Particulate optical scattering coefficients along an Atlantic Meridional Transect

doi:10.1364/OE.20.021532

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Particulate optical scattering coefficients along an Atlantic Meridional Transect

G. Dall’Olmo, E. Boss, M.J. Behrenfeld, and T.K. Westberry »View Author Affiliations

Optics Express, Vol. 20, Issue 19, pp. 21532-21551 (2012)
http://dx.doi.org/10.1364/OE.20.021532

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– Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
5. Conclusions
– References and links

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Abstract

The particulate optical backscattering coefficient (b_bp) is a fundamental optical property that allows monitoring of marine suspended particles both in situ and from space. Backscattering measurements in the open ocean are still scarce, however, especially in oligotrophic regions. Consequently, uncertainties remain in b_bp parameterizations as well as in satellite estimates of b_bp. In an effort to reduce these uncertainties, we present and analyze a dataset collected in surface waters during the 19^th Atlantic Meridional Transect. Results show that the relationship between particulate beam-attenuation coefficient (c_p) and chlorophyll-a concentration was consistent with published bio-optical models. In contrast, the particulate backscattering per unit of chlorophyll-a and per unit of c_p were higher than in previous studies employing the same sampling methodology. These anomalies could be due to a bias smaller than the current uncertainties in b_bp. If that was the case, then the AMT19 dataset would confirm that b_bp:c_p is remarkably constant over the surface open ocean. A second-order decoupling between b_bp and c_p was, however, evident in the spectral slopes of these coefficients, as well as during diel cycles. Overall, these results emphasize the current difficulties in obtaining accurate b_bp measurements in the oligotrophic ocean and suggest that, to first order, b_bp and c_p are coupled in the surface open ocean, but they are also affected by other geographical and temporal variations.

1. Introduction

Ocean biogeochemical cycles are tightly linked to the dynamics of suspended particles such as phytoplankton, heterotrophic organisms, detritus, and minerals. Understanding these dynamics is an important objective of oceanographic research and much can be learned by interpreting optical scattering measurements. Optical scattering can be measured remotely either by inversion of satellite ocean color data [1

IOCCG, Remote sensing of inherent optical properties: fundamentals, tests of algorithms, and applications. , Report Number 5 (International Ocean Colour Coordination Group, 2006).

] or by in situ autonomous platforms, such as floats and gliders [2

J. K. B. Bishop, “Autonomous observations of the ocean biological carbon pump,” Oceanography 22, 182–193 (2009). [CrossRef]

–5

IOCCG, Bio-optical sensors on Argo floats , Report Number 11 (International Ocean Colour Coordination Group, 2011).

]. Unraveling the links between optical scattering and the concentrations and characteristics of oceanic particles, therefore, has the potential of extending the range over which these particles and their dynamics can be observed.

The following inherent optical properties are typically employed to characterize the scattering of light by marine particles: the particulate backscattering, scattering, and beam-attenuation coefficients (b_bp, b_p, and c_p, respectively). Note that b_p and c_p are approximately equal in clear waters, due to the low influence of particulate absorption (a_p) on c_p [7

H. Loisel and A. Morel, “Light scattering and chlorophyll concentration in case 1 waters: A reexamination,” Limnol. Oceanogr. 43, 847–858 (1998). [CrossRef]

, 8

T. K. Westberry, G. Dall’Olmo, E. Boss, M. J. Behrenfeld, and T. Moutin, “Coherence of particulate beam attenuation and backscattering coefficients in diverse open ocean environments,” Opt. Express 18, 15419–15425 (2010). [CrossRef]

Previous studies demonstrated that b_bp, b_p and c_p are to first order correlated to the concentration of chlorophyll-a (Chl), which is often considered an index of phytoplankton abundance [7

H. Loisel and A. Morel, “Light scattering and chlorophyll concentration in case 1 waters: A reexamination,” Limnol. Oceanogr. 43, 847–858 (1998). [CrossRef]

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

,10

Y. Huot, A. Morel, M. S. Twardowski, D. Stramski, and R. A. Reynolds, “Particle optical backscattering along a chlorophyll gradient in the upper layer of the eastern south pacific ocean,” Biogeosci. 5, 495–507 (2008). [CrossRef]

]. More recently, however, it has been shown that these relationships are inherently noisy, because the Chl signal is strongly impacted by physiological variability [8

, 11

M. J. Behrenfeld and E. Boss, “The beam attenuation to chlorophyll ratio: an optical index of phytoplankton physiology in the surface ocean?” Deep-Sea Res. Part I 50, 1537–1549 (2003). [CrossRef]

–13

D. Antoine, D. A. Siegel, T. Kostadinov, S. Maritorena, N. B. Nelson, B. Gentili, V. Vellucci, and N. Guillocheau, “Variability in optical particle backscattering in contrasting bio-optical oceanic regimes,” Limnol. Oceanogr. 56, 955–973 (2011). [CrossRef]

The particulate optical scattering is thought to be generated by particles in the phytoplankton size range (0.5–20 μm, e.g., ref. [14

H. Pak, D. A. Kiefer, and J. C. Kitchen, “Meridional variations in the concentration of chlorophyll and microparticles in the north Pacific ocean,” Deep Sea Res. Part A 35, 1151–1171 (1988). [CrossRef]

, 15

D. Stramski and D. Kiefer, “Light scattering by microorganisms in the open ocean,” Progr. Oceanogr. 28, 343–383 (1991). [CrossRef]

]). The particle size domain responsible for b_bp, on the other hand, remains uncertain. Some studies suggest that b_bp is governed by submicron detrital particles and minerals [15

D. Stramski and D. Kiefer, “Light scattering by microorganisms in the open ocean,” Progr. Oceanogr. 28, 343–383 (1991). [CrossRef]

–18

D. Stramski, A. Bricaud, and A. Morel, “Modeling the inherent optical properties of the ocean based on the detailed composition of the planktonic community,” Appl. Opt. 40, 2929–2945 (2001). [CrossRef]

], while others have shown the importance of larger particles (including phytoplankton cells) in generating the observed b_bp variability [12

G. Dall’Olmo, T. K. Westberry, M. J. Behrenfeld, E. Boss, and W. H. Slade, “Significant contribution of large particles to optical backscattering in the open ocean,” Biogeosci. 6, 947–967 (2009). [CrossRef]

, 19

M. S. Quinby-Hunt, A. J. Hunt, K. Lofftus, and D. Shapiro, “Polarized-light scattering studies of marine chlorella,” Limnol. Oceanogr. 34, 1587–1600 (1989). [CrossRef]

, 20

J. C. Kitchen and J. R. V. Zaneveld, “A three-layered sphere model of the optical properties of phytoplankton,” Limnol. Oceanogr. 37, 1680–1690 (1992). [CrossRef]

The particulate backscattering efficiency (b_bp:b_p) is less dependent on the absolute concentration of particles than either property alone and is largely governed by particle size, composition, and morphology [22

O. Ulloa, S. Sathyendranath, and T. Platt, “Effect of the particle-size distribution on the backscattering ratio in seawater,” Appl. Opt. 33, 7070–7077 (1994). [CrossRef]

, 23

M. S. Twardowski, E. Boss, J. B. Macdonald, W. S. Pegau, A. H. Barnard, and 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.-Oceans 106, 14129–14142 (2001). [CrossRef]

]. Highly refractive particles, such as the minerals contained in atmospheric dust or coccolithophorids, are expected to be associated with high b_bp:b_p [22

O. Ulloa, S. Sathyendranath, and T. Platt, “Effect of the particle-size distribution on the backscattering ratio in seawater,” Appl. Opt. 33, 7070–7077 (1994). [CrossRef]

–24

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

]. On the other hand, b_bp:b_p for a given particle composition should, to first order, increase when small particles become relatively more abundant than large particles [22

O. Ulloa, S. Sathyendranath, and T. Platt, “Effect of the particle-size distribution on the backscattering ratio in seawater,” Appl. Opt. 33, 7070–7077 (1994). [CrossRef]

,23

]. However, the uncertainties on the sources of b_p and b_bp as well as potential limitations in current optical models of oceanic particles may limit the interpretation of the b_bp:b_p ratio.

Experimental studies have demonstrated a relatively large range of variation for b_bp:b_p (i.e., approximately 0.2%–2%, refs. [8

, 12

, 13

, 24

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

–26

D. Stramski, “Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern south Pacific and eastern Atlantic oceans (vol 5 pg 171, 2008),” Biogeosci. 5, 595–595 (2008). [CrossRef]

]), in part due to difficulties in accurately determining b_bp in clear oligotrophic waters. Nevertheless, a surprisingly coherent value for b_bp:b_p of around 1% was recently reported in diverse surface open-ocean waters, using data from a series of cruises where scattering measurements were conducted using a consistent methodology [8

]. Although other studies have also measured similar backscattering ratios [24

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

], this finding suggests that methodology may be an important source of uncertainty in b_bp and b_p measurements, especially in clear oligotrophic waters.

Both c_p and b_bp vary spectrally and their spectral dependency is commonly modelled as a power law [28

A. Morel, “Optical modeling of the upper ocean in relation to its biogenous matter content (case 1 water),” J. Geophys. Res.-Oceans 93, 10749–10768 (1988). [CrossRef]

c_{p} (λ) = c_{p} (λ_{0}) {(\frac{λ}{λ_{0}})}^{- γ_{c p}}

(1)

b_{b p} (λ) = b_{b p} (λ_{0}) {(\frac{λ}{λ_{0}})}^{- γ_{b b p}}

(2)

where γ_cp and γ_bbp are the spectral slopes of c_p and b_bp, respectively, and λ₀ is a reference wavelength. If particles are non-absorbing and their sizes are distributed according to a power law with exponent η over the entire range of particle sizes, then γ_cp ≅ η − 3 (Voltz, 1954 cited in ref. [6

H. C. van de Hulst, Light Scattering by Small Particles (Wiley, New York, 1957).

]; [29

A. Morel, Advisory Group for Aerospace Research and Development (NATO, 1973), chap. Diffusion de la lumiere par les eaux de mer. Resultat experimentaux et approach theorique, 3.1.1–76.

]; see also [30

E. Boss, M. S. Twardowski, and S. Herring, “Shape of the particulate beam attenuation spectrum and its inversion to obtain the shape of the particulate size distribution,” Appl. Opt. 40, 4885–4893 (2001). [CrossRef]

]). This latter equation establishes a link between the spectral properties of c_p and the relative distribution of large vs. small particles and it has been verified with in situ measurements from coastal waters [30

]. A drawback of using the spectral slope of c_p to infer information on the particle size distribution is that the particulate beam-attenuation coefficient cannot be determined from space. Moreover, due to the finite acceptance angle of commercial instruments, c_p and b_p are never exactly measured [31

E. Boss, W. H. Slade, M. Behrenfeld, and G. Dall’Olmo, “Acceptance angle effects on the beam attenuation in the ocean,” Opt. Express 17, 1535–1550 (2009). [CrossRef]

Loisel et al. (2006) inverted space-based ocean color measurements to estimate the spectral slope of b_bp [32

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

]. These authors found that γ_bbp exhibited positive values (relatively more small particles) in oligotrophic waters and negative values (relatively more large particles) in more eutrophic waters. Building on this insight, Kostadinov and collaborators [33

T. S. Kostadinov, D. A. Siegel, and S. Maritorena, “Retrieval of the particle size distribution from satellite ocean color observations,” J. Geophys. Res.-Oceans 114, C09015 (2009). [CrossRef]

] developed an inversion algorithm to relate γ_bbp to the slope of the particle size distribution and produced global maps of the abundances of three different size classes of phytoplankton [34

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

Despite these developments, simultaneous measurements of b_p and b_bp in the open ocean are still limited, especially in oligotrophic regions. Here, we present and analyze a dataset of particulate scattering and backscattering measurements collected during the 19^th Atlantic Meridional Transect (AMT19). Our main objectives are to investigate the variability of b_bp and c_p and to test existing bio-optical relationships. We show that b_bp was relatively high in the Atlantic compared to previous data from other oceanic regions. This discrepancy could either be due to a more significant contribution from particles smaller than 0.2 μm or, most likely, to a small bias in our measurements. In the latter case, this analysis confirms that the shape of the volume scattering function of marine particles is remarkably constant.

