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Non-algal particles and chromophoric dissolved organic matter (CDOM) are two major classes of seawater constituents that contribute substantially to light absorption in the ocean within the ultraviolet (UV) and visible (VIS) spectral regions. The similarities in the spectral shape of these two constituent absorption coefficients, a d (λ) and a g (λ), respectively, have led to their common estimation as a single combined non-phytoplankton absorption coefficient, a d g (λ), in optical remote-sensing applications. Given the different biogeochemical and ecological roles of non-algal particles and CDOM in the ocean, it is important to determine and characterize the absorption coefficient of each of these constituents separately. We describe an ADG model that partitions a d g (λ) into a d (λ) and a g (λ). This model improves upon a recently published model [Appl. Opt.58, 3790 (2019)APOPAI0003-693510.1364/AO.58.003790] through implementation of a newly assembled dataset of hyperspectral measurements of a d (λ) and a g (λ) from diverse oceanic environments to create the spectral shape function libraries of these coefficients, a better characterization of variability in spectral shape of a d (λ) and a g (λ), and a spectral extension of model output to include the near-UV (350-400 nm) in addition to the VIS (400-700 nm) part of the spectrum. We developed and tested two variants of the ADG model: the ADG_UV-VIS model, which determines solutions over the spectral range from 350 to 700 nm, and the ADG_VIS model, which determines solutions in the VIS but can also be coupled with an independent extrapolation model to extend output to the near-UV. This specific model variant is referred to as A D G _ V I S-U V E x t . Evaluation of the model with development and independent datasets demonstrates good performance of both ADG_UV-VIS and A D G _ V I S-U V E x t . Comparative analysis of model-derived and measured values of a d (λ) and a g (λ) indicates negligible or small median bias, generally within ±5% over the majority of the 350-700 nm spectral range but extending to or above 10% near the ends of the spectrum, and the median percent difference generally below 20% with a maximum reaching about 30%. The presented ADG models are suitable for implementation as a component of algorithms in support of satellite ocean color missions, especially the NASA PACE mission.
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Extending the capabilities of optical remote sensing and inverse optical algorithms, which have been commonly focused on the visible (VIS) range of the electromagnetic spectrum, to derive the optical properties of seawater in the ultraviolet (UV) range is important to advancing the understanding of various optical, biological, and photochemical processes in the ocean. In particular, existing remote-sensing reflectance models that derive the total spectral absorption coefficient of seawater, a(λ), and absorption partitioning models that partition a(λ) into the component absorption coefficients of phytoplankton, aph(λ), non-algal (depigmented) particles, ad(λ), and chromophoric dissolved organic matter (CDOM), ag(λ), are restricted to the VIS range. We assembled a quality-controlled development dataset of hyperspectral measurements of ag(λ) (N = 1294) and ad(λ) (N = 409) spanning a wide range of values across various ocean basins, and evaluated several extrapolation methods to extend ag(λ), ad(λ), and adg(λ) ≡ ag(λ) + ad(λ) into the near-UV spectral region by examining different sections of the VIS as a basis for extrapolation, different extrapolation functions, and different spectral sampling intervals of input data in the VIS. Our analysis determined the optimal method to estimate ag(λ) and adg(λ) at near-UV wavelengths (350 to 400 nm) which relies on an exponential extrapolation of data from the 400-450 nm range. The initial ad(λ) is obtained as a difference between the extrapolated estimates of adg(λ) and ag(λ). Additional correction functions based on the analysis of differences between the extrapolated and measured values in the near-UV were defined to obtain improved final estimates of ag(λ) and ad(λ) and then the final estimates of adg(λ) as a sum of final ag(λ) and ad(λ). The extrapolation model provides very good agreement between the extrapolated and measured data in the near-UV when the input data in the blue spectral region are available at 1 or 5 nm spectral sampling intervals. There is negligible bias between the modeled and measured values of all three absorption coefficients and the median absolute percent difference (MdAPD) is small, e.g., < 5.2% for ag(λ) and < 10.5% for ad(λ) at all near-UV wavelengths when evaluated with the development dataset. Assessment of the model on an independent dataset of concurrent ag(λ) and ad(λ) measurements (N = 149) yielded similar findings with only slight reduction of performance and MdAPD remaining below 6.7% for ag(λ) and 11% for ad(λ). These results are promising for integration of the extrapolation method with absorption partitioning models operating in the VIS.
