SOST Interagency Ocean Observation Committee
IOOC/IOOS Modeling Strategy Task Team Meeting
Attendees:
Consortium for Ocean Leadership | Washington, DC
June 18, 2014
Meeting Minutes
Sponsor:
Eric Lindstrom (IOOC Co-Chair, NASA)
Avichal Mehra (CMOP, NCEP)
Ed Meyers (CSDL)
Josie Quintrell (IOOS Association)
Dave Schwab (GLOS and University of
Michigan)
Rich Signell (USGS)
Howard Townsend (new member) (NOAA
Fisheries, Ecosystem Modeler)
Strategic Plan Task Team Members:
Leslie Rosenfeld, Co-chair (CeNCOOS)
John Wilkin, Co-chair (MARACOOS and
Rutgers University)
Art Allen (USCG)
Becky Baltes (U.S. IOOS Program Office)
Antonio Baptista (Center for Coastal Margin
Observation and Prediction)
Jesse Feyen (Coast Survey Development Lab)
Ruoying He (SECOORA and North Carolina
State University)
Pat Hogan (Navy Research Lab and GCOOS)
Alex Kurapov (NANOOS)
John Lehrter (EPA)
Invited guests:
Rick Luettich (SURA PI)
Allison Allen (NOAA Ecological Forecasting
Roadmap Portfolio Manager)
COL staff:
Hannah Dean
Courtney Edwards
Two team members, Jane Smith (USACE) and Hendrik Tolman (NOAA/National Centers for
Environmental Prediction (NCEP)) were unable to attend. Two other invitees, Liz Smith and Eoin
Howlett, were also unable to attend.
I. Chair and Co-Chair Introductions to the Meeting Purpose (L. Rosenfeld and J. Wilkin)
L. Rosenfeld introduced the meeting by laying out the goals for the meeting. Her vision for this
IOOS Modeling Strategy is that it will encourage mutual respect and understanding for the
contributions that each of the parties brings to the table, and lead to more efficient ways for them to
work together.
 Come to a common vision of a better way to do things
 Identify bottlenecks in the system
 End up with a timeline showing when input to decisions and evaluations can happen.
The IOOS modeling strategy should establish the process by which:
 ocean modeling needs will be prioritized nationally
 requirements (spatial and temporal resolution, length of forecast / hind-cast, uncertainty
measures etc.) for ocean models will be determined
 the observations (type, resolution, frequency, accuracy) for assimilation into different types
of ocean models will be determined
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various ocean models, whether on a national or regional scale, will be evaluated for
transition to operations by a federal agency
various regional ocean models will be evaluated to receive federal support for operations by
a non-federal government organization
various ocean models will be considered for federal support for further development in a
path to transition to operational status
ocean models run by different organizations can interface to provide forcing and boundary
conditions
ensemble forecasts can be produced from ocean models run by a variety of organizations
it will be determined how ocean model output should be archived and distributed
communication and funding pathways to share development and distribution of
information products based on ocean model output will be established
J. Wilkin followed up with an overview of his goals for the outcome of the meeting.
The makeup of the team was designed to have a geographic balance and a federal and regional
balance to gather a variety of perspectives on modeling. The team will aim to establish a
framework that will facilitate more interactions between Regional Association (RA) data streams
and the models developed by federal partners. The strategy should lead toward achieving
integrated modeling capabilities and products that utilize the full spectrum of data available from
observing systems.
“Communities of practice” that address common challenges in aspects of modeling might be focused
on identifying robust methods by establishing coordinated research partnerships targeting specific
problems. These smaller groups might also address particular problems by following the Task
Team structure within GODAE to encourage communication exchange of experience. The modeling
strategy should acknowledge the importance of coupling of models across ocean, ice, atmosphere
and land processes, possibly providing the framework for synthesis of presently disjoint observing
activities. J. Wilkin noted that he would like the team to keep in mind the possibility of promoting
international linkages.
II. Sponsor Introduction (J. Wilkin and E. Lindstrom)
E. Lindstrom followed the general introduction with a summary of his vision for the outcomes of
the Team’s activities. E. Lindstrom noted that the team should not try to encompass all of ocean
modeling – the team should focus on framing and communicating the way that modeling fits in with
the ocean observing committee from the national and regional level, and how that fits into federal
activities that are ongoing. The team has been tasked with taking the large system approach so that
we can get the best products out of ocean modeling and tie regional modeling needs to federal
activities so that federal agencies can make targeted investments with tangible results.
In short, the team will establish a framework for facilitating interaction between RA data streams
and modeling groups, to achieve an integrated approach that includes best practices to developing
model-based products. In addition, the team will establish communities of practice on model
development, which may or may not follow the model developed by GODAE for setting up task
teams that address priority areas. The team should also aim to address the coupling of models –
including waves, atmosphere, ocean, littoral zones (beaches, wetlands, groundwater), and overall
ecosystem modeling. By rallying around specific problems, the team can develop a framework that
can encourage and guide targeting investments by agencies like NSF and NASA as well as NOAA
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operational centers that will produce tangible and communicable results back to agencies and to
legislators. Finally, Eric emphasized that the team should keep in mind international linkages to
organizations such as EuroGOOS and IMOS, which may further facilitate model based integration
and unifying themes that can serve to network ongoing activities.
III. Introduction of Guests and Staff
Following general introductions, team members and guests introduced themselves with a short
explanation of their expectations for the outcome of the meeting.
A. Kurapov wants the team to articulate a vision that explains how the team’s work will fit in with
existing vision documents, including the NOAA’s roadmaps for Storm Surge and Ecological
Forecasting Services.
J. Quintrell emphasized the need to strengthen communication and partnerships, identify gaps, and
develop new RFPs for IOOS RAs and for RA Directors, who must act as business managers for the
regions. J. Quintrell also emphasized that she would like the team products to result in a better
understanding of what IOOS contributes to modeling and determine the niche and strategic
advantage to having IOOS contribute to modeling. She would also like to see a roadmap for
strengthening partnerships between federal agencies and regional partners and would like the
team to effectively develop a stronger Research and Development defined role for the RAs so that
there is a process and method for RAs to develop and communicate needs to the agencies and
partners with the capacity to create responsive modeling products. She would also like to see the
team frame observations and modeling as one system, which is an outlook that was developed
effectively during the IOOS Summit. J. Quintrell also noted that she spoke to each of the RA
Directors about the Team goals, and there was a general consensus that the RA Directors would like
to better understand the value of their investment in modeling and whether, in the context of the
overall system, their money would be better spent on actual observations. RA Directors must
strategically spend a limited cash flow, and if the Team could effectively determine and
communicate the role of the RAs in the observation/modeling system, this would be incredibly
valuable for RAs.
D. Schwab would like the team to take an issue-driven approach to developing a modeling
framework. Having been through the development of five and ten year partnership outlays with
NOAA, D. Schwab noted that issue-driven modeling and observations systems are more cost
effective and tell more effective stories about investment of money and creation of partnerships.