2. Methods

Data were collected on board the RRS James Cook from October 13^th to December 1^st 2009 covering a meridional transect approximately from 45°N to 40°S (Fig. 1).

Fig. 1 Locations of CTD casts during AMT19 indicating the cruise track. Background colors represent the bathimetry.

2.1. Flow through optical measurements

Optical measurements were conducted on seawater from the ship’s clean flow-through system pumped from a depth of about 5 m. The methodology described in ref. [12

] was followed, including one-minute data binning and the use of a 0.2μm-cartridge filter (Cole Parmer) through which the water supply was diverted every hour for ten minutes to provide a baseline for particulate absorption and attenuation measurements.

2.1.1. b_bp

Continuous b_bp measurements were made using a WET Labs ECO-BB3 meter (S/N 349, thereafter referred to as BB349) in a flow-through chamber, as described in ref. [12

]. The characterization of the instrument included an evaluation of the effective wavelengths as described in ref. [12

]. The instrument was calibrated by the manufacturer in July 2009. In addition, we conducted calibrations at the beginning (Oct. 20^th, 2009) and end (Nov. 22^nd, 2009) of the cruise, following the same protocol adopted for our previous studies [8

, 12

] and described in the Appendix. Table 1 reports the results of these calibrations and shows that the blue and green channels were relatively stable, while the scaling factor of the red channel (656 nm) varied by 21% from the factory calibration. Because of this drift, data from the red channel were not used in this analysis.

Table 1 Scaling factors for the BB349 and BB499 meters. “Final values” are those used to process the data presented in this study. Absolute uncertainties are standard error of the means of the AMT19 determinations. All values, except relative uncertainties, are in units of sr⁻¹ counts⁻¹ × 10⁻⁶. Number in parentheses are percent changes from the WetLabs (07/2009) calibration.

	BB349			BB499
	470	526	656	470	526	595
WetLabs (07/2009)	6.641	4.349	2.168	6.947	4.396	2.660
AMT19 (20/10/2009)	6.432(−3.2)	4.496(+3.4)	2.323 (+7.1)	7.347(+5.8)	4.975(+13.2)	-
AMT19 (22/11/2009)	6.771 (+2.0)	4.539(+4.4)	2.624(+21.0)	7.216(+3.9)	4.590 (+4.4)	2.535(−4.7)

Final values	6.601	4.517	2.473	7.281	4.782	2.598
Abs. uncertainties	0.170	0.021	0.151	0.066	0.192	0.063
Rel. uncertainties	0.026	0.005	0.061	0.009	0.040	0.024

Three dark counts determinations were carried out during the cruise (yeardays 293, 313, and 326) by covering the detectors with black tape and submerging the instrument in water. Results from these independent replicate measurements indicated that the dark counts varied at most by 2 counts in the blue and green channels, but as much as 6 counts in the red channel (Table 2). In addition, the dark counts determined during the cruise differed considerably from those provided by the manufacturer.

Table 2 Dark counts provided by manufacturer and measured during AMT19. Uncertainties represent half the central 68th percentile of the measurements conducted during AMT19. All units are counts.

	BB349			BB499
	470	526	656	470	526	595
WetLabs	52	46	42	44	42	27
AMT19	56	51	50	53	48	50
AMT19 uncertainties	1.0	1.5	1.5	2.0	2.0	1.5

Average scaling factors, S, and dark counts, D, measured during the cruise were employed in the processing of the BB349 data. The contribution to b_bp by reflections from the internal walls of the flow-through chamber, b_b_,wall, was determined in the laboratory (following the procedure described in ref. [12

]) after the cruise and found to be (3.70 ± 0.83) × 10⁻⁴ m⁻¹ and (3.14 ± 0.52) × 10⁻⁴ m⁻¹ for the blue and green channels, respectively. Calculation of the particulate backscattering coefficient was conducted as in ref. [12

], after subtracting the contribution of pure sea water, β_sw (differences in temperature and salinity were accounted for using data from the ship’s underway CTD system; [36

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

,37

X. Zhang and L. Hu, “Estimating scattering of pure water from density fluctuation of the refractive index,” Opt. Express 17, 1671–1678 (2009). [CrossRef]

]) and using a χ_p factor of 1.1 to relate the volume scattering function at 117° to b_bp [38

E. Boss and W. S. Pegau, “Relationship of light scattering at an angle in the backward direction to the backscattering coefficient,” Appl. Opt. 40, 5503–5507 (2001). [CrossRef]

b_{b p} = 2 π χ_{p} [S (C - D) - β_{s w}] - b_{b, wall}

(3)

where C are the digital counts recorded by the instrument. Finally, the particulate b_bp of water that passed through a 0.2 μm filter (hereafter b_b₀₂) was estimated from the BB349 measurements conducted each hour on the 0.2μm-filtered seawater (details of these calculations can be found in reference [12

]).

To understand how the uncertainty in dark counts affects the resulting b_bp values, the entire BB349 dataset was reprocessed using the dark counts supplied by the manufacturer. Resulting b_bp values were then compared to those derived using dark counts measured during the cruise. Relative differences ranged from 5% to 25% (not shown), with largest values in the clearest waters. This analysis demonstrates the importance of employing field-based determinations of dark counts for achieving maximally accurate b_bp estimates in oligotrophic regions [25

M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]

The combined uncertainty in b_bp due to the uncertainties in all its input parameters (Tables 3, 4) was computed using the standard law of propagation of uncertainty [39

BIPM and ISO, Guide to the Expression of Uncertainty in Measurement (International Organization for Standardization, Geneve, Switzerland, 1995).

] and assuming uncorrelated uncertainties. The median absolute uncertainties were 3.3 × 10⁻⁴ m⁻¹ and 2.5 × 10⁻⁴ m⁻¹, for the blue and green channels, respectively. Relative uncertainties in b_bp ranged approximately from 20% in eutrophic waters to 40% in oligotrophic waters.

Table 3 Uncertainties used to compute the combined experimental uncertainty of b_bp as a function of wavelength. Units of absolute uncertainties are the same as those reported in the text for the corresponding variables.

Variable	BB349		BB499		Reference
Variable	470 nm	526 nm	470 nm	526 nm	Reference
χ_p	2.9%	2.9%	2.9%	2.9%	[44 J. M. Sullivan and M. S. Twardowski, “Angular shape of the oceanic particulate volume scattering function in the backward direction,” App. Opt. 48, 6811–6819 (2009). [CrossRef] ]
S	10%	10%	10%	10%	[35 J.M. Sullivan, C.C. Moore, M.S. Twardowski, and J.R.V. Zaneveld, “Measuring optical backscattering in water” in “Light Scattering Reviews, Volume 7: Radiative transfer and optical properties of atmosphere and underlying surface ” (Praxis Publishing Ltd, in press). ]
C	1.5	2.5	3.0	2.5	measured
D	1.0	1.5	2.0	2.0	measured
β_sw	2.24%	2.24%	2.24%	2.24%	[36 X. Zhang, L. Hu, and M.-X. He, “Scattering by pure seawater: Effect of salinity,” Opt. Express 17, 5698–5710 (2009). [CrossRef] ]
b_b,wall	8.3 × 10⁻⁵	5.2 × 10⁻⁵	-	-	measured

Table 4 Uncertainty budget for b_bp based on the values presented in Table 3 and on all backscattering measurements collected during the cruise in flow-through mode (BB349). Numbers represent the median values of the squared percent contributions,

σ_{rel}^{2}

(unitless), and the median absolute contributions, σ (m⁻¹), by each input variable to the combined experimental uncertainty in b_bp as a function of wavelength.

Variable	$σ_{rel}^{2}$		σ × 10^–4
Variable	470 nm	526 nm	470 nm	526 nm
χ_p	1	1	0.28	0.24
S	85	81	3.01	2.19
C	5	9	0.68	0.78
D	2	4	0.46	0.47
β_sw	1	1	0.38	0.23
b_b,wall	6	4	0.83	0.52

Given that b_bp was accurately determined only at two wavelengths, γ_bbp was derived as γ_bbp = −log[b_bp(470)/b_bp(526)]/log(470/526). These γ_bbp values should be treated with caution, as they may be affected by uncertainties due to the limited number of wavelengths employed in the computation.

2.1.2. c_p, a_p, and b_p

Spectrally-resolved particulate beam-attenuation, c_p, and absorption, a_p, measurements were conducted with WET Labs ACs (hyperspectral between 400 and 750 nm, with a spectral resolution of 5 nm and a band pass of 15 nm) and AC9 (nine wavelengths between 412 and 715 nm, with a band pass of 10 nm) absorption and attenuation meters. The ACs was used from the beginning of the cruise, but after 13 days (i.e., yearday 299) the lamp of the attenuation channel (i.e., C-channel) failed. To ensure continuous measurements of spectral c_p after the ACs failure, the AC9 meter was added to the flow-through system, without removing the ACs. c_p and a_p for the ACs were computed after subtraction of baseline signals derived from the 0.2μm-filtered water following established protocols [12

, 40

W. H. Slade, E. Boss, G. Dall’Olmo, M. R. Langner, J. Loftin, M. J. Behrenfeld, C. Roesler, and T. K. Westberry, “Underway and moored methods for improving accuracy in measurement of spectral particulate absorption and attenuation,” J. Atmos. Ocean. Tech. 27, 1733–1746 (2010). [CrossRef]

]. a_p for the AC9 meter was computed by subtracting the 0.2μm-filtered signal and applying a scattering correction [41

J. R. V. Zaneveld, J. C. Kitchen, and C. C. Moore, “Scattering error correction of reflecting tube absorption meters,” in Ocean Optics XII 2258, S. Ackelson, ed. (SPIE, 1994), 44–55.

]. Particulate scattering coefficients, b_p, were derived as the difference between c_p and a_p. AC9 measurements were linearly interpolated to derive c_p and b_p at 470 and 526 nm. The spectral slope of c_p, γ_cp, was estimated by fitting Eq. (1) to c_p spectra.

2.1.3. Chl

Discrete water samples (2–4 liters) were collected from the flow-through system during the cruise, filtered onto Whatman GF/F filters and immediately stored in liquid nitrogen. Phytoplankton pigments were determined in the laboratory after the cruise by high performance liquid chromatography (HPLC) analysis [42

L. Van Heukelem and C. S. Thomas, “Computer-assisted high-performance liquid chromatography method development with applications to the isolation and analysis of phytoplankton pigments,” J. Chromatogr. A 910, 31–49 (2001). [CrossRef]

]. Total chlorophyll-a concentration (TChl-a) was calculated by summing the contributions of monovinylchl-a, divinyl-chl-a (DivChl-a), and chloro-phyllide a.

