Abstract

Ocean reflectance inversion models (ORMs) provide a mechanism for inverting the color of the water observed by a satellite into marine inherent optical properties (IOPs), which can then be used to study phytoplankton community structure. Most ORMs effectively separate the total signal of the collective phytoplankton community from other water column constituents; however, few have been shown to effectively identify individual contributions by multiple phytoplankton groups over a large range of environmental conditions. We evaluated the ability of an ORM to discriminate between Noctiluca miliaris and diatoms under conditions typical of the northern Arabian Sea. We: (1) synthesized profiles of IOPs that represent bio-optical conditions for the Arabian Sea; (2) generated remote-sensing reflectances from these profiles using Hydrolight; and (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N. miliaris. By comparing the estimates from the inversion model with those from synthesized vertical profiles, we identified those conditions under which the ORM performs both well and poorly. Even under perfectly controlled conditions, the absolute accuracy of ORM retrievals degraded when further deconstructing the derived total phytoplankton signal into subcomponents. Although the absolute magnitudes maintained biases, the ORM successfully detected whether or not Noctiluca miliaris appeared in the simulated water column. This quantitatively calls for caution when interpreting the absolute magnitudes of the retrievals, but qualitatively suggests that the ORM provides a robust mechanism for identifying the presence or absence of species.

© 2014 Optical Society of America

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2013 (4)

P. J. Werdell, B. A. Franz, S. W. Bailey, G. C. Feldman, E. Boss, V. E. Brando, M. Dowell, T. Hirata, S. J. Lavender, Z.-P. Lee, H. Loisel, S. Maritorena, F. Mélin, T. S. Moore, T. J. Smyth, D. Antoine, E. Devred, O. H. Fanton d’Andon, A. Mangin, “A generalized ocean color inversion model for retrieving marine inherent optical properties,” Appl. Opt. 52, 2019–2037 (2013).
[CrossRef]

P. J. Werdell, B. A. Franz, J. T. Lefler, W. D. Robinson, E. Boss, “Retrieving marine inherent optical properties from satellite using temperature and salinity-dependent backscattering by seawater,” Opt. Express 21, 32611–32622 (2013).

P. J. Werdell, C. W. Proctor, E. Boss, T. Leeuw, M. Ouhssain, “Underway sampling of marine inherent optical properties on the Tara Oceans expedition as a novel resource for ocean color satellite data product validation,” Meth. Oceanogr. 7, 40–51 (2013).
[CrossRef]

D. J. Bogucki, G. Spiers, “What percentage of the oceanic mixed layer is accessible to marine lidar? Global and the Gulf of Mexico prospective,” Opt. Express 21, 23997–24014 (2013).
[CrossRef]

2012 (3)

V. E. Brando, A. G. Dekker, Y. J. Park, T. Schroeder, “Adaptive semi-analytic inversion of ocean color radiometry in optically complex waters,” Appl. Opt. 51, 2808–2833 (2012).
[CrossRef]

S. Henson, R. Lampitt, D. Johns, “Variability in phytoplankton community structure in response to the North Atlantic Oscillation and implications for organic carbon flux,” Limnol. Oceanogr. 57, 1591–1601 (2012).
[CrossRef]

S. Alvain, H. Loisel, D. Dessailly, “Theoretical analysis of ocean color radiances anomalies and implications for phytoplankton groups detection in case 1 waters,” Opt. Express 20, 1070–1083 (2012).
[CrossRef]

2011 (4)

R. J. W. Brewin, E. Devred, S. Sathyendranath, S. J. Lavender, N. J. Hardman-Mountford, “Model of phytoplankton absorption based on three size classes,” Appl. Opt. 50, 4535–4549 (2011).
[CrossRef]

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, Y. Yamanaka, “Synoptic relationships between surface chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeoscience 8, 311–327 (2011).

R. J. W. Brewin, N. J. Hardman-Mountford, S. J. Lavender, D. E. Raitsos, T. Hirata, J. Uitz, E. Devred, A. Bricaud, A. Ciotti, B. Gentili, “An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing,” Remote Sens. Environ. 115, 325–339 (2011).
[CrossRef]

V. Vantrepotte, F. Mélin, “Inter-annual variations in the SeaWiFS global chlorophyll-a concentration (1997–2007),” Deep Sea Res. I 58, 429–441 (2011).

2010 (4)

S. A. Henson, J. L. Sarmiento, J. P. Dunne, L. Bopp, I. Lima, S. C. Doney, J. John, C. Beaulieu, “Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity,” Biogeoscience 7, 621–640 (2010).
[CrossRef]

D. G. Boyce, M. R. Lewis, B. Worm, “Global phytoplankton decline over the past century,” Nature 466, 591–596 (2010).
[CrossRef]

T. S. Kostadinov, D. A. Siegel, S. Maritorena, “Global variability of phytoplankton functional types from space: assessment via the particle size distribution,” Biogeoscience 7, 3239–3257 (2010).

