Retrieval of Particulate Backscattering Using Field and Satellite Radiometry: Assessment of the QAA Algorithm

Particulate optical backscattering (bbp) is a crucial parameter for the study of ocean biology and oceanic carbon estimations. In this work, bbp retrieval, by the quasi-analytical algorithm (QAA), is assessed using a large in situ database of matched bbp and remote-sensing reflectance (Rrs). The QAA is also applied to satellite Rrs (ESA OC-CCI project) as well, after their validation against in situ Rrs. Additionally, the effect of Raman Scattering on QAA retrievals is studied. Results show negligible biases above random noise when QAA-derived bbp is compared to in situ bbp. In addition, Rrs from the CCI archive shows good agreement with in situ data. The QAA’s functional form of spectral backscattering slope, as derived from in situ radiometry, is validated. Finally, we show the importance of correcting for Raman Scattering over clear waters prior to semi-analytical retrieval. Overall, this work demonstrates the high efficiency of QAA in the bbp detection in case of both in situ and ocean color data, but it also highlights the necessity to increase the number of observations that are severely under-sampled in respect to others environmental parameters.

[1]  Richard W. Gould,et al.  Inherent optical properties and diffuse attenuation coefficient aggregated within +/-6 nm of SeaWiFS, MODIS-AQUA, VIIRS, OLCI and MERIS bands, corrected Version 2019-06-12 , 2019 .

[2]  T. Kostadinov,et al.  Carbon-based phytoplankton size classes retrieved via ocean color estimates of the particle size distribution , 2015 .

[3]  F. D’Ortenzio,et al.  Assessment of uncertainty in the ocean reflectance determined by three satellite ocean color sensors (MERIS, SeaWiFS and MODIS-A) at an offshore site in the Mediterranean Sea (BOUSSOLE project) , 2008 .

[4]  ZhongPing Lee,et al.  On the non-closure of particle backscattering coefficient in oligotrophic oceans. , 2014, Optics express.

[5]  C. Mobley Light and Water: Radiative Transfer in Natural Waters , 1994 .

[6]  Michael J. Behrenfeld,et al.  Significant contribution of large particles to optical backscattering in the open ocean , 2009 .

[7]  David A. Siegel,et al.  Variability in optical particle backscattering in contrasting bio‐optical oceanic regimes , 2011 .

[8]  D. Stramski,et al.  Particle optical backscattering along a chlorophyll gradient in the upper layer of the eastern South Pacific Ocean , 2007 .

[9]  Rosalia Santoleri,et al.  Using overlapping VIIRS scenes to observe short term variations in particulate matter in the coastal environment , 2019, Remote Sensing of Environment.

[10]  Andrew H. Barnard,et al.  A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case I and case II waters , 2001 .

[11]  Dale A. Kiefer,et al.  Light scattering by microorganisms in the open ocean , 1991 .

[12]  F. Mélin,et al.  Comparison of SeaWiFS and MODIS time series of inherent optical properties for the Adriatic Sea , 2011 .

[13]  Robert Frouin,et al.  A compilation of global bio-optical in situ data for ocean-colour satellite applications – version two , 2015, Earth System Science Data.

[14]  Giuseppe Zibordi,et al.  Assessment of satellite ocean color products at a coastal site , 2007 .

[15]  Richard W. Gould,et al.  An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI) , 2019, Sensors.

[16]  Gianluca Volpe,et al.  Global Variability of Optical Backscattering by Non‐algal particles From a Biogeochemical‐Argo Data Set , 2019, Geophysical Research Letters.

[17]  Marcello Vichi,et al.  Using Optical Sensors on Gliders to Estimate Phytoplankton Carbon Concentrations and Chlorophyll-to-Carbon Ratios in the Southern Ocean , 2017, Front. Mar. Sci..

[18]  Robert J. W. Brewin,et al.  The open-ocean missing backscattering is in the structural complexity of particles , 2018, Nature Communications.

[19]  Gianluca Volpe,et al.  Influence of photoacclimation on the phytoplankton seasonal cycle in the Mediterranean Sea as seen by satellite , 2016 .

[20]  Alan Weidemann,et al.  Modeling of elastic and inelastic scattering effects in oceanic optics , 1997, Other Conferences.

[21]  Rosalia Santoleri,et al.  Use of the quasi-analytical algorithm to retrieve backscattering from in-situ data in the Mediterranean Sea , 2016 .