The concentration of chlorophyll-a (Chl) was also estimated from the a_p line height around 676 nm as: Chl = [a_p(676) – 39/65a_p(650) – 26/65a_p(715)]/0.014, ref. [43

E. S. Boss, R. Collier, G. Larson, K. Fennel, and W. S. Pegau, “Measurements of spectral optical properties and their relation to biogeochemical variables and processes in crater lake, Crater Lake National Park, OR,” Hydrobiologia 574, 149–159 (2007). [CrossRef]

]. While the AC9 instrument outputs measurements at 650, 676, and 715 nm, the ACs does not. Therefore, the ACs data were linearly interpolated to estimate a_p values at 650, 676, and 714 nm.

As mentioned above, two different instruments (i.e., ACs and AC9) were employed to measure a_p and estimate Chl during the cruise. Therefore, an intercalibration was required to make Chl estimated from the ACs a_p data comparable to the Chl derived from the AC9 a_p data. Simultaneous measurements of a_p by the ACs and AC9 instruments were, however, available only after the failure of the ACs C-channel, used for the scattering correction required to derive the a_p data. Thus, although simultaneous measurements of a_p from the two instruments were available, the a_p spectra derived from the ACs instrument could not be scattering corrected and thus were, in principle, not comparable to the AC9 a_p spectra. The sensitivity of the a_p-based Chl on the scattering correction was therefore investigated by exploiting the ACs a_p measurements collected at the beginning of the cruise, when the ACs C-channel was still functioning. The first 13 days of ACs a_p data were reprocessed without applying any scattering and residual temperature corrections and Chl was derived from these newly processed a_p spectra. The ratio between Chl derived from the ACs with and without the scattering correction was statistically indistinguishable from one (median ± σ₆₈ = 1.03 ± 0.08, where σ₆₈ is half the central 68^th percentile range and is equivalent to one standard deviation, if the data are normally distributed). This result indicates that Chl can be computed from the ACs a_p spectra, even if a scattering correction is not implemented. We therefore compared the Chl values estimated from the simultaneous AC9 and ACs a_p data collected after the failure of the ACs C-lamp, even though no scattering correction could be applied to the ACs a_p data. The ratio of these ACs-to-AC9 Chl was found to be 0.69± 0.08 (median ± σ₆₈), indicating that the Chl derived from the ACs was about 30% lower than that derived from the AC9. This difference is likely due to the “band pass” of the AC9 that is narrower (10 nm) than that of the ACs (15 nm). The median ACs-to-AC9 Chl ratio was finally employed to correct the Chl derived from the AC9 data.

Figure 2 compares coincident HPLC-derived TChl-a and optically-determined Chl (derived from both AC9 and ACs instruments) and shows that the optically-determined Chl was underestimated by about 10% (in median) and had a precision (σ₆₈ of relative residuals) of about 10%. The 10% bias was removed from Chl for the rest of the analysis.

Fig. 2 Comparison between Chl estimated from the AC9 and ACs instruments and HPLC derived TChl. The dashed line is the 1:1 line. N = 109. δ_r and σ_r are robust estimates of relative bias (median of the relative residuals) and precision (σ₆₈ of the relative residuals), respectively.

2.2. Measurements of b_bp from profiling package

An independent WetLabs ECO-BB3 backscattering meter (S/N 499, hereafter BB499) was installed on a profiling package that was deployed daily. The instrument was equipped with spectral channels at 470, 526, and 595 nm.

A calibration based on beads was not completed for this instrument at the beginning of the cruise. However, an intercalibration between flow-through and profiling meters was conducted at the beginning of the cruise (Oct. 16^th–18^th, 2009). This inter comparison consisted of collecting coincident data with the two meters by temporarily installing the profiling meter in a flow-through chamber similar to that where the flow-through meter was installed. Scaling factors,

S_{499}^{i}

, for the profiling BB499 meter were derived as

S_{499}^{i} = 〈 S_{349} (C_{499}^{i} - D_{499}) / (C_{349}^{i} - D_{349}) 〉

, where each variable depends on wavelength, S₃₄₉ is the scaling factor derived for the flow-through instrument as the average of the two cruise calibrations,

C_{349}^{i}

and

C_{499}^{i}

are the coincident raw counts recorded by the two instruments, D₃₄₉ and D₄₉₉ are the corresponding dark counts, and the 〈〉 brackets indicate that the median value was taken. In addition, a standard calibration was completed towards the end of the cruise using a dilution series of NIST-traceable 2-μm polystyrene beads, Thermo Scientific). The relative differences between the scaling factors derived from the intercalibration and standard calibration and those provided by the factory are presented in Table 1. Dark counts were also measured during the cruise and showed significant deviations from those provided by the manufacturer (Table 2). However, these D₄₉₉ value were not determined with the BB499 instrument installed on the profiling package and thus could be biased. Data from the 595-nm channel were excluded from the rest of the analysis because of the unexplained large change (23 counts) in its dark counts. The b_bp values and corresponding uncertainties derived from the profiling instrument (BB499) were computed following the same methodology employed for the flow-through instrument (BB349) (for in-water measurements no correction for wall effects was needed).

Median b_bp data were extracted from each upcast profile between 4 and 10 meters to match the depth of the ship’s water intake. A comparison of coincident b_bp values determined by the two independently-calibrated and deployed instruments indicated biases of −16% and −13% and precisions of 7% and 6% for the 470 and 526 nm channels, respectively (Fig. 3). The above biases may be due to uncertainties in dark counts, that were determined with the instrument connected to an electrical system (i.e., power supply and cables) different from the one used to collect measurements.

Fig. 3 Comparison between b_bp measurements collected at two different wavelengths by the instruments mounted on the flow-through and profiling systems. Error bars represent the combined uncertainties in the b_bp estimates. Dashed lines are the 1:1 lines. Note the logarithmic scales on all axes. δ and δ_r are robust estimates of the absolute and relative bias, respectively. σ and σ_r are estimates (σ₆₈ of residuals) of the absolute and relative precision, respectively. N = 24.

3. Results

Chl, b_bp and b_p displayed largest values in temperate and tropical regions and minimal values in the subtropical gyres (Fig. 4). Chl varied by over two orders of magnitude, while b_bp and b_p varied by over one order of magnitude. The broadscale patterns of b_bp(526) and Chl were in agreement with previous measurements in the Atlantic ocean [45

D. Stramski, R. A. Reynolds, M. Babin, S. Kaczmarek, M. R. Lewis, R. Rottgers, A. Sciandra, M. Stramska, M. S. Twardowski, B. A. Franz, and H. Claustre, “Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern south Pacific and eastern Atlantic oceans,” Biogeosci. 5, 171–201 (2008). [CrossRef]

, 46

W. M. Balch, B. C. Bowler, D. T. Drapeau, A. J. Poulton, and P. M. Holligan, “Biominerals and the vertical flux of particulate organic carbon from the surface ocean,” Geophys. Res. Lett. 37, L22605– (2010). [CrossRef]

]. The particulate backscattering vs. Chl relationship obtained during AMT19 was also in general agreement existing bio-optical models, although b_bp(526) was underestimated by existing models at low Chl (Fig. 5(a)). On the other hand, b_p(526) agreed better with existing bio-optical models (Fig. 5(b), [10

, 12

]).

Fig. 4 Time series of Chl, b_bp(526) and b_p(526), sea surface temperature (SST), salinity (from which a constant value of 10 psu was subtracted for plotting purposes, SSS-10, psu) and potential density anomaly (σ_θ, kg m⁻³).

Fig. 5 Bivariate histograms showing the relationships between b_bp(526) and b_p(526) versus Chl. Solid and dashed lines are the models presented in refs. [12

] and [10

], respectively. The inset presents the b_bp(526) vs. Chl bivariate histogram, but in linear scale (b_bp is multiplied by 1000). The colorbar identifies the number of data points in each bivariate bin.

The particulate backscattering ratio, b_bp:b_p, varied latitudinally, with maximum values (∼ 0.02) in oligotrophic regions and minimum values in the eutrophic waters (< 0.01, Fig. 6(a)). An important fraction of this variability (∼ 30%) appeared to be due to variations occurring at the diel scale. The chlorophyll-specific particulate scattering and backscattering coefficients (

b_{p}^{*}

and

b_{bp}^{*}

, respectively) varied by over an order of magnitude along the transect with maximum values in the most oligotrophic regions and also showed strong diel cycles (Fig. 6(b)). Finally, the spectral slopes of b_bp and c_p (γ_bbp and γ_cp, respectively) were inversely correlated, with γ_cp displaying higher values in productive regions and lower values in the most oligotrophic waters (Fig. 6(c)). Strong variations of γ_cp were observed at the end of the transect in the most productive region sampled. While γ_cp appeared to be affected by diel cycles, γ_bbp did not.

Fig. 6 Time series of b_bp:b_p at 526 nm, chl-specific b_p(526) and b_bp(526) (

b_{p}^{*}

and

b_{b p}^{*}

, respectively; m² mg⁻¹) and the spectral slopes of c_p (γ_cp) and b_bp (γ_bbp).

Particulate absorption contributed, as expected, only a relatively small fraction of c_p (data not shown): the largest values of a_p:c_p were found at 440 nm (8 – 16%, 95^th percentile range), while minimum values were found for wavelengths smaller than 532 nm (2 – 6%). The ratio of particulate backscattering to beam-attenuation at 526 nm, b_bp:c_p, ranged from less than 0.002 to 0.020, with a median value (± σ₆₈) of 0.0130 ± 0.0032 (Fig. 7, solid line). b_bp:c_p values measured during AMT19 were skewed towards higher values than those of previously published datasets [8

Fig. 7 Normalized frequency distribution of b_bp:c_p measured during AMT19 (solid line) and of (b_bp − b_b₀₂):c_p (dashed line). All measurements are at 526 nm. The shaded area represents the mean value of the normalized frequency distributions of the datasets presented in ref. [8

The backscattering signal measured on 0.2μm filtered samples after subtraction of the pure seawater signal (i.e., b_b₀₂) varied latitudinally with larger values in the most productive regions of the transect (Fig. 8). 95% confidence intervals suggest that b_b₀₂ was not significantly higher than zero along most of the transect (Fig. 8). This finding is in agreement with a previous study that reported negligible b_b₀₂ values in the surface equatorial Pacific [12

], although the average b_b₀₂ values measured during AMT19 appeared larger than previously observed. b_b₀₂ contributed a relatively important fraction of b_bp: 0.19 ± 0.06 and 0.11 ± 0.04 at 470 and 526 nm, respectively (Fig. 8). b_b₀₂ was positively, but weakly related to Chl and bulk values of c_p, b_bp and a_p (not shown).

Fig. 8 Time series of (a) b_b₀₂ with error bars indicating 95% confidence intervals and (b) b_b₀₂:b_bp with error bars representing standard errors plotted at discrete locations for clarity. Black dashed and red solid vertical lines indicate times when the flow-through system was cleaned and when the 0.2μm filter was replaced, respectively.

4. Discussion

4.1. b_bp:Chl, b_p:Chl

In this study, a dataset of surface optical scattering measurements collected along the 19^th Atlantic Meridional Transect is presented. As previously observed, b_bp and b_p were, to first order, related to Chl [8

, 10

, 12

, 13

], although considerable variability exists in these relationships. At least three reasons may explain this relatively large variability. First, changes in the ratio of backscattering to Chl may register changes in the phytoplankton carbon-to-Chl ratio associated with changes in phytoplankton acclimation to the diverse temperature, nutrient, light environments, and species compositions encountered during the transect [8

, 11

, 21

M. J. Behrenfeld, E. Boss, D. A. Siegel, and D. M. Shea, “Carbon-based ocean productivity and phytoplankton physiology from space,” Global Biogeochem. Cy. 19, 1–14, doi: [CrossRef] (2005).