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Optical proxies based on light scattering measurements have potential to improve the study and monitoring of aquatic environments. In this study, we evaluated several optical proxies for characterization of particle mass concentration, composition, and size distribution of suspended particulate matter from two contrasting coastal marine environments. We expanded upon our previous study of Southern California coastal waters, which generally contained high proportions of organic particles, by conducting angle-resolved polarized light scattering measurements in predominantly turbid and inorganic-particle dominated Arctic coastal waters near Prudhoe Bay, Alaska. We observed that the particulate backscattering coefficient bbp was the most effective proxy for the mass concentration of suspended particulate matter (SPM) when compared with particulate scattering and attenuation coefficients bp and cp. Improvements were seen with bbp as a proxy for the concentration of particulate organic carbon (POC), although only if particulate assemblages were previously classified in terms of particle composition. We found that the ratio of polarized-light scattering measurements at 110º and 18º was superior in performance as a proxy for the composition parameter POC/SPM in comparison to the particulate backscattering ratio bbp/bp. The maximum value of the degree of linear polarization DoLPp,max observed within the range of scattering angles 89°-106° was found to provide a reasonably good proxy for a particle size parameter (i.e., 90th percentile of particle volume distribution) which characterizes the proportions of small- and large-sized particles. These findings can inform the development of polarized light scattering sensors to enhance the capabilities of autonomous platforms.
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Material Particulado , Nefelometria e Turbidimetria , Isótopos de Oxigênio , Material Particulado/análise , Espalhamento de RadiaçãoRESUMO
This erratum serves to correct an inadvertent error made during the presentation of results involving the mislabeling of the orientation of linear polarization perpendicular as parallel and vice versa in Appl. Opt.59, 8314 (2020)APOPAI0003-693510.1364/AO.396709.
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This publisher's note corrects an equation in Appl. Opt.59, 8314 (2020)APOPAI0003-693510.1364/AO.396709.
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Polarized light scattering measurements have the potential to provide improved characterization of natural particle assemblages in terms of particle size and composition. However, few studies have investigated this possibility for natural assemblages of marine particles. In this study, seawater samples representing contrasting assemblages of particles from coastal environments have been comprehensively characterized with measurements of angle-resolved polarized light scattering, particle size distribution, and particle composition. We observed robust trends linking samples containing higher proportions of large-sized particles with lower values of the maximum degree of linear polarization and the second element of the scattering matrix at a scattering angle of 100°, p22(100∘). In contrast, lower values of p22(20∘) were found in more non-phytoplankton-or inorganic--dominated samples. We also determined that three measurements involving the combinations of linearly polarized incident and scattered beams at two scattering angles (110° and 18°) have the potential to serve as useful proxies for estimating particle size and composition parameters.
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An extensive data set of measurements within the Chukchi and Beaufort Seas is used to characterize the optical properties of seawater associated with different phytoplankton communities. Hierarchical cluster analysis of diagnostic pigment concentrations partitioned stations into four distinct surface phytoplankton communities based on taxonomic composition and average cell size. Concurrent optical measurements of spectral absorption and backscattering coefficients and remote-sensing reflectance were used to characterize the magnitudes and spectral shapes of seawater optical properties associated with each phytoplankton assemblage. The results demonstrate measurable differences among communities in the average spectral shapes of the phytoplankton absorption coefficient. Similar or smaller differences were also observed in the spectral shapes of nonphytoplankton absorption coefficients and the particulate backscattering coefficient. Phytoplankton on average, however, contributed only 25% or less to the total absorption coefficient of seawater. Our analyses indicate that the interplay between the magnitudes and relative contributions of all optically significant constituents generally dampens any influence of varying phytoplankton absorption spectral shapes on the total absorption coefficient, yet there is still a marked discrimination observed in the spectral shape of the ratio of the total backscattering to total absorption coefficient and remote-sensing reflectance among the phytoplankton assemblages. These spectral variations arise mainly from differences in the bio-optical environment in which specific communities were found, as opposed to differences in the spectral shapes of phytoplankton optical properties per se. These results suggest potential approaches for the development of algorithms to assess phytoplankton community composition from measurements of seawater optical properties in western Arctic waters.
