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Ocean Color Observations and Their Applications to Climate Studies

Ocean Color Observations and Their Applications to Climate Studies. Alex Gilerson , Soe Hlaing, Ioannis Ioannou, Sam Ahmed Optical Remote Sensing Laboratory, The City College of the City University of New York, NOAA CREST. CREST Symposium, June 5, 2013. Melin, 2013.

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Ocean Color Observations and Their Applications to Climate Studies

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  1. Ocean Color Observations and Their Applications to Climate Studies Alex Gilerson, Soe Hlaing, Ioannis Ioannou, Sam Ahmed Optical Remote Sensing Laboratory, The City College of the City University of New York, NOAA CREST CREST Symposium, June 5, 2013

  2. Melin, 2013

  3. Water Composition for the Open Ocean and Coastal Waters In the open ocean algae are the main component In coastal waters algae are mixed with CDOM and minerals Algae CDOM* Minerals *CDOM is the colored dissolved organic matter mostly of terrestrial origin

  4. Reflectance of Various Surfaces Signal from water is small in comparison with reflectance from other surfaces and atmosphere

  5. Total Radiance Signal at the Top of Atmosphere Lp Lw Ls Lw -Total water-leaving radiance. Ls - Radiance above the sea surface due to all surface reflection effects within the IFOV. Lp- Atmospheric path radiance. Signal from the atmospheric scattering is about 10 times stronger than from water. Atmospheric correction utilizes NIR bands (748, 865 nm)

  6. Outline • Introduction • System requirements • Vicarious calibration • Chl time series • Our applications to climate studies

  7. Main Requirements for Sensors and Observations(IOCCG report 13) • Easy intercomparison between sensors, and radiometric intercalibration in well-defined conditions; • A full compatibility of operational algorithms for atmospheric correction and derivation of end products; • A meaningful data merging, at the level of geophysical products (pigment index, aerosol optical thickness) or at the level of the initial quantities (e.g. spectral normalized radiances); • A long-term continuity of ocean-colour observations, based on stable, entirely comparable, parameters; and therefore • The building up of a coherent data base for global biogeochemical studies and related modelling activities

  8. Main Requirements for Climatic Data Records To gain insight into climate variability and change the requirement is continuous time series of observations to estimate ocean properties such as phytoplankton chlorophyll-a with the radiometric accuracy of current sensors or better (IOCCG report 13) Length: relevant for climate time scales (referred to as “long-term”) need for multiple decades of data (>~50 years) - Melin, 2013 Two levels of products - Water leaving radiance / Remote sensing reflectance (Rrs) – highly accurate measurements by well calibrated sensors and consistency through various missions - Chlorophyll-a concentration (Chla) – main ocean color product – continuous time series

  9. Remote Sensing of the Ocean RS of water areas provides an efficient way of monitoring water quality, biomass in the ocean, sediment plumes, spatial and temporal scales of the water structures, sea surface temperature, etc. • Phytoplankton are very • important part of ocean life: • Phytoplankton are the first link in the food chain. • Phytoplankton convert nutrients into plant material by using sunlight through photosynthesis and convert carbon dioxide from sea water into organic carbon and oxygen as a by-product and thus affect carbon balance. Amount of phytoplankton in the ocean can be traced by the concentration of the optically active pigment chlorophyll [Chl]

  10. Reflectance spectra for the open ocean [Chl] can be well characterized by blue-green ratio With increasing [Chl] water changes its color frombluetogreen SeaWiFS Blue-Green Ratio Algorithm Carder, et al. ,2003

  11. Chlorophyll Global and Regional Maps SeaWiFS, July 2006 MODIS, NE and Florida coasts

  12. Ocean Color Satellite Sensors NASA Coastal Zone Color Scanner (CZCS) – 1978 - 1986 Seaviewing Wide Field-of-view Sensor(SeaWiFS) – 1997 - 2011 NASA Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra satellite -1999-present NASA Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua satellite -2002-present MEdium Resolution Imaging Spectrometer (MERIS), European Space Agency (ESA) on ENVISAT satellite – 2002-2012 Suomi National Polar-orbiting Partnership - Visible Infrared Imaging Radiometer Suite (VIIRS) NOAA- NASA -2011-present

  13. MODIS Spectral Bands for Ocean Color and Atmospheric Correction (Terra,1999; Aqua, 2002)

  14. Vicarious calibration System Vicarious Calibration (e.g., calibration relying on the use of highly accurate in situ measurements of Lw and the application of the RT code embedded in the atmospheric correction scheme, thus leading to the calibration of the entire system, i.e., the sensor plus the algorithms (Gordon 1998)) specifically applied to perform (absolute) radiometric calibrations. Expected top-of-atmosphere calibration uncertainties are 0.3-0.5%, leading to uncertainties of 3-5% in Lw. This suggests that in situ data sources for vicarious calibration of satellite ocean color sensors need to be carefully evaluated accounting for the actual application of satellite data products recognizing that the creation of CDRs imposes the most stringent conditions. Early indications on the appropriateness of in situ data/sites included (Gordon 1998): 1. Cloud free, very clear, maritime atmosphere (τa<0.1 in the visible); 2. Horizontally uniform Lw over spatial scales of a few kms; 3. Oligotrophic-mesotrophic waters (to minimize in situ measurement errors of Lw in the blue); 4. Coincident aerosol measurements. Zibordi, 2013

  15. MOBY – Marine Optical Buoy McClain, 2013

  16. McClain, 2013

  17. McClain, 2013

  18. Regional trends Decomposition of the signal into seasonal, trend and irregular terms Melin, 2010, 2013

  19. Alternative Ocean Color Algorithms - NN [Chl] Algorithms 1) OC3 2) Rrs NN (NN [Chl]) 3) IOP+Rrs NN (IOP NN [Chl]) NN [Chl] and IOP NN [Chl] are trained based on the NOMAD Ioannou et al, 2011, 2013

  20. Alternative Ocean Color Algorithms - NN Sample Seasonal [Chl], Spring 2003 Algorithm Implementation on Satellite Data- OC3-[Chl], mg m-3

  21. Alternative Ocean Color Algorithms - NN Sample Seasonal [Chl], Spring 2003 Algorithm Implementation on Satellite Data- NN-[Chl], mg m-3

  22. Alternative Ocean Color Algorithms - NN Global Distributions of [Chl], as derived from the three algorithms for Spring 2003

  23. Alternative Ocean Color Algorithms - NN Global seasonal variation of [Chl]mg/m3 [Chl]mg/m3

  24. Polarization measurements with the hyperspectral multi-angular polarimeter + full Stokes vector imaging camera

  25. Polarization sensitive instruments are used to measure aerosols. We show that they are useful in the retrieval of additional water parameters: attenuation coefficient, particle characteristics Addition of polarization sensitive channels to the future satellite instruments Polarization channels 665 440 865 680 710 750 In collaboration with NASA-GISS and Raytheon we are working on a potential new sensor with polarization sensitivity, 3 observational angles for retrieval of aerosols and water parameters Japan will launch an instrument with 665 and 865nm polarization channels, 3 viewing angles, 250m resolution in 2016

  26. Algal Blooms - Progression of K. Brevis bloom using MODIS data and our algorithm

  27. GloboLakes Project Tyler, 2012

  28. GloboLakes Project Tyler, 2012

  29. Conclusions • Climate Ocean Color observations are challenging but possible for observation of global and regional trends • Require: - highly precise sensors - vicarious calibration; - accurate atmospheric correction algorithms - accurate and well established algorithms for ocean operational products - continuity between missions This work is partially supported by grants from NOAA, NASA and the Office of Naval Research

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