Appendix 3. Meeting Prospectus and Agenda

Modeling the Southern Ocean Ecosystem - Prospectus

Most numerical models of the upper ocean ecosystem are based on coupled partial differential equations with growth, loss, interaction, and diffusion terms. The basic model has been used in oceanography for many decades, although there have been many enhancements such as size classes, complex grazing and nutrient uptake terms, sophisticated mixed layer models, etc. As these models have grown in complexity, there are more adjustable parameters that must be estimated and more uncertainty about the exact forms of the parameterizations. Simple changes in parameters can have dramatic effects on model behavior. Several studies are investigating methods to reduce the number of parameters to those that capture most of the possible model behaviors.

As ocean models move towards a closer coupling with observations through assimilation, it becomes essential that we know far more about the various parameters and functional forms than simply their mean and variance. Assimilation models require that we characterize their temporal and spatial variability in order to fill in the gaps in time and space. This is a daunting task. For example, we know decorrelation scales of phytoplankton biomass in only a few locations in the world ocean; little is known about the decorrelation scales of phytoplankton growth rates.

The Southern Ocean will be the site of major field campaigns for both JGOFS and GLOBEC. There is still great uncertainty about the regulation of primary productivity in the Southern Ocean; iron limitation, grazing, and light limitation have been invoked. Near the ice edge, processes are even more complicated. Existing coupled biological/physical models must contend with a wide range of processes, many of which (such as iron limitation) have not yet been incorporated into existing models.

Given the expanse of the Southern Ocean and its isolation, field programs are by necessity both limited and costly. The upcoming JGOFS GLOBEC Southern Ocean projects represent a unique opportunity to collect data on Southern Ocean biogeochemistry and ecological processes. Campaigns by other countries, including the United Kingdom, Australia, France, Japan, and South Africa, will also provide important data sets along with long-term studies such as LTER. It is unlikely we will be able to assemble these resources again. Given the predicted sensitivity of the Southern Ocean to climate change (and the resulting feedbacks), we must improve our ability to make predictions about the functioning of the Southern Ocean with only limited data sets in the future.

The focus of the workshop will be an assessment of our present state of knowledge from both observations and models. We will assess where are our greatest uncertainties lie and where small improvements in observations and models will result in large increases in understanding. We will estimate the time and space scales over which we can make useful predictions about the Southern Ocean. As part of this assessment, we will explore the needs of the observational community in terms of models. We will also seek to outline the type of measurement program that will lead to significantly improved models.

As a strawman question, I suggest the following to organize our thinking:

"To predict seasonal anomalies in the f-ratio on regional scales in response to changes in atmospheric forcing."

Tuesday, January 17
Cascade Locks C

7:30-8:30  	Continental breakfast - fruit, pastries, juices, coffee, etc.

8:30-8:45  	Welcome and focus of the workshop - M. Abbott

8:45-9:15  	Status of JGOFS Southern Ocean project - R. Anderson

9:15-9:45 	LTER results and GLOBEC plans - E. Hofmann

9:45-10:30 	Physical processes in the Southern Ocean - J. Klinck

10:30-10:45 	Break

10:45-11:30	Biological processes in the Southern Ocean - W. Smith

11:30-12:15 	What can be done with data assimilation? - A. Bennett

12:15-1:30 	Lunch

1:30-2:15	Examples of assimilation of biological data - E. Hofmann

2:15-3:00  	Models of sea ice and ecological processes - K. Arrigo

3:00-3:15  	Break

3:15-4:00   	Coupled biological/physical models - P. Franks

4:00-4:45   	New approaches in biological models - J. Moisan

4:45-5:30   	Large-scale biological models - I. Totterdell

Wednesday, January 18
Cascade Locks B
Cascade Locks D (breakout room)

7:30-8:30   	Continental breakfast

8:30-9:00   	Plenary session to discuss working groups

9:00-12:00  	Working groups meet

	Group #1 Field measurements--T. Powell (chair)  D. Nelson (rapporteur)

What types of field measurements should be made during the upcoming JGOFS and GLOBEC
programs to improve the quality of our models?

	Group #2 Models--K. Denman (chair)  T. Cowles (rapporteur)

What types of models need to be developed in order to exploit field measurements during JGOFS and

12:00-1:30  	Lunch

1:30-3:00   	Working groups meet

3:15-4:00   	Group #1 reports to plenary

4:00-4:45   	Group #2 reports to plenary

5:30-6:00   	Reception

Thursday, January 19
Cascade Locks B
Cascade Locks D (breakout room)

7:30-8:30   	Continental breakfast

8:30-10:30  	Writing session for both groups

10:30-11:30 	Discussion of Group #1 report

11:30-12:30 	Discussion of Group #2 report


Mark Abbott		Oregon State University
Bob Anderson		LDEO
Rob Armstrong		Princeton
Kevin Arrigo		NASA/GSFC
Andrew Bennett		Oregon State University
Tim Cowles		Oregon State University
Ken Denman		IOS Canada
Scott Doney		NCAR
Glenn Flierl		MIT
Peter Franks		Scripps Institution of Oceanography
David Glover		WHOI
Danny Grunbaum		University of Washington
Eileen Hofmann		Old Dominion University
John Klinck		Old Dominion University
Ricardo Letelier	Oregon State University
John Moisan		Scripps Institution of Oceanography
Dave Nelson		Oregon State University
Angelica Peña		IOS Canada
Tom Powell		University of California, Berkeley
Jim Richman		Oregon State University
Walker Smith		University of Tennessee
Ted Strub		Oregon State University
Ian Totterdell		James Rennell Centre
John Walsh		University of South Florida
Leonard Walstad		University of Maryland

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