Remote-sensing reflectance in the Beaufort and Chukchi seas: observations and models

Two semianalytical remote-sensing reflectance models were evaluated and validated by use of bio-optical data collected in the Beaufort and Chukchi seas. Both models were efficient at retrieving chlorophyll concentration, phytoplankton absorption coefficients,and particulate backscattering coefficients. In contrast, they were not accurate in predicting an absorption coefficient for colored dissolved organic matter plus nonpigmented particulates. The poor model performance is attributed to the high variability in the concentrations of these colored materials. A chlorophyll-dependent reflectance model was also assessed, and it proved to be highly successful in reproducing measured reflectance spetra. A four-component, case 2 model with mean absorption spectra for phytoplankton, soluble materials, and nonpigmented particulates was employed in Hydrolight radiative-transfer model simulations. The remote sensing reflectance spectra simulated inthe radiative-transfer model were in excellent agreement with field data. The similarity between the model and the measurement confirms the accuracy of the underlying bio-optical relationships and underscores the utility of modeling for better understanding of the variability of ocean color observations. The latest SeaWiFS algorithm (OC4V4) overestimated chlorophyll by approximately 1.5 fold across most of the observed range of biomass (0.07-9 mg chlorophyll m(-3)). Regionally tuned algorithms explained > 93% of the variability in the surface chlorophyll concentration.     

Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results

The analytical development and underlying hypothesis of a three-band algorithm for estimating chlorophyll-a concentration ([Chla]) in turbid productive waters are presented. The sensitivity of the algorithm to the spectral location of the bands used is analyzed. A large set of experimental observations ([Chla] varied between 4 and 217 mg m(-3) and turbidity between 2 and 78 nephelometric turbidity units) was used to calibrate and validate the algorithm. It was found that the variability of the chlorophyll-a fluorescence quantum yield and of the chlorophyll-a specific absorption coefficient can reduce considerably the accuracy of remote predictions of [Chla]. Instead of parameterizing these interferences, their effects were minimized by tuning the spectral regions used in the algorithm. This allowed us to predict [Chla] with a relative root-mean-square error of less than 30%.     

Uncertainties of inherent optical properties obtained from semianalytical inversions of ocean color

We present a method to quantify the uncertainties in the in-water constituent absorption and backscattering coefficients obtained from an inversion of remotely sensed reflectance (rrs). We first find a set of positive inversion solutions within a given uncertainty range around the values of the inverted rrs. The uncertainties of the solutions are then computed based on the statistics of these solutions. We demonstrate the uncertainty calculation algorithm using a specific semianalytic inversion model applied to both a field and a simulated data set. When the associated uncertainties are taken into account, the inverted parameters are generally within the uncertainties of the measured (or simulated) parameters, highlighting the success of the inversion and the method to obtain uncertainties. The specific inversion we use, however, fails to retrieve two spectral parameters within a usable range. The method presented is general and can be applied to all existing semianalytical inversion algorithms.     

Model of phytoplankton absorption based on three size classes

Using the phytoplankton size-class model of Brewin et al. [Ecol. Model.221, 1472 (2010)], the two-population absorption model of Sathyendranath et al. [Int. J. Remote. Sens.22, 249 (2001)] and Devred et al. [J. Geophys. Res.111, C03011 (2006)] is extended to three populations of phytoplankton, namely, picophytoplankton, nanophytoplankton, and microphytoplankton. The new model infers total and size-dependent phytoplankton absorption as a function of the total chlorophyll-a concentration. A main characteristic of the model is that all the parameters that describe it have biological or optical interpretation. The three-population model performs better than the two-population model at retrieving total phytoplankton absorption. Accounting for the contributions of picophytoplankton and nanophytoplankton, rather than the combination of both as in the two-population model, improved significantly the retrieval of phytoplankton absorption at low chlorophyll-a concentrations. Class-dependent specific absorption of phytoplankton derived using the model compares well with previously published models. However, the model presented in this paper provides the specific absorption of three size classes and is applicable to a continuum of chlorophyll-a concentrations. Absorption obtained from remotely sensed chlorophyll-a using our model compares well with in situ absorption measurements.     

