Ozflux Portal Presentation


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TERN Symposium 2011

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  • Screen shot of RTMC display on dial-up PC at Monash to demonstrate near-real time display of site data for quality control.
    Play button launches Ultra-VNC viewer (will need to change app for Ubuntu). If PC has an internet connection and a Monash digital certificate, this will allow a VNC session to the dial-up PC to demonstrate access to sites for monitoring and control.
  • Screen shot of Sturt Plains flux data displayed in browser window to demonstrate ability to display site data in near-real time to a wide audience.
    Play button starts FireFox and loads Sturt Plains web page.
  • ASCII files of 30 minute average data are manually collated into a L1 spreadsheet. This process could be easily automated but making site operators do this step manually forces them to look at their data at least once a month.
    Subsequent quality control and post-processing steps are done by a collection of Python scripts. The general model is batch-oriented, semi-interactive. The design philosophy was to combine the best features of humans (great pattern recognition but get bored easily) and computers (pattern recognition hard to do but they never get bored).
    netCDF chosen as the file type so that meta-data is stored with the data and the file is fully self-documenting. If I give you a netCDF file from this process and you can read netCDF files then you will know everything that has been done to the data during quality control and post-processing.
    Submission of L3 netCDF files to the OzFlux DMS satisfies contract obligation to supply data. Submission to DMS automatically publishes meta-data of the data set and a URL pointing to the data set on the ANDS web site.
  • Play button has hyperlink to OzFlux DMS via FireFox browser.
    Click on button during presentation, login and demonstrate creation of data collection, upload and download of data and automatic publishing of data to ANDS web site.
  • Ozflux Portal Presentation

    1. 1. OzFlux: The Australian flux and ecosystem research network Data Path, Access and Publication Presentation by Dr Peter Isaac, Dr Jason Beringer, Dr Eva van Gorsel and Dr Helen Cleugh
    2. 2. Knowledge of ecosystem water and carbon cycles Surface fluxes Radiation Meteorology Soil properties Ecosystem dynamics Spatial and temporal dynamics Continental & global budgets Vegetation type Leaf area index Gross primary product Soil moisture Hyperspectral Flux tower network Remote sensing Land surface models Site characteristics Biomass Soil carbon & nutrients Leaf-level photosynthesis Intensive field campaigns
    3. 3. 10-3 10-2 10-1 100 101 102 103 104 metres Length Scale 10-1 100 101 102 103 104 105 106 Leaf Canopy Patch Region Seconds Minutes Days Years seconds Leaf Level Observations Flux Tower Aircraft Fluxes Aircraft Remote Sensing Satellite Remote Sensing Land Surface Model GCM Plot Level Observations Leaf Level Physiology assumed to apply Time Scale Direct measurement Indirect measurement (remote sensing) Modelling
    4. 4. OzFlux Data Types • Turbulence (u’,v’,w’,T’,q’,c’) – Sampled and stored at 10 Hz (“fast”), retrieved ~monthly – Wind components, temperature, water vapour and CO2 concentration • Meteorological (T,RH,WS,WD,Fsd,Tsoil,Rain etc) – Sampled at 0.1 Hz (“slow”), stored as 30 minute averages, retrieved ~daily – Wind speed, direction, temperature, relative humidity, soil temperature, soil moisture, rainfall, CO2 and H2O profiles • Ancillary – Sampled and stored as required (~daily to monthly) – Leaf area index, soil properties, vegetation morphology • Intensive campaign – Sampled and stored as required (~1 – 2 yearly) – Photosynthetic properties, above and below ground biomass, soil carbon, etc
    5. 5. u’, v’, w’, T’ q’,c’ WS, WD, T, RH Fsd, Fsu, Fld, Flu Fg, Sws, Tsoil Rain 10 Hz 0.1 Hz Fast (10 Hz raw) Slow (30 minute average) CR3000 data logger Slow (30 minute average) Fast (10 Hz) (optional with ethernet modem) Modmax modem CF card OzFlux Data Path: Tower
    6. 6. OzFlux Tower Data Output • Average data (30 or 60 minute, ASCII files) – surface fluxes • momentum (Fm), sensible heat (Fh), latent heat (Fe), carbon dioxide (Fc) – solar and terrestrial radiation • incoming & outgoing shortwave (Fsd & Fsu), incoming and outgoing longwave (Fld & Flu), net allwave (Fn) – meteorology • air temperature (T), relative humidity (RH), wind speed and direction (WS & WD) – soil • soil temperature (Tsoil), soil moisture (Sws), ground heat flux (Fg)
    7. 7. OzFlux Data Path: Real Time Display Wombat State Forest Victoria Requires digcert for access to dialup PC at Monash
    8. 8. Sturt Plains Northern Territory OzFlux Data Path: Web Display
    9. 9. OzFlux Data Path: Processing CF card modem manual collection “slow” data 30 min. avg ASCII files Collate L1 spreadsheet L1 netCDF Quality control Convert & subset L2 netCDF Post- processing L3 netCDF Manual Python Python Python OzFlux DMSWWW Batch-oriented processing Consistent across all sites Submission to DMS via web Automatic publishing from DMS to ANDS rif-cs
    10. 10. OzFlux Data Management System
    11. 11. OzFlux Network Example • 9 sites with data collection by modem • 1/11/2010 to 7/11/2010 inclusive • Basic QC only (not rotated, no gap fill, no u* threshold) • Incoming shortwave (Fsd, yellow) • sensible heat (Fh, red) • latent heat (Fe, blue) • Net ecosystem exchange (Fc, green)
    12. 12. Acknowledgements ARC ACCSP DCCEE Bushfire CRC TRaCK CSIRO James Cook University Queensland University of Technology Monash University University of Melbourne Forestry Tasmania University of Adelaide Charles Darwin University University of Technology, Sydney The University of Sydney University of Waikato, NZ Landcare Research, NZ