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BAS & Equadratures Workshop | 1 Dec 2022

Zoom: https://turing-uk.zoom.us/j/94968554438?pwd=TzJPczIvRnJHVjlFNUZ6TVIrTnlQUT09&from=addon

Agenda

  • Introductions
  • Progress update - (Peter: here are my slides)
  • Deployment Opportunities before March 2023
  • Next Steps

Attendees

  • Scott
  • James
  • Steve
  • Peter
  • Jen
  • Hari

Meeting Notes

  • Presentation Notes
    • If we have a good interpolating model for direct sun, we can use this for zenith sun (relate zenith observables to actual ozone that could have been measured with direct sun)
    • Data processing/challenges
      • Minute resolution, missing data, noise
      • Springtime depletion (southern hemisphere)
    • Set up simplest model - binning observation by month (for 8 months of measurement)
      • Generally not a ton of spread besides month 11
      • Introducing annual feature
      • Combo of GPs
      • Slide 5: Blue is the error (95% confidence interval)
      • SH: we can potentially find other info to lower error
        • SC: not sure because even satellites can't data because they rely on reflective sunlight
        • SH: maybe some balloon data? this is where AI can help to blend in datasets together
    • Discussion:
      • maybe a better fit to start the year in May?
      • Questions about tightening priors, bin to daily (does daily or weekly ozone make more sense?), transforms
    • SH comments
      • Setting of year boundaries starting Jan doesn't make sense re: atmospheric chemistry. Ozone season?
      • SC: No measurements from May - August because there is no sunlight and it can't work in the dark; stay clear of May and September
        • Perhaps 1 July or 1 August as starting point (June, July or August)
      • Minute binning feels very high; there is a potential cycle within the day - is daily averaging too coarse?
        • SC: direct sun measurements are manual measurement and there are 5-10 of those a day (Auto Dobson is every 5 min)
        • SC: maybe better to compare direct sun measurements with Auto Dobson at the same time (rather than a daily average)
        • Currently two equations (1. high sun 2. low sun)
        • **SC: what we're hoping to get from the AI is to get 10-20 zenith equations depending on the sun angle (and process using computer rather than by hand)
  • Next Steps**
    * SC: ozone layer moves around and changes throughout the day, so looking at individual observations
    * SC: there should be same moment between a few minutes (should be around the same amount of Ozone)
    * PY: instead of annual, focus on resolving on a space of an hour
    * SC: Need to get down to specific observations and find the right equation based on mu value; we see a step change in the data right now because of where we change equations
    * PY: Where are models for Zenith coming from?
    * SC: trial and error trying different models over time to get zenith/direct to match; 3rd, 4th, 5th order polynomials
    * Angle of sun has a big effect because of scattering
    * PY: are location important? should be fine to have a few km different; all measurements in this dataset taken from Halley station
    • Next steps:
      • Peter visits BAS to see Dobson - to schedule
        • Ideally Monday or Friday when Jonathan is there
        • SC: maybe one day before Christmas and then a few days in January (e.g. Mon, Tue, Wed)?
      • Start with GP; using equadratures
      • ASG end in March 2023
        • SC: If we can come up with new Zenith equations to apply to auto-dobson data for past 3 winters, we could reprocess the data with new equations for more accurate measurements (this data is available online and labeled as provisional)
        • SH: Another potential option is to provide model online? Through a different website?
        • JB: BAS PR - if we are able to move towards demonstrating BAS automation efforts (not just progress on the science side)
        • SH: internal toy experiment: build a system - compare what's going online from Auto Dobson against model data
          • Potential pipeline: integrate Peter's model data to this?
          • Trustworthy AI
        • JB: Pipelines/automation - loop in James when it's becoming more important to create a robust implementation (data delivery/APIs)
          • SC: Tim Barnes may be the right person to speak to for automation (rather than someone coming in every week to process)