advanced global imaging radiometer geophysical parameters pigment absorption phytoplankton carbon...
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Advanced Global Imaging Radiometer
Geophysical ParametersPigment absorptionPhytoplankton carbonNet primary productionExport productionDissolved Organic CarbonCDOM photochemistrySlope of CDOM absorptionParticulate Organic CarbonParticle size spectrumParticulate beam attenuationCarbon loading & dispersalSolar radiation & KdParticulate inorganic carbonFunctional groupsHABsEutrophication….others….
Objectives• Improved separation of in-water constituents through expanded spectral range and resolution• Improved atmospheric correction – aerosols, bright targets, ozone
Measurement Characteristics• LEO, 2-day global coverage, noon/sun-synchronous polar orbit• Minimum 20 aggregated wavebands 350 – 1400 nm, +ozone band• 1 km spatial resolution• SNR 1500:1 (UV) to ~ 500 NIR• 200 tilt to minimize sun glint contamination• Polarization scrambler to minimize polarization sensitivity (tenths of a percent)• Minimal & well-characterized spectral response (in-band & out-of-band)• Minimal & well-characterized focal plane electronic cross-talk• Minimal & well-characterized stray light• Well-characterized response as a function of scan angle• Sequential sampling to minimize image stripping• No band saturation over bright targets• Solar and lunar on-orbit calibration• Complete sensor optical model• Data system for near real-time processing, distribution, algorithm evaluations, & periodic reprocessing.• Comprehensive calibration/validation program
Advanced Global Imaging Radiometer
Hyperspectral
• Multiple grating spectrometer
• 5 nm resolution from 350 to 800 nm
• Discrete bands from 800 to 1400 nm (20 – 50 nm bandwidth)
• On-board or post-download binning
• Full spectral download = 1 Tb science data per day
• 300 Mbps X-band transfer to polar ground station
• On-ground 20 nm binned data for standard global products
• High resolution data for regional applications, events, science development
Primary telescope
Aft Optics
Aerosols
Objective• Global characterization of absorbing aerosol properties (height, column thickness, species) in support of ocean science missions (global LEO, regional GEO, … etc)
Equivalent Aerosol Optical Depths
Spring Fall
Issues • Aerosol characteristics are source dependent Urban particular problem (coastal challenge) Dust significant over vast ocean regions Non-absorbing not a problem
• Seasonally and spatially varying Monitoring required
• Current atmospheric correction model does not achieve required accuracy (+/-0.002 reflectance units) without correct vertical distribution (assuming correct aerosol type)
• Atmospheric correction errors increase at shorter wavelengths, thus critical for effectively utilizing UV wavelengths
• Aerosol loads also link to land-atmosphere-ocean feedbacks
Measurement Characteristics (minimum)• Aerosol Heights to 0.5 km• Aerosol optical thickness range 0.05 to 1• 10 km horizontal resolution• 10% accuracy• Extrapolation to global fields • Aerosol absorption column optical depth
Aerosols
Aerosol Lidar(a) Vertical aerosol backscatter & extinction profiles(b) Layer-wise optical, microphysical, & macrophysical properties
(#/surf./vol. concentrations, eff. radius, complex index of refr., SSA)(c) Aerosol particle shape and cloud liquid/ice phase
Multi-Angle or Scanning Aerosol Spectropolarimeter (a) Column-average optical, microphysical, & macrophysical aerosol properties (AOD, particle sizes & shape, SSA, size-resolved real RI…)
(b) Tropospheric ozone to determine short- & long-term changes (c) Aerosol heights for ocean color correction (d) NO2, HCHO, O3 and SO2
MISR (image from David Diner)
GLAS (image from Jim Spinhirne)
Particle Profiler
CA
LIP
SO
’s C
AL
IOP
lida
rSpec’s• 2-wavelength, 3-channel (532, 532, 1064)• 110 mJ Nd:Yg laser • Repetition rate = 20.25 Hz• 1 m telescope• Footprint/FOV = 100m/130rad• Mass = 300 kg• Variable vertical resolution• Aerosol height & thickness for AOD > 0.005• Altitude = 600 km
Photons per 1 m bin per shot
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Depth Oligo Meso Maine
Similar to typical cirrus cloud
Objective• Active measurement of subsurface scattering as independent measure of particle abundance
Measurement Characteristics• Global survey coupled with passive ocean color measurements
• ‘Sampling’ of the mixed layer
• Dark- and Light-side measurements
• Eyesafe lidar with surface penetrating (e.g. 532 nm) and non-penetrating wavelengths (e.g., 1064 nm)
• > 15o tilt to avoid surface flash
• < 20 km resolution
• 1 – 2 m vertical resolution
• Minimum 2 vertical depth bins
• Can be same instrument as aerosol profiler
Particle Profiler
Lidar In-space Technology Experiment (LITE)
• 3-wavelength Nd-Yg lidar • Space Shuttle in 1994• Multi-angle (+/-300) maneuvers • Increased gain at higher angles
532 nm
High Gain HG
150 150
1064 nm
150 150
Low Gain
Off
-Nad
ir A
ngl
e
0
30
15
Time Time
Variable Fluorescence
Objective• Mapping & Monitoring Nutrient Regimes• Physiological Indices• Functional Groups
Measurement Characteristics• Midnight vs Dawn differences in Variable Fluorescence (Fv/Fm)
(two platforms)
• Distinguish Fv/Fm values between 0.05 and 0.65 to 0.05 units
• 10 – 30 km spatial resolution
• Water-penetrating stimulation (e.g., 532 nm), detection at 680 nm
• Spectral fluorescence detection (?)
