Arctic Data and Modeling Needs for Improved Arctic System Synthesis: Community-Identified Issues Workshop Organizing Committee: Charles J. Vörösmarty & Dave McGuire (Co-Chairs), Janet Intrieri, Larry Hinzman, Marika Holland, Maribeth Murray, Josh Schimel, John Weatherly Data & Modeling Synthesis Workshop 2 April 2007, Bell Harbor Center, Seattle WA

Goals for This Talk 1.Brief history leading to this event 2.Rationale for a community statement on data and modeling for synthesis 3.Overview, goals, and structure of this Workshop

Community Discussions on Arctic Data, Modeling and Synthesis Not New 1996 ARCSS All-Hands Workshop 2000 ARCSS Synthesis, Integration, Modeling Studies (SIMS) AO 2003 Report by AC's ad hoc ARCSS Data Working Group 2004 Report by AC's ad hoc ARCSS Data Working Group 2005 Letter by AC outlining recommendations for a revised ARCSS data management structure 2006 (March) 1st ARCSS eTown Meeting 2006 (Dec) Fall AGU Town Meeting 2007 (March) 2nd ARCSS eTown Meeting And…in the same time frame - SEARCH, IPY, AON, and the current ARCSS move toward synthesis planned and implemented

ARCSS Move Toward Synthesis Aim is improved understanding of the Arctic as a system and of its particular role in the larger Earth system and its response to change Aim also is to engage decision-makers and the public on the importance of these issues

Motivation to Think about Data: Situation Today Project-specific, discipline-specific models/data sets employ highly specialized structures, resolutions, time/space domains (e.g. hunting tags vs polar orbiting satellite data) Data restrictions/data policy places barriers to full access (e.g. human subjects/social science data sets)

Motivation to Think about Data: Situation Today (continued) Arguably, the typical PI focuses on his/her science; frameworks for wide data & model dissemination generally lacking Opportunities on the horizon….IT…new analysis tools: models, instrumentation, remote sensing…IPY, AON challenges looming

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?

Expressed as questions * : 1.What are the data and modeling needs to advance synthesis-focused arctic system science? 2.What's currently working and what is needed in terms of applying data and modeling for analysis to advance science? What are the keys to success? 3. What are the practical steps forward as far as mechanisms, approaches, tools and procedures, organization, standards, and related issues? * “Workshop Focus Questions” at top of agenda

ARCSS Synthesis Workshop: New Perspectives through Data Discovery and Modeling 2-4 April 2007, Bell Harbor Center, Seattle WA CONVENED BY: ARCSS, SEARCH, IARC PARTICIPANTS (>50): Data Providers, Technology and Information Technology Experts, Data Consumers, Knowledge Brokers VISION TALKS Data Provider Perspectives (Marc Levy, Columbia University) Technology and IT Perspectives (Mark Parsons, NSIDC) Data Consumer Perspectives (John Walsh, IARC/UAF; Larry Hamilton, UNH) Knowledge Broker Perspectives (Elena Sparrow, IARC/UAF)

ARCSS Synthesis Workshop: New Perspectives through Data Discovery and Modeling 2-4 April 2007, Bell Harbor Center, Seattle WA MODE OF EXECUTION: Plenary sessions for general discussion, reviews, and consensus-building Breakout sessions with teams focusing on -“worked science examples” - broad integrative and cross-cut topics Poster sessions and “beer time” Facilitation meetings of the OC, facilitators, ARCSS, breakout leads eParticipation: Plenary sessions video-streamed, online bulletin board MAJOR OUTPUT: Community-reviewed report on key issues, opportunities, challenges, lessons-learned, and ideas for steps forward - with specific recommendations to NSF on science investments

Workshop Break-out Topics First break-out groups will be organized around 3 "worked science examples," science challenges to frame the discussion on needs & future approaches to advance arctic system science These are not science planning priorities, but rather are a means of stimulating discussion on the broad issues of data management, modeling, and innovation The workshop discussions will move from these break-out “science examples” to more integrative and broad cross-cutting issues

Using the following criteria: –Synthesize understanding of the arctic system –Cross disciplinary boundaries –Integrate a variety of data sources (field data, modeling outputs, historical or archived data, social science data, remote sensing, etc.) –Link the Arctic to the broader Earth system –Enhance communications between scientists, stakeholders, decision-makers, and the public Three examples were identified by the OC that lend themselves well to supporting our first set of breakout discussions First Set of Breakouts

Identify major commonalities, cross-cutting issues, and general data and modeling-related topics: –Of a scientific nature (e.g. use of intercomparison exercises, ESM fingerprinting, innovative statistical techniques) –Of a technical nature (e.g. metadata standards, using open source map serving, exploiting peta-scale computing) –Of an outreach nature (e.g. expressing complex data to lay public and policymakers) –Of an administrative nature (e.g. peer-review in the age of interdisciplinary science, virtual collaboratories vs bricks and mortar facilities) Day 2/3 Breakout Sessions

Then…. Findings from this workshop to be provided by BO Chairs, distilled, and incorporated w/ additional text by OC as a draft document (early-June) Document to be reviewed by WS participants and community at large (mid-June) Comments incorporated into final report text (early-July) Publication (August/Sept)