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Using ocean observatories to support NASA satellite ocean color objectives

Using ocean observatories to support NASA satellite ocean color objectives. Jeremy Werdell NASA Goddard Space Flight Center Ocean Observatories Workshop Ocean Optics XXI Conference 7 Oct 2012. outline. great field data enable great satellite data products

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Using ocean observatories to support NASA satellite ocean color objectives

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  1. Using ocean observatories to support NASA satellite ocean color objectives Jeremy Werdell NASA Goddard Space Flight Center Ocean Observatories Workshop Ocean Optics XXI Conference 7 Oct 2012

  2. outline great field data enable great satellite data products an abundance of field data is hard to come by ocean observatories can provide rich data streams QA/QC metrics are essential (or this all falls apart) PJW, NASA, 7 Oct 2012, OOW @ OO2012

  3. NASA Ocean Biology & Biogeochemistry Program field work funded by OBB Program QA/QC by data contributor by NASA in situ data submitted to NASA SeaBASS (GSFC) within 1-year in situ data publicly released in situ data used to validate satellite data products & to develop / evaluate algorithms in situ used to calibrate satellite PJW, NASA, 7 Oct 2012, OOW @ OO2012

  4. SeaBASS @ http://seabass.gsfc.nasa.gov AOPs, IOPs, carbon stocks, CTD, pigments, aerosols, etc. continuous & discrete profiles; some fixed observing or along-track PJW, NASA, 7 Oct 2012, OOW @ OO2012

  5. outline great field data enable great satellite data products an abundance of field data is hard to come by ocean observatories can provide rich data streams QA/QC metrics are essential (or this all falls apart) PJW, NASA, 7 Oct 2012, OOW @ OO2012

  6. great field data enable great satellite data products satellite vicarious calibration (instrument + algorithm adjustment) satellite data product validation bio-optical algorithm development, tuning, & evaluation PJW, NASA, 7 Oct 2012, OOW @ OO2012

  7. satellite vicarious calibration S.W. Bailey, et al. “Sources and assumptions for the vicarious calibration of ocean color satellite observations,” Appl. Opt. 47, 2035-2045 (2008). PJW, NASA, 7 Oct 2012, OOW @ OO2012

  8. satellite data product validation: discrete match-ups SeaWiFS in situ Chl http://seabass.gsfc.nasa.gov/seabasscgi/beta/search.cgi S.W. Bailey and P.J. Werdell, “A multi-sensor approach for the on-orbit validation of ocean color satellite data products,” Rem. Sens. Environ. 102, 12-23 (2006). PJW, NASA, 7 Oct 2012, OOW @ OO2012

  9. satellite data product validation: population statistics Chl-a (mg m-3) Chesapeake Bay P.J. Werdell et al., “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Rem. Sens. Environ. 113, 1319-1330 (2009). PJW, NASA, 7 Oct 2012, OOW @ OO2012

  10. bio-optical algorithm development Rrs related to pigments, IOPs, carbon stocks, etc. what satellite sees what you might want to study PJW, NASA, 7 Oct 2012, OOW @ OO2012

  11. outline great field data enable great satellite data products an abundance of field data is hard to come by ocean observatories can provide rich data streams QA/QC metrics are essential (or this all falls apart) PJW, NASA, 7 Oct 2012, OOW @ OO2012

  12. an abundance of field data is hard to come by spatial & temporal distributions “complete” suites of measurements (Rrs, IOPs, biogeochemistry) PJW, NASA, 7 Oct 2012, OOW @ OO2012

  13. SeaBASS @ http://seabass.gsfc.nasa.gov PJW, NASA, 7 Oct 2012, OOW @ OO2012

  14. SeaBASS holdings by year: 2006-2009 2006 2007 2009 2008 PJW, NASA, 7 Oct 2012, OOW @ OO2012

  15. satellite data product validation: discrete match-ups S.W. Bailey and P.J. Werdell, “A multi-sensor approach for the on-orbit validation of ocean color satellite data products,” Rem. Sens. Environ. 102, 12-23 (2006). PJW, NASA, 7 Oct 2012, OOW @ OO2012

  16. SeaBASS @ http://seabass.gsfc.nasa.gov PJW, NASA, 7 Oct 2012, OOW @ OO2012

  17. coincident SeaWiFS & in situ data PJW, NASA, 7 Oct 2012, OOW @ OO2012

  18. valid SeaWiFS-in situ match-ups PJW, NASA, 7 Oct 2012, OOW @ OO2012

  19. bio-optical algorithm development data sets Rrs Rrs & Chl Rrs & Chl & absorption & backscattering Rrs & Chl & absorption PJW, NASA, 7 Oct 2012, OOW @ OO2012

