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  4. 5th annual NEON Surface Atmosphere Exchange Workshop | AGU 2018

Workshop

5th annual NEON Surface Atmosphere Exchange Workshop | AGU 2018

American Geophysical Union Annual Meeting

December 11, 2018

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Continuing a tradition, we present the 5th annual NEON Surface Atmosphere Exchange Workshop at the 2018 AGU Fall Meeting. There have been many developments in the last year, including:

  • 19 eddy-covariance data products available from NEON’s Data Portal;
  • 14 NEON sites registered with AmeriFlux, data submission imminent;
  • Publicly available code packages on GitHub;
  • Tutorials and other training materials for working with NEON data;
  • Development and Operations framework for direct community input.
We will explore these NEON Surface Atmosphere Exchange resources and solicit input to guide development of NEON SAE community resources for 2019. Additionally, the workshop offers hands-on tutorials utilizing eddy4R vignettes in a cloud-computing environment.
 

Workshop Goals

  • Explore these NEON SAE resources
  • Solicit input to guide development of NEON SAE community resources for 2019
  • Test CyVerse cloud compute environment for hosting code tutorials
  • Provide a forum to discuss important topics in the SAE community, with the hope to answer the following three questions:
    • What are the goals the breakout groups suggest?
    • What can the community do to achieve goals?
    • How can NEON help achieve goals?

Before attending the workshop, please read about the eddy4R package:

Metzger, S., Durden, D., Sturtevant, C., Luo, H., Pingintha-Durden, N., Sachs, T., Serafimovich, A., Hartmann, J., Li, J., Xu, K., and Desai, A. R.: eddy4R 0.2.0: a DevOps model for community-extensible processing and analysis of eddy-covariance data based on R, Git, Docker, and HDF5, Geosci. Model Dev., 10, 3189-3206, doi:10.5194/gmd-10-3189-2017, 2017.

Schedule

Location: Hilton Garden Inn, 815 14th Street, NW, Washington, DC; Georgetown C

Date: Tuesday December 11th from 7:00-9:30 PM ET

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
  • Chris Florian - National Ecological Observatory Network
  • Natchaya Durden - National Ecological Observatory Network
  • Cove Sturtevant- National Ecological Observatory Network
  • Stefan Metzger - National Ecological Observatory Network

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

Schedule

| Time | Topic | Lead | |-------------|---------------| | 18:30 | Help desk and room set up| | | 19:00 | Welcome & Introductions| Dave, Stefan, Chris | | | 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 | Chris | | | New budgeting approach reveals source of terrestrial carbon uptake overestimation | Anne Griebel | | | Flux data fusion for ecosystem understanding–flux fusion | Bijan Seyednasrollah| | | Developing end-to-end QAQC routines for flux observations – Intro to Tovi | Gerardo Fratini | | | Developing end-to-end QAQC routines for flux observations – Intro to openeddy | Ladislav Sigut | | 19:35 | Break| | | 19:50 | Breakout Groups| | | | Tutorial: Getting started with eddy4R hand-on tutorial | Dave | | | Discussion: Scale-aware flux data products and integration with remote-sensing data | Stefan & Anne | | | Discussion: Fusing flux data with other data products | Chris & Natchaya | | | Discussion: QAQC routines for EC and Met | Cove | | 21:15 | Breakout summary, next steps, and debrief | Stefan |

Discussion Outcomes

Tutorial: Getting started with eddy4R hands-on tutorial

  • Eddy4R vignette was run in the CyVerse Discovery Environment
  • The CyVerse Discovery Environment worked well for learning 
  •  Participants also interest in NEON EC data exploration vignette for usability tools 

Discussion: Scale-aware flux data products and integration with remote-sensing data

Discussion centered around several goals:

  • Provide simple/little processed data products
  • How to use remote sensing and flux tower data together, e.g. to explain the impact of management practices using eddy covariance network footprints together with remote sensing map?
  • Flux budgets that are spatio-temporally representative at the scale of remote-sensing/modeling data; impact of such equitable fluxes on energy balance; possibility to apply to gap-filling.
  • Space-time resolved flux (state variable?) maps around flux towers, to use together e.g. with point-based measurements, remote sensing data etc. for value-added or derived data products.

Discussion: Fusing flux data with other data products

Discussion centered around mostly on how NEON could help facilitate data fusion, such as:

  • Improvements to discoverability of NEON API information.
  • Usability tools for NEON EC HDF5 data.
  • Flux partitioned data products.
  • Working toward easy integration with outside data products including OCO3 satellite NEON site cutouts and Phenocam derived products (greenness).

Discussion: QAQC routines for EC and Met

Discussions centered around addressing the following:

  • What are the tendencies of a QC test to remove certain kinds of data. Where does it do well? Where does it fail? What are the systematic problems with specific tests at certain site types.
  • Can we develop a scheme for all sites, or how do sites need to be characterized to know what tests are applicable (e.g. forests, tall tower, etc?). How about developing a decision tree for what tests to employ, given the measurement and site type.
  • Define a metric that characterizes the efficiency of QC tests. Efficiency is defined as the balance between the amount of removed data compared to how much that loss of data increases uncertainty.
  • What variables do we need to be reporting? e.g. wbar residual for planar fit. Need to balance amount of variables reported with needs for QC. Don't want data deluge.

The group thought that the community could perform the analysis and NEON could help by providing the standardized data to perform the analysis.

Meeting Notes

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Presentations

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