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. 6th annual NEON Surface Atmosphere Exchange Workshop | AGU 2019

Workshop

6th annual NEON Surface Atmosphere Exchange Workshop | AGU 2019

American Geophysical Union Annual Meeting

December 11, 2019

Share

Continuing a tradition, we present the 6th annual NEON Surface Atmosphere Exchange Workshop at the 2019 AGU Fall Meeting. There have been many developments in the last year, including:

  • 900 additional site-months of eddy-covariance data are available from NEON’s Data Portal;
  • All NEON flux data holdings have been submitted to AmeriFlux;
  • New eddy4R functionalities provide additional data quality information;
  • All NEON data products required for energy balance calculation are now available in the bundled eddy covariance HDF5 file;
  • neonUtilities R package provides functinality to easily interact with the eddy covariance HDF5 files;
  • New tutorials and other training materials for working with NEON data;
  • Publications on the NEON system design (Metzger et al. 2019) and the eddy covariance storage term (Xu et al. 2019).

We will explore these NEON SAE resources and solicit input to guide development of NEON SAE community resources for 2020. Additionally, the workshop offers hands-on tutorials for working with eddy-covariance and other NEON data.

 

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 is limited to 40 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

  • TBD based on feedback from the registration form

 

Schedule

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

Date: Wednesday December 11th from 7:00-9:30 PM PT (local time)

Below is a sample schedule from 2018. Exact topics and timing will be determined by participant feedback.

Time Topic
18:30 Help desk and room set up
19:00 Welcome & Introductions
19:15 Lightning talks: community use and applications of interest
19:35 Break
19:50 Breakout Groups
Tutorial: Interactive (basic) eddy4R in CyVerse Discovery Environment
Discussion: Scale-aware flux data products and integration with remote-sensing data
Discussion: Fusing flux data with other data products
Discussion: QAQC routines for EC and Met
21:15 Breakout summary, next steps, and debrief

Organizers

  • David Durden - National Ecological Observatory Network, Battelle
  • Natchaya Durden - National Ecological Observatory Network, Battelle
  • Chris Florian - National Ecological Observatory Network, Battelle
  • Hongyan Luo- National Ecological Observatory Network, Battelle
  • Stefan Metzger - National Ecological Observatory Network, Battelle

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

Example from 2018 - will be updated for 2019 based on participant suggestions.

Time Topic Lead
18:30 Help desk and room set up
19:00 Welcome & Introductions
History of NEON SAE meeting at AGU
Recent developments: Outcomes of previous AGU meetings & structure of DevOps approach
Goals & expectations
Workshop structure
19:15 Brief community presentations on utilizing or synergizing with NEON SAE resources
Introduction to NEON data and usability tools
New budgeting approach reveals source of terrestrial carbon uptake overestimation
Flux data fusion for ecosystem understanding–flux fusion
Developing end-to-end QAQC routines for flux observations – Intro to Tovi
Developing end-to-end QAQC routines for flux observations – Intro to openeddy
19:35 Break
19:50 Breakout Groups
Tutorial: Getting started with eddy4R hand-on tutorial
Discussion: Scale-aware flux data products and integration with remote-sensing data
Discussion: Fusing flux data with other data products
Discussion: QAQC routines for EC and Met
21:15 Breakout summary, next steps, and debrief

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.