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We evaluated the performance of a recently developed absorption partitioning model [J. Geophys. Res. Oceans120, 2601 (2015)JGRCEY0148-022710.1002/2014JC010604] that derives the spectral absorption coefficients of non-algal particles, a N A P (λ), and colored dissolved organic matter, a g (λ), from the total absorption coefficient of seawater. The model's performance was found unsatisfactory when the model was tested with a large dataset of absorption measurements from diverse open-ocean and coastal aquatic environments. To address these limitations, we developed a new model based on a different approach for estimating a N A P (λ) and a g (λ) from the sum of these two coefficients, a d g (λ), within the visible spectral region. The very good overall performance of the model is demonstrated, with no tendency for bias and relatively small absolute differences (the median ≤20%) between the model-derived and measured values of a N A P (λ) and a g (λ) over a wide range of aquatic environments.
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We measured the linearly polarized light scattering of pure water and seawater at various salinities and estimated the depolarization ratio using five different methods of data analysis after removing the scattering due to contamination by residual nanoparticles. The depolarization ratio values (δ) estimated for pure water using these different methods are largely consistent with each other and result in a mean value of 0.039±0.001. For seawater, our results reveal a trend of a slight linear increase of δ with salinity (S), δ=0.039+a1×S, where a1 varies in the range of 1×10-4 to 2×10-4 between the methods.
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Ocean color measured from satellites provides daily global, synoptic views of spectral waterleaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.
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Extrapolation of near-surface underwater measurements is the most common method to estimate the water-leaving spectral radiance, Lw(λ) (where λ is the light wavelength in vacuum), and remote-sensing reflectance, Rrs(λ), for validation and vicarious calibration of satellite sensors, as well as for ocean color algorithm development. However, uncertainties in Lw(λ) arising from the extrapolation process have not been investigated in detail with regards to the potential influence of inelastic radiative processes, such as Raman scattering by water molecules and fluorescence by colored dissolved organic matter and chlorophyll-a. Using radiative transfer simulations, we examine high-depth resolution vertical profiles of the upwelling radiance, Lu(λ), and its diffuse attenuation coefficient, KLu (λ), within the top 10 m of the ocean surface layer and assess the uncertainties in extrapolated values of Lw(λ). The inelastic processes generally increase Lu and decrease KLu in the red and near-infrared (NIR) portion of the spectrum. Unlike KLu in the blue and green spectral bands, KLu in the red and NIR is strongly variable within the near-surface layer even in a perfectly homogeneous water column. The assumption of a constant KLu with depth that is typically employed in the extrapolation method can lead to significant errors in the estimate of Lw. These errors approach â¼100% at 900 nm, and the desired threshold of 5% accuracy or less cannot be achieved at wavelengths greater than 650 nm for underwater radiometric systems that typically take measurements at depths below 1 m. These errors can be reduced by measuring Lu within a much shallower surface layer of tens of centimeters thick or even less at near-infrared wavelengths longer than 800 nm, which suggests a requirement for developing appropriate radiometric instrumentation and deployment strategies.
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Spectrophotometric measurement of particulate matter retained on filters is the most common and practical method for routine determination of the spectral light absorption coefficient of aquatic particles, ap(λ), at high spectral resolution over a broad spectral range. The use of differing geometrical measurement configurations and large variations in the reported correction for pathlength amplification induced by the particle/filter matrix have hindered adoption of an established measurement protocol. We describe results of dedicated laboratory experiments with a diversity of particulate sample types to examine variation in the pathlength amplification factor for three filter measurement geometries; the filter in the transmittance configuration (T), the filter in the transmittance-reflectance configuration (T-R), and the filter placed inside an integrating sphere (IS). Relationships between optical density measured on suspensions (ODs) and filters (ODf) within the visible portion of the spectrum were evaluated for the formulation of pathlength amplification correction, with power functions providing the best functional representation of the relationship for all three geometries. Whereas the largest uncertainties occur in the T method, the IS method provided the least sample-to-sample variability and the smallest uncertainties in the relationship between ODs and ODf. For six different samples measured with 1 nm resolution within the light wavelength range from 400 to 700 nm, a median error of 7.1% is observed for predicted values of ODs using the IS method. The relationships established for the three filter-pad methods are applicable to historical and ongoing measurements; for future work, the use of the IS method is recommended whenever feasible.