J. Lehrter noted that the EPA tends to produce one-off models for individual projects, which is not
as efficient a process as it could be. He added there is relatively little modeling development activity
and capability within EPA. He would like to see the team develop a community of practice around
the development of models, a common set of open boundary information, the inclusion of land side
influences in ocean modeling; and standards to judge models by. Given that agencies have varying
levels of capacity to develop models, but that each agency is fulfilling missions that could be
improved through modeling, it is essential that this effort help contribute to a community of
practice and communication that will help leverage capacity, perspectives, and needs across
agencies, regions, stakeholders, and geographies.
A. Baptista noted that a framework can transform a system. However, in order to be effective, it
needs the input of technical expertise and bold steps that can garner the attention of those with
funding to apply to identified needs. A. Baptista would like to avoid the development of another
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incremental document that does not achieve tangible results. He recommends bold action and a
transformative framework – maybe a "modeling center without walls".
E. Myers noted that he would like to see the team develop tangible mechanisms for engaging the
RAs early on in the planning stages for model development and then throughout the OFS (ocean
forecasting system) projects. The team should focus on developing a clear framework to better
communicate the requirements needed to conceive, develop, and apply models to specific issues.
Identifying common, cross cutting problems could be one way to bring together federal, regional,
and sub-regional partners together on a meaningful product and this should be part of the
framework and process developed by the team.
R. Signell noted that IOOS already has standards for the models that they vet, and that he hopes that
the outcome of the team efforts will be to develop a common set of tools with a common set of
models so that we can work on a set of identified and cross cutting problems. Based on his
experience, he has found that when you bring people together on a clear problem with a tangible
and beneficial outcome to solving that problem, really great things can happen. The job of the
Modeling Task Team will be to create an environment, setting, and toolbox that will provide the
platform for those collaborations. Part of this will be developing a vision that can leverage
sustained funding and technical development at the federal and regional scales.
B. Baltes emphasized that the Coastal and Ocean Modeling Testbed has been a good start, but that
she hopes that this team will work to meet the National Ocean Policy implementation goals and
develop a better tie between federal and regional partners.
A. Mehra would like to see the team develop a framework that provides maximum leverage with
partners within the federal agencies and also industries. Atmospheric modeling centers are
currently issue based, and there is feedback as to what is working and what is not working for
particular problems. NCEP can then prioritize which issues need to be addressed first. The team
would ideally develop a similar prioritization process for issues in the ocean and coastal modeling
context that would parallel the weather prioritization process. There are gains to be had both from
internal and external partnerships, and the framework that the team develops needs to lay out a
clear roadmap for operations to research and research to operations information and needs flows.
R. He works on circulation and interdisciplinary modeling, including HAB models. He would like to
see the team improve interactions between federal agencies and RAs, as well as between academia
and operational centers. In addition, he would like to see a way to more systematically tie in
international collaboration and ensemble modeling that leverages across scales of current modeling
activities. He also emphasized linkages between modeling and observations.
H. Townsend works in fisheries modeling in the Chesapeake Bay NMFS Office. He has knowledge of
national ecosystem modeling workshop community of practices and with connecting ocean models
to mandates within fisheries policy, endangered species policy, habitat conservation, and
ecosystem charges. He noted that as fisheries has moved from managing a single species to
managing an ecosystem, developing responsive models has been a major challenge, and he is
especially interested in the team developing a framework for ecosystem modeling.
Art Allen from the Coast Guard noted that at the current time, no model covers the entire area that
his agency needs in terms of search and rescue issues. This means that the agency employs 36
ocean models and 25 meteorological models. While these models are good, they could be better.
He noted that better surface current modeling is a real and current need. He would like to see the
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team develop a framework that yields tangible outcomes and assesses the quality of a model for use
in events, such as Search and Rescue (SAR).
P. Hogan is responsible for developing HYCOM-based global ocean systems and also has experience
working on regional issues. He would like to see a breakdown of barriers between the modeling
efforts of Department of Defense (DOD) and those of other federal agencies. He would also like to
see multi-model and single-model ensembles, with attention paid to error predictions. He would
also like to see the team develop a better framework for providing resources to RAs. He would
specifically like to see the barriers broken between the Navy and the regions. NRL outputs are
unclassified, and he would like to see NRL expertise extended to the community. He also referred
to the coupled modeling efforts being undertaken by the Earth System Prediction Capability (ESPC)
R. Luettich suggested that building on the coastal and ocean modeling testbed (COMT) system
currently in place is one way to proceed, but added that there is no imperative to stick with this
framework unnecessarily.
Alison Allen from NOAA would like to see the team develop programmatic requirements and best
practices for ecosystem modeling, keeping in mind and referencing existing resources, such as
NOAA’s ecological forecasting roadmap.
IV. Relevant highlights of the six must-read documents are presented
Following introductions and individual vision statements, the team turned to presenting and
discussing the six must-read documents that the team identified as at the core of the materials and
background from which the team is working.
1. The Integrated Ocean Observing System (IOOS) Modeling and Analysis Workshop Report
(MAST Report) (2008) (J. Wilkin)
J. Wilkin gave a brief overview of the 2008 MAST Report. IOOS is comprised of three components:
observing systems, modeling subsystems, and data management and communications. The Federal
Government National Backbone covers scales from global to coastal ocean and includes the Great
Lakes. The Regional Coastal Ocean Observing Systems (RCOOS) comprise the same triad of
subsystems regionally, but these are not tightly coordinated or integrated. RCOOS focus on the U.S.
coastal ocean and EEZ and commonly use products from Navy and NOAA centers and from global
peer systems for downscaling to coastal domains. In turn, the RCOOS provide observations, model
products, and skill assessments at high resolution for feedback to the modeling subsystem of the
National Backbone. The report addressed strategies to implement the prediction and analysis
component of IOOS.
The report also described a five year plan, which included establishing a Joint Working Group that
would convene a periodic and regular forum to foster prediction system development,
implementation, and assessment; and to enhance exchanges across national agencies and across the
science community. Short term requirements emphasized communication, coordination, and
collaboration; improved cyber-infrastructure, including a standards-based national data portal and
archive, including leveraging CI resources of NOAA, Navy, and NASA; a more logical and tractable
division of effort between the National Backbone and the RCOOS; and long-term, stable and
adequate funding for both the national and regional scale prediction and analysis activities.
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In terms of a 5-25 year conceptual plan, the report laid out a need for clear, quantified
requirements statements from different categories of users; an overall Systems Engineering design
and management scheme; and a Concept of Operations linking the prediction and analysis of the
national and regional scales, with more clearly defined roles and responsibilities and mutually
beneficial partnerships.