• Eyesafe
Options• Lidar• Solar Power• Clouds• Fv/Fm or simply Fo?• Suborbital or Space?• ‘Pump-n-Probe’ or ‘Painting the Surface’ (LIFT)?
LIFT (image from Zbignew Kolber)
Mixed Layer Depth and Illumination
Objective• Time-resolved global mixed layer depths• Quantification of ocean net primary production• Characterization of photochemical reactions (CO, DMS, CO2, COS, CS2, …etc)• Surface heat budget
Measurement Strategies• Assimilation of field observations into physical ocean models
• Application of remotely sensed geophysical parameters (e.g., winds, heat flux, E-P, currents, SSH, SST,…etc)
• Empirical retrievals from remote sensing biological or chemical stocks and transformations
• Application of passive remote sensing data and optical models to calculate illumination
Mission Phasing
Backup Slides
Timeline
MissionThemes
Immediate(1 – 5 Years)
Long-Term(10 - 25 Years)
Near-Term(5 - 10 Years)
Global ImagingRadiometer
Aerosols &Particle Abund.
Physiology, Functional Groups, &Fluorescence
Mixed LayerDepth
MissionTheme
Technology Development
Launch/Mission
Ultraviolet
Issues & Approaches
Geophysical Parameters
Near Ultraviolet • Information Rich• High Energy• High Transparency
Ocean Carbon, Ecosystems and Near-Shore
Unexplored Territory
Mid
-UV
Nea
r-U
V
Visible Near InfraRed
* Remote Sensing Reflectance = water leaving / incident
*
Santa Barbara Channel
South Pacific photo (Andre Morel)
• Accurate separation and characterization of CDOM & Pigment Absorption
Ocean Carbon, Ecosystems and Near-Shore
Issues & Approaches
• Spectral Matching more sensitive to radiance reflectance errors than empirical ratio algorithms
• ‘Black water’ assumption invalid in coastal zones for historical wavebands
• Optical distinctions are subtle b/w ecosystem components (functional groups, HABS)
• Particulate scattering is key attribute for addressing many Carbon, Ecosystem, and Near -shore issues
• Coastal waters are optically complex, with particularly problematic atmospheres
• Relating particulate scattering to biomass requires description of particle size spectrum
• Fluorescence measurements
• Independent, active scattering measurements
• Expansion to near UV
• Enhanced Spectral Resolution UV
• Enhanced Spectral Resolution Visible
• Advanced Atmospheric Correction OzoneAbsorbing aerosol heightsUV band near 350 nmExpanded NIR
• Rigorous prelaunch characterization, regular lunar and solar calibration, field validation
Ocean Carbon, Ecosystems and Near-Shore
Passive Geophysical Parameters
GLAS profile data Geophysical Parameter
• Pigment absorption
• Phytoplankton carbon
• Net primary production
• Export production
• Dissolved Organic Carbon
• CDOM photochemistry
• Slope of CDOM absorption
• Particulate Organic Carbon
• Particle size spectrum (pss)
• Particulate beam attenuation
• Carbon loading & dispersal
• Solar radiation & Kd
• Particulate inorganic carbon
• Functional groups
• HABs
• Eutrophication
bbp (spectral matching, lidar)
aph (spectral matching)
Phyto C, C:Chl, PAR, MLD, Kd, part. size spec., fluor.
Algorthm Product
(Phyto C, NPP, MLD)t, Ecosystem Model
CDOM (spectral matching), empirical algorithms
CDOMt, PAR, MLD, Kd, Degredation model
CDOM (enhanced spectral UV/VIS resolution)
bbp, pss (spectral matching, lidar)
Spectral matching with enhanced VIS resolution
High VIS spectral resolution, Lidar
Near-shore particulate and dissolved carbont
UV/VIS radiances, modeling
High VIS (UV?) spectral resolution
High VIS (UV?) spectral resolution
Near-shore Phyto C & NPP, fluorescence
bbp (spectral matching), empirical algorithm
0 0.5 1.0 1.5 2.0Growth Rate (div d-1)
Growth Rate (day-1)
Los
s R
ate
(day
-1)
Johannessen et al. 2003
Spectral beam attenuation coefficient retrieved from ocean color inversionCollin S. Roesler, Emmanuel Boss (2003)
W.Balch, Bigelow LaboratoryAlvain et al. 2005