Summary of the Day• From Breakout reports, vision talks, Q&A, informal

discussions…repeated statements on

• Need for integrated physical, biological, social science data sets

“Incentive structures to encourage inter-d work”

“Identification of relations between bio and socio-ec

components and climate indicators”

“To integrate atmospheric/ocean/biological/socio-ec data

faces fundamental challenges in data comparability.”

• Need for frameworks to allow for data harmonization

“If you build a data platform, the data will come”

“…lots of time/money to force data into common formats…”

• Need for data searching across disparate sources

“..no mechanisms in place to inventory what’s out there”

“..so many places to get these data…that it is confusing”

• Community-model should not = monopoly

“Community-type models (CCSM-style)”

• Downscaling global model data / upscaling process data

“…create iterative process among modelers, providers, idea generators”

• Consider near-real time horizon

• Statements (continued)

Model development and improvement represent the highest level of integration

and synthesisIntegration of

basic disciplinesMathematics

Integration among models

GSFC

Sea Ice Physics

Integration of latest parameterizations based on

process studies

Ice ridging

mixing

convection

eddiesIce formationand decay

Ocean Physics

Integration of data

Oceanography

Atmosphere Sea ice

Hydrology

IARC

RASM

RASN

NYU

NCAR

LLN

NPS

UWLLA

IOS

Integration of model results

decadal

synoptic

seasonal

Atlantic layer

Fresh water

Improved models, diagnostics and predictions of Arctic system variability

ice

AWI

Slide courtesy A. Proshutinsky

SYNERGY BETWEEN OBSERVATIONS AND MODELED OUTPUTS

Early Tests of Coherence between Models/Obs

PHCOBS

SSS simulation looks reasonableAtlantic inflow generally too saline.

Shelf regions generally too fresh.

1980-1999 AvgB30.030b.ES01

CCSM3; Holland et al.

“ARCTIC SYSTEM FRAMEWORK”

• High resolution• Modules to accommodate advances in disciplinary knowledge

• Near real time…like NWP (snapshot of current state)

• Mid-term (push forecast capability over yrs/decades)

• Century-scale (test scenarios and impacts of strategic policy decisions)

CSDMS-Community Surface Dynamics Modeling System: New NSF National Center

@UCBoulder (NSF Cyberinfrastructure Directorate)

Module-based software architecture to foster community model development and synthesis studies

Such Frameworks Already Exist and Could Be Capitalized Upon

Proposed Charge

AM:

• What ideal framework / data / modeling system could we build as a community w/o constraint?

TheWhat

PM:

• What gaps, challenges, obstacles prevent us from attaining the vision now?…..what new research investments should be made?

TheHow

Products

IT Toolbox, Flux Couplers

Process Study, Monitoring Data

Simulation Modules

“ARCTIC SYSTEM FRAMEWORK”

Science Outputs Policy, public info demands

ARCSS Synthesis Workshop: New Perspectives through Data Discovery and Modeling

2-4 April 2007, Bell Harbor Center, Seattle WA

GOAL: Bring together data provider & data user communities to identify innovative approaches on data management and assimilation, recent developments in technology, and modeling that will advance arctic system synthesis

-more than IT, archiving, metadata standards, data management alone

-process as much as products: identify challenges holding us back, but also success stories & promising new approaches

-ways to structure the way we do business to identify and nurture advances not yet identified

-advice can we give NSF on investments in data and modeling-rich synthesis?