C. Mouw, J. A. Yoder, “Optical determination of phytoplankton size composition from global SeaWiFS imagery,” J. Geophys. Res. 115, C12018 (2010).
[CrossRef]

2009 (5)

E. Martinez, D. Antoine, F. D’Ortenzio, B. Gentili, “Climate-driven basin-scale decadal oscillations of oceanic phytoplankton,” Science 326, 1253–1256 (2009).
[CrossRef]

P. J. Werdell, S. W. Bailey, B. A. Franz, L. W. Harding, G. C. Feldman, C. R. McClain, “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Remote Sens. Environ. 113, 1319–1330 (2009).
[CrossRef]

T. S. Moore, J. W. Campbell, M. D. Dowell, “A class-based approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product,” Remote Sens. Environ. 113, 2424–2430 (2009).
[CrossRef]

A. Bracher, M. Vountas, T. Dinter, J. P. Burrows, R. Rottgers, I. Peeken, “Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data,” Biogeoscience 6, 751–764 (2009).

X. Zhang, L. Hu, M.-X. He, “Scattering by pure seawater: effect of salinity,” Opt. Express 17, 5698–5710 (2009).
[CrossRef]

2008 (4)

H. D. R. Gomes, J. I. Goes, S. G. P. Matondkar, S. G. Parab, A. R. N. Al-Azri, P. G. Thoppil, “Blooms of Noctiluca miliaris in the Arabian Sea–an in situ and satellite study,” Deep Sea Res. I 55, 751–765 (2008).

V. Smetacek, J. E. Cloern, “On phytoplankton trends,” Science 319, 1346–1348 (2008).
[CrossRef]

T. Hirata, J. Aiken, N. Hardman-Mountford, T. J. Smyth, R. G. Barlow, “An absorption model to determine phytoplankton size classes from satellite ocean colour,” Remote Sens. Environ. 112, 3153–3159 (2008).
[CrossRef]

B. Lubac, H. Loisel, N. Guiselin, R. Astoreca, L. F. Artigas, X. Mériaux, “Hyperspectral and multispectral ocean color inversions to detect Phaeocystis globosa blooms in coastal waters,” J. Geophys. Res. 113, C06026 (2008).
[CrossRef]

2007 (5)

M. Defoin-Platel, M. Chami, “How ambiguous is the inverse problem of ocean color in coastal waters?” J. Geophys. Res. 112, C03004 (2007).
[CrossRef]

J. Aiken, J. R. Fishwick, S. Lavender, R. Barlow, G. F. Moore, H. Sessions, S. Bernard, J. Ras, N. J. Hardman-Mountford, “Validation of MERIS reflectances and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters,” Int. J. Remote Sens. 28, 497–516 (2007).
[CrossRef]

B. A. Franz, S. W. Bailey, P. J. Werdell, C. R. McClain, “Sensor-independent approach to the vicarious calibration of satellite ocean color radiometry,” Appl. Opt. 46, 5068–5081 (2007).
[CrossRef]

A. Whitmire, E. Boss, T. J. Cowles, W. S. Pegau, “Spectral variability of the particulate backscattering ratio,” Opt. Express 15, 7019–7031 (2007).
[CrossRef]

Z.-P. Lee, K. Carder, R. Arnone, M.-X. He, “Determination of primary spectral bands for remote sensing of aquatic environments,” Sensors 7, 3428–3441 (2007).
[CrossRef]

2006 (7)

M. Tzortziou, J. R. Hermn, C. L. Gallegos, P. J. Neale, A. Subramaniam, L. W. Harding, Z. Ahmad, “Bio-optics of the Chesapeake Bay from measurements and radiative transfer closure,” Estuarine, Coastal Shelf Sci. 68, 348–362 (2006).
[CrossRef]

S. G. Parab, S. G. Prabhu Matondkar, H. D. R. Gomes, J. I. Goes, “Monsoon-driven changes in phytoplankton populations in the eastern Arabian Sea as revealed by microscopy and HPLC pigment analysis,” Continent. Shelf Res. 26, 2538–2558 (2006).
[CrossRef]

M. J. Behrenfeld, R. T. O’Malley, D. A. Siegel, C. R. McClain, J. L. Sarmiento, G. C. Feldman, A. J. Milligan, P. G. Falkowski, R. M. Letelier, E. S. Boss, “Climate-driven trends in contemporary ocean productivity,” Nature 444, 752–755 (2006).
[CrossRef]

H. Loisel, J.-M. Nicolas, A. Sciandra, D. Stramski, A. Poteau, “Spectral dependency of optical backscattering by marine particles from satellite remote sensing of the global ocean,” J. Geophys. Res. 111, C09024 (2006).
[CrossRef]

A. M. Ciotti, A. Bricaud, “Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water-leaving radiances at SeaWiFS channels in a continental shelf region off Brazil,” Limnol. Oceanogr. 4, 237–253 (2006).
[CrossRef]

J. Uitz, H. Claustre, A. Morel, S. B. Hooker, “Vertical distribution of phytoplankton communities in open ocean: an assessment based on surface chlorophyll,” J. Geophys. Res. 111, C08005 (2006).
[CrossRef]

E. Devred, S. Sathyendranath, V. Stuart, H. Maass, O. Ulloa, T. Platt, “A two-component model of phytoplankton absorption in the open ocean: theory and applications,” J. Geophys. Res. 111, C03011 (2006).
[CrossRef]

2005 (4)

T. K. Westberry, D. A. Siegel, A. Subramaniam, “An improved bio-optical model for the remote sensing of Trichodesmium spp. blooms,” J. Geophys. Res. 110, C06012 (2005).
[CrossRef]

P. Wang, E. Boss, C. S. Roesler, “Uncertainties of inherent optical properties obtained from semi-analytical inversions of ocean color,” Appl. Opt. 44, 4074–4085 (2005).
[CrossRef]

