Measurements Of Inherent Optical Properties Research Articles

Optical closure in highly absorptive coastal waters: significance of inelastic scattering processes.

In hydrological optics, "optical closure" means consistency between the apparent optical properties (AOPs) determined from radiometric measurements and those derived from radiative transfer modelling based on concurrently measured inherent optical properties (IOPs) and boundary conditions (sea and sky states). Good optical closure not only provides confidence in the data quality but also informs on the adequacy of the radiative transfer parameterization. Achieving optical closure in highly absorptive coastal waters is challenging due to the low signal-to-noise ratio of radiometric measurements and uncertainties in the measurements of IOPs, namely the spectral absorption and backscattering coefficients. Here, we present an optical closure assessment using a comprehensive set of in situ IOPs acquired in highly absorptive coastal waters optically dominated by chromophoric dissolved organic matter (CDOM). The spectral remote sensing reflectance, Rrs(λ), was modeled using the software HydroLight (HL) with measured IOPs and observed boundary conditions. Corresponding in-water in situRrs(λ) was derived from radiometric measurements made with a Compact Optical Profiling System (C-OPS; Biospherical). The assessment revealed that the inclusion of inelastic scattering processes in the model, specifically sun-induced CDOM fluorescence (fDOM) and sun-induced chlorophyll fluorescence (SICF) from Chlorophyll-a ([chl]), significantly improved the optical closure and led to good agreement between measured and modeled Rrs (i.e., for 440 ≤ λ ≤ 710 nm with no inelastic processes: R2=0.90, slope=0.64; with inelastic processes: R2=0.96, slope=0.90). The analysis also indicated that fDOM and SICF contributed a substantial fraction of the green-red wavelength Rrs in these waters. Specifically, fDOM contributed ∼18% of the modeled Rrs in the green region and SICF accounted for ∼20% of the modeled Rrs in the red region. Overall, this study points out the importance of accounting for fDOM in remote sensing applications in CDOM-dominated waters.

The Imprint of Primary Production on High-Frequency Profiles of Lake Optical Properties.

Water inherent optical properties (IOPs) contain integrative information on the optical constituents of surface waters. In lakes, IOP measurements have not been traditionally collected. This study describes how high-frequency IOP profiles can be used to document short-term physical and biogeochemical processes that ultimately influence the long-term trajectory of lake ecosystems. Between October 2018 and May 2020, we collected 1373 high-resolution hyperspectral IOP profiles in the uppermost 50 m of the large mesotrophic Lake Geneva (Switzerland-France), using an autonomous profiler. A data set of this size and content does not exist for any other lake. Results showed seasonal variations in the IOPs, following the expected dynamic of phytoplankton. We found systematic diel patterns in the IOPs. Phases of these diel cycles were consistent year-round, and amplitudes correlated to the diurnal variations of dissolved oxygen, clarifying the link between IOPs and phytoplankton metabolism. Diel amplitudes were largest in spring and summer under low wind condition. Wind-driven changes in thermal stratification impacted the dynamic of the IOPs, illustrating the potential of high-frequency profiles of water optical properties to increase our understanding of carbon cycling in lake ecosystems.

Development of a diffuse reflectance probe for in situ measurement of inherent optical properties in sea ice

