integrating data management into climate change science research
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Integrating Data Management into Climate Change Science Research
Bruce WilsonGroup Leader,Client and Collaboration TechnologiesInformation Technology Services Division
Adjunct Professor of Information SciencesUniversity of Tennessee
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My background and perspective
Wilson IDCC Integrated Reearch 2010-12-06
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• Carbon Cycle and Carbon Sequestration• Climatic Change Research• Atmospheric Radiation Measurements• Biogeochemistry of Terrestrial Ecosystems• Biodiversity
We provide value-added data and analysis tools used to: • Enable an objective assessment of the potential for, and
consequences of, global change• Improve the treatment of cloud and radiation physics in global climate
models in order to improve the climate simulation capabilities of these models
• Understand the complexity of the carbon cycle and the linkages to physical, biogeochemical and ecological processes and human influences
• Harvest, index, and search metadata for the discovery and delivery of spatiotemporal data
Objective: Advance environmental research and policy by developing and providing leading-edge, integrated environmental data management and delivery systems, particularly in the areas of:
Wilson IDCC Integrated Reearch 2010-12-06
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Data Centers at a GlanceARM Archive DAAC CDIAC
Sponsor DOE BER NASA SMD DOE BER
Type of dataAtmospheric
processes, cloud dynamics
Biogeochemical dynamics, carbon cycle, FLUXNET
Atmospheric gasses, emissions
data, Ameriflux
Archive Size > 200 TB~ 1 TB + 30 TB of MODIS data
~ 400 GB
Users/year ~1500 ~15000 ~300,000
Year Started 1991 1993 1982
• Broad range of users: modelers, field scientists, educators, NGO’s, general public
• Broad range of atmospheric, land process, and ocean data
• Additional projects within and between data centers
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Climate Data Explosion (hundreds of XB by 2020)
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Climate Data Integration Challenges
• Complexities of field research data
• Volume of remote sensing and model data
• Challenges of spatial projections and scale– Earth System Grid vs biodiversity data
• Tremendous range of length and time scales– What scale is relevant depends on what question you ask
• Widely varying cultures and data sharing expectations
• Semantics– What is the sign for NPP when carbon is sequestered
Wilson IDCC Integrated Reearch 2010-12-06
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Cost is a huge challenge
• How good is good enough?
• Should we close down 4 flux towers to improve data management at the remaining 90?
• What kind of mortgage can we afford?
• How do we train scientists in data, when they already have to learn so much “in domain”?
• How do data centers adopt new technologies while maintaining legacy operations?
• How do we move tools from proof-of-concept to production quality?
• How do we deal with data that has commercial value and governments that want to recoup investment?
Wilson IDCC Integrated Reearch 2010-12-06
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