[22]  David A. Siegel,et al.  Retrieval of the particle size distribution from satellite ocean color observations , 2009 .

[23]  E. Boss,et al.  Influence of Raman scattering on ocean color inversion models. , 2013, Applied optics.

[24]  B. Ripley,et al.  Robust Statistics , 2018, Encyclopedia of Mathematical Geosciences.

[25]  Annick Bricaud,et al.  Retrieval of Colored Detrital Matter (CDM) light absorption coefficients in the Mediterranean Sea using field and satellite ocean color radiometry: Evaluation of bio-optical inversion models , 2016 .

[26]  P. J. Werdell,et al.  An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation , 2005 .

[27]  Peter Regner,et al.  The Ocean Colour Climate Change Initiative: III. A round-robin comparison on in-water bio-optical algorithms , 2015 .

[28]  G. Dall’Olmo,et al.  Particle backscattering as a function of chlorophyll and phytoplankton size structure in the open-ocean. , 2012, Optics express.

[29]  C. Jamet,et al.  An Inverse Model for Estimating the Optical Absorption and Backscattering Coefficients of Seawater From Remote-Sensing Reflectance Over a Broad Range of Oceanic and Coastal Marine Environments: INVERSION OF SEAWATER IOPS , 2018 .

[30]  Stanford B. Hooker,et al.  BOUSSOLE: A Joint CNRS-INSU, ESA, CNES, and NASA Ocean Color Calibration and Validation Activity , 2006 .

[31]  R. Arnone,et al.  Penetration of UV-visible solar radiation in the global oceans: Insights from ocean color remote sensing , 2013 .

[32]  D. Antoine,et al.  The “BOUSSOLE” Buoy—A New Transparent-to-Swell Taut Mooring Dedicated to Marine Optics: Design, Tests, and Performance at Sea , 2008 .

[33]  K. Halsey,et al.  Phytoplankton strategies for photosynthetic energy allocation. , 2015, Annual review of marine science.

[34]  E. Boss,et al.  Evaluating satellite estimates of particulate backscatter in the global open ocean using autonomous profiling floats. , 2019, Optics express.

[35]  David A. Siegel,et al.  Revaluating ocean warming impacts on global phytoplankton , 2016 .

[36]  Rosalia Santoleri,et al.  The Mediterranean Ocean Colour Level 3 Operational Multi-Sensor Processing , 2018 .

[37]  E. Boss,et al.  Regional to global assessments of phytoplankton dynamics from the SeaWiFS mission , 2013 .

[38]  E. Boss,et al.  Retrieving marine inherent optical properties from satellites using temperature and salinity-dependent backscattering by seawater. , 2013, Optics express.

[39]  Frédéric Mélin,et al.  Band shifting for ocean color multi-spectral reflectance data. , 2015, Optics express.

[40]  Dariusz Stramski,et al.  Evaluation of the Quasi-Analytical Algorithm for estimating the inherent optical properties of seawater from ocean color: Comparison of Arctic and lower-latitude waters , 2014 .

[41]  Jorge J. Moré,et al.  Computing a Trust Region Step , 1983 .

[42]  Dariusz Stramski,et al.  The role of seawater constituents in light backscattering in the ocean , 2004 .

[43]  R. Santoleri,et al.  Global Distribution of Non‐algal Particles From Ocean Color Data and Implications for Phytoplankton Biomass Detection , 2018, Geophysical Research Letters.

[44]  P. Deschamps,et al.  Seasonal variability of the backscattering coefficient in the Mediterranean Sea based on satellite SeaWiFS imagery , 2001 .

[45]  Emmanuel Boss,et al.  Spectral attenuation and backscattering as indicators of average particle size. , 2015, Applied optics.

[46]  G. Dall’Olmo,et al.  Intercomparison of Ocean Color Algorithms for Picophytoplankton Carbon in the Ocean , 2017, Front. Mar. Sci..

[47]  Xiaodong Zhang,et al.  Scattering by pure seawater: effect of salinity. , 2009, Optics express.

[48]  David A. Siegel,et al.  Carbon‐based ocean productivity and phytoplankton physiology from space , 2005 .

[49]  R. Arnone,et al.  Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters. , 2002, Applied optics.

[50]  André Morel,et al.  Optics of heterotrophic nanoflagellates and ciliates : a tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algal cells , 1991 .