Abstract. Detailed characterization of the spatially and temporally varying inherent optical properties (IOPs) of sea ice is necessary to better predict energy and mass balances, as well as ice-associated primary production. Here we present the development of an active optical probe to measure IOPs of a small volume of sea ice (dm3) in situ and non-destructively. The probe is derived from the diffuse reflectance method used to measure the IOPs of human tissues. The instrument emits light into the ice by the use of an optical fibre. Backscattered light is measured at multiple distances away from the source using several receiving fibres. Comparison to a Monte Carlo simulated lookup table allows, in theory, retrieval of the absorption coefficient, the reduced scattering coefficient and a phase function similarity parameter γ, introduced by Bevilacqua and Depeursinge (1999). γ depends on the two first moments of the Legendre polynomials, allowing the analysis of the backscattered light not satisfying the diffusion regime. The depth reached into the medium by detected photons was estimated using Monte Carlo simulations: the maximum depth reached by 95 % of the detected photons was between 40±2 and 270±20 mm depending on the source–detector distance and on the ice scattering properties. The magnitude of the instrument validation error on the reduced scattering coefficient ranged from 0.07 % for the most scattering medium to 35 % for the less scattering medium over the 2 orders of magnitude we validated. Fixing the absorption coefficient and γ, which proved difficult to measure, vertical profiles of the reduced scattering coefficient were obtained with decimetre resolution on first-year Arctic interior sea ice on Baffin Island in early spring 2019. We measured values of up to 7.1 m−1 for the uppermost layer of interior ice and down to 0.15±0.05 m−1 for the bottommost layer. These values are in the range of polar interior sea ice measurements published by other authors. The inversion of the reduced scattering coefficient at this scale was strongly dependent on the value of γ, highlighting the need to define the higher moments of the phase function. This newly developed probe provides a fast and reliable means for measurement of scattering in sea ice.

Single dual mode (continuous and cast) instrumentation package for inherent optical property measurements: Characterization of the bucket for backscattering observation

AbstractThis work describes a continuous sampling system that has been designed, implemented, and tested for the acquisition of Inherent Optical Properties (IOPs) during field campaigns. The major challenge of the work was to design and build a flow‐through housing accounting for the complex sensing geometry of the ECO‐VSF3, a backscattering meter, i.e., three sensor heads each of which measures the VSF at three angles. A detailed characterization of the ECO‐VSF3 housing in terms of impact of the boundaries and overall system inertia is reported. A key feature of the system design is the possibility to easily detach the IOP package from the flow‐through hydraulic circuit and use it in cast mode at fixed stations. This, to the best of authors' knowledge, is the first time the ECO‐VSF3 is used in an underway system. Results from the comparison of continuous (Co) and cast (Ca) bb measurements show excellent agreement, with differences not exceeding 7%, thus proving the system to be reliable and highlighting the feasibility for increasing the spatio‐temporal sampling of surface observations.

Impact of Thermohaline Conditions on Vertical Variability of Optical Properties in the Gulf of Finland (Baltic Sea): Implications for Water Quality Remote Sensing

Vertical variability of inherent optical properties (IOPs) affect the water quality retrievals from remote sensing data. Here, we studied the vertical variability of IOPs and simulated apparent optical properties (AOPs) in the Gulf of Finland (Baltic Sea) under three characteristic (non)stratification conditions. In the case of mixed water column, the vertical variability of optically significant constituents (OSC) and IOPs was relatively small. While in case of stratified water column the IOPs of surface layer were three times higher compared to the IOPs below the thermocline and the IOPs were strongly correlated with the physical parameters (temperature, salinity). Measurements of IOPs in stratified water column showed that the ratio of scattering (b(440)) to absorption (a(440)) changed under the thermocline (b(440)/a(440) < 1) i.e., absorption became the dominant component of attenuation under thermocline while the opposite is true for the upper layer. Simulated (from IOPs) spectral irradiance reflectance (R(λ)) and spectral diffuse attenuation coefficient (Kd(λ)) from deeper layers (below thermocline) have significantly smaller magnitude and smoother shape. This becomes relevant during upwelling events—a common process in the coastal Baltic Sea. We quantified the effect of upwelling on surface water properties using simulated AOPs. The simulated AOPs (from IOPs measurements) showed a decrease of the signal up to 68.8% and an increase of optical depth (z90(λ)) from 2.3 to 4.3 m in the green part of the spectrum in case upwelled water mass reaches the surface. In the coastal waters a vertical decrease of Kd(λ) in the PAR region (400–700 nm) by 6.8% (surface to 20 m depth) was observed, while vertical decrease of chlorophyll-a (Chl-a) and total suspended matter (TSM) was 31.7 and 42.1%, respectively. The ratio R(490)/R(560)≥0.77 indicates also the upwelled water mass. The study showed that upwelling is a process that, in addition to biological activity, horizontal transport of OSC, and temperature changes, alters the optical signal of surface water measured by a remote sensor. Knowledge about the vertical variability of IOPs and AOPs relation to upwelling can help the parametrisation of remote sensing algorithms for retrieving water quality estimates in the coastal regions.