J. R. V. Zaneveld, A. H. Barnard, E. Boss, “Theoretical derivation of the depth average of remotely sensed optical parameters,” Opt. Express 13, 9052–9061 (2005).
[CrossRef]

P. J. Werdell, S. W. Bailey, “An improved in situ bio-optical data set for ocean color algorithm development and satellite data product validation,” Remote Sens. Environ. 98, 122–140 (2005).
[CrossRef]

2004 (3)

D. Stramski, E. Boss, D. Bogucki, K. J. Voss, “The role of seawater constituents in light backscattering in the ocean,” Prog. Oceanogr. 61, 27–56 (2004).
[CrossRef]

M. Sydor, R. W. Gould, R. A. Arnone, V. I. Haltrin, W. Goode, “Uniqueness in remote sensing of inherent optical properties of ocean water,” Appl. Opt. 43, 2156–2162 (2004).
[CrossRef]

S. Sathyendranath, L. Watts, E. Devred, T. Platt, C. Caverhill, H. Maass, “Discrimination of diatoms from other phytoplankton using ocean-color data,” Mar. Ecol. Prog. Ser. 272, 59–68 (2004).
[CrossRef]

2003 (1)

M. Babin, A. Morel, V. Fournier-Sicre, F. Fell, D. Stramski, “Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration,” Limnol. Oceanogr. 48, 843–859 (2003).
[CrossRef]

2002 (2)

Z.-P. Lee, K. L. Carder, R. Arnone, “Deriving inherent optical properties form water color: a multi-band quasi-analytical algorithm for optically deep water,” Appl. Opt. 41, 5755–5772 (2002).
[CrossRef]

S. Maritorena, D. A. Siegel, A. Peterson, “Optimization of a semi-analytic ocean color model for global scale applications,” Appl. Opt. 41, 2705–2714 (2002).
[CrossRef]

2001 (2)

A. Morel, S. Maritorena, “Bio-optical properties of oceanic waters: a reappraisal,” J. Geophys. Res. 106, 7163–7180 (2001).
[CrossRef]

M. S. Twardowski, E. Boss, J. B. Macdonald, W. S. Pegain, A. H. Barnard, J. R. V. Zaneveld, “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,” J. Geophys. Res. 106, 14129–14142 (2001).
[CrossRef]

1998 (4)

A. Bricaud, A. Morel, M. Babin, K. Allali, H. Clauster, “Variations of light absorption by suspended particles with chlorophyll-a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models,” J. Geophys. Res. 103, 31033–31044 (1998).
[CrossRef]

S. L. McLeroy-Etheridge, C. S. Roesler, “Are the inherent optical properties of phytoplankton responsible for the distinct ocean colors observed during harmful algal blooms?” Ocean Opt. 14, 109–116 (1998).

C. S. Roesler, “Theoretical and experimental approaches to improve the accuracy of particulate absorption coefficients from the quantitative filter technique,” Limnol. Oceanogr. 43, 1649–1660 (1998).
[CrossRef]

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, C. R. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. 103, 24937–24953 (1998).
[CrossRef]

1997 (2)

R. M. Pope, E. S. Fry, “Absorption spectrum (380–700  nm) of pure water. II. integrating cavity measurements,” Appl. Opt. 36, 8710–8723 (1997).
[CrossRef]

D. Stramski, C. D. Mobley, “Effects of microbial particles on ocean optics: a database of single-particle optical properties,” Limnol. Oceanogr. 42, 538–549 (1997).
[CrossRef]

1994 (1)

H. R. Gordon, M. Wang, “Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: a preliminary algorithm,” Appl. Opt. 33, 443–452 (1994).
[CrossRef]

1990 (1)

B. G. Mitchell, “Algorithms for determining the absorption coefficient for aquatic particulates using the quantitative filter technique,” Proc. SPIE 1302, 137 (1990).
[CrossRef]

1989 (2)

C. S. Roesler, M. J. Perry, K. L. Carder, “Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters,” Limnol. Oceanogr. 34, 1510–1523 (1989).
[CrossRef]

A. Morel, J.-F. Berthon, “Surface pigments, algal biomass profiles, and potential production of the euphotic layer: relationships reinvestigated in view of remote-sensing applications,” Limnol. Oceanogr. 34, 1545–1562 (1989).
[CrossRef]

1988 (1)

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. 93, 10909–10924 (1988).
[CrossRef]

1987 (1)

A. Morel, “Chlorophyll-specific scattering coefficient of phytoplankton: a simplified theoretical approach,” Deep Sea Res. 34, 1093–1105 (1987).

1985 (1)

M. Kishino, N. Okami, S. Ichimura, “Estimation of the spectral absorption coefficients of phytoplankton in the sea,” Bulletin of Marine Science 37, 634–642 (1985).

1975 (1)

H. R. Gordon, W. R. McCluney, “Estimation of the depth of sunlight penetration in the sea for remote sensing,” Appl. Opt. 14, 413–416 (1975).
[CrossRef]

Ahmad, Z.

M. Tzortziou, J. R. Hermn, C. L. Gallegos, P. J. Neale, A. Subramaniam, L. W. Harding, Z. Ahmad, “Bio-optics of the Chesapeake Bay from measurements and radiative transfer closure,” Estuarine, Coastal Shelf Sci. 68, 348–362 (2006).
[CrossRef]

Aiken, J.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, Y. Yamanaka, “Synoptic relationships between surface chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeoscience 8, 311–327 (2011).