The report developed the following set of Findings and Recommendations:
1. Integrated Ocean Prediction and Analysis (OPA) activity that requires an OPA Joint Working
Group (OPA-JWG)
2. Establish a forum to maintain periodic group communication (to be responsibility of the
OPA-JWG)
3. Aggregate a set of standard attributes (space-time resolution, accuracy, forecast horizons,
and timeliness) for ocean prediction core variables that can be traced back to user
requirements (this task has parallels to the Essential Climate Variable (ECV) and Essential
Ocean Variable (EOV) methodology being pursued by WMO/WCRP Observing Panels)
4. Assemble a suite of model skill assessment metrics that form the basis for uncertainty
estimates of predictions, tradeoff studies between observing system components, and
validation studies (partially addressed by COMT but not fully realized)
5. Summarize attributes of observations (ocean, topography, hydrology, meteorology,
ecosystems; space-time resolution and accuracy) needed for model forcing, verification,
validation, and data assimilation
6. Define needs and outline design and implementation plan for a distributed national data
portal and archive system for ocean prediction inputs and outputs
7. Draft a CONOPS that delineates the respective roles and responsibilities of the NB and
RCOOS, including joint activities; e.g., testbeds and ocean prediction experiments
8. Regional ocean prediction products produced by NAVO should be provided to NOAA for use
by NWS, NCEP, NOS and the RCOOS for open boundary conditions, skill assessments and
diagnostic studies etc.
9. OPA activities should lead to infrastructure components (skill assessment metrics, testbeds,
data assimilation schemes, and observing system evaluation (OSE)) that support the overall
system design and performance evaluation of IOOS. These are encouraged to provide a
defensible, logical basis for the design and management of the long-term program.
In subsequent years, the OPA-JWG would be responsible for #3 and #7 in the above list, and would
be tasked with the following:
 Assess present operational and R&D ocean prediction capabilities relative to the traceable
user requirements, yielding a gap analysis
 Recommend implementation and R&D strategies based upon the gap analysis
 Foster discussions of implementation efforts, model skill assessments, other analysis
activities, technical issues, extensions of the physical predictions to biogeochemical and
ecological predictions, and other topics requiring coupled modeling
 Prioritize needed ocean model and data assimilation developments
 Foster community-wide communications via periodic forums
2. Synthesis of Regional IOOS Build-out Plans for the Next Decade (IOOS, 2012) (L. Rosenfeld)
Each RA has a build-out plan that was developed during the last half of 2011 based on discussions
with users and scientists regarding needs and capabilities. These plans were developed under the
following guidance: “The plans you are building should be an ‘idealized’ system at the end of a ten
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year build-out.” Plans were based on templates for user needs and assets. There was follow-up in a
workshop with all RAs and in individual calls. Common elements, as well as unique characteristics
were summarized in the Synthesis of Regional IOOS Build-out Plans.
Build-out plan components included products, platforms, and models, product development and
user engagement, data management and communication, education, research and development,
and system management. Within the Product heading, four themes were served to focus inquiries:
marine operations; coastal, beach and nearshore hazards; ecosystems, fisheries and water quality;
long-term changes. Under each theme, user needs and goals were identified and corresponding
products and services were described. For example, under marine operations, "safe passage into
and inside ports, harbors, marinas and passages" was one user need and goal, with real-time high
resolution observation and models (waves, currents, bathymetry, water level, density) identified as
products to meet that need.
A template was utilized to develop modeling build-out needs for the plans as follows:
MODELING & ANALYSIS SUBSYSTEM
For each required model component provide:
Dynamical Models: Most regions will deploy a dynamical numerical modeling framework that consists
of one or more models providing forecasts, nowcasts, and/or hindcasts to produce one or more enduser products. Most of the models work with each other (e.g. an atmospheric model provides forcing
for the circulation or wave models). Some models (for instance, ROMS) are capable of performing
numerous tasks. For this task, please use the following categories: (see terms and definitions for
fuller description)
1) Atmospheric models
2) Circulation models
3) Inundation models
4) Wave models
5) Hydrologic models
6) Sediment transport models
7) Water Quality/Ecosystem models
8) Fisheries models
Statistical Models: For some applications a dynamic model is not practical/feasible/available, and a
statistical approach is employed to relate observations to a desired output. Most take the form of a
regression of one or more input variables that are combined to estimate the output and serve as
decision support tools. Please indicate the type of output provide. Examples:
i) statistical surface current prediction – Short Term Prediction Systems (STPS) – uses HF
radar input and produces a 24 hour forecast
ii) statistical water quality model – uses varied inputs to predict harmful pathogen levels in
shellfish areas
iii) statistical rip current forecast – uses surface wave information to estimate the likelihood of
dangerous rip currents
For each model, the following set of information was gathered from the regions:
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Model Name
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Type of Model (see above – e.g. circulation model)
Geographic Domain (entire region, specific harbor, etc)
Themes/Issues Addressed
Important Variables to be modeled (see terms and definitions)
Spatial (horizontal and vertical requirements)
Temporal
Computing infrastructure, including redundancy of operations
Personnel
o (FTEs/year)
Expected Initial and Boundary conditions
o (to identify resource needs, e.g. basin-scale circulation model)
Development Needs
o If necessary, describe development efforts required for advancing, operationalizing or
refining each of the identified issues.
Following this process, a synthesis of regional needs was conducted. The model types identified as
being needed by all regions were weather, circulation, water quality, inundation, waves, and
ecosystem models.
The role of the RAs in numerical modeling varied across the regions. The following levels of
involvement in modeling were identified:
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RAs that make products using results from models run by other organizations
RAs that run models for their geographic region, and in addition provide model-derived
products. These include
 RAs that develop hindcasts and process studies
 RAs that run some models in a real-time "operational", data-assimilating mode,
meaning that the model runs, incorporates observations, and produces nowcasts and
forecasts on a continuing basis
Some RAs also undertake research in order to develop new modeling capabilities or models of
higher quality to meet their needs
The synthesis of the build-out plans also yielded some generally agreed upon results:
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Regional models should have much finer spatial resolution than the global or basin scale
ocean models that they use for boundary conditions. (The larger domain models may be run
by a member of the regional observing system, or an operational model run by Navy or NOAA
may be used.)
The regional models should assimilate observations made within their domains
The frequency with which the models should run, and the temporal resolution of their output,
depends on the type of model and its intended use
Taking advantage of ensembles may produce more reliable forecasts.
Model results must be formulated into products that meet stakeholder needs.
In order to be most useful, all regional models should be objectively assessed and results
should be communicated with a measure of uncertainty.
It was recommended that expert teams should address such issues as: boundary conditions, data
assimilation, freshwater input, validation, ensemble forecasting, model coupling, ecosystem
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modeling, OSSEs, regional testbeds. Regarding modeling, the report concluded that a more
integrated, strategic approach to modeling is needed that creates synergism among modeling
efforts in all the regions, evaluating and building on successful approaches, and that there is a need
to consider developing a national ocean modeling plan, including clarification of the federal role in
regional ocean modeling.