, 47

R. J. Geider, “Light and temperature dependence of the carbon to chlorophyll a ratio in microalgae and cyanobacteria: implications for physiology and growth of phytoplankton,” New Phytol. 106, 1–34 (1987). [CrossRef]

–49

H. L. MacIntyre, T. M. Kana, T. Anning, and R. J. Geider, “Photoacclimation of photosynthesis irradiance response curves and photosynthetic pigments in microalgae and cyanobacteria,” J. Phycol. 38, 17–38 (2002). [CrossRef]

]. Second, since the AMT samples a wide range of ecological provinces, the large variability observed in b_bp:Chl may have also been driven by changes in the efficiency with which phytoplankton backscatter light due to variations in cell size, composition, and morphology. Third, b_bp:Chl may depend on both phytoplankton (driving changes in Chl) and other particles (mostly driving changes in b_bp) and the coupling between these drivers may vary with the trophic status of the ocean [13

, 48

A. Morel, “Chlorophyll-specific scattering coefficient of phytoplankton a simplified theoretical approach,” Deep-Sea Res. Part I 34, 1093–1106 (1987). [CrossRef]

, 50

H. R. Gordon and A. Morel, Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery. A Review (Springer-Verlag, New York, 1983).

]. Most likely, a combination of these factors explains the observed variability in the

b_{p}^{*}

and

b_{b p}^{*}

ratios.

4.2. b_bp:c_p

The b_bp:c_p ratio over most of the transect was higher than in previous cruises that employed the same flow-through methodology [8

,12

]. This observation, if verified, is at odds with the findings of refs. [12

] and [8

] that there is a consistent relationship between b_bp and c_p in the surface open ocean. These authors argued that, since the particulate beam-attenuation coefficient is likely controlled by variations in phytoplankton carbon biomass, then a consistent b_bp:c_p ratio would imply that one could estimate c_p, and thus phytoplankton carbon, from remotely sensed b_bp [8

, 12

, 21

M. J. Behrenfeld, E. Boss, D. A. Siegel, and D. M. Shea, “Carbon-based ocean productivity and phytoplankton physiology from space,” Global Biogeochem. Cy. 19, 1–14, doi: [CrossRef] (2005).

]. Results from the analysis of the AMT19 dataset suggest that such endeavour might be more complex than previously thought and could require regional parametrizations. Alternatively, the deviation of the measured b_bp:c_p ratio from published values could be also due to a small bias in b_bp (∼ 1 × 10⁻⁴ m⁻¹ at 526 nm; see sections 4.3 and 4.4). Importantly, this bias is smaller than the median uncertainty of our b_bp measurements (∼ 2.5 × 10⁻⁴ m⁻¹ at 526 nm, Table 4).

Previous studies reported b_bp:b_p measurements from two independent datasets of optical scattering collected in the ultra-oligotrophic South Pacific sub-tropical gyre [25

M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]

,26

,45

]. Despite the general agreement demonstrated between the b_bp values measured in these two datasets [25

M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]

], the near-surface b_bp:b_p values reported showed considerable variability ranging from less that 0.004 at 650 nm (Fig. 5 in ref. [25

M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]

]) to more than 0.015 at 555 nm (Fig. 11 in [26

]). These large discrepancies are unexpected given the relatively neutral spectral shape of b_bp:b_p (refs. [22

O. Ulloa, S. Sathyendranath, and T. Platt, “Effect of the particle-size distribution on the backscattering ratio in seawater,” Appl. Opt. 33, 7070–7077 (1994). [CrossRef]

, 24

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

, 25

M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]

]). However, although in the more productive waters the b_bp:b_p ratio at 555 nm was relatively stable and similar to the average value reported in ref. [8

], higher values of b_bp:b_p were observed in the most oligotrophic waters sampled (Chl < 0.075 – 0.100 mg m⁻³ see Figs. 2 and 11 in [26

, 45

]). The b_bp:b_p values recorded during AMT19 were also maximal in the most oligotrophic waters (Figs. 4 and 6). This similarity suggests that the increase of b_bp:b_p in oligotrophic waters could be a general bio-optical feature [9

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

, 28

A. Morel, “Optical modeling of the upper ocean in relation to its biogenous matter content (case 1 water),” J. Geophys. Res.-Oceans 93, 10749–10768 (1988). [CrossRef]

] or could be related to a decrease in the achievable b_bp accuracy in very clear waters.

4.3. b_b02

The backscattering measured on sample water that passed through the 0.2-μm filter was found to be higher than zero, although not significantly at the 95% confidence level, and contributed about 10% of the b_bp signal at 526 nm (Fig. 8). Previously, b_b₀₂(526) was found to be indistinguishable from zero (at the 95% confidence level) in the Equatorial Pacific [12

] and in the Mediterranean Sea (Dall’Olmo G., unpublished data), or significantly higher than zero, but negligible with respect to the bulk b_bp, in the North Atlantic and North Pacific (Westberry T.K., unpublished data).

It is important to recognize that b_b₀₂ may not accurately represent the backscattering of colloids smaller than 0.2 μm. This is because it may be affected by biases due to the use of filters to partition the particle size distribution, including particle breakage and retention of particles smaller than the nominal pore size (see discussion in ref. [12

]). However, the same methodology was employed in the current and previous studies. Thus, similar biases should apply, which supports the comparison of b_b₀₂ values between cruises. Excessive clogging of filters or particle accumulation on the optical surface of the flow-through instrument were limited during AMT19, as shown by the negligible changes in b_b₀₂ after filters were replaced and after the flow-through system was cleaned, respectively (Fig. 8). Therefore, the unusually high b_b₀₂ values measured during AMT19 could either represent the contribution of particles smaller than 0.2 μm to the bulk b_bp coefficient, or reflect the magnitude of the small bias that seems to affect our b_bp measurements.

To quantify the importance of b_b₀₂ on the observed b_bp:c_p ratio, we subtracted b_b₀₂ from b_bp and recomputed the backscattering efficiency: (b_bp−b_b₀₂)/c_p. We found that (b_bp−b_b₀₂)/c_p was in good agreement with previous estimates of b_bp:c_p obtained using the same methodology (dashed line in Fig. 7(b)) and thus that most of the anomaly observed during AMT19 in the b_bp:c_p ratio was removed by subtracting b_b₀₂ from b_bp. One advantage of subtracting b_b₀₂ from b_bp is that any bias caused by uncertainties in dark counts and/or in b_b,wall should cancel out. Thus, the improved agreement between (b_bp−b_b₀₂)/c_p and published values of b_bp:c_p supports the hypothesis that a bias of the same magnitude as the estimated uncertainties in b_b may affect our measurements.

Ancillary measurements would otherwise be needed to explain the real origin of b_b₀₂ and why it was higher during AMT19 than in other previous cruises in oligotrophic waters. Unfortunately these ancillary data (e.g., colloidal size distributions) were not collected. Some potential explanations are therefore discussed below.

If b_b₀₂ was indeed related to the presence of very small particles (i.e., colloids), it would seem reasonable to find a correlation between b_b₀₂ and the concentration of dissolved organic carbon (DOC). No measurements of DOC were available during AMT19, but some insights can be gained by comparing the spatial distributions of b_b₀₂ and existing DOC measurements. In general, DOC is relatively high in the tropical and subtropical surface ocean, where a stable mixed layer allows refractory DOC to accumulate [51

D. A. Hansell, C. A. Carlson, D. J. Repeta, and R. Schlitzer, “Dissolved organic matter in the ocean: A controversy stimulates new insights,” Oceanography 22, 202–211 (2009). [CrossRef]

]. On the other hand, DOC is lower at higher latitudes where the water column is less stable and DOC-depleted deep waters are mixed to the surface [51

D. A. Hansell, C. A. Carlson, D. J. Repeta, and R. Schlitzer, “Dissolved organic matter in the ocean: A controversy stimulates new insights,” Oceanography 22, 202–211 (2009). [CrossRef]

]. The observed b_b₀₂ values have a spatial distribution opposite to that expected for DOC, with higher values in the regions where the mixed layer was less stable (Fig. 8(a)). DOC, therefore, is unlikely to be the dominant control of b_b₀₂, possibly because colloids are thought to contribute only 10% of DOC [52

I. Koike, S. Hara, K. Terauchi, and K. Kogure, “Role of sub-micrometre particles in the ocean,” Nature 345, 242–244 (1990). [CrossRef]

, 53

P. H. Santschi, E. Balnois, K. J. Wilkinson, J. W. Zhang, J. Buffle, and L. D. Guo, “Fibrillar polysaccharides in marine macromolecular organic matter as imaged by atomic force microscopy and transmission electron microscopy,” Limnol. Oceanogr. 43, 896–908 (1998). [CrossRef]

Another potential explanation for the relatively high values of b_b₀₂ could be the presence of fine Saharan dust particles in the water. Dust deposition, however, is estimated to be one order of magnitude more intense in the northern than in the southern Atlantic (e.g., ref. [54

Y. P. Shao, K. H. Wyrwoll, A. Chappell, J. P. Huang, Z. H. Lin, G. H. McTainsh, M. Mikami, T. Y. Tanaka, X. L. Wang, and S. Yoon, “Dust cycle: An emerging core theme in earth system science,” Aeolian Res. 2, 181–204 (2011). [CrossRef]

]). If atmospheric dust was responsible for the relatively elevated b_b₀₂ values, one would expect b_b₀₂ to be higher in the north than in the south Atlantic. Figure 8, however, does not show important differences in b_b₀₂ values between the northern and southern parts of the transect, suggesting that atmospheric dust is unlikely to be the cause of the elevated b_b₀₂.

In conclusion, the b_b₀₂ measurements were anomalously higher than in previous cruises in meso- and oligotrophic regions, accounted for about 10% of the b_bp signal at 526 nm, and could explain the observed anomalies in the b_bp:c_p ratio. However, based on the available data, no clear biogeochemical explanation can be provided for this anomaly. It therefore seems most plausible that the b_b₀₂ values could be due to a bias of about 1 × 10⁻⁴ m⁻¹ in our b_bp(526) determinations. Importantly, such bias is well within the uncertainties of b_bp(526). If such a bias was indeed the cause of the observed anomalies in b_bp:c_p and b_b₀₂, then we could conclude that the AMT19 dataset confirmed the previous finding that b_bp:c_p is remarkably constant in the surface open ocean.

4.4. Uncertainties in b_bp and b_b02

Particulate backscattering estimates in oligotrophic regions are extremely sensitive to measurement uncertainties [25

M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]

]. In this study, the main source of b_bp error was the uncertainty in the scaling factors (S) (Table 4). These uncertainties in S, in turn, depend on the uncertainties in multiple variables including the spectral and angular weighting functions of the instrument, as well as the complex refractive index and size of the beads used in the dilution series [35

J.M. Sullivan, C.C. Moore, M.S. Twardowski, and J.R.V. Zaneveld, “Measuring optical backscattering in water” in “Light Scattering Reviews, Volume 7: Radiative transfer and optical properties of atmosphere and underlying surface ” (Praxis Publishing Ltd, in press).