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Two single-waveband low-light radiometers were developed to characterize properties of the underwater light field relevant to biological camouflage at mesopelagic ocean depths. Phenomena of interest were vertical changes in downward irradiance of ambient light at wavelengths near 470 nm and 560 nm, and flashes from bioluminescent organisms. Depth profiles were acquired at multiple deep stations in different geographic regions. Results indicate significant irradiance magnitudes at 560 nm, providing direct evidence of energy transfer as described by Raman scattering. Analysis of a night profile yielded multiple examples of bioluminescent flashes. The selection of high-sensitivity, high-speed silicon photomultipliers as detectors enabled measurement of spectrally-resolved irradiance to greater than 400 m depth.
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Luz , Oceanos e Mares , Radiometria/instrumentação , Animais , Calibragem , Ecossistema , Cinética , Medições Luminescentes , Dinâmica não Linear , Óptica e Fotônica/instrumentação , Análise EspectralRESUMO
A radiative transfer model was applied to examine the effects of vertically stratified inherent optical properties of the water column associated with near-surface plumes of suspended particulate matter on spectral remote-sensing reflectance, R(rs)(λ), of coastal marine environments. The simulations for nonuniform ocean consisting of two layers with different concentrations of suspended particulate matter (SPM) are compared with simulations for a reference homogeneous ocean whose SPM is identical to the surface SPM of the two-layer cases. The near-surface plumes of particles are shown to exert significant influence on R(rs)(λ). The sensitivity of R(rs)(λ) to vertical profile of SPM is dependent on the optical beam attenuation coefficient within the top layer, c(1)(λ), thickness of the top layer, z(1), and the ratio of SPM in the underlying layer to that in the top layer, SPM(2)/SPM(1), as well as the wavelength of light, λ. We defined a dimensionless spectral parameter, P(λ)=c(1)(λ)×z(1)×(SPM(2)/SPM(1)), to quantify and examine the effects of these characteristics of the two-layer profile of SPM on the magnitude and spectral shape of R(rs)(λ). In general, the difference of R(rs)(λ) between the two-layer and uniform ocean decreases to zero with an increase in P(λ). For the interpretation of ocean color measurements of water column influenced by near-surface plumes of particles, another dimensionless parameter P'(λ) was introduced, which is a product of terms representing homogenous ocean and a change caused by the two-layer structure of SPM. Based on the analysis of this parameter, we found that for the two-layer ocean there is a good relationship between R(rs)(λ) in the red and near-infrared spectral regions and the parameters describing the SPM(z) profile, i.e., SPM(1), SPM(2), and z(1).
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We describe a methodology for determining the volume scattering function ß(ψ) of aqueous particle suspensions from measurements with a laboratory multi-angle light scattering instrument called DAWN (Wyatt Technology Corporation). In addition to absolute and angular calibration, the key component of the method is the algorithm correcting for reflection errors that reduce the percent error in ß(ψ) from as much as ~300% to <13% at backward scattering angles. The method is optimized and tested with simulations of three-dimensional radiative transfer of exact measurement geometry including the key components of the instrument and also validated experimentally using aqueous suspensions of polystyrene beads. Example applications of the method to samples of oceanic waters and comparisons of these measurements with results obtained with other light scattering instruments are presented.
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Algoritmos , Luz , Nefelometria e Turbidimetria/instrumentação , Espalhamento a Baixo Ângulo , Suspensões/análise , Poluentes da Água/análise , Calibragem , Tamanho da Partícula , Poliestirenos , RodaminasRESUMO
A dataset of nearly 400 measurements of the particle size distribution (PSD) compiled from the Pacific, Atlantic, and Arctic Oceans is used to examine variability in the magnitude and shape of the PSD, and to characterize the partitioning of particle number, cross-sectional area, and volume concentration among defined size intervals. The results indicate that the relative contributions of three size classes based upon the pico-, nano-, and microplankton size range exhibit substantial changes among measures of particle size and between oceanic environments. The single-slope power law model commonly employed to characterize the PSD in aquatic studies is demonstrated to have significant limitations in capturing the complexity of PSD shapes observed for natural particle assemblages, and in consequence poorly predicts the relative contributions of these different size intervals. We show that specific percentile diameters derived from the cumulative distributions of particle size are strongly correlated with the contributions of these three size classes, and that these non-parametric descriptors of the cumulative distribution provide superior performance for estimating their contributions while requiring no assumption of underlying PSD shape. A comparison of these predictive relationships with independent field measurements suggests that this approach is generally robust for particle assemblages representing a wide diversity of marine environments.
