OCEaNS

1. OCEaNS Ocean Carbon, Ecosystems and Near-Shore

2. OCEaNS Ocean Carbon, Ecosystems and Near-Shore “Quantifying, monitoring, and predicting transformations between organic and inorganic ocean carbon stocks, and their interactions with atmospheric and terrestrial systems” CO2 regenerated production regenerated production phytoplantkon DIC DIC zooplankton fish bacteria detritus ‘new’ primary production DOC POC base of euphotic zone • Phytoplankton Biomass • Ocean Productivity • Total Particulate Carbon • Dissolved Organic Carbon • Particulate Inorganic Carbon • Export Carbon export production mid-water biota and bacteria DIC benthic biota and bacteria POC

3. OCEaNS Ecosystems, Ocean Carbon, and Near-Shore “Characterizing how the composition (i.e., ‘who’s there?’) and structure of marine food webs impact elemental cycles, including carbon” • Functional Groups • Carbon Exporters (diatoms) • Nitrogen Fixers (trichodesmium) • Calcium Carbonate (coccolithophores) • Microbial Loop (prochlorococcus) • Net Primary Productivity • Trophic Energy Transfer • Biogeography

4. OCEaNS Near-Shore Ocean Carbon, Ecosystems, and “Ocean carbon and ecosystem functioning in the local zone between the beach and shelf break, plus health and hazard issues” Yangtze River • Carbon cycling • 10% of global production • shelves >50% of carbon export • Land to Ocean Materials Exchange • Eutrophication • Harmful Algal Blooms Sea of Azov Lagoa dos Patos

5. OCEaNS OCEaNS/ORCA: A Quantum Leap In Ocean Biogeochemistry Remote Sensing • CZCS (1978-1985): - 4 Visible Bands (443, 520, 550, 670 nm) - 1 NIR Band (750 nm – cloud detection only) • SeaWiFS (1997-present) - 6 Visible Bands (412, 443, 490, 510, 555, 670 nm) - 2 NIR Bands (765, 865 nm) • MODIS (Terra/Aqua; 2000/2002-present) - 7 Visible Bands (412, 443, 488, 531, 547, 667, 678 nm) - 2 NIR Bands (748, 865 nm) - 3 SWIR (land) Bands (1240, 1640, 2130 nm) • VIIRS (NPP & NPOESS; future operational sensor) - 5 Visible Bands (412, 443, 490, 555, 670 nm) - 2 NIR (748, 865 nm) • OCEaNS/ORCA (minimum requirements) - 14 bands (335-700 nm) - 2 bands (700-900 nm) - 2 SWIR Bands (1240, 1640 nm) Visible bands: bio-optical products NIR-SWIR bands: atmospheric corrections UV bands: bio-optical products & atmos. corrections

6. SeaWiFS: a starting point for the OCRA designSeptember 1997- present • Orbit: Noontime, sun-synchronous descending • Spatial Resolution: • 1.1 km (Local Area Coverage from HRPT stations) • Swath: 2800 km • 4.4 km (Global Area Coverage recorded on S/C) • Swath: 1500 km • Instrument Components & Spectral Bands: • Fore optics: rotating telescope • Wavelengths: 412, 443, 490, 510, 555, 670, 765, 865 nm • 4 detectors/band in TDI with bilinear gains • 4 commandable gain settings (science 1, science 2, solar, lunar) • Depolarizer: Polarization sensitivity ~ 0.25% • Digitization: 10 bits • On-Orbit Calibration • Sensor degradation: monthly lunar views near full-moon • Solar diffuser: daily (track short term sensitivity variations) • Calibration pulse: daily (track instrument electronics stability) • Vicarious calibration gain adjustments: Marine Optical Buoy off Lanai, Hawaii

7. SeaWiFS Lunar Calibration (Relative) OCEaNS Ocean Carbon, Ecosystems and Near-Shore Once a month, the SeaWiFS satellite (Orbview-2) is pitched to observe the Moon at a phase angle ~ 7°.

8. OCEaNS Ocean Carbon, Ecosystems and Near-Shore Oceans, Aerosols, & Clouds: A ‘Natural’ Collaboration • Historically, the Ocean Science community has largely worked independently of the Atmospheric Science community. • - Future mission must foster a much closer working relationship. • Progress in satellite ocean biogeochemistry and ecosystem research hinges on more accurate atmospheric corrections, e.g., over turbid water & in the presence of absorbing aerosols. • - SeaWiFS, MODIS & VIIRS do not have capabilities required to detect & remove absorbing aerosol contamination of derived products. • - SWIR & UV bands are required to make accurate atmospheric corrections in presence of turbid water. • There are a variety of linkages between ocean biology, aerosols, and cloud processes that have not been quantified. • - Aeolian dust/Fe fluxes: Iron is a limiting nutrient over most of the global ocean. • - Marine DMS production: A key process in generation of cloud condensation nuclei? • - Marine particulates and biomass: Independent estimates from aerosol lidar & ORCA.