3. Storm Surge (E. Myers)
E. Myers gave a summary of NOAA’s Storm Surge Roadmap (2013). The Roadmap framed three
goals for improving surge mapping across boundaries:
1. Total water level prediction (this involves integrating non-tidal and tidal data coming out of
different models into a single water level product)
2. Vertical datum (this involves developing consistent vertical datum for projects and products)
3. Improve communication with users
The roadmap also summarized standards and tools that can bring together outputs from models
and shared data and observations that can be combined in a common way. The more the
community can work towards a common toolbox, the better individual regional testbed products
can be transitioned into operations.
E. Myers noted that there is a need to coordinate across activities and a need to develop a total
water level product into a single system. Vertical datum remains a confusion for users. Inundation
depends on understanding water above ground level in a common way, and this means maintaining
communication across the regions. COMT made advances in modeling that could be transitioned to
operations. Hurricane centers now use netCDF, TDS (THREDDS Data Servers) and Matlab tools and
to visualize output, thereby making the most of progress in standards and interoperable tools.
4. NOAA Science Advisory Board Review of National Center for Environmental Prediction
Ocean Modeling (NCEP, 2004) (A. Mehra)
A. Mehra gave a brief overview of the NCEP final report review by NOAA’s Science Advisory Board.
He noted that the report was from ten years ago, but that broad recommendations resulted,
including a need for improved earth system forecasts and transition to operations. A. Mehra noted
that the report highlighted that making remote and in situ observations globally and coastally
accessible needs to be paralleled by a similar effort in terms of model data outputs and tools. The
report also noted that QA/QC in the context of operational models is not done comprehensively.
The existing mission of NWS/NCEP is the 4R’s as follows:
 On time (Reliable)
 Real-time (Ready)
 All the time (Robustness)
 Accurate (Right)
Specific recommendations/steps and their current status:
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Availability and use of remote sensed and in situ observations for both global and coastal
ocean
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addressed by IOOS DIF project but need a similar effort for model data –
inputs/outputs/products
Assist observational systems through operational data distribution, field support and QA/QC
standardization
o more needs to be done
Towards an Earth System capability
o NEMS (NOAA Environmental Modeling System) being built with NUOPC/ESMF coupling
Advanced data assimilation efforts with JCSDA
o just beginning
Integrate ocean prediction with NCEP mission
o 2008 strategic plan, to be revised in 2015
Multiple ocean models under use, need for UMA
o need testbeds for skill assessment, improvements
Close partnership with NOS
o a lot of progress with COMF, ESTOFS
Close partnership with Navy
o RTOFS Global, NCODA MoU
NCEP research links
o some but still not adequate; lack avenues, resources
o
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5. Ecological Forecasting Roadmap (NOAA, 2013) (J. Quintrell)
J. Quintrell gave a brief overview of the Ecological Forecasting Roadmap developed by NOAA. This
report consisted of the following sections: Definitions, Vision, Constituencies and Users Served,
Guiding Principles, Goals/Priorities, and Roles and Governance Structure. Under Goals/Priorities,
the following immediate priorities were identified:
 Harmful Algal Blooms
 Hypoxia
 Pathogens
 Habitat/Species Distribution
The review of the roadmap went into detail on each of these priority areas, and identified key
forecast issues under each theme.
J. Quintrell noted that NOAA has been reaching out to regions on a strategic basis depending on
interests and has been successfully exchanging information on NOAA ecological modeling and
regional modeling and needs. NOAA started with SECOORA and is now developing similar outreach
efforts that are theme based within each region. This process has been targeted and effective and
one that should be pursued further. Each region differs significantly in terms of needs, regional
modeling and data integration maturity and regional themes of interest.
A short discussion followed, during which the group discussed the difference between ecological
forecasting and ecosystem modeling. The group differed in perception of these two terms, with
some members of the team having considered the two terms to be interchangeable.
L. Rosenfeld asked whether other federal agencies should be or have been involved in the regional
outreach efforts in the context of ecological forecasting. The group confirmed that NOAA is
reaching out to other federal agencies, and in some regions, agencies other than NOAA are in fact
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taking the lead on ecological forecasting.
6. Requirements for Global Implementation of the Strategic Plan for Coastal GOOS (Panel for
Integrated Coastal Observation (PICO-I)) (SC-2012/ GOOS-193) (J. Wilkin)
J. Wilkin gave a brief overview of the GOOS Implementation Document. He noted that the goal of the
report on Coastal GOOS was to develop a plan for sustained provision of data and information to
inform the Ecosystem Based Approaches for managing human uses of coastal ecosystem goods and
services and adapting to climate change. Addressing the Coastal GOOS plan priorities will require
investments by developed nations in a coordinated global network of national and regional
observing systems that are locally relevant and based on interoperable data and information
exchange. The Joint Commission for Oceanography and Marine Meteorology (JCOMM) is the
coordinating body for implementing the ocean-climate observing systems of GOOS and GCOS. No
such body is in place for coordinating the global implementation of coastal networks of
observations, data management, and modeling that includes the full spectrum of required
geophysical, biophysical, chemical and biological variables.
Similar to other summaries of documents, J. Wilkin noted that there is a need to communicate
between communities developing model capacity and those communities that understand the
fundamental needs that need to be met. Regional demonstration projects with an integrated
project cycle in terms of observing system deployment and model development are a way to frame
more generalizable project cycle frameworks.
A brief discussion followed. L. Rosenfeld asked if there are any federal models using Ocean System
Simulation Experiments (OSSEs). GODAE has engaged in holding workshops on OSSE/OSE
development. The group discussed the fact that the Great Lakes has been using a similar process for
a significant period of time, though it was not categorized specifically as an OSSE. Antonio's group
used OSSEs to rebuild their observing system after it was destroyed by a storm.
V. Development of a Common Vision Statement for IOOC/IOOS Modeling Strategy in Regards
to Coordination of Modeling Activities across Regional and Federal Partners (E. Lindstrom)
A discussion on developing a Vision for the Modeling Strategy followed and included input from all
team members. The following bullet points will serve to act as a starting point for the Vision
Statement:
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The Group doesn't have to plan the entire IOOS modeling enterprise. It needs to develop a
strategy by which that enterprise can efficiently evolve and respond to achieve the
objectives.
Coastal IOOS at the global and national level should be a priority. A modeling center
without walls could serve to integrate individuals across regional, state, and international
boundaries.
The strategy needs to more concretely define the IOOS niche within the context of
partnerships with regions, federal agencies, universities, and labs.
The strategy needs to focus on regional and coastal IOOS, but also include and fold in
relationships to global and basin. (Define regional influence out to the limits of the EEZ?)
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US CLIVAR could be tapped for inclusion in the strategy development, given that CLIVAR
Project Teams have been developed and could be a model for targeting efforts in the context
of the National Modeling Strategy.
The team agreed that this strategy should develop a virtual organization, similar to
European Centre for Medium-Range Weather Forecasts (ECMWF), in order to share
expertise.