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We develop a computationally fast radiative transfer model for simulating the fluctuations of the underwater downwelling irradiance E(d) at near-surface depths, which occur due to focusing of sunlight by wind-driven surface waves. The model is based on the hybrid matrix operator-Monte Carlo method, which was specifically designed for simulating radiative transfer in a coupled atmosphere-surface-ocean system involving a dynamic ocean surface. In the current version of the model, we use a simplified description of surface waves, which accounts for surface slope statistics, but not surface wave elevation, as a direct source of underwater light fluctuations. We compare the model results with measurements made in the Santa Barbara Channel. The model-simulated and measured time series of E(d)(t) show remarkable similarity. Major features of the probability distribution of instantaneous irradiance, the frequency content of irradiance fluctuations, and the statistical properties of light flashes produced by wave focusing are also generally consistent between the model simulations and measurements for a few near-surface depths and light wavelengths examined. Despite the simplification in the representation of surface waves, this model provides a reasonable first-order approximation to modeling the wave focusing effects at near-surface depths, which require high temporal and spatial resolution (of the order of 1 ms and 1 mm, respectively) to be adequately resolved.
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The size distribution of suspended particles influences several processes in aquatic ecosystems, including light propagation, trophic interactions, and biogeochemical cycling. The shape of the particle size distribution (PSD) is commonly modeled as a single-slope power law in oceanographic studies, which can be used to further estimate the relative contributions of different particle size classes to particle number, area, and volume concentration. We use a data set of 168 high size-resolution PSD measurements in Arctic oceanic waters to examine variability in the shape of the PSD over the particle diameter range 0.8 to 120 µm. An average value of -3.6 ± 0.33 was obtained for the slope of a power law fitted over this size range, consistent with other studies. Our analysis indicates, however, that this model has significant limitations in adequately parameterizing the complexity of the PSD, and thus performs poorly in predicting the relative contributions of different size intervals such as those based on picoplankton, nanoplankton, and microplankton size classes. Similarly, median particle size was also generally a poor indicator of these size class contributions. Our results suggest that alternative percentile diameters derived from the cumulative distribution functions of particle number, cross-sectional area, and volume concentration may provide better metrics to capture the overall shape of the PSD and to quantify the contributions of different particle size classes.
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Light emerging from natural water bodies and measured by radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities for characterizing aquatic ecosystems. Such upcoming missions include NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission; the NASA Surface Biology and Geology designated observable mission; and NASA Airborne Visible/Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) airborne missions. In anticipation of these missions, we present an organized dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP-AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water types, including inland waters, estuaries, and oceans. Specific in situ measurements include remote-sensing reflectance, irradiance reflectance, and coefficients describing particulate absorption, particulate attenuation, non-algal particulate absorption, colored dissolved organic matter absorption, phytoplankton absorption, total absorption, total attenuation, particulate backscattering, and total backscattering. The dataset can be downloaded from https://doi.org/10.1594/PANGAEA.902230 (Casey et al., 2019).
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We examined the effect of individual bubble clouds on remote-sensing reflectance of the ocean with a 3-D Monte Carlo model of radiative transfer. The concentrations and size distribution of bubbles were defined based on acoustical measurements of bubbles in the surface ocean. The light scattering properties of bubbles for various void fractions were calculated using Mie scattering theory. We show how the spatial pattern, magnitude, and spectral behavior of remote-sensing reflectance produced by modeled bubble clouds change due to variations in their geometric and optical properties as well as the background optical properties of the ambient water. We also determined that for realistic sizes of bubble clouds, a plane-parallel horizontally homogeneous geometry (1-D radiative transfer model) is inadequate for modeling water-leaving radiance above the cloud.