Skip to main content
NSF NEON, Operated by Battelle

Main navigation

  • About
    • NEON Overview
      • Vision and Management
      • Spatial and Temporal Design
      • History
    • About the NEON Biorepository
      • ASU Biorepository Staff
      • Contact the NEON Biorepository
    • Observatory Blog
    • Newsletters
    • Staff
    • FAQ
    • Contact Us

    About

  • Data
    • Data Portal
      • Data Availability Charts
      • API & GraphQL
      • Prototype Data
      • Externally Hosted Data
    • Data Collection Methods
      • Airborne Observation Platform (AOP)
      • Instrument System (IS)
        • Instrumented Collection Types
        • Aquatic Instrument System (AIS)
        • Terrestrial Instrument System (TIS)
      • Observational System (OS)
        • Observation Types
        • Observational Sampling Design
        • Sampling Schedules
        • Taxonomic Lists Used by Field Staff
        • Optimizing the Observational Sampling Designs
      • Protocols & Standardized Methods
    • Getting Started with NEON Data
      • neonUtilities for R and Python
      • Learning Hub
      • Code Hub
    • Using Data
      • Data Formats and Conventions
      • Released, Provisional, and Revised Data
      • Data Product Bundles
      • Usage Policies
      • Acknowledging and Citing NEON
      • Publishing Research Outputs
    • Data Notifications
    • NEON Data Management
      • Data Availability
      • Data Processing
      • Data Quality

    Data

  • Samples & Specimens
    • Biorepository Sample Portal at ASU
    • About Samples
      • Sample Types
      • Sample Repositories
      • Megapit and Distributed Initial Characterization Soil Archives
    • Finding and Accessing Sample Data
      • Species Checklists
      • Sample Explorer - Relationships and Data
      • Biorepository API
    • Requesting and Using Samples
      • Loans & Archival Requests
      • Usage Policies

    Samples & Specimens

  • Field Sites
    • Field Site Map and Info
    • Spatial Layers & Printable Maps

    Field Sites

  • Resources
    • Getting Started with NEON Data
    • Research Support Services
      • Field Site Coordination
      • Letters of Support
      • Mobile Deployment Platforms
      • Permits and Permissions
      • AOP Flight Campaigns
      • Research Support FAQs
      • Research Support Projects
    • Code Hub
      • neonUtilities for R and Python
      • Code Resources Guidelines
      • Code Resources Submission
      • NEON's GitHub Organization Homepage
    • Learning Hub
      • Tutorials
      • Workshops & Courses
      • Science Videos
      • Teaching Modules
    • Science Seminars and Data Skills Webinars
    • Document Library
    • Funding Opportunities

    Resources

  • Impact
    • Research Highlights
    • Papers & Publications
    • NEON in the News

    Impact

  • Get Involved
    • Upcoming Events
    • Research and Collaborations
      • Environmental Data Science Innovation and Inclusion Lab
      • Collaboration with DOE BER User Facilities and Programs
      • EFI-NEON Ecological Forecasting Challenge
      • NEON Great Lakes User Group
      • NCAR-NEON-Community Collaborations
    • Advisory Groups
      • Science, Technology & Education Advisory Committee
      • Technical Working Groups
    • NEON Ambassador Program
      • Exploring NEON-Derived Data Products Workshop Series
    • Partnerships
    • Community Engagement
    • Work Opportunities

    Get Involved

  • My Account
  • Search

Search

Learning Hub

  • Tutorials
  • Workshops & Courses
  • Science Videos
  • Teaching Modules

Breadcrumb

  1. Resources
  2. Learning Hub
  3. Workshops & Courses
  4. CHEESEHEAD and Environmental Response Functions: Bridging Scales Workshop | AGU 2019

Workshop

CHEESEHEAD and Environmental Response Functions: Bridging Scales Workshop | AGU 2019

American Geophysical Union Annual Meeting

December 11, 2019

Share

How to make sense of complex observational datasets, such as collected by CHEESEHEAD, the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors? Could it be possible to bridge scale-mismatches such as between observations and models by jointly using spatial grids, continuous time series and discrete surveys? This workshop offers practical solutions through tutorials on accessing CHEESEHEAD data and using Environmental Response Functions (ERF) to combine multiple data sources for inference across observational and model perspectives!

Registration 

As in previous years, the final workshop agenda will be informed by your interests, potential contributions, and desired outcomes as submitted with your registration. The workshop has a limited number of participants. This workshop is not affiliated with the AGU Annual Meeting and participants in this workshop do not have to be registered for the AGU meeting. 

Registration is now closed. 

 

Workshop Goals

Through participation in this workshop, our goals are to:

  • Explore the origin, consequences, and possible remedies of scale mismatch;
  • Learn tools for distributed data access, collaborative data merging and analysis;
  • Empower participants to contribute and implement their own ideas;
  • Coalesce topical interest teams for continued collaboration.

Schedule

Location: San Francisco, CA. Additional details will be provided to registered participants.

Date: Wednesday December 11th, 3:00-6:00 PM PT (local time)

Time Topic
14:30 Help desk and room set up. Please come early if you have any computer set up issues.
15:00 Welcome & Introductions
15:15 Lightning talks: Scale Mismatch; CHEESEHEAD Project; ERFs
15:30 Access CyVerse to send your inquiries to the data – on high-performance computer
16:00 Breakout Groups
Interactive eddy4R to create ERF data cubes with unified space-time resolution/extend
Identify and self-organize interest-specific collaborative group
17:30 Breakout summary, next steps, and debrief
18:00 Adjourn

Organizers

  • Stefan Metzger - National Ecological Observatory Network, Battelle
  • David Durden - National Ecological Observatory Network, Battelle
  • Ankur Desai, University of Wisconsin-Madison
  • Brian Butterworth, University of Wisconsin-Madison
  • Chris Florian - National Ecological Observatory Network, Battelle
  • Sreenath Paleri, University of Wisconsin-Madison

If you have questions about the workshop materials, please contact one of the instructors.

Twitter?

Please tweet using #NEONData & @NEON_Sci during this workshop!

Schedule

Time Topic
14:30 Help desk and room set up. Please come early if you have any computer set up issues.
15:00 Welcome & Introductions
15:15 Lightning talks: Scale Mismatch ; CHEESEHEAD Project; ERF Project
15:30 Access CyVerse to send your inquiries to the data – on high-performance computer
16:00 Breakout Groups
Interactive eddy4R to create ERF data cubes with unified space-time resolution/extend
Identify and self-organize interest-specific collaborative group
17:30 Breakout summary, next steps, and debrief
18:00 Adjourn

Share

NSF NEON, Operated by Battelle

Follow Us:

Join Our Newsletter

Get updates on events, opportunities, and how NEON is being used today.

Subscribe Now

Footer

  • About Us
  • Contact Us
  • Terms & Conditions
  • Careers
  • Code of Conduct

Copyright © Battelle, 2026

The National Ecological Observatory Network is a major facility fully funded by the U.S. National Science Foundation.

Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the U.S. National Science Foundation.