Bio-optical properties and ocean color algorithms for coastal waters influenced by the Mississippi River during a cold front

During the passage of a cold front in March 2002, bio-optical properties examined in coastal waters impacted by the Mississippi River indicated that westward advective flows and increasing river discharge containing high concentrations of nonalgal particles contributed significantly to surface optical variability. A comparison of seasonal data from three cruises indicated spectral models of absorption and scattering to be generally consistent with other coastal environments, while their parameterization in terms of chlorophyll (Chl) alpha concentration showed seasonal variability. The exponential slope of the colored dissolved organic matter (CDOM) averaged 0.0161+/-0.00054 nm(-1) and nonalgal absorption averaged 0.011 nm(-1) with deviations from general trends observed due to anomalous water properties. Although the phytoplankton specific absorption coefficients varied over a wide range [0.02 to 0.1 m2 (mg Chl)(-1) at 443 nm] being higher in offshore surface waters, values of phytoplankton absorption spectra at the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) wave bands were highly correlated to modeled values. Particulate scattering characteristics were similar to observations for other coastal waters, while backscattering ratios were on average lower in phytoplankton-dominated surface waters (0.011+/-0.003) and higher in low Chl near-bottom waters (0.0191+/-0.0045). Average percent differences in remote sensing reflectance Rrs derived from modeled and in-water radiometric measurements were highest in the blue wave bands (52%) and at locations with more stratified water columns. SeaWiFS estimates of Chl and CDOM absorption derived using regional empirical algorithms were highly correlated to in situ data.     

Model for the interpretation of hyperspectral remote-sensing reflectance

Remote-sensing reflectance is easier to interpret for the open ocean than for coastal regions because the optical signals are highly coupled to the phytoplankton (e.g., chlorophyll) concentrations. For estuarine or coastal waters, variable terrigenous colored dissolved organic matter (CDOM), suspended sediments, and bottom reflectance, all factors that do not covary with the pigment concentration, confound data interpretation. In this research, remote-sensing reflectance models are suggested for coastal waters, to which contributions that are due to bottom reflectance, CDOM fluorescence, and water Raman scattering are included. Through the use of two parameters to model the combination of the backscattering coefficient and the Q factor, excellent agreement was achieved between the measured and modeled remote-sensing reflectance for waters from the West Florida Shelf to the Mississippi River plume. These waters cover a range of chlorophyll of 0.2-40 mg/m(3) and gelbstoff absorption at 440 nm from 0.02-0.4 m(-1). Data with a spectral resolution of 10 nm or better, which is consistent with that provided by the airborne visible and infrared imaging spectrometer (AVIRIS) and spacecraft spectrometers, were used in the model evaluation.     

Spectral parameters of inherent optical property models: method for satellite retrieval by matrix inversion of an oceanic radiance model

Inherent optical property (IOP) spectral models for the phytoplankton absorption coefficient, chromophoric dissolved organic matter (CDOM) absorption coefficient, and total constituent backscattering (TCB) coefficient are linear in the reference wavelength IOP and nonlinear in the spectral parameters. For example, the CDOM absorption coefficient IOP a(CDOM)(lambda(i)) = a(CDOM)(lambda(ref))exp[-S(lambda(i)- lambda(ref))] is linear in a(CDOM)(lambda(ref)) and nonlinear in S. Upon linearization by Taylor's series expansion, it is shown that spectral model parameters, such as S, can be concurrently accommodated within the same conventional linear matrix formalism used to retrieve the reference wavelength IOP's. Iteration is used to adjust for errors caused by truncation of the Taylor's series expansion. Employing an iterative linear matrix inversion of a water-leaving radiance model, computer simulations using synthetic data suggest that (a) no instabilities or singularities are introduced by the linearization and subsequent matrix inversion procedures, (b) convergence to the correct value can be expected only if starting values for a model parameter are within certain specific ranges, (c) accurate retrievals of the CDOM slope S (or the phytoplankton Gaussian width g) are generally reached in 3-20 iterations, (d) iterative retrieval of the exponent n of the TCB wavelength ratio spectral model is not recommended because the starting values must be within approximately +/-5% of the correct value to achieve accurate convergence, and (e) concurrent retrieval of S and g (simultaneously with the phytoplankton, CDOM, and TCB coefficient IOP's) can be accomplished in a 5 x 5 iterative matrix inversion if the starting values for S and g are carefully chosen to be slightly higher than the expected final retrieved values.     

