Contributions by C. A. Edwards

1
Contributions byC. A. Edwards C.V. Lewis

• CIMT Meeting June 5-6, 2006

• Emphasize Integration of CIMT data
• 2 Parts
• Visualization
• Ecosystem component

2
Edwards Lewis (part 1)Graphical synthesis of
CIMT datafor web distribution

• HF Radar
• Wind stress
• SST
• Ship survey T/S/F profiles
• Ocean color
• Underway data

3
CIMT Cruise, May 2004
Temperature
SST
4
August 2003
5
Jan 2004
Temperature
Salinity
River flow
6
Edwards Lewis (part 2)Modeling Synthesis of
CIMT results

• CIMT data reveals iron limitation on coastal
  ecosystem
• Hypothesized to induce alongshore variability in
  production
• Present published ecosystem models of California
  Current System do not explicitly include iron
• We developed an ecosystem model based on this
  hypothesis
• Explicitly includes iron
• Tested model in simplified system to evaluate its
  potential for alongshore variability

7
MOTIVATION SeaWiFS ChlorophyllMonthly Average
(May) 1998-2004
8
1998
1999
2000
2001
2002
2003
2004
9
Conceptual Ecosystem Model

• Integrates observations by Bruland, Chavez, and
  Kudela
• Simple NPZ model with Iron
• Dissolved
• Cellular

Based on Franks et al. (1986), Edwards et al.
(2000), Edwards et al. (2002)
10
Hypothesize that distribution derives from iron
limitation
Bathymetry

• idealized 2D bathymetries
• Pt. Sur
• Davenport
• Pescadero
• Investigates COAMPS wind stress from three
  locations
• Examine net production
• Promising sensitivity to iron

11
IOOS Modeling and Analysis Objectives

• Improve, develop, test, and validate
  operational models
• Produce accurate estimates of current states of
  marine systems (e.g., estimates of the
  distributions of core variables)
• Develop data assimilating techniques to
  initialize and update models for more accurate
  forecasts of state changes and
• Optimize the observing subsystem (e.g.,
  observing system simulation experiments).
• Models include dynamical models based on first
  principles (e.g. storm surge models, numerical
  ecosystem models in both Lagrangian and Eulerian
  frames of reference), or coupled models of the
  biological and non-biological components of the
  marine ecosystem (e.g. coupled atmosphere-ocean-wa
  ve-sediment-biogeochemistry and ecosystem models).

12
IOOS Modeling and Analysis Objectives

• Improve, develop, test, and validate
  operational models
• Produce accurate estimates of current states of
  marine systems (e.g., estimates of the
  distributions of core variables)
• Develop data assimilating techniques to
  initialize and update models for more accurate
  forecasts of state changes and
• Optimize the observing subsystem (e.g.,
  observing system simulation experiments).
• Models include dynamical models based on first
  principles (e.g. storm surge models, numerical
  ecosystem models in both Lagrangian and Eulerian
  frames of reference), or coupled models of the
  biological and non-biological components of the
  marine ecosystem (e.g. coupled atmosphere-ocean-wa
  ve-sediment-biogeochemistry and ecosystem models).

13
Contributions byC. A. Edwards C.V. Lewis

• CIMT Meeting June 5-6, 2006

IOOS Goals

1. Improve predictions of climate change and weather
   and their effects on coastal communities and the
   nation
2. Improve the safety and efficiency of maritime
   operations
3. Mitigate the effects of natural hazards more
   effectively
4. Improve national and homeland security
5. Reduce public health risks
6. Protect and restore healthy coastal ecosystems
   more effectively
7. Enable the sustained use of ocean and coastal
   resources.