]. The relatively strong dependency between the uncertainties in S and b_bp, as well as the sensitivity analysis to the dark counts described in the method section highlight the need for a detailed understanding, characterization, and validation of the the instrument(s) employed for the measurements and the importance of identifying, quantifying and minimizing all sources of uncertainty affecting b_bp [35

]. In particular, future studies should strive to validate particulate backscattering estimates by comparing measurements collected using instruments that employ different calibration procedures [35

, 43

, 61

R. A. Maffione and D. R. Dana, “Instruments and methods for measuring the backward-scattering coefficient of ocean waters,” Appl. Opt. 36, 6057–6067 (1997). [CrossRef]

]. It is noteworthy that a recent publication by WET Labs scientists [35

] has re-evaluated the angular weighting function, W, of WET Labs ECO-BB meters and suggests that W is centered at 124 degrees (instead of 117 degrees) and it is significantly wider than what was previously reported [25

M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]

]. Nevertheless, to be consistent with our previous studies and until independent verification of this new specification is provided, in this study we have chosen to maintain the “standard” W function [25

M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]

Overall our results and the above considerations emphasize the difficulties in obtaining accurate particulate backscattering measurements in the open ocean with the current instrumentation. This limitation is likely biasing the development and validation of open-ocean remote-sensing algorithms and it is hampering progress in the understanding of the sources of b_bp and in the application of b_bp measurements to the study of ocean biology and biogeochemistry.

4.5. Spectral slopes of c_p and b_bp

Important qualitative differences in the spectral slopes of b_bp and c_p were observed in this study (Figs. 6, 9). Under the hypotheses described in the introduction, the spectral slope of c_p should, theoretically, be linearly related to the slope of particle size distribution (PSD). Thus, γ_cp should increase as small particles become relatively more abundant than large ones [6

H. C. van de Hulst, Light Scattering by Small Particles (Wiley, New York, 1957).

, 29

A. Morel, Advisory Group for Aerospace Research and Development (NATO, 1973), chap. Diffusion de la lumiere par les eaux de mer. Resultat experimentaux et approach theorique, 3.1.1–76.

, 30

]. Similarly, spectral b_bp has also been used to estimate the parameters of the particle size distribution [33

T. S. Kostadinov, D. A. Siegel, and S. Maritorena, “Retrieval of the particle size distribution from satellite ocean color observations,” J. Geophys. Res.-Oceans 114, C09015 (2009). [CrossRef]

Fig. 9 Subset of time series showing diel cycles in each variable. Filled circles in the bottom plot are TChl-a estimates from discrete HPLC measurements. Values for γ_bbp were median filtered (window size of 120 minutes) to remove noise.

During AMT19, b_bp spectra followed expected patterns [32

, 33

T. S. Kostadinov, D. A. Siegel, and S. Maritorena, “Retrieval of the particle size distribution from satellite ocean color observations,” J. Geophys. Res.-Oceans 114, C09015 (2009). [CrossRef]

]: γ_bbp increased from the most eutrophic regions, where large cells are abundant, to the most oligotrophic regions that are dominated by small cells (Fig. 6). In contrast, γ_cp was maximal in eutrophic regions and minimal in oligotrophic waters (Fig. 6). To account for this anomalous behavior in γ_cp, one or more of the above hypotheses must be invalid. Indeed, deviations from the power law approximation of the PSD are common in the open ocean, both in oligotrophic [32

] and productive regions and have been shown to cause significant perturbations to γ_cp in coastal waters [56

R. Astoreca, D. Doxaran, K. Ruddick, V. Rousseau, and C. Lancelot, “Influence of suspended particle concentration, composition and size on the variability of inherent optical properties of the southern North Sea,” Cont. Shelf Res. 35, 117–128 (2012). [CrossRef]

]. In addition, the acceptance angles of the AC9 and ACs transmissometers (0.93°) are known to reduce the instrument sensitivity to particles larger than about 10–20 μm [31

E. Boss, W. H. Slade, M. Behrenfeld, and G. Dall’Olmo, “Acceptance angle effects on the beam attenuation in the ocean,” Opt. Express 17, 1535–1550 (2009). [CrossRef]

During diel cycles, on the other hand, γ_cp followed expected dynamics, increasing during the day and decreasing at night (Figs. 6 and 9). These patterns have been previously observed [40

,57

K. Oubelkheir and A. Sciandra, “Diel variations in particle stocks in the oligotrophic waters of the Ionian Sea (Mediterranean),” J. Mar. Syst. 74, 364–371 (2008). [CrossRef]

,58

G. Dall’Olmo, E. Boss, M. J. Behrenfeld, T. K. Westberry, C. Courties, L. Prieur, M. Pujo-Pay, N. Hardman-Mountford, and T. Moutin, “Inferring phytoplankton carbon and eco-physiological rates from diel cycles of spectral particulate beam-attenuation coefficient,” Biogeosci. 8, 3423–3439 (2011). [CrossRef]

] and are thought to be caused by the increase in size of synchronous cell populations during the day and their decrease at night following cell division [58

, 59

M. D. DuRand and R. J. Olson, “Contributions of phytoplankton light scattering and cell concentration changes to diel variations in beam attenuation in the equatorial pacific from flow cytometric measurements of pico-, ultra-and nanoplankton,” Deep-Sea Res. Part II 43, 891–906 (1996). [CrossRef]

4.6. Diel variability

Although spatial and temporal variability are superimposed in this dataset, diel cycles appeared to considerably affect the measured optical properties. As in previous studies [12

, 40

, 57

K. Oubelkheir and A. Sciandra, “Diel variations in particle stocks in the oligotrophic waters of the Ionian Sea (Mediterranean),” J. Mar. Syst. 74, 364–371 (2008). [CrossRef]

, 58

], these diel variations became most evident when the dependence on particle concentration was minimised by plotting ratios of optical properties (Fig. 6). b_bp:c_p, b_p*, b_bp^*, γ_cp, and on closer inspection c_p, all showed diel variations, while b_bp and γ_bbp did not. Chl also showed clear diel cycles, at least during some parts of the transect, decreasing during the day and increasing at night (Fig. 9). These diel cycles of Chl are confirmed by discrete HPLC measurements (Fig. 9). Diel cycles in optical properties are believed to be related to the dynamics of synchronized populations of phytoplankton cells (and associated living and non-living particles) [59

,60

H. Claustre, A. Morel, M. Babin, C. Cailliau, D. Marie, J. C. Marty, D. Tailliez, and D. Vaulot, “Variability in particle attenuation and chlorophyll fluorescence in the tropical Pacific: Scales, patterns, and biogeochemical implications,” J. Geophys. Res.-Oceans 104, 3401–3422 (1999). [CrossRef]

]. Our dataset further demonstrates that this phenomenon is widespread in the surface Atlantic ocean.

5. Conclusions

An extensive data set of flow-through optical scattering properties collected in the surface Atlantic ocean was analyzed. The the main results are:

The b_bp:c_p and b_bp:Chl ratios were higher than those predicted by existing bio-optical relationships and measured using the same methodology in other oceanic regions.
b_bp from water filtered through 0.2 μm filters was higher than previous studies and contributed about 10% of the bulk b_bp(526).
The most parsimonious explanation for these anomalously high values of b_bp and b_b₀₂ is that a bias of the same order of magnitude of the measurement uncertainties (1×10⁻⁴ m⁻¹ at 526 nm) affected our b_bp and b_b₀₂ measurements.
If such bias indeed affected our b_bp measurements, then b_bp:c_p and b_bp:Chl ratios measured during AMT19 would be consistent with other global data sets and confirm the constancy of the b_bp:c_p ratio in surface open-ocean waters.
These results emphasize the difficulties in obtaining accurate b_bp measurements in the oligotrophic open ocean.
The spectral slopes of c_p and b_bp were found to be inversely correlated during the cruise, with γ_bbp following expected patterns.
Diel cycles in all optical properties (except b_bp and γ_bbp) and bulk Chl were evident along the entire meridional transect, especially when ratios of properties were computed.

Appendices

6. Appendix: Calibration of WET Labs ECO-BB3 meters

This section describes in detail the methodology employed to calibrate our BB3 meters for the AMT19 cruises and for our previous studies [8

, 12

The BB3 meter, C-star transmissometer (660 nm) and flow-through chamber were thoroughly cleaned with Milli-Q water and a mild detergent and then thoroughly rinsed with Milli-Q water.
The BB3 was installed in the flow-through chamber and connected in series to the C-star transmissometer and to a 2L flask that was used as a reservoir.
A filter holder containing a 0.2-μm cartridge filter (Cole Parmer) was also installed in series in the above system.
The system was then filled with Milli-Q water. To minimize impurities in the system, the water was continuously recirculated through the 0.2-μm cartridge filter for about 1hr by means of an in-line pump.
The filter and filter holder were removed from the system.
With the pump switched off, data were recorded from both the BB3 meter and C-star transmissometer for about 1–2 minutes.
1 or 2 drops of 2-μm NIST-traceable polystyrene beads (that had been sonicated for about 5 minutes; Thermo Scientific) were then added inside the reservoir and the pump was switched on to thoroughly mix the beads in the system, as verified by monitoring the data in real time. Note that WET Labs now recommends to use NIST-traceable 0.1-μm beads for channels at blue and green wavelengths [35
J.M. Sullivan, C.C. Moore, M.S. Twardowski, and J.R.V. Zaneveld, “Measuring optical backscattering in water” in “Light Scattering Reviews, Volume 7: Radiative transfer and optical properties of atmosphere and underlying surface ” (Praxis Publishing Ltd, in press).
], but this information was not available when the instruments used in this study were deployed. The use of 2-μm instead of 0.1-μm beads is expected to cause an underestimation of the scaling factors of about 5–10% (J. Sullivan, personal communication).
With the pump switched off, data were recorded from both the BB3 meter and C-star transmissometer for about 1–2 minutes.
The above two steps were repeated until the BB3 meter counts reached a value of 1000 (which was well above the counts encountered during AMT19).
Median values from the scattering data were linearly regressed vs. the median values of the BB3 counts at each dilution step to determine the slope of the relationship.
To compute the scaling factor S(θ, λ) the following equation was employed [25
M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]
, 35
J.M. Sullivan, C.C. Moore, M.S. Twardowski, and J.R.V. Zaneveld, “Measuring optical backscattering in water” in “Light Scattering Reviews, Volume 7: Radiative transfer and optical properties of atmosphere and underlying surface ” (Praxis Publishing Ltd, in press).
]:

S (θ, λ) = [\frac{β (θ, λ)}{b_{AC 9} (λ)}] [\frac{Q_{b}^{AC 9} (λ)}{Q_{b}^{Cstar} (650)}] [\frac{b_{Cstar} (650)}{C (λ)}]

(4)

where:

θ is the centroid angle of the BB3 (i.e., 117°). Note that a recent publication [35
J.M. Sullivan, C.C. Moore, M.S. Twardowski, and J.R.V. Zaneveld, “Measuring optical backscattering in water” in “Light Scattering Reviews, Volume 7: Radiative transfer and optical properties of atmosphere and underlying surface ” (Praxis Publishing Ltd, in press).
] suggests that the centroid angle of ECO-BB3 meters is now believed to be 124°. However, to be consistent with our previous studies [8
T. K. Westberry, G. Dall’Olmo, E. Boss, M. J. Behrenfeld, and T. Moutin, “Coherence of particulate beam attenuation and backscattering coefficients in diverse open ocean environments,” Opt. Express 18, 15419–15425 (2010). [CrossRef]
, 12
G. Dall’Olmo, T. K. Westberry, M. J. Behrenfeld, E. Boss, and W. H. Slade, “Significant contribution of large particles to optical backscattering in the open ocean,” Biogeosci. 6, 947–967 (2009). [CrossRef]
], we decided to adopt the 117° value until the new 124° value will be independently verified.
λ is the wavelength (weighted by the spectral response of each instrument).
[β (θ, λ)/b_AC9(λ)] is a theoretical coefficient that relates the volume scattering function at the centroid angle and wavelength of the BB3 instrument to the scattering coefficient measured by a WET Labs AC9 meter at the same wavelength. This coefficient is computed through Mie simulations and depends on the characteristics of the beads (i.e., refractive index and size distribution) used, the spectral response and acceptance angle of the AC9, as well as on the the spectral responses and angular weighting function, W, of the BB3 meter (see definition of W and Eq. (9) in ref. [25
M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci. 4, 1041–1058 (2007). [CrossRef]
]). Comparisons with the coefficients computed by WET Labs showed absolute differences of 4%, 9% and 1% in the 470, 526, and 656 nm channels, respectively. The larger difference in the green channel could be related to the shift from the nominal green wavelength that we observed [12
G. Dall’Olmo, T. K. Westberry, M. J. Behrenfeld, E. Boss, and W. H. Slade, “Significant contribution of large particles to optical backscattering in the open ocean,” Biogeosci. 6, 947–967 (2009). [CrossRef]
]. Note also that WET Labs did not routinely employ NIST-traceable beads and that the difference in scaling factors estimated based on dilution series using NIST-traceable and non-NIST-traceable beads (of the same nominal size) can be up to 8% (J. Sullivan, personal communication).
$[Q_{b}^{AC 9} (λ) / Q_{b}^{Cstar} (650)]$ is a theoretical coefficient used to convert C-star scattering measurements into equivalent AC9 scattering measurements. $Q_{b}^{AC 9} (λ)$ and $Q_{b}^{Cstar} (650)$ are the efficiency factors for scattering. We derived these coefficients by means of Mie simulations that accounted for the characteristics of the beads employed and the spectral responses and acceptance angles of the two instruments.
[b_Cstar(650)/C(λ)] is the experimental slope computed by linearly regressing median C-star measurements, b_Cstar(650), versus the median counts recorded by the BB3 instrument at each wavelength, C(λ), and at each bead dilution step.

Acknowledgments

The authors would like to thank the captain and crew members of the RSS James Cook. C. Gallienne is thanked for his help in deploying the profiling package. J. Sullivan at WET Labs and an anonymous reviewer are thanked for their comments on an earlier draft of this manuscript. G.D.O. was funded by NASA grant NNX09AK30G and by the UK National Centre for Earth Observations. This study was supported by the UK Natural Environment Research Council National Capability funding to Plymouth Marine Laboratory and the National Oceanography Centre, Southampton. This is contribution number 218 of the AMT programme.

References and links

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OCIS Codes
(010.4450) Atmospheric and oceanic optics : Oceanic optics
(010.4458) Atmospheric and oceanic optics : Oceanic scattering
(010.1350) Atmospheric and oceanic optics : Backscattering

ToC Category:
Atmospheric and Oceanic Optics

History
Original Manuscript: June 20, 2012
Revised Manuscript: August 31, 2012
Manuscript Accepted: August 31, 2012
Published: September 5, 2012

Virtual Issues
Vol. 7, Iss. 11 Virtual Journal for Biomedical Optics

Citation
G. Dall’Olmo, E. Boss, M.J. Behrenfeld, and T.K. Westberry, "Particulate optical scattering coefficients along an Atlantic Meridional Transect," Opt. Express 20, 21532-21551 (2012)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-20-19-21532

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References

IOCCG, Remote sensing of inherent optical properties: fundamentals, tests of algorithms, and applications., Report Number 5 (International Ocean Colour Coordination Group, 2006).
J. K. B. Bishop, “Autonomous observations of the ocean biological carbon pump,” Oceanography22, 182–193 (2009). [CrossRef]
E. Boss, D. Swift, L. Taylor, P. Brickley, R. Zaneveld, S. Riser, M. J. Perry, and P. G. Strutton, “Observations of pigment and particle distributions in the western north atlantic from an autonomous float and ocean color satellite,” Limnol. Oceanogr.53, 2112–2122 (2008). [CrossRef]
N. Briggs, M. J. Perry, I. Cetinic, C. Lee, E. D’Asaro, A. M. Gray, and E. Rehm, “High-resolution observations of aggregate flux during a sub-polar north atlantic spring bloom,” Deep Sea Res. Part I58, 1031–1039 (2011). [CrossRef]
IOCCG, Bio-optical sensors on Argo floats, Report Number 11 (International Ocean Colour Coordination Group, 2011).
H. C. van de Hulst, Light Scattering by Small Particles (Wiley, New York, 1957).
H. Loisel and A. Morel, “Light scattering and chlorophyll concentration in case 1 waters: A reexamination,” Limnol. Oceanogr.43, 847–858 (1998). [CrossRef]
T. K. Westberry, G. Dall’Olmo, E. Boss, M. J. Behrenfeld, and T. Moutin, “Coherence of particulate beam attenuation and backscattering coefficients in diverse open ocean environments,” Opt. Express18, 15419–15425 (2010). [CrossRef]
A. Morel and S. Maritorena, “Bio-optical properties of oceanic waters: a reappraisal,” J. Geophys. Res.-Oceans106, 7163–7180 (2001). [CrossRef]
Y. Huot, A. Morel, M. S. Twardowski, D. Stramski, and R. A. Reynolds, “Particle optical backscattering along a chlorophyll gradient in the upper layer of the eastern south pacific ocean,” Biogeosci.5, 495–507 (2008). [CrossRef]
M. J. Behrenfeld and E. Boss, “The beam attenuation to chlorophyll ratio: an optical index of phytoplankton physiology in the surface ocean?” Deep-Sea Res. Part I50, 1537–1549 (2003). [CrossRef]
G. Dall’Olmo, T. K. Westberry, M. J. Behrenfeld, E. Boss, and W. H. Slade, “Significant contribution of large particles to optical backscattering in the open ocean,” Biogeosci.6, 947–967 (2009). [CrossRef]
D. Antoine, D. A. Siegel, T. Kostadinov, S. Maritorena, N. B. Nelson, B. Gentili, V. Vellucci, and N. Guillocheau, “Variability in optical particle backscattering in contrasting bio-optical oceanic regimes,” Limnol. Oceanogr.56, 955–973 (2011). [CrossRef]
H. Pak, D. A. Kiefer, and J. C. Kitchen, “Meridional variations in the concentration of chlorophyll and microparticles in the north Pacific ocean,” Deep Sea Res. Part A35, 1151–1171 (1988). [CrossRef]
D. Stramski and D. Kiefer, “Light scattering by microorganisms in the open ocean,” Progr. Oceanogr.28, 343–383 (1991). [CrossRef]
A. Morel and Y. H. Ahn, “Optics of heterotrophic nanoflagellates and ciliates - a tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algal cells,” J. Mar. Res.49, 177–202 (1991). [CrossRef]
Y. Ahn, A. Bricaud, and A. Morel, “Light backscattering efficiency and related properties of some phytoplankters,” Deep-Sea Res. Part A38, 1835–1855 (1992). [CrossRef]
D. Stramski, A. Bricaud, and A. Morel, “Modeling the inherent optical properties of the ocean based on the detailed composition of the planktonic community,” Appl. Opt.40, 2929–2945 (2001). [CrossRef]
M. S. Quinby-Hunt, A. J. Hunt, K. Lofftus, and D. Shapiro, “Polarized-light scattering studies of marine chlorella,” Limnol. Oceanogr.34, 1587–1600 (1989). [CrossRef]
J. C. Kitchen and J. R. V. Zaneveld, “A three-layered sphere model of the optical properties of phytoplankton,” Limnol. Oceanogr.37, 1680–1690 (1992). [CrossRef]
M. J. Behrenfeld, E. Boss, D. A. Siegel, and D. M. Shea, “Carbon-based ocean productivity and phytoplankton physiology from space,” Global Biogeochem. Cy.19, 1–14, doi:(2005). [CrossRef]
O. Ulloa, S. Sathyendranath, and T. Platt, “Effect of the particle-size distribution on the backscattering ratio in seawater,” Appl. Opt.33, 7070–7077 (1994). [CrossRef]
M. S. Twardowski, E. Boss, J. B. Macdonald, W. S. Pegau, A. H. Barnard, and 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.-Oceans106, 14129–14142 (2001). [CrossRef]
A. L. Whitmire, E. Boss, T. J. Cowles, and W. S. Pegau, “Spectral variability of the particulate backscattering ratio,” Opt. Express15, 7019–7031 (2007). [CrossRef]
M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci.4, 1041–1058 (2007). [CrossRef]
D. Stramski, “Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern south Pacific and eastern Atlantic oceans (vol 5 pg 171, 2008),” Biogeosci.5, 595–595 (2008). [CrossRef]
F. Nencioli, G. Chang, M. Twardowski, and T. D. Dickey, “Optical characterization of an eddy-induced diatom bloom west of the island of Hawaii,” Biogeosci.7, 151–162 (2010). [CrossRef]
A. Morel, “Optical modeling of the upper ocean in relation to its biogenous matter content (case 1 water),” J. Geophys. Res.-Oceans93, 10749–10768 (1988). [CrossRef]
A. Morel, Advisory Group for Aerospace Research and Development (NATO, 1973), chap. Diffusion de la lumiere par les eaux de mer. Resultat experimentaux et approach theorique, 3.1.1–76.
E. Boss, M. S. Twardowski, and S. Herring, “Shape of the particulate beam attenuation spectrum and its inversion to obtain the shape of the particulate size distribution,” Appl. Opt.40, 4885–4893 (2001). [CrossRef]
E. Boss, W. H. Slade, M. Behrenfeld, and G. Dall’Olmo, “Acceptance angle effects on the beam attenuation in the ocean,” Opt. Express17, 1535–1550 (2009). [CrossRef]
H. Loisel, J. M. Nicolas, A. Sciandra, D. Stramski, and A. Poteau, “Spectral dependency of optical backscattering by marine particles from satellite remote sensing of the global ocean,” J. Geophys. Res.-Oceans111, C09024 (2006). [CrossRef]
T. S. Kostadinov, D. A. Siegel, and S. Maritorena, “Retrieval of the particle size distribution from satellite ocean color observations,” J. Geophys. Res.-Oceans114, C09015 (2009). [CrossRef]
T. S. Kostadinov, D. A. Siegel, and S. Maritorena, “Global variability of phytoplankton functional types from space: assessment via the particle size distribution,” Biogeosci.7, 3239–3257 (2010). [CrossRef]
J.M. Sullivan, C.C. Moore, M.S. Twardowski, and J.R.V. Zaneveld, “Measuring optical backscattering in water” in “Light Scattering Reviews, Volume 7: Radiative transfer and optical properties of atmosphere and underlying surface” (Praxis Publishing Ltd, in press).
X. Zhang, L. Hu, and M.-X. He, “Scattering by pure seawater: Effect of salinity,” Opt. Express17, 5698–5710 (2009). [CrossRef]
X. Zhang and L. Hu, “Estimating scattering of pure water from density fluctuation of the refractive index,” Opt. Express17, 1671–1678 (2009). [CrossRef]
E. Boss and W. S. Pegau, “Relationship of light scattering at an angle in the backward direction to the backscattering coefficient,” Appl. Opt.40, 5503–5507 (2001). [CrossRef]
BIPM and ISO, Guide to the Expression of Uncertainty in Measurement (International Organization for Standardization, Geneve, Switzerland, 1995).
W. H. Slade, E. Boss, G. Dall’Olmo, M. R. Langner, J. Loftin, M. J. Behrenfeld, C. Roesler, and T. K. Westberry, “Underway and moored methods for improving accuracy in measurement of spectral particulate absorption and attenuation,” J. Atmos. Ocean. Tech.27, 1733–1746 (2010). [CrossRef]
J. R. V. Zaneveld, J. C. Kitchen, and C. C. Moore, “Scattering error correction of reflecting tube absorption meters,” in Ocean Optics XII2258, S. Ackelson, ed. (SPIE, 1994), 44–55.
L. Van Heukelem and C. S. Thomas, “Computer-assisted high-performance liquid chromatography method development with applications to the isolation and analysis of phytoplankton pigments,” J. Chromatogr. A910, 31–49 (2001). [CrossRef]
E. S. Boss, R. Collier, G. Larson, K. Fennel, and W. S. Pegau, “Measurements of spectral optical properties and their relation to biogeochemical variables and processes in crater lake, Crater Lake National Park, OR,” Hydrobiologia574, 149–159 (2007). [CrossRef]
J. M. Sullivan and M. S. Twardowski, “Angular shape of the oceanic particulate volume scattering function in the backward direction,” App. Opt.48, 6811–6819 (2009). [CrossRef]
D. Stramski, R. A. Reynolds, M. Babin, S. Kaczmarek, M. R. Lewis, R. Rottgers, A. Sciandra, M. Stramska, M. S. Twardowski, B. A. Franz, and H. Claustre, “Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern south Pacific and eastern Atlantic oceans,” Biogeosci.5, 171–201 (2008). [CrossRef]
W. M. Balch, B. C. Bowler, D. T. Drapeau, A. J. Poulton, and P. M. Holligan, “Biominerals and the vertical flux of particulate organic carbon from the surface ocean,” Geophys. Res. Lett.37, L22605– (2010). [CrossRef]
R. J. Geider, “Light and temperature dependence of the carbon to chlorophyll a ratio in microalgae and cyanobacteria: implications for physiology and growth of phytoplankton,” New Phytol.106, 1–34 (1987). [CrossRef]
A. Morel, “Chlorophyll-specific scattering coefficient of phytoplankton a simplified theoretical approach,” Deep-Sea Res. Part I34, 1093–1106 (1987). [CrossRef]
H. L. MacIntyre, T. M. Kana, T. Anning, and R. J. Geider, “Photoacclimation of photosynthesis irradiance response curves and photosynthetic pigments in microalgae and cyanobacteria,” J. Phycol.38, 17–38 (2002). [CrossRef]
H. R. Gordon and A. Morel, Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery. A Review (Springer-Verlag, New York, 1983).
D. A. Hansell, C. A. Carlson, D. J. Repeta, and R. Schlitzer, “Dissolved organic matter in the ocean: A controversy stimulates new insights,” Oceanography22, 202–211 (2009). [CrossRef]
I. Koike, S. Hara, K. Terauchi, and K. Kogure, “Role of sub-micrometre particles in the ocean,” Nature345, 242–244 (1990). [CrossRef]
P. H. Santschi, E. Balnois, K. J. Wilkinson, J. W. Zhang, J. Buffle, and L. D. Guo, “Fibrillar polysaccharides in marine macromolecular organic matter as imaged by atomic force microscopy and transmission electron microscopy,” Limnol. Oceanogr.43, 896–908 (1998). [CrossRef]
Y. P. Shao, K. H. Wyrwoll, A. Chappell, J. P. Huang, Z. H. Lin, G. H. McTainsh, M. Mikami, T. Y. Tanaka, X. L. Wang, and S. Yoon, “Dust cycle: An emerging core theme in earth system science,” Aeolian Res.2, 181–204 (2011). [CrossRef]
M. Jonasz and G. Fournier, “Approximation of the size distribution of marine particles by a sum of log-normal functions,” Limnol. Oceanogr.41, 744–754 (1996). [CrossRef]
R. Astoreca, D. Doxaran, K. Ruddick, V. Rousseau, and C. Lancelot, “Influence of suspended particle concentration, composition and size on the variability of inherent optical properties of the southern North Sea,” Cont. Shelf Res.35, 117–128 (2012). [CrossRef]
K. Oubelkheir and A. Sciandra, “Diel variations in particle stocks in the oligotrophic waters of the Ionian Sea (Mediterranean),” J. Mar. Syst.74, 364–371 (2008). [CrossRef]
G. Dall’Olmo, E. Boss, M. J. Behrenfeld, T. K. Westberry, C. Courties, L. Prieur, M. Pujo-Pay, N. Hardman-Mountford, and T. Moutin, “Inferring phytoplankton carbon and eco-physiological rates from diel cycles of spectral particulate beam-attenuation coefficient,” Biogeosci.8, 3423–3439 (2011). [CrossRef]
M. D. DuRand and R. J. Olson, “Contributions of phytoplankton light scattering and cell concentration changes to diel variations in beam attenuation in the equatorial pacific from flow cytometric measurements of pico-, ultra-and nanoplankton,” Deep-Sea Res. Part II43, 891–906 (1996). [CrossRef]
H. Claustre, A. Morel, M. Babin, C. Cailliau, D. Marie, J. C. Marty, D. Tailliez, and D. Vaulot, “Variability in particle attenuation and chlorophyll fluorescence in the tropical Pacific: Scales, patterns, and biogeochemical implications,” J. Geophys. Res.-Oceans104, 3401–3422 (1999). [CrossRef]
R. A. Maffione and D. R. Dana, “Instruments and methods for measuring the backward-scattering coefficient of ocean waters,” Appl. Opt.36, 6057–6067 (1997). [CrossRef]