Apparent and inherent optical properties of turbid estuarine waters: measurements, empirical quantification relationships, and modeling

Spectral measurements of remote-sensing reflectance (Rrs) and absorption coefficients carried out in three European estuaries (Gironde and Loire in France, Tamar in the UK) are presented and analyzed. Typical Rrs and absorption spectra are compared with typical values measured in coastal waters. The respective contributions of the water constituents, i.e., suspended sediments, colored dissolved organic matter, and phytoplankton (characterized by chlorophyll-a), are determined. The Rrs spectra are then reproduced with an optical model from the measured absorption coefficients and fitted backscattering coefficients. From Rrs ratios, empirical quantification relationships are established, reproduced, and explained from theoretical calculations. These quantification relationships were established from numerous field measurements and a reflectance model integrating the mean values of the water constituents' inherent optical properties. The model's sensitivity to the biogeochemical constituents and to their nature and composition is assessed.     

Effect of the particle-size distribution on the backscattering ratio in seawater

Mie theory is used to model the backscattering ratio (the ratio of the backscattering coefficient to the total scattering coefficient) of marine particles with the assumption that they follow a Junge-type size distribution. Results show that the backscattering ratio is very sensitive to the presence of submicrometer particles and depends strongly on the shape of the size distribution. However, it is not affected significantly by absorption and does not vary with wavelength over the visible range. The implications for modeling of backscattering and ocean color in terms of phytoplankton pigment concentration are discussed.     

Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters

For open ocean and coastal waters, a multiband quasi-analytical algorithm is developed to retrieve absorption and backscattering coefficients, as well as absorption coefficients of phytoplankton pigments and gelbstoff. This algorithm is based on remote-sensing reflectance models derived from the radiative transfer equation, and values of total absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. In the calculation of total absorption coefficient, no spectral models for pigment and gelbstoff absorption coefficients are used. Actually those absorption coefficients are spectrally decomposed from the derived total absorption coefficient in a separate calculation. The algorithm is easy to understand and simple to implement. It can be applied to data from past and current satellite sensors, as well as to data from hyperspectral sensors. There are only limited empirical relationships involved in the algorithm, and they are for less important properties, which implies that the concept and details of the algorithm could be applied to many data for oceanic observations. The algorithm is applied to simulated data and field data, both non-case1, to test its performance, and the results are quite promising. More independent tests with field-measured data are desired to validate and improve this algorithm.     

Modeling the optical properties of mineral particles suspended in seawater and their influence on ocean reflectance and chlorophyll estimation from remote sensing algorithms

The optical properties of mineral particles suspended in seawater were calculated from the Mie scattering theory for different size distributions and complex refractive indices of the particles. The ratio of the spectral backscattering coefficient to the sum of the spectral absorption and backscattering coefficients of seawater, b(b)(lambda)/[a(lambda) + b(b)(lambda)], was analyzed as a proxy for ocean reflectance for varying properties and concentrations of mineral particles. Given the plausible range of variability in the particle size distribution and the refractive index, the general parameterizations of the absorption and scattering properties of mineral particles and their effects on ocean reflectance in terms of particle mass concentration alone are inadequate. The variations in the particle size distribution and the refractive index must be taken into account. The errors in chlorophyll estimation obtained from the remote sensing algorithms that are due to the presence of mineral particles can be very large. For example, when the mineral concentration is 1 g m(-3) and the chlorophyll a concentration is low (0.05 mg m(-3)), current global algorithms based on a blue-to-green reflectance ratio can produce a chlorophyll overestimation ranging from approximately 50% to as much as 20-fold.     

