
• Coastal Ocean Regional Ocean Modeling System
  (ROMS)

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Variables of Interest

• Temperature
• Salinity
• Current velocities
• Chlorophyll concentration
• Nutrient concentrations
• Dissolved oxygen concentration
• Biomass estimates and taxonomic information of
  phyto- and zooplankton

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Biogeochemical and Ecological Forecasting

• We are coupling a simple biogeochemical/ecosystem
  model to ChesROMS
• This model will generate mechanistic
  biogeochemical/ecological forecasts

Biogeochemical/ecological model
ChesROMS physical model
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Biogeochemical and Ecological Forecasting

• Prognostic State Variables
• chlorophyll
• Nitrate
• Ammonium
• DON
• Oxygen
• Detritus
• Zooplankton
• Biogeochemical/ecological forecasts
• Additional forcing variables for empirical
  habitat models

ChesROMS modeled oxygen
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Migrating to the NOAA Chesapeake ROMS

• We propose to migrate our ecological forecasting
  models to CBOFS2
• Higher resolution allows better bathymetric
  representation
• This improves simulation of physical processes
  (particularly salinity)
• This provides more accurate forcing for our
  empirical and mechanistic models

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The Need for High Performance Computing

• Our model development efforts (spin up, test and
  validation runs) are currently constrained by our
  computational resources
• Spin up, test and validation runs using CBOFS2
  will require much higher performance computing
  capabilities
• Computational demand of running CBOFS2
  operationally with a coupled biogeochemical/ecolog
  ical forecasting model may also require HPC

Microway 12 node (24 processor) cluster at Horn
Point Laboratory currently used for ChesROMS spin
up, test and validation runs
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Ecological Modeling in Fisheries

• Traditional View
• Focus on Population dynamics
• Surveys and catch monitoring to understand fish
  biology and fishers
• Goal Population Status Assessment

• Ecosystem-based View
• Broad view on how multiple factors affect
  fisheries and interact
• Research on fishes, their food, and biotic and
  physical environment
• Forecasting could be important for Marine Spatial
  Planning

H. Townsend, NCBO
12
Moving Towards Forecasting in Fisheries

• Several Nascent Forecasting attempts
• Coho Salmon return for spawning in Columbia river
• NEMURO.FISH for global climate change simulation
  projects
• Marine Mammal Density Forecasts

H. Townsend, NCBO
13
What ecological forecasts for fisheries can we
create in the Chesapeake?

• Forecast disease microbe density in shellfish
  beds and aquaculture farms
• Climate change simulation projections for
  commercially and recreationally important fish
• Forecast recruitment of major fisheries species

H. Townsend, NCBO
14
What do we need for a fisheries ecological
forecasts in the Chesapeake?

• Operational backbone modeling suite to create
  forecasts of environmental variables
• Research and monitoring to provide data for
  developing and validating forecast models
  (statistical and process models to overlay on
  environmental variable forecast
• Forecast office that works with regional
  management agencies and structure (e.g.,
  Chesapeake Bay Program) to ensure utility of and
  support for forecast

H. Townsend, NCBO
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Extra Slides
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Statistical Mechanistic Approach
V1
Prediction
Using real-time and forecast data acquired and
derived from a variety of sources and techniques
to drive multi-variate empirical habitat models
that predict the probability of the target
species.
V2
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ROMS
Precipitation
Solar Radiation
Wind
Heat Flux
Sediment Transport
Atmospheric Deposition and Ventilation
Currents
Zooplankton
Temperature, Salinity, O2, Light
Phytoplankton
Nutrients (N,P)
Tidal Harmonics
Sediment Resuspension
Particle Sinking Remineralization

• Conditions at Bays Mouth
• Near-real time water level
• Climatological vertical profiles of temperature,
  salinity, and NO3, PO4, O2 concentrations

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Chesapeake Bay Forecast System

• Objective Develop a fully integrated, ecological
  model of the Chesapeake Bay and its watershed
  that assimilates in-situ and satellite-derived
  data by adapting and coupling existing models
• Purpose
• Near-Real Time Applications Nowcasting and
  forecasting of marine organisms, ocean health,
  and coastal conditions
• Climate Research Estimating effect of climate
  change on the health of coastal marine ecosystems
• Partners ESSIC, UM, UMCES, NOAA, and others

SeaWiFS true-color image of Mid-Atlantic
Region from April 12, 1998. Image provided by
the SeaWiFS Project, NASA/Goddard Space Flight
Center and ORBIMAGE