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 SeaDAS Training ~ NASA Ocean Biology Processing Group

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

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

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

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

MODIS instrument design SeaDAS Training ~ NASA Ocean Biology Processing Group

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

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

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

Lunar calibration SeaDAS Training ~ NASA Ocean Biology Processing Group

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

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

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

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

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

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

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

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

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

Vicarious calibration SeaDAS Training ~ NASA Ocean Biology Processing Group

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

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

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

Introduction to ocean color satellite calibration

Introduction to ocean color satellite calibration

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