  20. bio-optical algorithm development data sets PJW, NASA, 7 Oct 2012, OOW @ OO2012

  21. new missions, new requirements • new missions • VIIRS: launched Oct 2011, viable data Feb 2012 • OLCI (Europe), SGLI (Japan): scheduled for CY12, CY15 • PACE: scheduled for CY19 • ACE, GEO-Cape: scheduled for ~CY23 • dynamic range of problem set is growing • emphasis on research in shallow, optically complex water • emphasis on “new” products (carbon, rates, etc.) • spectral domain stretching to UV and SWIR • immediate, operational requirements PJW, NASA, 7 Oct 2012, OOW @ OO2012

  22. outline great field data enable great satellite data products an abundance of field data is hard to come by ocean observatories can provide rich data streams QA/QC metrics are essential (or this all falls apart) PJW, NASA, 7 Oct 2012, OOW @ OO2012

  23. depth latitude longitude moving forward: community innovations AERONET (fixed-above water platforms) buoy networks towed & underway sampling gliders, drifters, & other autonomous platforms PJW, NASA, 7 Oct 2012, OOW @ OO2012

  24. validation exercises with autonomous data AERONET-OC match-ups with VIIRS (data since Feb 2012) PJW, NASA, 7 Oct 2012, OOW @ OO2012

  25. outline great field data enable great satellite data products an abundance of field data is hard to come by ocean observatories can provide rich data streams QA/QC metrics are essential (or this all falls apart) PJW, NASA, 7 Oct 2012, OOW @ OO2012

  26. QA/QC metrics are essential a single entity (e.g., NASA or equivalent) cannot collect sufficient volumes of in situ data to satisfy its operational calibration & validation needs following, flight projects rely on multiple entities to collect in situ data robust protocols for data collection & QA/QC ensures measurements are of the highest possible quality – well calibrated & understood, properly & consistently acquired, within anticipated ranges robust QA/QC provides confidence in utility & quality of data PJW, NASA, 7 Oct 2012, OOW @ OO2012

  27. QA/QC metrics are essential QA/QC methods vary in maturity – exist for many established instruments & platforms, but not always for newer or autonomous systems where do we want to be in 10 years? QA/QC methods are ideal when: they accommodate routine time-series reprocessing they are well documented they consistently maintain consensus from vendor  institution  end user revisited by subject matter experts routinely recommend invested agencies/institutions facilitate routine activities (workshops, round robins, inter-comparisons) to revisit QA/QC protocols PJW, NASA, 7 Oct 2012, OOW @ OO2012

  28. a recent QA/QC workshop Consortium for Ocean Leadership (COL) & NASA hosted an oceanographic QA/QC workshop in Jun 2012 at the U. Maine Darling Marine Center 25 attendees, 16 institutions, 4 countries (US, Australia, France, Canada) expertise in a wide variety of oceanographic measurements & platforms (bio-optics, hydrography, buoys, gliders, ARGO floats, fixed platforms, etc.) COL goals: review & revise Ocean Observatories Initiative (OOI) data plan NASA goals: interact with OOI & subject matter experts to collectively improve QA/QC methods for autonomously collected bio-optical data PJW, NASA, 7 Oct 2012, OOW @ OO2012

  29. a recent QA/QC workshop topics of discussion: system-level QA/QC approaches (vs. sensor-level) centralized versus distributed approaches levels of QA/QC and associated effort (workforce) required laboratory instrument inter-calibration & verification at-sea instrument inter-calibration detection of slow drifts against large background variability bio-fouling: susceptibility, mitigation, identification, correction utilizing external (field or remote) observations workshop report: presents recommendations, identifies state-of-the-art available at http://oceancolor.gsfc.nasa.gov/DOCS PJW, NASA, 7 Oct 2012, OOW @ OO2012

  30. a recent QA/QC workshop http://www.wordle.net PJW, NASA, 7 Oct 2012, OOW @ OO2012

  31. questions & comments? PJW, NASA, 7 Oct 2012, OOW @ OO2012

  32. Chesapeake Bay Program satellite data product validation: population statistics http://www.chesapeakebay.net routine data collection since 1984 12-16 cruises / year 49 stations 19 hydrographic measurements algal biomass water clarity dissolved oxygen others PJW, NASA, 7 Oct 2012, OOW @ OO2012

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