Bloomcast - Python Facilitating Operational Oceanography (Doug Latornell)

Bloomcast - Python Facilitating Operational Oceanography (Doug Latornell)

Bloomcast is a daily prediction of the beginning of the aquatic growing season in the Strait of Georgia. Python makes it possible by collecting meteorological and river flow data, running a Fortran code, analyzing its results, and publishing the prediction to the web - all while I sleep.

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PyCon Canada

August 10, 2013
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Transcript

  1. Bloomcast: Python Facilitating Operational Oceanography Doug Latornell @djlatornell Dept of

    Earth, Ocean & Atmospheric Sciences University of British Columbia
  2. Operational Oceanography ???

  3. Operational Meteorology Weather Forecasts

  4. • Run Daily-ish • Driven by Most Current Available Real-World

    Data Operational Model:
  5. Bloomcast: Python Facilitating Operational Oceanography

  6. Bloomcast ???

  7. • Run SOG Model Daily • Forced by Weather and

    River Flows • Predict Date of 1st Spring Phytoplankton Bloom in the Strait of Georgia Bloomcast:
  8. None
  9. http://www.fields.utoronto.ca/video-archive/static/2013/06/166-1777/mergedvideo.ogv

  10. None
  11. Bloomcast: Python Facilitating Operational Oceanography

  12. Python !!!

  13. FORTRAN codes are the idiot savants of the modern software

    world SOG is in FORTRAN
  14. SOG YAML Requests ElementTree BeatifulSoup Logging (SMTP Handler) Colander Subprocess

    NumPy Matplotlib Mako cron rsync
  15. SOG YAML Requests ElementTree BeatifulSoup Logging (SMTP Handler) Colander Subprocess

    NumPy Matplotlib Mako cron rsync
  16. Requests

  17. SOG YAML Requests ElementTree BeatifulSoup Logging (SMTP Handler) Colander Subprocess

    NumPy Matplotlib Mako cron rsync
  18. SOG YAML Requests ElementTree BeatifulSoup Logging (SMTP Handler) Colander Subprocess

    NumPy Matplotlib Mako cron rsync
  19. http://www.eos.ubc.ca/~sallen/SoG-bloomcast/results.html

  20. 2013 was bloomcast’s 2nd year in production 2012: • Cloud

    fraction interpolation problem • Bloom date agreed with satellite and cruise chlorophyll data 2013: • New Cloud fraction interpolation algorithm (thanks to Requests and NumPy) • Bloom date agreed with satellite and chlorophyll data from an instrumented ferry
  21. Future: • Operational deployment of SOG to do daily calculation

    of productivity in Strait of Georgia year-round • SOG in the Gulf of St. Lawrence ◦ GSL-bloomcast, GSL-productivity ?? • Bloomcast 2014 and onward
  22. Allen, S.E. and M.A. Wolfe. Hindcast of the timing of

    the spring phytoplankton bloom in the Strait of Georgia, 1968-2010. Progress in Oceanography. Volume 115, Pages 6-13, 2013. http://dx.doi.org/10.1016/j.pocean.2013.05.026 Collins, A.K., S.E. Allen, and R. Pawlowicz. The role of wind in determining the timing of the spring bloom in the Strait of Georgia. Canadian Journal of Fisheries and Aquatic Sciences, Volume 66, Pages 1597-1616, 2009. http://www.nrcresearchpress.com/doi/abs/10.1139/f09-071 J.R. Irvine, J.R., W.R. Crawford. State of physical, biological, and selected fishery resources of Pacific Canadian marine ecosystems in 2012. Fisheries and Ocean Canada Research Document - 2013/032. http://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs- DocRech/2013/2013_032-eng.html
  23. SOG YAML Requests ElementTree BeatifulSoup Logging (SMTP Handler) Colander Subprocess

    NumPy Matplotlib Mako cron rsync