Ahn, Y.
Ahn, Y. H.
Anning, T.
Antoine, D.
Astoreca, R.
Babin, M.
Balch, W. M.
Balnois, E.
Barnard, A. H.
Behrenfeld, M.
Behrenfeld, M. J.
Bishop, J. K. B.
Boss, E.
Boss, E. S.
Bowler, B. C.
Bricaud, A.
Brickley, P.
Briggs, N.
Buffle, J.
Cailliau, C.
Carlson, C. A.
Cetinic, I.
Chang, G.
Chappell, A.
Claustre, H.
Collier, R.
Courties, C.
Cowles, T. J.
D’Asaro, E.
Dall’Olmo, G.
Dana, D. R.
Dickey, T. D.
Doxaran, D.
Drapeau, D. T.
DuRand, M. D.
Fennel, K.
Fournier, G.
Franz, B. A.
Freeman, S. A.
Geider, R. J.
Gentili, B.
Gordon, H. R.
Gray, A. M.
Guillocheau, N.
Guo, L. D.
Hansell, D. A.
Hara, S.
Hardman-Mountford, N.
He, M.-X.
Herring, S.
Holligan, P. M.
Hu, L.
Huang, J. P.
Hunt, A. J.
Huot, Y.
Jonasz, M.
Kaczmarek, S.
Kana, T. M.
Kiefer, D.
Kiefer, D. A.
Kitchen, J. C.
Kogure, K.
Koike, I.
Kostadinov, T.
Kostadinov, T. S.
Lancelot, C.
Langner, M. R.
Larson, G.
Lee, C.
Lewis, M. R.
Lin, Z. H.
Lofftus, K.
Loftin, J.
Loisel, H.
Macdonald, J. B.
MacIntyre, H. L.
Maffione, R. A.
Marie, D.
Maritorena, S.
Marty, J. C.
McTainsh, G. H.
Mikami, M.
Moore, C. C.
Moore, C.C.
Morel, A.
Moutin, T.
Nelson, N. B.
Nencioli, F.
Nicolas, J. M.
Olson, R. J.
Oubelkheir, K.
Pak, H.
Pegau, W. S.
Perry, M. J.
Platt, T.
Poteau, A.
Poulton, A. J.
Prieur, L.
Pujo-Pay, M.
Quinby-Hunt, M. S.
Rehm, E.
Repeta, D. J.
Reynolds, R. A.
Riser, S.
Roesler, C.
Rottgers, R.
Rousseau, V.
Ruddick, K.
Santschi, P. H.
Sathyendranath, S.
Schlitzer, R.
Sciandra, A.
Shao, Y. P.
Shapiro, D.
Shea, D. M.
Siegel, D. A.
Slade, W. H.
Stramska, M.
Stramski, D.
Strutton, P. G.
Sullivan, J. M.
Sullivan, J.M.
Swift, D.
Tailliez, D.
Tanaka, T. Y.
Taylor, L.
Terauchi, K.
Thomas, C. S.
Twardowski, M.
Twardowski, M. S.
Twardowski, M.S.
Ulloa, O.
van de Hulst, H. C.
Van Heukelem, L.
Vaulot, D.
Vellucci, V.
Wang, X. L.
Westberry, T. K.
Whitmire, A. L.
Wilkinson, K. J.
Wyrwoll, K. H.
Yoon, S.
Zaneveld, J. R. V.
Zaneveld, J.R.V.
Zaneveld, R.
Zhang, J. W.
Zhang, X.

Aeolian Res.

Y. P. Shao, K. H. Wyrwoll, A. Chappell, J. P. Huang, Z. H. Lin, G. H. McTainsh, M. Mikami, T. Y. Tanaka, X. L. Wang, and S. Yoon, “Dust cycle: An emerging core theme in earth system science,” Aeolian Res.2, 181–204 (2011). [CrossRef]

App. Opt.

J. M. Sullivan and M. S. Twardowski, “Angular shape of the oceanic particulate volume scattering function in the backward direction,” App. Opt.48, 6811–6819 (2009). [CrossRef]

Appl. Opt.

Biogeosci.

T. S. Kostadinov, D. A. Siegel, and S. Maritorena, “Global variability of phytoplankton functional types from space: assessment via the particle size distribution,” Biogeosci.7, 3239–3257 (2010). [CrossRef]
M. S. Twardowski, H. Claustre, S. A. Freeman, D. Stramski, and Y. Huot, “Optical backscattering properties of the “clearest” natural waters,” Biogeosci.4, 1041–1058 (2007). [CrossRef]
D. Stramski, “Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern south Pacific and eastern Atlantic oceans (vol 5 pg 171, 2008),” Biogeosci.5, 595–595 (2008). [CrossRef]
F. Nencioli, G. Chang, M. Twardowski, and T. D. Dickey, “Optical characterization of an eddy-induced diatom bloom west of the island of Hawaii,” Biogeosci.7, 151–162 (2010). [CrossRef]
Y. Huot, A. Morel, M. S. Twardowski, D. Stramski, and R. A. Reynolds, “Particle optical backscattering along a chlorophyll gradient in the upper layer of the eastern south pacific ocean,” Biogeosci.5, 495–507 (2008). [CrossRef]
G. Dall’Olmo, T. K. Westberry, M. J. Behrenfeld, E. Boss, and W. H. Slade, “Significant contribution of large particles to optical backscattering in the open ocean,” Biogeosci.6, 947–967 (2009). [CrossRef]
G. Dall’Olmo, E. Boss, M. J. Behrenfeld, T. K. Westberry, C. Courties, L. Prieur, M. Pujo-Pay, N. Hardman-Mountford, and T. Moutin, “Inferring phytoplankton carbon and eco-physiological rates from diel cycles of spectral particulate beam-attenuation coefficient,” Biogeosci.8, 3423–3439 (2011). [CrossRef]
D. Stramski, R. A. Reynolds, M. Babin, S. Kaczmarek, M. R. Lewis, R. Rottgers, A. Sciandra, M. Stramska, M. S. Twardowski, B. A. Franz, and H. Claustre, “Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern south Pacific and eastern Atlantic oceans,” Biogeosci.5, 171–201 (2008). [CrossRef]

Cont. Shelf Res.