T. Hirata, J. Aiken, N. Hardman-Mountford, T. J. Smyth, R. G. Barlow, “An absorption model to determine phytoplankton size classes from satellite ocean colour,” Remote Sens. Environ. 112, 3153–3159 (2008).
[CrossRef]

J. Aiken, J. R. Fishwick, S. Lavender, R. Barlow, G. F. Moore, H. Sessions, S. Bernard, J. Ras, N. J. Hardman-Mountford, “Validation of MERIS reflectances and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters,” Int. J. Remote Sens. 28, 497–516 (2007).
[CrossRef]

Al-Azri, A. R. N.

H. D. R. Gomes, J. I. Goes, S. G. P. Matondkar, S. G. Parab, A. R. N. Al-Azri, P. G. Thoppil, “Blooms of Noctiluca miliaris in the Arabian Sea–an in situ and satellite study,” Deep Sea Res. I 55, 751–765 (2008).

Allali, K.

A. Bricaud, A. Morel, M. Babin, K. Allali, H. Clauster, “Variations of light absorption by suspended particles with chlorophyll-a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models,” J. Geophys. Res. 103, 31033–31044 (1998).
[CrossRef]

Alvain, S.

S. Alvain, H. Loisel, D. Dessailly, “Theoretical analysis of ocean color radiances anomalies and implications for phytoplankton groups detection in case 1 waters,” Opt. Express 20, 1070–1083 (2012).
[CrossRef]

Antoine, D.

P. J. Werdell, B. A. Franz, S. W. Bailey, G. C. Feldman, E. Boss, V. E. Brando, M. Dowell, T. Hirata, S. J. Lavender, Z.-P. Lee, H. Loisel, S. Maritorena, F. Mélin, T. S. Moore, T. J. Smyth, D. Antoine, E. Devred, O. H. Fanton d’Andon, A. Mangin, “A generalized ocean color inversion model for retrieving marine inherent optical properties,” Appl. Opt. 52, 2019–2037 (2013).
[CrossRef]

E. Martinez, D. Antoine, F. D’Ortenzio, B. Gentili, “Climate-driven basin-scale decadal oscillations of oceanic phytoplankton,” Science 326, 1253–1256 (2009).
[CrossRef]

Arnone, R.

Z.-P. Lee, K. Carder, R. Arnone, M.-X. He, “Determination of primary spectral bands for remote sensing of aquatic environments,” Sensors 7, 3428–3441 (2007).
[CrossRef]

Z.-P. Lee, K. L. Carder, R. Arnone, “Deriving inherent optical properties form water color: a multi-band quasi-analytical algorithm for optically deep water,” Appl. Opt. 41, 5755–5772 (2002).
[CrossRef]

Arnone, R. A.

M. Sydor, R. W. Gould, R. A. Arnone, V. I. Haltrin, W. Goode, “Uniqueness in remote sensing of inherent optical properties of ocean water,” Appl. Opt. 43, 2156–2162 (2004).
[CrossRef]

Artigas, L. F.

B. Lubac, H. Loisel, N. Guiselin, R. Astoreca, L. F. Artigas, X. Mériaux, “Hyperspectral and multispectral ocean color inversions to detect Phaeocystis globosa blooms in coastal waters,” J. Geophys. Res. 113, C06026 (2008).
[CrossRef]

Astoreca, R.

B. Lubac, H. Loisel, N. Guiselin, R. Astoreca, L. F. Artigas, X. Mériaux, “Hyperspectral and multispectral ocean color inversions to detect Phaeocystis globosa blooms in coastal waters,” J. Geophys. Res. 113, C06026 (2008).
[CrossRef]

Babin, M.

M. Babin, A. Morel, V. Fournier-Sicre, F. Fell, D. Stramski, “Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration,” Limnol. Oceanogr. 48, 843–859 (2003).
[CrossRef]

A. Bricaud, A. Morel, M. Babin, K. Allali, H. Clauster, “Variations of light absorption by suspended particles with chlorophyll-a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models,” J. Geophys. Res. 103, 31033–31044 (1998).
[CrossRef]

Bailey, S. W.

P. J. Werdell, B. A. Franz, S. W. Bailey, G. C. Feldman, E. Boss, V. E. Brando, M. Dowell, T. Hirata, S. J. Lavender, Z.-P. Lee, H. Loisel, S. Maritorena, F. Mélin, T. S. Moore, T. J. Smyth, D. Antoine, E. Devred, O. H. Fanton d’Andon, A. Mangin, “A generalized ocean color inversion model for retrieving marine inherent optical properties,” Appl. Opt. 52, 2019–2037 (2013).
[CrossRef]

P. J. Werdell, S. W. Bailey, B. A. Franz, L. W. Harding, G. C. Feldman, C. R. McClain, “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Remote Sens. Environ. 113, 1319–1330 (2009).
[CrossRef]

B. A. Franz, S. W. Bailey, P. J. Werdell, C. R. McClain, “Sensor-independent approach to the vicarious calibration of satellite ocean color radiometry,” Appl. Opt. 46, 5068–5081 (2007).
[CrossRef]

P. J. Werdell, S. W. Bailey, “An improved in situ bio-optical data set for ocean color algorithm development and satellite data product validation,” Remote Sens. Environ. 98, 122–140 (2005).
[CrossRef]

Baker, K. S.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. 93, 10909–10924 (1988).
[CrossRef]

Barlow, R.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, Y. Yamanaka, “Synoptic relationships between surface chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeoscience 8, 311–327 (2011).

