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Introduction to ocean color satellite calibration

Introduction to ocean color satellite calibration. NASA Ocean Biology Processing Group Goddard Space Flight Center, Greenbelt, Maryland, USA SeaDAS Training Material. Ocean color calibration. scope of the calibration paradigm:

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Introduction to ocean color satellite calibration

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  1. Introduction to ocean color satellite calibration NASA Ocean Biology Processing Group Goddard Space Flight Center, Greenbelt, Maryland, USA SeaDAS Training Material SeaDAS Training ~ NASA Ocean Biology Processing Group

  2. Ocean color calibration • scope of the calibration paradigm: • to meet the accuracy goals, top-of-the-atmosphere radiances need to have uncertainties lower than 0.5% • uncertainties are present in • * instrument characterization and calibration • * atmospheric and in-water data processing algorithms SeaDAS Training ~ NASA Ocean Biology Processing Group

  3. Instrument calibration stages • direct calibration • pre-launch: sensor is calibrated in a laboratory (thermal vacuum) • on-orbit: regular solar, deep-space, and lunar observations track changes in sensor response (possible additional on-board calibrators) • vicarious calibration • on-orbit: force instrument + atmospheric correction system to agree with sea-truth data (e.g., in situ measurements) SeaDAS Training ~ NASA Ocean Biology Processing Group

  4. Elements of instrument operation photons to data each stage in this sequence contributes to uncertainties every element needs: to be well characterized its calibration parameters derived radiant source (Earth surface and atmosphere) scanning mirror calibrators optics (aperture, mirrors, beam splitters, objectives) filters detectors electronics analog to digital (A/D) converters data formatters and data recorders ground receiving antenna digital count to radiance conversion SeaDAS Training ~ NASA Ocean Biology Processing Group

  5. Example sensor specifications • SeaWiFS (12 noon descending orbit) • Rotating telescope • 8 bands: 412, 443, 490, 510, 555, 670, 765, 865 nm • 12 bit digitization truncated to 10 bits on spacecraft • 4 focal planes, 4 detectors/band, 4 gain settings, bilinear gain configuration • Polarization scrambler: sensitivity at 0.25% level (for fully polarized light) • Solar diffuser (SD) daily observations • Monthly lunar views at 7° phase angle via pitch maneuvers • MODIS-Aqua (1:30 pm ascending orbit) • Rotating mirror • 9 OC bands: 412, 443, 488, 531, 551, 667, 678, 748, 869 nm • 12 bit digitization • 2 VIS-NIR focal planes, 10 to 40 detector arrays depending on band resolution, 0.25 to 1 km • No polarization scrambler: sensitivity up to 6% at 412 nm • Spectral Radiometric Calibration Assembly (SRCA) • Solar diffuser (observations every two weeks), Solar Diffuser Stability Monitor (SDSM) • Monthly lunar views at 55° phase angle via space view port • NPP/VIIRS (1:30 pm descending orbit) • SeaWiFS-like rotating telescope • MODIS-like focal plane arrays • No polarization scrambler • Solar diffuser with stability monitor • 7 OC bands: 412, 445, 488, 555, 672, 746, 865 nm differences in sensor design differences in orbits SeaDAS Training ~ NASA Ocean Biology Processing Group

  6. MODIS instrument design SeaDAS Training ~ NASA Ocean Biology Processing Group

  7. MODIS pre-launch characterization concerns mirror degradation, response vs. scan-angle (RVS), two mirror sides detector calibration changes polarization sensitivity in-band and out-of-band response instrument and focal plane temperature effects electronic cross-talk stray-light contamination solar diffuser stability • solar diffuser characterization • bidirectional reflectance factor (BRF) impact on calibration • Earth shine effect – sunlight reflecting off the Earth and onto the diffuser and adding to the solar irradiance • attenuation screen characterization through vignetting function • SDSM uncertainty in monitoring SD reflectance changes • stray-light contamination • photons in the optical path from Earth coming from bright sources, i.e. clouds, land, and sun glitter (characterized by point spread function) SeaDAS Training ~ NASA Ocean Biology Processing Group

  8. Solar calibration * MODIS solar diffuser calibrations performed at the Pole every 2 weeks * North Pole for Terra and South Pole for Aqua * at the dark side of the terminator to limit the stray light entering the instrument SeaDAS Training ~ NASA Ocean Biology Processing Group

  9. Lunar calibration Moon acts as an external diffuser Moon is viewed at specific lunar phase angles SeaDAS Training ~ NASA Ocean Biology Processing Group