Analytic model of ocean color

Ocean color is determined by spectral variations in reflectance at the sea surface. In the analytic model presented here, reflectance at the sea surface is estimated with the quasi-single-scattering approximation that ignores transspectral processes. The analytic solutions we obtained are valid for a vertically homogeneous water column. The solution provides a theoretical expression for the dimensionless, quasi-stable parameter (r), with a value of ~0.33, that appears in many models in which reflectance at the sea surface is expressed as a function of absorption coefficient (a) and backscattering coefficient (b(b)). In the solution this parameter is represented as a function of the mean cosines for downwelling and upwelling irradiances and as the ratio of the upward-scattering coefficient to the backscattering coefficient. Implementation of the model is discussed for two cases: (1) that in which molecular scattering is the main source of upwelling light, and (2) that in which particle scattering is responsible for all the upwelled light. Computations for the two cases are compared with Monte Carlo simulations, which accounts for processes not considered in the analytic model (multiple scattering, and consequent depth-dependent changes in apparent optical properties). The Monte Carlo models show variations in reflectance with the zenith angle of the incident light. The analytic model can be used to reproduce these variations fairly well for the case of molecular scattering. For the particle-scattering case also, the analytic and Monte Carlo models show similar variations in r with zenith angle. However, the analytic model (as implemented here) appears to underestimate r when the value of the backscattering coefficient b(b) increases relative to the absorption coefficient a. The errors also vary with the zenith angle of the incident light field, with the maximum underestimate being approximately 0.06 (equivalent to relative errors from 12 to 17%) for the range of b(b)/a studied here. One implication of this result is that the model could also be used to obtain approximate solutions for the Q factor, defined for a given look angle as the ratio of the upwelling irradiance at the surface to the upwelling radiance at the surface at that angle. This is a quantity that is important in remote-sensing applications of ocean-color models. An advantage of the model discussed here is that its implementation requires inputs that are in principle accessible only in a remote-sensing context.     

Covariance of the absorption of phytoplankton, colored dissolved organic matter, and detritus in case I waters, as deduced from the Coastal Zone Color Scanner bio-optical algorithm

The universal bio-optical algorithm of the Coastal Zone Color Scanner (CZCS) for case I waters implicitly contains an average covariance of the absorption by phytoplankton and colored dissolved organic matter (CDOM) and detritus. We made that covariance explicit by combining the CZCS algorithm with an expression for reflectance. The spectral variation of absorption by CDOM plus detritus for case I waters may be estimated by the expression a(gd(λ)) = 2a(ph)(443)*chl{exp[-0.013(λ - 443)].     

Remote sensing of ocean color and aerosol properties: resolving the issue of aerosol absorption

Current atmospheric correction and aerosol retrieval algorithms for ocean color sensors use measurements of the top-of-the-atmosphere reflectance in the near infrared, where the contribution from the ocean is known for case 1 waters, to assess the aerosol optical properties. Such measurements are incapable of distinguishing between weakly and strongly absorbing aerosols, and the atmospheric correction and aerosol retrieval algorithms fail if the incorrect absorption properties of the aerosol are assumed. We present an algorithm that appears promising for the retrieval of in-water biophysical properties and aerosol optical properties in atmospheres containing both weakly and strongly absorbing aerosols. By using the entire spectrum available to most ocean color instruments (412-865 nm), we simultaneously recover the ocean's bio-optical properties and a set of aerosol models that best describes the aerosol optical properties. The algorithm is applied to simulated situations that are likely to occur off the U.S. East Coast in summer when the aerosols could be of the locally generated weakly absorbing Maritime type or of the pollution-generated strongly absorbing urban-type transported over the ocean by the winds. The simulations show that the algorithm behaves well in an atmosphere with either weakly or strongly absorbing aerosol. The algorithm successfully identifies absorbing aerosols and provides close values for the aerosol optical thickness. It also provides excellent retrievals of the ocean bio-optical properties. The algorithm uses a bio-optical model of case 1 waters and a set of aerosol models for its operation. The relevant parameters of both the ocean and atmosphere are systematically varied to find the best (in a rms sense) fit to the measured top-of-the-atmosphere spectral reflectance. Examples are provided that show the algorithm's performance in the presence of errors, e.g., error in the contribution from whitecaps and error in radiometric calibration.     