J. Aiken, J. R. Fishwick, S. Lavender, R. Barlow, G. F. Moore, H. Sessions, S. Bernard, J. Ras, N. J. Hardman-Mountford, “Validation of MERIS reflectances and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters,” Int. J. Remote Sens. 28, 497–516 (2007).
[CrossRef]

Barlow, R. G.

T. Hirata, J. Aiken, N. Hardman-Mountford, T. J. Smyth, R. G. Barlow, “An absorption model to determine phytoplankton size classes from satellite ocean colour,” Remote Sens. Environ. 112, 3153–3159 (2008).
[CrossRef]

Barnard, A. H.

J. R. V. Zaneveld, A. H. Barnard, E. Boss, “Theoretical derivation of the depth average of remotely sensed optical parameters,” Opt. Express 13, 9052–9061 (2005).
[CrossRef]

M. S. Twardowski, E. Boss, J. B. Macdonald, W. S. Pegain, A. H. Barnard, J. R. V. Zaneveld, “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,” J. Geophys. Res. 106, 14129–14142 (2001).
[CrossRef]

Basu, S.

H. D. R. Gomes, J. I. Goes, S. G. P. Matondkar, E. Buskey, S. Basu, S. Parab, P. Thoppil, “Massive outbreaks of Noctiluca scintillans blooms in the Arabian Sea due to spread of hypoxia,” Nat. Commun. (submitted).

Beaulieu, C.

S. A. Henson, J. L. Sarmiento, J. P. Dunne, L. Bopp, I. Lima, S. C. Doney, J. John, C. Beaulieu, “Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity,” Biogeoscience 7, 621–640 (2010).
[CrossRef]

Behrenfeld, M. J.

M. J. Behrenfeld, R. T. O’Malley, D. A. Siegel, C. R. McClain, J. L. Sarmiento, G. C. Feldman, A. J. Milligan, P. G. Falkowski, R. M. Letelier, E. S. Boss, “Climate-driven trends in contemporary ocean productivity,” Nature 444, 752–755 (2006).
[CrossRef]

Bernard, S.

J. Aiken, J. R. Fishwick, S. Lavender, R. Barlow, G. F. Moore, H. Sessions, S. Bernard, J. Ras, N. J. Hardman-Mountford, “Validation of MERIS reflectances and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters,” Int. J. Remote Sens. 28, 497–516 (2007).
[CrossRef]

Berthon, J.-F.

A. Morel, J.-F. Berthon, “Surface pigments, algal biomass profiles, and potential production of the euphotic layer: relationships reinvestigated in view of remote-sensing applications,” Limnol. Oceanogr. 34, 1545–1562 (1989).
[CrossRef]

Bogucki, D.

D. Stramski, E. Boss, D. Bogucki, K. J. Voss, “The role of seawater constituents in light backscattering in the ocean,” Prog. Oceanogr. 61, 27–56 (2004).
[CrossRef]

Bogucki, D. J.

D. J. Bogucki, G. Spiers, “What percentage of the oceanic mixed layer is accessible to marine lidar? Global and the Gulf of Mexico prospective,” Opt. Express 21, 23997–24014 (2013).
[CrossRef]

Bopp, L.

S. A. Henson, J. L. Sarmiento, J. P. Dunne, L. Bopp, I. Lima, S. C. Doney, J. John, C. Beaulieu, “Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity,” Biogeoscience 7, 621–640 (2010).
[CrossRef]

Boss, E.

P. J. Werdell, B. A. Franz, S. W. Bailey, G. C. Feldman, E. Boss, V. E. Brando, M. Dowell, T. Hirata, S. J. Lavender, Z.-P. Lee, H. Loisel, S. Maritorena, F. Mélin, T. S. Moore, T. J. Smyth, D. Antoine, E. Devred, O. H. Fanton d’Andon, A. Mangin, “A generalized ocean color inversion model for retrieving marine inherent optical properties,” Appl. Opt. 52, 2019–2037 (2013).
[CrossRef]

P. J. Werdell, B. A. Franz, J. T. Lefler, W. D. Robinson, E. Boss, “Retrieving marine inherent optical properties from satellite using temperature and salinity-dependent backscattering by seawater,” Opt. Express 21, 32611–32622 (2013).

P. J. Werdell, C. W. Proctor, E. Boss, T. Leeuw, M. Ouhssain, “Underway sampling of marine inherent optical properties on the Tara Oceans expedition as a novel resource for ocean color satellite data product validation,” Meth. Oceanogr. 7, 40–51 (2013).
[CrossRef]

A. Whitmire, E. Boss, T. J. Cowles, W. S. Pegau, “Spectral variability of the particulate backscattering ratio,” Opt. Express 15, 7019–7031 (2007).
[CrossRef]

J. R. V. Zaneveld, A. H. Barnard, E. Boss, “Theoretical derivation of the depth average of remotely sensed optical parameters,” Opt. Express 13, 9052–9061 (2005).
[CrossRef]

P. Wang, E. Boss, C. S. Roesler, “Uncertainties of inherent optical properties obtained from semi-analytical inversions of ocean color,” Appl. Opt. 44, 4074–4085 (2005).
[CrossRef]

D. Stramski, E. Boss, D. Bogucki, K. J. Voss, “The role of seawater constituents in light backscattering in the ocean,” Prog. Oceanogr. 61, 27–56 (2004).
[CrossRef]

M. S. Twardowski, E. Boss, J. B. Macdonald, W. S. Pegain, A. H. Barnard, J. R. V. Zaneveld, “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,” J. Geophys. Res. 106, 14129–14142 (2001).
[CrossRef]

Boss, E. S.