The strategy should frame the way that models are being used and can be used to assess the
observation network in a way that serves to identify observing system design, needs, and
gaps.
o Models can be a catalyst for driving observation funding. For example, team
members discussed that NSF S&T Centers take community ideas and invest it in
concentrated efforts on a focus point for a sustained time, while integrating
checkpoints into the workflow.
o The strategy should be issue driven while enabling the community to identify
products that can cut across specific issues.
The team engaged in a discussion of the governance structure of a virtual organization and
debated whether or not it would make sense to have a portfolio manager or managing
external council/advisory board in order to develop clear roadmaps and initiate leadership
for various teams. In addition, the team discussed utilizing transient investigators to
respond to tasks as they evolve and change. The team also discussed the need for regular
and sustained monitoring of progress and external review.
The team also discussed a need for the vision to include some kind of impetus for being part
of the center without walls – to create incentives for individuals to participate.
Climate Process Teams, which embed researchers into operations center, or field programs
that can point team members back to solving particular issues could be one model.
VI. Templates Summarizing Modeling Capacity at National, Regional, and Global Scales (B.
Baltes)
A. Templates for summarizing Federal agency needs, responsibilities and capabilities
A discussion of templates for summarizing federal agency needs, responsibilities and
capabilities followed. H. Dean developed the initial draft of templates for understanding the
various federal mission statements and approaches to developing and utilizing models, and the
team used this as a starting point for discussing the best approach.
A variety of uses for such a federal ocean model inventory were identified:
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Allows RAs to see how they might impact federal capabilities
Avoid duplication or overlap in efforts
Make it easier for model developers/operators to see who they might go to for help
Facilitate communication of modeling needs
The team determined that this part of the strategy needs to be detailed enough to establish a
process, moving forward on how federal agencies can engage with regional model development,
and the type of information that would be valuable to socialize among community members.
However, the team agreed that it is not perhaps completely necessary to fill in all aspects of the
summarizing table. The need could be met by serving as a living document that will
12
periodically be updated with agency capabilities, missions, and activities in regards to
modeling.
The IOOC could play an important role in maintaining this living document by vetting current
input into the table by COL staff, by flagging shortcomings of the format, and by identifying gaps
in information that may not be transparent from available online resources used to summarize
federal agency activities and priorities in the context of modeling. Maintaining and tracking
changes could be achieved through a platform like GitHub. Currently the document is housed as
a Google document.
It would be valuable to map IOOS regional modeling networks to agency missions and goals in
order to align and develop appropriate partnerships that can drive funding, and that would be
aided by the development of this template. Federal agencies need to provide quality control,
but at the same time, the information input cannot be so onerous as to be problematic. The
team agreed that the federal agencies can provide oversight but that staff should develop the
template in a way that makes it simple enough to make that task approachable. One way to
limit the template could be to go back to IOOS goals and frame the template that way – this
would both keep the template manageable and would help keep it in line with current IOOS
goals.
Additional columns should include contact information and a gaps column, which would allow
agencies to identify existing gaps in available modeling capabilities and products. The team
discussed ways to maintain the document as a living document, and that could be to place it on
GitHub so as to allow community contributed addition of tags that describe agencies and issues,
and create a discussion-based and tracking platform. Having the templates continually updated
would be a good selling point for federal agencies to update their activities so as to effectively
communicate with the community.
The team agreed that this effort could be taken on by a sub-working group that would then
make recommendations back to the working group and discuss the content of the template and
the platform. This effort would allow RAs to understand the activities of federal agencies and
for there to be a feedback platform for information to flow from RAs to federal partners.
The team needs to establish the framework for this template, and needs to put in place metrics
for understanding the usefulness of the templates, but that does not mean that the burden of
maintaining content falls entirely on the heads of the task team. One way to measure the
usefulness of this endeavor, for both federal and regional inventories, will be to capture and
communicate stories of partnerships or cross-cutting activities that result as a result of this
information gathering activity.
B. Templates for Regional Association Modeling Capabilities
The team also discussed the template developed for RAs. This was based on existing templates
of current regional products. The team agreed that there is value in maintaining a living
document that describes regional modeling capabilities in detail and identifies common as well
as novel information products.
The team agreed that there are interoperability issues between the federal and regional
templates. Ideally, the team should create a searchable database of capabilities and needs at the
federal and regional levels that could aid communication between the national and regional
13
scales and which could help the team monitor and assess progress towards identified goals and
developing communities of practice. An annual update process based on quarterly reports and
maintained by the IOOS Office, which would issue requests for information from RAs in a
determined format could facilitate the process. Support from the team would be provided in
terms of developing content and format. The team emphasized that in developing the
framework for these tables and templates, it is essential that the team develops
milestones/goals.
The federal and regional ocean model templates should be available, searchable, and updatable.
In addition to the uses outlined above for the federal model inventory, the regional model
inventory will facilitate interoperability issues such as analyses that use multiple model
products (or relative skill assessment, or ensemble prediction.
VII. Overview of Coastal Ocean Model Testbed lessons as a prototype instrument for
implementing strategic plan objectives (R. Luettich)
The Coastal Ocean Model Testbed (COMT Site) was a prototype – but has become an on-going and
principal instrument for advancing an integrated modeling strategy on the part of IOOS.
The mission of the COMT is to accelerate the transition of advances from the coastal ocean
modeling research community to improved operational ocean products and services. The longrange vision of the program is to increase the accuracy, reliability, and scope of operational coastal
and ocean forecasting products. Drivers of the testbed include the roadmaps as well as other
federal agency operational requirements. Regional requirements are not currently a driver for the
COMT.
As the team discussed, the Testbed lacks certain mechanisms that would facilitate longer range
planning and accomplishments. The testbed was originally funded as an earmark, and that
14
mechanism is no longer available as earmarks were banned in the House of Representatives. While
the COMT has developed significantly and is NOAA’s only ocean testbed, it was not originally
planned as a fully conceived long-term project, but rather reflects an ongoing issue driven effort. It
is not an NCEP ocean testbed – there is no mandate from the NCEP side to transition to operations
from the testbed. The Testbed has been working on an issue driven basis that may serve to guide
the strategy/framework that the Modeling Task Team ultimately develops. Currently, project
teams have formed around Cyber-infrastructure, Inundation, Shelf Hypoxia, Estuarine Hypoxia, and
West Coast modeling issues including data assimilation and boundary conditions.
The success of the COMT has depended on partnerships, but at times has stepped on the toes of the
RAs, which may be an issue that needs to be addressed in the framework for a modeling strategy.
The second round of projects engaged in by the COMT utilized an internal advisory and review
panel. The COMT has also developed a clear flow chart for operations to research/research to
operations processes (figure below).
COMT challenges include coordinating planning and award cycles and processes, maintaining
engagement with other agencies, allowing for continuity of efforts while developing new projects and
bringing on new PIs, and developing a clearer role for COMT to help define metrics of success. COMT
has also resulted in a series of lessons learned, which R. Luettich summarized as the following
bullet points:
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Often modelers are more different than models
o Sustained effort required to bring different modeling groups together
o Usually worth the effort - can lead to rapid learning and model improvement
Often largest difference in models is specialization and performance
Capacity building is often a critical part of transition – partnerships are key
Mature modeling groups already have many CI tools
A standards based, multi-model archive is difficult
15
VIII. Discuss case studies illustrating impediments and paths to success (R. Signell)
R. Signell facilitated a discussion and overview of federal/regional modeling case studies.
Case Study 1: Huron to Erie Connecting Waterways Forecasting System (HECWFS) – D.