9. OCEaNS Ocean Carbon, Ecosystems and Near-Shore Chl (mg m-3) CDOM (m-1) bbp (m-1) Problem #1: Separation of absorbing marine constituents • Past, present, and currently planned missions were designed for empirical • algorithms (statistical) that rely on the ‘bio-optical assumption’ that all • absorbing and scattering components in the water • covary in a globally consistent manner. We now • know that the ‘bio-optical assumption’ is without • question wrong! • The ‘semi-analytic approach’ (i.e., spectral matching) • yield a suite of internally consistent Carbon/ • Ecosystem products and does not rely on the • ‘bio-optical assumption’, but the historic suite • of ocean color wavebands prevents the • effective application of this new approach Chlorophyll, CDOM, & particulate backscatter from semi-analytic model reflectance inversion

10. OCEaNS Ocean Carbon, Ecosystems and Near-Shore 0 400 800 1200 1500 Photosynthesis (mg m-2 d-1) Problem #1 cont. : NPP Uncertainty • Net Primary Production • (note: 1999 to 2005 rate of change = -0.4 to -0.8 Pg C y-1) Difference = 16 Pg C y-1 Standard Empirical norm. % diff. CDOM Spectral Matching m-1

11. OCEaNS Ocean Carbon, Ecosystems and Near-Shore -0.4 to -0.8 Pg y-1 Current uncertainty from inaccurate separation of CDOM and Chlorophyll alone is 16 Pg C y-1 New approaches to productivity modeling and ocean color analysis can solve this problem, but we lack the satellite data to do so… Problem #1cont. : Impact on Ocean Productivity Estimates 1999 2005

12. OCEaNS Ocean Carbon, Ecosystems and Near-Shore Problem #2: Atmospheric Aerosols • Aerosol Characteristics Source Dependent • coastal regions problematic (turbid water, wider variety of aerosol types, NO2 absorption) • dust significant over vast ocean region • non-absorbing aerosols not a problem • Seasonally and Spatially Varying • requires coincident observations in space & time • Vertical Distribution Critical • modeling, lidar, polarimeter • SeaWiFS, MODIS, VIIRS • no capability to uniquely identify low-moderate concentrations of absorbing aerosols Equivalent Aerosol Optical Depths Fall Spring

13. OCEaNS Ocean Carbon, Ecosystems and Near-Shore Problem #2 cont.: Over-correction of Aerosol Radiances • Negative water-leaving radiances in coastal regions • - Absorbing aerosols • - NO2 absorption • - Finite NIR reflectance (very turbid waters) • River deltas, estuaries, etc. Percent of clear pixels processed having negative water-leaving radiances (courtesy J. O’Reilly, NOAA/National Marine Fisheries). Current aerosol model suite inadequate & dated!

14. Problem #2 cont.: Aerosol Correction Over Turbid Water OCEaNS Ocean Carbon, Ecosystems and Near-Shore Ocean is not that black for Case-2 waters at the NIR bands

15. 340 360 380 412 440 460 490 532 555 583 620 655 670 680 750 865 300 400 500 600 700 800 900 Multispectral Passive Radiometry 1240 1640 NIR: Open ocean atmospheric correction SWIR: Coastal/estuarine atmos. corr. VISIBLE: Taxonomy Pigment biomass Light Attenuation ULTRAVIOLET: CDOM Particulate scattering Atmospheric correction +

16. OCEaNS Ocean Carbon, Ecosystems and Near-Shore Radiometer/Mission Requirements • 2-day global coverage • Data collected to 75o latitude of subsolar point • Spatial resolution: 1 km resolution @ nadir • Minimum band set (λ range) 3 Near-UV bands (335-400 nm) 9 VIS bands (400-660 nm) 2 Fluorescence bands (667 & 678 nm) 2 NIR atmospheric correction bands (740-900 nm) 2 SWIR atmospheric correction bands (1200-1700) • 0.1% radiometric accuracy on orbit • < 1% polarization sensitivity • Monthly lunar calibration maneuver (dark side) • Daily Solar Calibration (pole) • Spectral calibration (solar based) • Sun glint avoidance (sensor tilting) • Orbit - Sun synchronous orbit, noon descending node - 650 km • 5 year mission design life SNR Specs.: 750-1500 > 1500 > 1000 > 750 > 180 Current ORCA design meets or exceeds all sensor requirements. Chlorophyll Fluorescence

17. OCEaNS Ocean Carbon, Ecosystems and Near-Shore Backup Slides

18. Ocean Color Reconstruction 400 Wavelength 700 Net Spectrum Ocean Color 412 443 490 510 555 400 Wavelength 700 Chlorophyll-a Chlorophyll-b Chlorophyll-c Carotenoids Particulate backscatter CDOM Spectral Shape 400 Wavelength 700 Spectral Matching

19. OCEaNS Ocean Carbon, Ecosystems and Near-Shore Absorbing Aerosols GLAS profile data • Demonstration of Absorbing Aerosol Effects (Howard Gordon) • Radiative Transfer calculations of top of atmosphere reflectances • Dust Aerosol with distributions as suggested by GLAS data • Aerosol Optical Depth of 0.8 at 865 nm (note: reflectance is essentially independent of vertical structure at 865) • Compared reflectances for 420 and 360 nm for different vertical structures and with results for dust model of Moulin et al. (2004) used for SeaWiFS processing

20. OCEaNS Ocean Carbon, Ecosystems and Near-Shore 30 Off-Nadir Angle 15 0 Time Particle Scattering Lidar In-space Technology Experiment (LITE) • 3-wavelength Nd-Yg lidar • Space Shuttle in 1994 • Multi-angle (+/-300) maneuvers over Lake Superior and Gulf of California • Increased gain at higher angles • Surface return diminishes with angle • 1064 and 532 nm channels have similar real-part of refractive indices and thus similar surface returns GLAS profile data

21. OCEaNS Ocean Carbon, Ecosystems and Near-Shore 150 150 150 150 Particle Scattering High Gain Low Gain HG High Gain Low Gain HG GLAS profile data 532 nm 1064 nm 1064 nm 532 nm 355 nm

22. OCEaNS Ocean Carbon, Ecosystems and Near-Shore Conclusions: Scattering • Lidar measurements at >15º and 532 nm can provide active measurement of in-water particle scattering • Active measurements of particle scattering coefficients can be used to constrain global ‘Spectral Matching’ products • Eye-safe Lidar may require spatial averaging • May be dark-side of earth measurement