M. J. Behrenfeld, R. T. O’Malley, D. A. Siegel, C. R. McClain, J. L. Sarmiento, G. C. Feldman, A. J. Milligan, P. G. Falkowski, R. M. Letelier, E. S. Boss, “Climate-driven trends in contemporary ocean productivity,” Nature 444, 752–755 (2006).
[CrossRef]

Boyce, D. G.

D. G. Boyce, M. R. Lewis, B. Worm, “Global phytoplankton decline over the past century,” Nature 466, 591–596 (2010).
[CrossRef]

Bracher, A.

A. Bracher, M. Vountas, T. Dinter, J. P. Burrows, R. Rottgers, I. Peeken, “Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data,” Biogeoscience 6, 751–764 (2009).

Brando, V. E.

P. J. Werdell, B. A. Franz, S. W. Bailey, G. C. Feldman, E. Boss, V. E. Brando, M. Dowell, T. Hirata, S. J. Lavender, Z.-P. Lee, H. Loisel, S. Maritorena, F. Mélin, T. S. Moore, T. J. Smyth, D. Antoine, E. Devred, O. H. Fanton d’Andon, A. Mangin, “A generalized ocean color inversion model for retrieving marine inherent optical properties,” Appl. Opt. 52, 2019–2037 (2013).
[CrossRef]

V. E. Brando, A. G. Dekker, Y. J. Park, T. Schroeder, “Adaptive semi-analytic inversion of ocean color radiometry in optically complex waters,” Appl. Opt. 51, 2808–2833 (2012).
[CrossRef]

Brewin, R. J. W.

R. J. W. Brewin, E. Devred, S. Sathyendranath, S. J. Lavender, N. J. Hardman-Mountford, “Model of phytoplankton absorption based on three size classes,” Appl. Opt. 50, 4535–4549 (2011).
[CrossRef]

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, Y. Yamanaka, “Synoptic relationships between surface chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeoscience 8, 311–327 (2011).

R. J. W. Brewin, N. J. Hardman-Mountford, S. J. Lavender, D. E. Raitsos, T. Hirata, J. Uitz, E. Devred, A. Bricaud, A. Ciotti, B. Gentili, “An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing,” Remote Sens. Environ. 115, 325–339 (2011).
[CrossRef]

Bricaud, A.

R. J. W. Brewin, N. J. Hardman-Mountford, S. J. Lavender, D. E. Raitsos, T. Hirata, J. Uitz, E. Devred, A. Bricaud, A. Ciotti, B. Gentili, “An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing,” Remote Sens. Environ. 115, 325–339 (2011).
[CrossRef]

A. M. Ciotti, A. Bricaud, “Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water-leaving radiances at SeaWiFS channels in a continental shelf region off Brazil,” Limnol. Oceanogr. 4, 237–253 (2006).
[CrossRef]

A. Bricaud, A. Morel, M. Babin, K. Allali, H. Clauster, “Variations of light absorption by suspended particles with chlorophyll-a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models,” J. Geophys. Res. 103, 31033–31044 (1998).
[CrossRef]

Brown, J. W.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. 93, 10909–10924 (1988).
[CrossRef]

Brown, O. B.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. 93, 10909–10924 (1988).
[CrossRef]

Burrows, J. P.

A. Bracher, M. Vountas, T. Dinter, J. P. Burrows, R. Rottgers, I. Peeken, “Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data,” Biogeoscience 6, 751–764 (2009).

Buskey, E.

H. D. R. Gomes, J. I. Goes, S. G. P. Matondkar, E. Buskey, S. Basu, S. Parab, P. Thoppil, “Massive outbreaks of Noctiluca scintillans blooms in the Arabian Sea due to spread of hypoxia,” Nat. Commun. (submitted).

Campbell, J. W.

T. S. Moore, J. W. Campbell, M. D. Dowell, “A class-based approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product,” Remote Sens. Environ. 113, 2424–2430 (2009).
[CrossRef]

Carder, K.

Z.-P. Lee, K. Carder, R. Arnone, M.-X. He, “Determination of primary spectral bands for remote sensing of aquatic environments,” Sensors 7, 3428–3441 (2007).
[CrossRef]

Carder, K. L.

Z.-P. Lee, K. L. Carder, R. Arnone, “Deriving inherent optical properties form water color: a multi-band quasi-analytical algorithm for optically deep water,” Appl. Opt. 41, 5755–5772 (2002).
[CrossRef]

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, C. R. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. 103, 24937–24953 (1998).
[CrossRef]

C. S. Roesler, M. J. Perry, K. L. Carder, “Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters,” Limnol. Oceanogr. 34, 1510–1523 (1989).
[CrossRef]

Caverhill, C.