Schwab
The discussion began with a focus on the Huron to Erie Connecting Waterways Forecasting System.
GLOS identified the need to extend modeling to a smaller area using an unstructured grid. Now it's
part of Great Lakes Forecast System, which is an example of a system that has established a longterm relationship between a research lab and a regional NOAA office – U. Michigan and the NOAA
Great Lakes lab. The HECWFS is used for issues relating to oil spills and drinking water use. CG SAR
uses it. The pre-existing relationship between GLOS, the NOAA lab, and academia. helped facilitate
the development of the HECWFS. Full 24/7 ops is being done at GLERL – a NOAA R&D lab. Longterm simulations have been used as an archive of variability in the region. The system is also highly
issue driven and has pulled in federal partners, including NSF and the State Department on
particular projects.
The GLCFS also has developed tools such as the Point Query, which provides quick access to the
forecasting system input data and model output for a given location and time period. The GLCFS has
long term funding and a dedicated full time staff, with continuity and a sense of ownership of the
work and products that are developed. These aspects of the GLCFS are ideal and have been a large
part of why the System has had such high success rate.
DISCUSSION
The Team discussed the need to create a similarly long-term dedicated framework in the context of
the national strategy. One aspect of this will be determining whether the framework should require
a portfolio manager. J. Feyen, who is currently the Storm Surge Roadmap portfolio manager for
NOAA, noted the value of having a point person to oversee and guide the development and
distribution of research efforts and resources across a spectrum of issues. A portfolio manager may
also serve to effectively manage timelines and the logistical aspects of developing an issue context
and determining when it is appropriate to solicit feedback from the community so that output can
be appropriately timed and facilitated. While a strategy or framework can be issue and small team
driven, there may need to be a facilitator/portfolio manager in order to create continuity and the
kind of institutional and long-term knowledge that can help establish early on the types of
partnerships, funding mechanisms, patrons, dedicated resources, and strategic research foci that
are required to achieve success.
Case Study 2: Science and Technology University Research Network (SATURN)
Collaboratory, Center for Coastal Margin Observation and Prediction (CMOP) – A. Baptisita
The SATURN Collaboratory is an interdisciplinary, river-to-shelf observational network that
includes a variety of observing technology, including tidal freshwater stations, ocean gliders,
autonomous underwater vehicles, and estuarine and plume stations measuring a variety of
variables on a 24 hour basis. It is a subsystem of NANOOS. Data collection feeds into a Virtual
Columbia River, which is a modeling system that offers representations of processes, variability and
changes that span the ocean to river scales.
16
NMFS had need to know where Columbia R outflow went. Many other uses wanted multiple years
of flow scenario. Long simulations are used as an archive of variability to look at things like salmon
habitat conditions. The Army Corps of Engineers E also uses for impacts of channel deepening.
The work of SATURN had a role to play in the recent debates and discussions surrounding the 2014
deadline for renegotiating the Columbia River Treaty. The Columbia River Basin is a transboundary,
U.S./Canada, area that covers 700,000 square miles. Because the Columbia has been heavily utilized
and developed by both countries, including the construction of dams for power generation and
flood control, as well as use of the river for navigation, it has been a focus of U.S./Canada
collaboration and study over sharing the costs and benefits of various aspects of river water
distribution. In 1964 a treaty was ratified to provide a framework for a basin-wide system that
could allow both countries to utilize the resource for power generation, irrigation, navigation, and
flood control. Since then, the collaboration has become a model for transboundary water resource
management. In 2013, both countries considered the economic, environmental and social effects of
the treaty arrangement given the 2014 deadline for notification of a desire to renegotiate or
terminate the agreement approach. SATURN was able to contribute a better understanding of
basins for potential inclusion in the agreement as part of the overall Columbia River Basin system.
Similar to the GLCSF, SATURN has a critical mass of long term funding from NSF (~$1M/yr over a
10 year span) and has focused on issue areas that emerge from the community of users and
researchers. As a result of this funding and issue based structure, the organization has developed a
robust institutional knowledge and has developed a sense of ownership over products and services.
In addition, as a result of the long term activities of the organization, a community has grown up
around the services provided with an understanding of the value of the organization underlying
those services. In other words, the structure has created an organization that is too valuable for the
region to allow it to disappear when NSF funding runs out in 2 years.
DISCUSSION
The group agreed that, like the first case study examined, the Collaboratory demonstrates that issue
driven, product driven, and small team driven projects that bubble up directly from the user
community are the most valuable and the most successful. At the same time, while it is valuable to
maintain an issue driven, project based approach, it is also vital to have long term buy in, funding,
dedicated personnel and a sustained framework and directive to maintain the institutional
knowledge necessary for success. Scientists from many disciplines (observations, models, users)
need to be involved.
Case Study 3: National Centers for Environmental Prediction (NCEP) – A. Mehra
NCEP uses the Navy as a framework, with 10 research groups working on operational frameworks
and advanced models. For example, there are 9-10 groups funded through NOPP to advance wave
modeling using the WAVEWATCH III framework. NOPP wrote requirements for these groups using
input from Navy, NOAA, NSF, and NASA. This resulted in an interagency approach to developing an
RFP that catered to the work nested within the overall framework.
NCEP is an arm of the NOAA's National Weather Service (NWS), is comprised of nine distinct
Centers, and the Office of the Director, which provide a wide variety of national and international
weather guidance products to National Weather Service field offices, government agencies,
emergency managers, private sector meteorologists, and meteorological organizations and societies
17
throughout the world. NCEP is a critical national resource in national and global weather
prediction. NCEP is the starting point for nearly all weather forecasts in the United States.
Currently, NCEP includes the following National Centers:
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The Aviation Weather Center provides aviation warnings and forecasts of hazardous flight
conditions at all levels within domestic and international air space.
The Climate Prediction Center monitors and forecasts short-term climate fluctuations and
provides guidance information on the long-term global effects climate patterns can have on
the nation.
The Environmental Modeling Center develops and improves numerical weather, climate,
hydrological and oceanic predictions through applied research in partnership with the
broader research community.
The Hydrometeorological Prediction Center provides analysis and forecast products,
specializing in quantitative precipitation forecasts
The Ocean Prediction Center issues weather warnings and forecasts out to five days, in
graphic, text and voice formats for the Atlantic and Pacific Oceans.
The NCEP Central Operations sustains and executes the operational suite of the numerical
analysis and forecast models and prepares NCEP products for dissemination. It also links all
nine of the national Centers together via computer and communications-related services.