Optical assessment of particle size and composition in the Santa Barbara Channel, California

The suspended particle assemblage in complex coastal waters is a mixture of living phytoplankton, other autochthonous matter, and materials of terrestrial origin. The characterization of suspended particles is important for understanding regional primary productivity and rates of carbon sequestration, the fate of anthropogenic materials released to the coastal environment, as well as its effects on bulk optical properties, which influence the passive optical remote sensing of the coastal ocean. Here, the extensive bio-optical Plumes and Blooms data set is used to characterize the surface particle assemblage in the Santa Barbara Channel, California, a highly productive, upwelling-dominated, coastal site affected by episodic sediment inputs. Available variables sensitive to characteristics of the particle assemblage include particle beam attenuation and backscattering coefficients, High Performance Liquid Chromatography (HPLC) pigment concentration observations, chlorophyll and particulate organic carbon concentration, particulate and phytoplankton absorption coefficients, and Laser In-situ Scattering and Transmissometry (LISST) 100-X particle sizer observations. Comparisons among these particle assemblage proxy variables indicate good agreement and internal consistency among the data set. Correlations among chlorophyll concentration, particulate organic carbon concentration (POC), HPLC pigments, and proxies sensitive to the entire particle assemblage such as backscattering and LISST data strongly indicate that in spite of its coastal character, variability in the particle assemblage in the Santa Barbara Channel is dominated by its marine biogenic component. Relatively high estimates of the bulk real index of refraction and its positive correlation with chlorophyll and lithogenic silica concentration tentatively indicate that there is minerogenic particle influence in the Santa Barbara Channel that tends to covary with the phytoplankton blooms. Limitations of each particle assemblage proxy and remote-sensing applications are discussed.     

Satellite retrieval of the absorption coefficient of phytoplankton phycoerythrin pigment: theory and feasibility status

Oceanic radiance model inversion methods are used to develop a comprehensive algorithm for retrieval of the absorption coefficients of phycourobilin (PUB) pigment, type I phycoerythrobilin (PEB) pigment rich in PUB, and type II PEB deficient in PUB pigment (together with the usual "big three" inherent optical properties: the total backscattering coefficient and the absorption coefficients of chromophoric dissolved organic matter (CDOM)-detritus and phytoplankton). This fully modeled inversion algorithm is then simplified to yield a hybrid modeled-unmodeled inversion algorithm in which the phycoerythrin (PE) absorption coefficient is retrieved as unmodeled 488-nm absorption (which exceeds the modeled phytoplankton and the CDOM-detritus absorption coefficients). Each algorithm was applied to water-leaving radiances, but only hybrid modeled-unmodeled inversions yielded viable retrievals of the PE absorption coefficient. Validation of the PE absorption coefficient retrieval was achieved by relative comparison with airborne laser-induced PEB fluorescence. The modeled-unmodeled retrieval of four inherent optical properties by direct matrix inversion is rapid and well conditioned, but the accuracy is strongly limited by the accuracy of the three principal inherent optical property models across all four spectral bands. Several research areas are identified to enhance the radiance-model-based retrievals: (a) improved PEB and PUB absorption coefficient models, (b) PE spectral shifts induced by PUB chromophore substitution at chromophore binding sites, (c) specific absorption-sensitive phytoplankton absorption modeling, (d) total constituent backscattering modeling, (e) unmodeled carotinoid and phycocyanin absorption that are not now accounted for in the chlorophyll-dominated phytoplankton absorption coefficient model, and (f) iterative inversion techniques to solve for six constituents with only five radiances. Although considerable progress has been made toward the satellite recovery of PE absorption, the maturity of the retrieval is presently insufficient for routine global application. Instead it must currently be used on a regional basis where localized ship and aircraft validation can be made available. The algorithm was developed for the MODIS (Moderate-Resolution Imaging Spectroradiometer) sensor but is applicable to any sensor having comparable band locations.     