S. Sathyendranath, L. Watts, E. Devred, T. Platt, C. Caverhill, H. Maass, “Discrimination of diatoms from other phytoplankton using ocean-color data,” Mar. Ecol. Prog. Ser. 272, 59–68 (2004).
[CrossRef]

Chami, M.

M. Defoin-Platel, M. Chami, “How ambiguous is the inverse problem of ocean color in coastal waters?” J. Geophys. Res. 112, C03004 (2007).
[CrossRef]

Ciotti, A.

R. J. W. Brewin, N. J. Hardman-Mountford, S. J. Lavender, D. E. Raitsos, T. Hirata, J. Uitz, E. Devred, A. Bricaud, A. Ciotti, B. Gentili, “An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing,” Remote Sens. Environ. 115, 325–339 (2011).
[CrossRef]

Ciotti, A. M.

A. M. Ciotti, A. Bricaud, “Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water-leaving radiances at SeaWiFS channels in a continental shelf region off Brazil,” Limnol. Oceanogr. 4, 237–253 (2006).
[CrossRef]

Clark, D. K.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. 93, 10909–10924 (1988).
[CrossRef]

Clauster, H.

A. Bricaud, A. Morel, M. Babin, K. Allali, H. Clauster, “Variations of light absorption by suspended particles with chlorophyll-a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models,” J. Geophys. Res. 103, 31033–31044 (1998).
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S. A. Henson, J. L. Sarmiento, J. P. Dunne, L. Bopp, I. Lima, S. C. Doney, J. John, C. Beaulieu, “Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity,” Biogeoscience 7, 621–640 (2010).
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P. J. Werdell, S. W. Bailey, B. A. Franz, L. W. Harding, G. C. Feldman, C. R. McClain, “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Remote Sens. Environ. 113, 1319–1330 (2009).
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Sensors (1)

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Figures (11)

Fig. 1.
Fig. 1.

Absorption spectra for N. miliaris and diatoms, normalized to 440 nm [7]. Thin blue lines show spectra from in situ stations dominated by diatoms, with the thick blue line indicating the mean spectrum. Thin orange lines show spectra from in situ stations dominated by N. miliaris, with the thick red line indicating the mean spectrum. The average a ϕ D * ( 440 ) and a ϕ N * ( 440 ) were 0.052 ( ± 0.022 ) and 0.066 ( ± 0.015 ) m 2 mg 1 , respectively. Vertical solid lines indicate center MODISA wavelengths. Vertical dotted lines show the additional wavelengths considered in this study.

Fig. 2.
Fig. 2.

Example simulated profiles for C ϕ , absorption coefficients at 443 nm, and scattering coefficients at 443 nm. The simulation parameters for these profiles are: C ϕ D = 1 mg m 3 , N Z = 5 m , N W = 5 m , N max = 6 mg m 3 , a d ( 443 ) = 0.02 m 1 , a g ( 443 ) = 0.05 m 1 , and b d ( 555 ) = 0.2 m 1 (Table 1). Panel (A) shows C ϕ and C ϕ D and indicates the three parameters that describe the Gaussian-shaped C ϕ N ( N Z , N W , and N max ). Panel (B) shows the corresponding a ϕ N ( 443 ) , a ϕ D ( 443 ) , a d ( 443 ) , and a g ( 443 ) . Panel (C) shows the corresponding b ϕ N ( 443 ) , b ϕ D ( 443 ) , and b d ( 443 ) .

Fig. 3.
Fig. 3.

R rs ( λ ) collected in situ (thick black lines) and synthesized using HE5 (colored thin lines). Panel (A) shows all synthesized and in situ R rs ( λ ) . Panel (B) shows only synthesized R rs ( λ ) with optically weighted C ϕ ranging from 0.95 to 1.05 mg m 3 . Colors are only used to visually distinguish between spectra.

Fig. 4.
Fig. 4.

Comparison of ground-truth (synthesized) and ORM-derived b b p ( 443 ) (A) and (B), a p g ( 443 ) (C) and (D), and a ϕ ( 443 ) (E) and (F) using all available wavelengths in the inversion (left column) and only MODISA visible wavelengths in the inversion (right column). Colors show the numerical density of the retrievals, with red to purple indicating high to low volumes of sample sizes. We present comparative statistics in Table 2.

Fig. 5.
Fig. 5.

Optically weighted C ϕ and corresponding R rs ( λ ) as a function of N. miliaris bloom depth ( N Z ) and magnitude ( N max ). This subset of simulations has constant C ϕ D ( = 0.5 mg m 3 ), N W ( = 5 m ) , a g ( 443 ) ( = 0.005 m 1 ) , a d ( 443 ) ( = 0.002 m 1 ) , and b p ( 555 ) ( = 0.1 m 1 ) . Panel (A) shows optically weighted C ϕ versus bloom depth, with colors representing different bloom magnitudes. Panel (B) shows R rs ( λ ) for a bloom magnitude of 0.5 mg m 3 , with different line styles representing different bloom depths. Panels (C)–(E) follow Panel (B), but for bloom magnitudes of 1, 3, and 6 mg m 3 . Colors in Panels (B)–(E) follow Panel (A) for clarity.

Fig. 6.
Fig. 6.

Comparison of ground-truth (synthesized) and ORM-derived C ϕ (A) and (B), C ϕ D (C) and (D), and C ϕ N (E) and (F) using all available wavelengths in the inversion (left column) and only MODISA visible wavelengths in the inversion (right column). Colors as in Fig. 4.