R. Astoreca, D. Doxaran, K. Ruddick, V. Rousseau, and C. Lancelot, “Influence of suspended particle concentration, composition and size on the variability of inherent optical properties of the southern North Sea,” Cont. Shelf Res.35, 117–128 (2012). [CrossRef]

Deep Sea Res. Part A

H. Pak, D. A. Kiefer, and J. C. Kitchen, “Meridional variations in the concentration of chlorophyll and microparticles in the north Pacific ocean,” Deep Sea Res. Part A35, 1151–1171 (1988). [CrossRef]

Deep Sea Res. Part I

N. Briggs, M. J. Perry, I. Cetinic, C. Lee, E. D’Asaro, A. M. Gray, and E. Rehm, “High-resolution observations of aggregate flux during a sub-polar north atlantic spring bloom,” Deep Sea Res. Part I58, 1031–1039 (2011). [CrossRef]

Deep-Sea Res. Part A

Y. Ahn, A. Bricaud, and A. Morel, “Light backscattering efficiency and related properties of some phytoplankters,” Deep-Sea Res. Part A38, 1835–1855 (1992). [CrossRef]

Deep-Sea Res. Part I

M. J. Behrenfeld and E. Boss, “The beam attenuation to chlorophyll ratio: an optical index of phytoplankton physiology in the surface ocean?” Deep-Sea Res. Part I50, 1537–1549 (2003). [CrossRef]
A. Morel, “Chlorophyll-specific scattering coefficient of phytoplankton a simplified theoretical approach,” Deep-Sea Res. Part I34, 1093–1106 (1987). [CrossRef]

Deep-Sea Res. Part II

M. D. DuRand and R. J. Olson, “Contributions of phytoplankton light scattering and cell concentration changes to diel variations in beam attenuation in the equatorial pacific from flow cytometric measurements of pico-, ultra-and nanoplankton,” Deep-Sea Res. Part II43, 891–906 (1996). [CrossRef]

Geophys. Res. Lett.

W. M. Balch, B. C. Bowler, D. T. Drapeau, A. J. Poulton, and P. M. Holligan, “Biominerals and the vertical flux of particulate organic carbon from the surface ocean,” Geophys. Res. Lett.37, L22605– (2010). [CrossRef]

Global Biogeochem. Cy.

M. J. Behrenfeld, E. Boss, D. A. Siegel, and D. M. Shea, “Carbon-based ocean productivity and phytoplankton physiology from space,” Global Biogeochem. Cy.19, 1–14, doi:(2005). [CrossRef]

Hydrobiologia

E. S. Boss, R. Collier, G. Larson, K. Fennel, and W. S. Pegau, “Measurements of spectral optical properties and their relation to biogeochemical variables and processes in crater lake, Crater Lake National Park, OR,” Hydrobiologia574, 149–159 (2007). [CrossRef]

J. Atmos. Ocean. Tech.

W. H. Slade, E. Boss, G. Dall’Olmo, M. R. Langner, J. Loftin, M. J. Behrenfeld, C. Roesler, and T. K. Westberry, “Underway and moored methods for improving accuracy in measurement of spectral particulate absorption and attenuation,” J. Atmos. Ocean. Tech.27, 1733–1746 (2010). [CrossRef]

J. Chromatogr. A

L. Van Heukelem and C. S. Thomas, “Computer-assisted high-performance liquid chromatography method development with applications to the isolation and analysis of phytoplankton pigments,” J. Chromatogr. A910, 31–49 (2001). [CrossRef]

J. Geophys. Res.-Oceans

H. Claustre, A. Morel, M. Babin, C. Cailliau, D. Marie, J. C. Marty, D. Tailliez, and D. Vaulot, “Variability in particle attenuation and chlorophyll fluorescence in the tropical Pacific: Scales, patterns, and biogeochemical implications,” J. Geophys. Res.-Oceans104, 3401–3422 (1999). [CrossRef]
A. Morel and S. Maritorena, “Bio-optical properties of oceanic waters: a reappraisal,” J. Geophys. Res.-Oceans106, 7163–7180 (2001). [CrossRef]
A. Morel, “Optical modeling of the upper ocean in relation to its biogenous matter content (case 1 water),” J. Geophys. Res.-Oceans93, 10749–10768 (1988). [CrossRef]
M. S. Twardowski, E. Boss, J. B. Macdonald, W. S. Pegau, A. H. Barnard, and 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.-Oceans106, 14129–14142 (2001). [CrossRef]
H. Loisel, J. M. Nicolas, A. Sciandra, D. Stramski, and A. Poteau, “Spectral dependency of optical backscattering by marine particles from satellite remote sensing of the global ocean,” J. Geophys. Res.-Oceans111, C09024 (2006). [CrossRef]
T. S. Kostadinov, D. A. Siegel, and S. Maritorena, “Retrieval of the particle size distribution from satellite ocean color observations,” J. Geophys. Res.-Oceans114, C09015 (2009). [CrossRef]

J. Mar. Res.

A. Morel and Y. H. Ahn, “Optics of heterotrophic nanoflagellates and ciliates - a tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algal cells,” J. Mar. Res.49, 177–202 (1991). [CrossRef]

J. Mar. Syst.

K. Oubelkheir and A. Sciandra, “Diel variations in particle stocks in the oligotrophic waters of the Ionian Sea (Mediterranean),” J. Mar. Syst.74, 364–371 (2008). [CrossRef]

J. Phycol.

H. L. MacIntyre, T. M. Kana, T. Anning, and R. J. Geider, “Photoacclimation of photosynthesis irradiance response curves and photosynthetic pigments in microalgae and cyanobacteria,” J. Phycol.38, 17–38 (2002). [CrossRef]

Limnol. Oceanogr.

P. H. Santschi, E. Balnois, K. J. Wilkinson, J. W. Zhang, J. Buffle, and L. D. Guo, “Fibrillar polysaccharides in marine macromolecular organic matter as imaged by atomic force microscopy and transmission electron microscopy,” Limnol. Oceanogr.43, 896–908 (1998). [CrossRef]
M. Jonasz and G. Fournier, “Approximation of the size distribution of marine particles by a sum of log-normal functions,” Limnol. Oceanogr.41, 744–754 (1996). [CrossRef]
D. Antoine, D. A. Siegel, T. Kostadinov, S. Maritorena, N. B. Nelson, B. Gentili, V. Vellucci, and N. Guillocheau, “Variability in optical particle backscattering in contrasting bio-optical oceanic regimes,” Limnol. Oceanogr.56, 955–973 (2011). [CrossRef]
E. Boss, D. Swift, L. Taylor, P. Brickley, R. Zaneveld, S. Riser, M. J. Perry, and P. G. Strutton, “Observations of pigment and particle distributions in the western north atlantic from an autonomous float and ocean color satellite,” Limnol. Oceanogr.53, 2112–2122 (2008). [CrossRef]
H. Loisel and A. Morel, “Light scattering and chlorophyll concentration in case 1 waters: A reexamination,” Limnol. Oceanogr.43, 847–858 (1998). [CrossRef]
M. S. Quinby-Hunt, A. J. Hunt, K. Lofftus, and D. Shapiro, “Polarized-light scattering studies of marine chlorella,” Limnol. Oceanogr.34, 1587–1600 (1989). [CrossRef]
J. C. Kitchen and J. R. V. Zaneveld, “A three-layered sphere model of the optical properties of phytoplankton,” Limnol. Oceanogr.37, 1680–1690 (1992). [CrossRef]

Nature

I. Koike, S. Hara, K. Terauchi, and K. Kogure, “Role of sub-micrometre particles in the ocean,” Nature345, 242–244 (1990). [CrossRef]

New Phytol.

R. J. Geider, “Light and temperature dependence of the carbon to chlorophyll a ratio in microalgae and cyanobacteria: implications for physiology and growth of phytoplankton,” New Phytol.106, 1–34 (1987). [CrossRef]

Oceanography

D. A. Hansell, C. A. Carlson, D. J. Repeta, and R. Schlitzer, “Dissolved organic matter in the ocean: A controversy stimulates new insights,” Oceanography22, 202–211 (2009). [CrossRef]
J. K. B. Bishop, “Autonomous observations of the ocean biological carbon pump,” Oceanography22, 182–193 (2009). [CrossRef]

Opt. Express

Progr. Oceanogr.

D. Stramski and D. Kiefer, “Light scattering by microorganisms in the open ocean,” Progr. Oceanogr.28, 343–383 (1991). [CrossRef]

Other

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IOCCG, Bio-optical sensors on Argo floats, Report Number 11 (International Ocean Colour Coordination Group, 2011).
H. C. van de Hulst, Light Scattering by Small Particles (Wiley, New York, 1957).
J.M. Sullivan, C.C. Moore, M.S. Twardowski, and J.R.V. Zaneveld, “Measuring optical backscattering in water” in “Light Scattering Reviews, Volume 7: Radiative transfer and optical properties of atmosphere and underlying surface” (Praxis Publishing Ltd, in press).
A. Morel, Advisory Group for Aerospace Research and Development (NATO, 1973), chap. Diffusion de la lumiere par les eaux de mer. Resultat experimentaux et approach theorique, 3.1.1–76.
H. R. Gordon and A. Morel, Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery. A Review (Springer-Verlag, New York, 1983).
J. R. V. Zaneveld, J. C. Kitchen, and C. C. Moore, “Scattering error correction of reflecting tube absorption meters,” in Ocean Optics XII2258, S. Ackelson, ed. (SPIE, 1994), 44–55.
BIPM and ISO, Guide to the Expression of Uncertainty in Measurement (International Organization for Standardization, Geneve, Switzerland, 1995).

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Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

Particulate optical scattering coefficients along an Atlantic Meridional Transect

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Abstract

1. Introduction

2. Methods

2.1. Flow through optical measurements

2.1.1. bbp

2.1.2. cp, ap, and bp

2.1.3. Chl

2.2. Measurements of bbp from profiling package

3. Results

4. Discussion

4.1. bbp:Chl, bp:Chl

4.2. bbp:cp

4.3. bb02

4.4. Uncertainties in bbp and bb02

4.5. Spectral slopes of cp and bbp

4.6. Diel variability

5. Conclusions

Appendices

6. Appendix: Calibration of WET Labs ECO-BB3 meters

Acknowledgments

References and links

References

Aeolian Res.

App. Opt.

Appl. Opt.

Biogeosci.

Cont. Shelf Res.

Deep Sea Res. Part A

Deep Sea Res. Part I

Deep-Sea Res. Part A

Deep-Sea Res. Part I

Deep-Sea Res. Part II

Geophys. Res. Lett.

Global Biogeochem. Cy.

Hydrobiologia

J. Atmos. Ocean. Tech.

J. Chromatogr. A

J. Geophys. Res.-Oceans

J. Mar. Res.

J. Mar. Syst.

J. Phycol.

Limnol. Oceanogr.

Nature

New Phytol.

Oceanography

Opt. Express

Progr. Oceanogr.

Other

Cited By

Figures

2.1.1. b_bp

2.1.2. c_p, a_p, and b_p

2.2. Measurements of b_bp from profiling package

4.1. b_bp:Chl, b_p:Chl

4.2. b_bp:c_p

4.3. b_b02

4.4. Uncertainties in b_bp and b_b02

4.5. Spectral slopes of c_p and b_bp