  10. Lunar calibration SeaDAS Training ~ NASA Ocean Biology Processing Group

  11. Direct calibration uncertainty limits MODIS absolute radiometric accuracy reflective solar bands (0.41–2.1m): ±2% in reflectance and ±5% in radiance MODIS relative accuracy over time reflective solar bands (0.41–2.1m): ±0.2% in reflectance SeaDAS Training ~ NASA Ocean Biology Processing Group

  12. Vicarious calibration approach on-orbit calibration temporal change through the mission vicarious calibration single radiometric gain adjustment calibration of the combined instrument + algorithm system NIR band calibration NIR band calibration SeaDAS Training ~ NASA Ocean Biology Processing Group

  13. Criteria for vicarious calibration cloud-free air mass with low optical thickness (e.g., AOT(865) < 0.1) spatially homogeneous Lw() ~ or, Lw(NIR) = 0 for NIR calibration) limited solar and sensor geometries, wind speed, stray-light and glint contamination VIS calibration NIR calibration SeaDAS Training ~ NASA Ocean Biology Processing Group

  14. SATELLITE Lttarget TOP OF ATMOSPHERE from the satellite + Lr , td , … TARGET Criteria for vicarious calibration SeaDAS Training ~ NASA Ocean Biology Processing Group

  15. NIR vicarious calibration provides a relative calibration between the two NIR bands based on assumptions of the most probable maritime atmosphere NIR{ assumptions open ocean is black in the NIR, i.e. Lw(748) and Lw(869) = 0 vicarious gain of band 869-nm is fixed at 1 based on on-orbit calibration only maritime aerosol with 90% humidity (M90) is chosen over the calibration sites band 869-nm defines the amount of aerosol, AOT(869) aerosol radiance is tabulated for M90 and any geometry SeaDAS Training ~ NASA Ocean Biology Processing Group

  16. Lw( , 0 ) cos( 0 ) t( , 0 ) Visible band vicarious calibration the Marine Optical Buoy (MOBY) alternatives: ocean surface reflectance model alternative buoy accumulated field campaigns SeaDAS Training ~ NASA Ocean Biology Processing Group

  17. Vicarious calibration locate L1A files extract 101x101 pixel box process to L2 target data extract 5x5 box SeaDAS Training ~ NASA Ocean Biology Processing Group

  18. Vicarious calibration locate L1A files extract 101x101 pixel box process to L2 target data extract 5x5 box limit to scenes with average values: < 0.20 Ca < 0.15 (865) < 60 sensor zenith < 75 solar zenith identify flagged pixels: LAND, CLDICE, HILT, HIGLINT, ATMFAIL, STRAYLIGHT, LOWLW require 25 valid pixels calculate gpixel for each pixel in semi-interquartile range; then: gscene = gpixel / npixel • calculate gains for each matchup SeaDAS Training ~ NASA Ocean Biology Processing Group

  19. Vicarious calibration locate L1A files extract 101x101 pixel box process to L2 target data extract 5x5 box limit to scenes with average values: < 0.20 Ca < 0.15 (865) < 60 sensor zenith < 75 solar zenith identify flagged pixels: LAND, CLDICE, HILT, HIGLINT, ATMFAIL, STRAYLIGHT, LOWLW require 25 valid pixels calculate gpixel for each pixel in semi-interquartile range; then: gscene = gpixel / npixel • calculate gains for each matchup • calculate final, average gain limit to gscene within semi-interquartile range visually inspect all scenes g = gscene / nscene SeaDAS Training ~ NASA Ocean Biology Processing Group

  20. Vicarious calibration SeaDAS Training ~ NASA Ocean Biology Processing Group

  21. Vicarious calibration SeaDAS Training ~ NASA Ocean Biology Processing Group

  22. Vicarious calibration SeaDAS Training ~ NASA Ocean Biology Processing Group

  23. Vicarious calibration changes in g with increasing sample size … standard error of g decreases to 0.2% overall variability (min vs. max g) approaches 0.5% provides insight into temporal calibration, statistical choices SeaDAS Training ~ NASA Ocean Biology Processing Group

  24. Vicarious calibration future ruminations … … statistical and visual exclusion criteria influence g only slightly, yet … they reduce the standard deviations … can uncertainties be quantified … for the assigned thresholds? … how do the uncertainties of the embedded models (e.g., f / Q, the NIR- … correction, etc.) propagate into the calibration? … what are the uncertainties associated with Lwtarget? SeaDAS Training ~ NASA Ocean Biology Processing Group

  25. Vicarious calibration references Franz et al., Appl. Opt.(2007) ~ vicarious calibration approach, using MOBY Werdell et al., Appl. Opt. (2007) ~ vicarious calibration using an ocean surface reflectance model Bailey et al., Appl. Opt. (in press) ~ vicarious calibration using alternative in situ data sources (e.g., NOMAD, BOUSSOLE) SeaDAS Training ~ NASA Ocean Biology Processing Group

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