Fig. 7.
Fig. 7.

Comparison of ground-truth (synthesized) and ORM-derived C ϕ D and C ϕ N for a mono-species subset of simulations using all available wavelengths in the inversion (left column) and only MODISA visible wavelengths in the inversion (right column). We considered only synthesized C ϕ D = 0.02 and C ϕ N 0.5 mg m 3 in panels (A) and (B). We considered only synthesized C ϕ D 0.1 and C ϕ N = 0 mg m 3 in panels (C) and (D). Crosses and filled circles show C ϕ N and C ϕ D , respectively.

Fig. 8.
Fig. 8.

Five example simulated R rs ( λ ) and their corresponding ORM-derived C ϕ . Each simulation was created using a d ( 443 ) = 0.002 , a g ( 443 ) = 0.005 , and b d ( 555 ) = 0.1 m 1 . Panel (A) presents spectra for C ϕ D 0.5 mg m 3 without N. miliaris (black) and C ϕ N 0.5 mg m 3 without diatoms (orange). Panel (B) presents spectra for C ϕ D 1 mg m 3 without N. miliaris (blue), C ϕ N 1 mg m 3 without diatoms (green), and a mixed population with C ϕ D and C ϕ N 0.5 mg m 3 each (red). Panel (C) presents ground-truth (synthesized) versus ORM comparisons, with colors referring to the corresponding R rs ( λ ) , and circles, crosses, and asterisks indicating C ϕ , C ϕ D , and C ϕ N , respectively.

Fig. 9.
Fig. 9.

Comparisons of ground-truth (synthesized) and ORM-derived C ϕ N (left column) and C ϕ D (center column) using all available wavelengths in the inversion. Results are stratified by depth of the N. miliaris subsurface maxima, with N Z = 1 , 5, 10, and 15 m shown from top to bottom. The right column presents frequency distributions of relative percent differences, calculated as 100%* (ORM/synthesized-1). Solid and dotted lines indicate differences for C ϕ N and C ϕ D , respectively.

Fig. 10.
Fig. 10.

Comparisons of ground-truth (synthesized) and ORM-derived C ϕ N using all available wavelengths in the inversion. Results are stratified by the varied a g ( 443 ) (left), a d ( 443 ) (center), and b d ( 555 ) (right) used to generate the synthesized IOP profiles and R rs ( λ ) .

Fig. 11.
Fig. 11.

C ϕ versus b b p ( 443 ) . Panel (A) shows C ϕ from our simulated profiles versus backscattering from HE5. Panel (B) shows C ϕ from the ORM versus backscattering from the ORM. Colors indicate the magnitude of C ϕ N in mg m 3 .

Tables (4)

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Table 1. Values Used to Simulate Vertical IOP Profiles for Input in HE5

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Table 2. Ordinary Least Squares Regression Statistics for Ground-Truth-Synthesized Versus ORM-Derived IOPs a

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Table 3. Optically weighted C ϕ , K d ( 490 ) , and z 90 for the Example Simulations Presented in Fig. 5

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Table 4. Median Relative Percent Differences (MPD) and Absolute Biases between the Ground-Truth-Synthesized and ORM-Derived C ϕ N and C ϕ D a

Equations (11)

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r rs ( λ , 0 ) = R rs ( λ ) 0.52 + 1.7 R rs ( λ ) .
r rs ( λ , 0 ) = 0.0949 u ( λ ) + 0.0794 u ( λ ) 2 u ( λ ) = b b ( λ ) a ( λ ) + b b ( λ ) ,
a ( λ ) = a w ( λ ) + M ϕ a ϕ * ( λ ) + M d g a d g * ( λ ) ,
M ϕ a ϕ * ( λ ) = M ϕ D a ϕ D * ( λ ) + M ϕ N a ϕ N * ( λ ) ,
b b ( λ ) = b b w ( λ ) + M b p b b p * ( λ ) ,
a p g ( λ , z ) = a d g ( λ , z ) + a ϕ D ( λ ) + a ϕ N ( λ ) a p g ( λ , z ) = a d g ( λ , z ) + C ϕ D ( z ) a ϕ D * ( λ ) + C ϕ N ( z ) a ϕ N * ( λ ) ,
c p g ( λ , z ) = a p g ( λ , z ) + b p ( λ , z ) ,
b p ( λ , z ) = b d ( λ ) + b ϕ D ( λ ) + b ϕ N ( λ ) b p ( λ , z ) = M d ( z ) b d * ( λ ) + C ϕ D ( z ) b ϕ D * ( λ ) + C ϕ N ( z ) b ϕ N * ( λ ) .
b p ( λ , z ) = b d ( 555 , z ) ( λ 555 ) η d + C ϕ D ( z ) b ϕ D * ( 555 ) ( λ 555 ) η ϕ D + C ϕ N ( z ) b ϕ N * ( 555 ) ( λ 555 ) η ϕ N .
a d g ( λ , z ) = M d ( z ) a d * ( λ ) + M g ( z ) a g * ( λ ) a d g ( λ , z ) = a d ( 443 , z ) exp ( S d ( λ 443 ) ) + a g ( 443 , z ) exp ( S g ( λ 443 ) ) .
a ϕ * ( λ ) = C ϕ N C ϕ N + C ϕ D a ϕ N * ( λ ) + C ϕ D C ϕ N + C ϕ D a ϕ D * ( λ ) .

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