Developing a Harmful Algal Bloom Prediction System for Chesapeake Bay

1
Developing a Harmful Algal Bloom Prediction
System for Chesapeake Bay

• Presented by
• Christopher Brown

2
Requirement, Science, and Benefit

• Requirement/Objective
• Ecosystem Mission Goal
• Forecasting Ecosystem Events
• Science
• Can blooms of three species of harmful algae in
  the Chesapeake Bay be predicted?
• Benefit
• Enhance first responder capabilities, improve
  efficiency of monitoring efforts, and aid in
  mitigating deleterious effects of HABs

3
Challenges and Path Forward

• Science Challenges
• Develop a regional Earth System Model that
  couples air, land, and coastal ocean models that
  incorporates satellite imagery
• Next Steps
• Implement integrated ocean observing system
• Incorporate socio-economic models into prediction
  system
• Transition Path
• Disseminate to appropriate state agencies, e.g.
  Maryland Department of Natural Resources
• Requires collaboration between NOAA LOs

4
Project Goal

• Develop an automated harmful algal bloom
  prediction system for Chesapeake Bay and its
  major tributaries that will be used by the state
  and federal agencies to improve their HAB
  response and monitoring capabilities.

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
5
General Approach

• Use 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 blooms caused by
  the target HAB species

6
Predicting the Relative Abundanceof Karlodinium
veneficum
Relative Abundance of K. veneficum

1. Generate daily nowcasts and 3-day forecasts using
   SST, salinity, and month
2. Estimate surface salinity and temperature fields
3. Apply statistical habitat model
4. Generate predictions illustrating the relative
   abundance of K. veneficum
5. Display and stage predictions on WWW

7
Recent Developments

• Recent Accomplishments
• Generate hindcasts of K. veneficum relative
  abundance
• Implement biogeochemical model to predict
  relevant water quality variables
• Add habitat model and infrastructure to generate
  forecasts of the probability of water-borne
  pathogens in the Chesapeake Bay

Animation of predicted daily Karlodinium
veneficum relative abundance from January
1-December 31, 2005.
8
Next Steps

• Continue validation and skill assessment
• Incorporate satellite imagery into prediction
  process
• Include habitat models of remaining two HAB
  species
• Transition prototype HAB prediction system to
  operations

Relative Abundance of K. veneficum
Low
Medium
High