The Space Environment Center provides space weather alerts and warnings
The Storm Prediction Center provides tornado and severe weather watches for the
contiguous United States along with a suite of hazardous weather forecasts,
The Tropical Prediction Center provides official NWS forecasts of the movement and
strength of tropical weather systems and issues the appropriate watches and warnings for
the US and surrounding areas, and marine products covering the tropical Atlantic and
eastern Pacific.
DISCUSSION
This Case study again prompted a discussion of the value/role of a portfolio manager. J. Feyen
noted that the need for a portfolio manager depends on what is trying to be accomplished. A
manager means that there will be a single point person who is not invested in any one project, and
therefore will distribute resources and make judgments on an objective basis, taking the entire
framework goals into account. Similarly, B. Baltes noted that a project manager is highly valuable
for maintaining timelines, and making sure that all components of the portfolio are on track.
Individual project participants simply do not have the time and energy to invest in the logistical
side of management over the entire scope of projects. In addition, a point person that can
understand the entire portfolio will be able to facilitate any cross-pollination of resources and
research approaches across different projects.
Case Study 4: Ocean Surface Topography – J. Wilkin
NASA Science Teams are a good paradigm for fostering communication and scientific exchange
while reviewing the engineering and design aspects. Starting in 1992, NASA, NOAA and European
partners have been tracking global ocean surface topography with joint ocean altimeter satellite
missions. Similar to the other case studies discussed, this project involves developing application
related projects. The groups involved meet once a year to present results and have developed a
calibration and validation platform. The project has also clearly linked their output to societal
18
benefits within a variety of categories (Climate, Marine Operations, Marine Research, Land
Operations, Education, and NRT Data Resources).
DISCUSSION
The team discussed the need to address academic versus agency timelines which often differ in
terms of developing and improving models. The team needs to tie those timelines to regional
expertise, which requires that the relationships develop into long term commitments and develop
ongoing processes for communications. While the team agreed that the framework should attempt
to develop these processes, team members also acknowledged that in many cases of success,
processes for timeline development and communications have involved trial and error. Therefore,
an approach that allows for adaptation and change in the process as new lessons are learned will be
vital.
Case Study 5: International Modeling – P. Hogan
The team then turned to a discussion of international modeling efforts, including GODAE
OceanView and some of the lessons learned. Like other case studies, GODAE OceanView meets once
a year, but there are individual task teams that are issue based which then meet more regularly.
The document bank is highly developed and could serve as a resource for the Team. In addition, it
was noted that this international effort is not just driven by science and technical expertise, it also
involves resource providers, and those groups providing funding are in constant communications.
This model has been applied to various international ocean observing systems including the Indian
Ocean, and provides a strong tie between technical groups and program managers to facilitate
faster timelines for funding needed tasks as they bubble up, and more efficient issue driven
approaches.
DISCUSSION
The IOOC has funded an initial network
analysis of international organizational
collaboration, which could serve as the
basis for a more focused and validated
approach to analyzing the networks of
international organizations involved in
modeling activities. Currently, the database
has been developed on the basis of online
research, and has included the cataloging
organizations, a high level assessment of
their missions, roles (Data,
Communications, Human Resources,
Infrastructure) and the partnerships
they’ve engaged in with other
organizations. By investing in this analysis,
the Framework could put forward
recommendations for gaps in collaboration,
or highlight and socialize information on
modeling activities at the international
scale that could serve to facilitate U.S.
modeling missions and issue based
projects.
of
Example output from network analysis (H. Dean)
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Case Study 5: San Francisco Bay Operational Forecast System (SF-BOFS) – L. Rosenfeld
Criteria for NOAA OFS is primarily about use for navigation. It would be helpful for OFS
evaluations if output were provided, and input solicited from the community, earlier in the
process. Pre-existing relationships and early-established partnerships are important. Also
encourage coordination with RAs on in situ evaluation data sets (e.g. salinity for under keel
clearance.
Eric Lindstrom's departing comments:
Crossing the valley of death from research to operations is hard. Focus on research funding.
IOOC is not looking for a national modeling strategy. Can’t be all of ocean modeling. How do
we make the observing system better? What changes can be made at the federal level to make it
better? Grow values of coastal IOOS observing. Not too grandiose. Be at the project and task
level.
Stimulating research activities that would change the mind of operational centers, brilliant
research that would persuade change in methods. Virtual ECMWF is a good idea. Aim at centers
that don’t have the research capabilities.
IX. Identify the priority multi-regional and federal information needs that modeling can help
solve; Identify impediments to solving those needs – technical, economic and bureaucratic;
Needs for capacity building within RAs and Federal partners
The Team's discussion developed the following broad categories that the Framework should
address:
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Developing a process for an issue driven approach
Developing testbeds
Workforce issues (need for developing intellectual capacity)
Instruments (high performance computing, communication between groups of modelers
and data providers, research community access to a National Backbone Data Portal).
The group agreed that the best structure for the final product coming out of the framework would
be a “center without walls” but this would not necessarily be the sole instrument proposed to
implement objectives of the plan. The “Center” would be an ongoing way for researchers to network
and develop within a structure that is not geographically based and which can take on additional
capacity in a more fluid way. It would provide a way for RAs to make their needs known. It was
emphasized that this would need to be funded by new money – not come out of the existing RA
money – through a redirection of some RA modeling resources would be appropriate where the
Center objectives aligned with RA objectives and plans and those regional efforts would be
enhanced by the pooling of resources, the coordination aspects supported by the Center.
The group identified several research and development issues that the framework should attempt
to address:
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Coupled modeling, including land/sea and coastal/open ocean
Ensemble modeling
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Data assimilation
Ecological models
Federal agency responsibilities, distribution, and coordination in the context of model
development and the coordination flow between modeling/data management/observations
Since federal agency responsibilities are distributed, how do we coordinate coupled model
development – e.g. in land/ocean interaction, wave-ocean circulation (NWS does waves,
NOS does circulation), or coupling sediment transport (ACE) to circulation (NOAA), or
discharge nearfield (EPA) to shelf circulation.
Cyber infrastructure
Observing system design, optimal control of mobile assets, analysis of gaps in the observing
system, robustness to service interruptions or instrument failure, and quantifying loss of
skill in these events
Need to address the operations to use issue – whose responsibility is it to train the users to use
model output and products? There's a 3-way triangle among R&D, Operations, and Users.
Need to learn from what NWP does – researchers adopt existing frameworks and add to them.
Need to have some organized way to do user model evaluation; for NWS, the WFOs do
evaluation.
Think about value-added products – private industry drives part of weather forecasting.
X. Focus areas for the next 5 years
There was a wide-ranging discussion of user/societal needs and modeling/observing system issues
to meet those needs.
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Ecosystem modeling, including data assimilation; distribution of species (protected and
commercially fished) in time and space
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Need better climatologies for hindcasting
Probabilistic predictions for coastal forecasts – e.g. HABs, inundation
Modeling metrics and skills
Climate downscaling
Coastal discharges – coupling between estuaries, nearshore, shelf needed.