Satellite retrieval of inherent optical properties by inversion of an oceanic radiance model: a preliminary algorithm

A previously published radiance model inversion theory has been field tested by using airborne water-leaving radiances to retrieve the chromophoric dissolved organic matter (CDOM) and detritus absorption coefficient, the phytoplankton absorption coefficient, and the total backscattering coefficient. The radiance model inversion theory was tested for potential satellite use by comparing two of the retrieved inherent optical properties with concurrent airborne laser-derived truth data. It was found that (1) matrix inversion of water-leaving radiances is well conditioned even in the presence of instrument-induced noise, (2) retrieved CDOM and detritus and phytoplankton absorption coefficients are both in reasonable agreement with absorption coefficients derived from airborne laser-induced fluorescence spectral emissions, (3) the total backscattering retrieval magnitude and variability are consistent with expected values for the Middle Atlantic Bight, and (4) the algorithm performs reasonably well in Sargasso Sea, Gulf Stream, slope, and shelf waters but is less consistent in coastal waters.     

Optical influence of ship wakes

The optical variations observed within ship wakes are largely due to the generation of copious amounts of air bubbles in the upper ocean, a fraction of which accumulate as foam at the surface, where they release scavenged surfactants. Field experiments were conducted to test previous theoretical predictions of the variations in optical properties that result from bubble injection in the surface ocean. Variations in remote-sensing reflectance and size distribution of bubbles within the ship-wake zone were determined in three different optical water types: the clear equatorial Pacific Ocean, moderately turbid coastal waters, and very turbid coastal waters, the latter two of which were offshore of New Jersey. Bubbles introduced by moving vessels increased the backscattering in all cases, which in turn enhanced the reflectance over the entire visible and infrared wave bands. The elevated reflectance had different spectral characteristics in the three locations. The color of ship wakes appears greener in the open ocean, whereas little change in color was observed in near-coastal turbid waters, consistent with predictions. Colorless themselves, bubbles increase the reflected radiance and change the color of the ocean in a way that depends on the spectral backscattering and absorption of the undisturbed background waters. For remote observation from aircraft or satellite, the foam and added surfactants further enhance the reflectance to a degree dependent on the illumination and the viewing geometry.     

Comparison of optically derived particle size distributions: scattering over the full angular range versus diffraction at near forward angles

The volume scattering function (VSF) of particles in water depends on the particles' size distribution and composition as well as their shape and internal structure. Inversion of the VSF thus provides information about the particle population. The commercially available LISST instrument measures the scattering at near forward angles to estimate the bulk size distribution of particles larger than about 1?μm. By using scattering over the full angular range (0°-180°), the recently improved VSF-inversion method [X. Zhang, M. Twardowski, and M. Lewis, Appl. Opt. 50, 1240 (2011).10.1364/AO.50.001240APOPAI0003-6935] can characterize particles in terms of particle subpopulations, which are described by their unique size distribution and composition. Concurrent deployments of the Multispectral Volume Scattering Meter and the LISST in three coastal waters (i.e., Chesapeake Bay, Mobile Bay, and Monterey Bay) allowed us to compare the size distributions derived from these two different methods. We also obtained indirect validation of the results for submicrometer particles and for the composition of particles provided by the VSF-inversion method. For particle sizes ranging from 1 to 100?μm, the concentration was shown to vary over 10 orders of magnitude, and excellent agreement was found between the two methods with a mean relative difference less than 10% for the total size distributions. The inversion results also reproduced spectral variations in the shape of the VSF, although these spectral variations were not frequently observed in our study. The increased backscattering towards the shorter wavelengths was explained by the stronger influence of submicrometer particles affecting the backscattering. Based on published measurements of cell sizes and intracellular chlorophyll-a [Chl] concentrations over a wide range of phytoplankton species and strains, [Chl] was estimated for the inverted subpopulations that were identified as phytoplankton based on their refractive index and mean sizes. The estimated [Chl] agreed well with the fluorescence-based estimates in both magnitude and trend, thus reproducing a bloom event observed at a time series station.     

Influence of small inhomogeneities on the spectral characteristics of single thin films

It is well known that the spectral transmittance and reflectance of a thin film can be influenced by even small inhomogeneities or variations in its complex refractive-index profile. Formulas are derived that describe the theoretical variation of the spectral characteristics for small changes in the refractive index and the extinction coefficient of a homogeneous thin film. These formulas, accurate to the first order in the change in the complex refractive index, are compared with exact calculations for a number of different types of inhomogeneities. It is shown that specific qualitative features in the refractive-index profile of a nearly homogeneous thin film frequently can be determined from an examination of the change in the spectral transmittance and reflectance at normal incidence.