Use ecosystem and storm surge forecasting roadmaps
Navigation, inundation, filtering (bioaction)/water quality (broad defn), living marine
resources. (where does Search and Rescue fall within this)
Don’t forget the states. They’re very interested in FIBs, hypoxia, eutrophication
There is tremendous capacity in modeling (in federal agencies and RAs) and observations –
how do we best take advantage of it. Investment in modeling helps to take advantage of
observations. What does society get in return?
Unique opportunity to take advantage of observations because of IOOS
Smaller scale features, non-hydrostatic models
Improve ability to model surface currents
Oceanographers without ships but with chips – Art Allen
Forecasting in subpolar regions
A. Baptista suggested the following statement of six topics as focus areas:
21
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Integrated river-to-shelf physical and biogeochemical models, addressing long-term
variability and change in hypoxia, acidification, and nitrogen/carbon budgets
Integrated river-to-shelf models for short-scale events (HABs, fecal contamination, etc)
Model-independent data assimilation strategies applicable to shallow non-linear
environments
Model-informed protocols for design of observation networks
Strategies for fast predictors (statistical, machine learning, etc) informed by archives of
detailed models
Strategies for probabilistic predictions
John focused the discussion by posing the question: In five years' time what modeling capabilities
would we like to have that we don't have now:
1. Coupled ecological data assimilative modeling for estimating ocean state conditions
relevant to users, BGC, acidification.
a. Coastal data assimilation, bio-optical model data assimilation, assimilation/prediction
on short spatial and temporal scales.
b. The team discussed the need to include within the modeling strategy a place for landocean interactions, sub-polar regions, meteo-tsunami, high resolution, and nonhydrostatic physics.
2. Probabilistic ensemble coastal ocean prediction (weather, inundation, navigation, extreme
events, climate downscaling).
3. Climate downscaling, reanalysis state estimation with uncertainty.
4. Coupling of land/ocean/atmosphere/ice connections via surface water, groundwater, and
wetlands to estuaries, with waves, near-shore surf zone dynamics, geomorphology and
coastal sediment dynamics, and including dispersion and plume modeling, aerosol
deposition, pathogens, toxins and harmful algae, littoral zones, rivers to beaches,
biogeochemical and RWQM, prediction on short spatial and temporal scales
5. Pan-regional IOOS CI data portal and comprehensive tools for interoperability, modeling
metrics, and skills.
6. OSSE implementation of a regional demonstration project at a “super site” through a
sustained and iterative life cycle for designing, implementing, evaluating, and improving a
Regional Coastal Ocean Observing System (RCOOS) over time, include end users to hone the
metrics for evaluation.
7. Fast predictors, using dynamical models and observations to train specialized models for
targeted applications.
XI. Identify paths, and instruments, for making progress in those focus areas
The team agreed that the Framework should ideally and more clearly define the roles of RAs,
federal partners, and the research community so that the various components are aware and
remain aware of modeling activities being carried out. This community building will help to
maintain an understanding of roles and avoid overlap. The team also discussed the need to
recognize that the paths and instruments may differ between focus areas, so that depending on the
issue driven project, stakeholder involvement from the various types may vary and fluctuate.
The team started to flesh out the idea of the “center without walls”. Models to look at for this
include:
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ECMWF paradigm – w/o walls – research and operations co-developing new capabilities
and systems, think of the countries in ECMWF as being the different agencies in US.
NSF Science and Technology Centers
NCAR (this was noted by co-chairs immediately following the meeting), although NCAR also
has a physical structure.
Gulf of Mexico Research Initiative
National HF radar program
The center without walls could potentially subsume the COMT. A 10-year strategic plan was
suggested. Various levels of oversight were discussed:
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A director
An advisory board (of high level people - patrons).
Steering group including non-modelers – policy, observationalists etc.
Joint working committee as recommended by MAST – more technical. Reps from federal
agencies and RAs.
It was suggested that the center have an active fellowship program with researchers working at
operational centers. NRL has something similar. It was also suggested that there could be a
permanent center but the people working at it would shift. Or for given projects, there might be a
physical place where everyone worked together for a time.
B. Baltes pointed out that this the team is working on a national strategy, not a plan, and as such no
funding is implied. The group identified other Collaboration Tools/Instruments, for which new
money might not be required.
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Working Groups, Committees, Task Teams; e.g. NASA science teams, GODAE task teams;
CLIVAR process teams
Workshops
Testbeds
Funded projects
Re-tasking of IOOS RA Work Plans
XII. Synthesis of deliberations on focus areas, paths and instruments
The group suggested that the Framework establish a Joint Working Group for Ocean Prediction and
Analysis which would establish a center without walls. This would be a structure similar to an RA
but pan-regional and focused on modeling, while including representatives from the modeling
community and from outside that community. The group agreed that the framework needs to be
established in a way that creates a long-standing framework and with a planning process and
governing structure that develops long-term strategies. The team discussed developing a
fellowship system which could cultivate new talent within the center without walls which could
then be tapped for permanent positions. The team also discussed the need for an oversight body or
individual that could tie together the different aspects of the framework as well as provide input
into COMT priorities. Developing a community of practice via a Science and Technology Center will
be of value. A permanent center with core staff (IT and HPC resources) will help provide a
23
permanent backbone for the center without walls that can house institutional knowledge and a
long-term outlook, which will include a vision for what modeling capabilities need to look like on a
5-8 year timeline. Operational centers may then be established on a sub-regional basis. An online
operational center that will focus on developing data portals, sharing code, sharing modeling
scripts, and developing a quality control process will also be important.
XIII. Assignments/Working Groups
The last component of the workshop involved developing a set of working groups to synthesize and
move forward on the various elements of the framework as well as assigning participants (and
proposed group leaders in bold) to those groups as follows:
1. Vision
(A. Kurapov, J. Quintrell, B. Baltes, H. Dean)
2. Templates for model inventories (Federal/Regional and including most relevant
international partners/collaborators)
(B. Baltes, H. Dean, L. Rosenfeld)
3. Case studies – lessons learned
(A. Baptista, D. Schwab, L. Rosenfeld)
4. Joint Working Group:
(a) Activities to advance collaboration and federal/academia partnerships: Workshops, Task
Teams, and complements to GODAE Oceanview activities
(B. Baltes, H. Townsend, E. Meyers, J. Wilkin, H. Tolman, J. Smith)
(b) Center without walls – flesh out structure, governance, practicalities of implementing
and operating.
(A. Baptista, R. Signell, D. Schwab, R. Luettich, A. Mehra, H. Tolman)
5. Model capabilities 5-8 years in the future
(A. Mehra, R. He, P. Hogan, John W., John L., A. Allen, R. Signell, H. Tolman, J. Smith)
The next teleconference for the group is scheduled for July 17 at 1 pm ET.
Suggested audiences/uses for this report:
 IOOC
 NOAA Science Advisory Board
 NCEP strategic plan
 RA directors
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