A closure study of ocean inherent optical properties using flow cytometry measurements

Flow cytometry and inherent optical property measurements of UK coastal waters were used to evaluate optical closure of different combinations of models for particle size, refractive index and shape. The particle size and refractive index distributions were derived from flow cytometry measurements and subsequently simplified through averaging down to the simplest model consisting of a Junge size distribution with a single bulk refractive index. Models for particle shapes included homogeneous spheres, coated spheres, and hexahedra. The simplest particle model, based on a Junge size distribution and a single bulk refractive index, gave the poorest quality of closure, suggesting that it underestimates particle complexity in the sampled waters. Other particle models using more detailed combinations of size and refractive index distributions gave broadly equivalent results for absorption and scattering. Backscattering was better represented by the most complex particle size and refractive index model, indicating that backscattering is sensitive to those factors. The homogeneous spherical model gave relatively good results, which is expected because the inversion of size and refractive index distributions from flow cytometry is based on the homogeneous spherical model using forward and side scattering signals. Lorenz-Mie theory, assuming homogeneous spheres, provided optical closure that was generally as accurate as models with more complex particle shape and structure. Cumulative contribution simulations revealed that particles between 0.5 and 20 µm substantially contributed to attenuation, scattering and backscattering, while particles larger than 20 µm mainly contributed to absorption and small particles (< 0.5 µm) contribute to 30–40% of backscattering.

Optimal Cyanobacterial Pigment Retrieval from Ocean Colour Sensors in a Highly Turbid, Optically Complex Lake

To date, several algorithms for the retrieval of cyanobacterial phycocyanin (PC) from ocean colour sensors have been presented for inland waters, all of which claim to be robust models. To address this, we conducted a comprehensive comparison to identify the optimal algorithm for retrieval of PC concentrations in the highly optically complex waters of Lake Balaton (Hungary). MEdium Resolution Imaging Spectrometer (MERIS) top-of-atmosphere radiances were first atmospherically corrected using the Self-Contained Atmospheric Parameters Estimation for MERIS data v.B2 (SCAPE-M_B2). Overall, the Simis05 semi-analytical algorithm outperformed more complex inversion algorithms, providing accurate estimates of PC up to ±7 days from the time of satellite overpass during summer cyanobacteria blooms (RMSElog &lt; 0.33). Same-day retrieval of PC also showed good agreement with cyanobacteria biomass (R2 &gt; 0.66, p &lt; 0.001). In-depth analysis of the Simis05 algorithm using in situ measurements of inherent optical properties (IOPs) revealed that the Simis05 model overestimated the phytoplankton absorption coefficient [aph(λ)] by a factor of ~2. However, these errors were compensated for by underestimation of the mass-specific chlorophyll absorption coefficient [a*chla(λ)]. This study reinforces the need for further validation of algorithms over a range of optical water types in the context of the recently launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3.

Deriving inherent optical properties from classical water color measurements: Forel-Ule index and Secchi disk depth.

Secchi disk depth (ZSD) and Forel-Ule index (FUI) are the two oldest and easiest measurements of water optical properties based on visual determination. With an overarching objective to obtain water inherent optical properties (IOPs) using these historical measurements, this study presents a model for associating remote-sensing reflectance (Rrs) with FUI and ZSD. Based upon this, a scheme (FZ2ab) for converting FUI and ZSD to absorption (a) and backscattering coefficients (bb) is developed and evaluated. For a data set from HydroLight simulations, the difference is <11% between FZ2ab-derived a and known a, and <28% between FZ2ab-derived bb and known bb. Further, for a data set from field measurements, the difference is < 30% between FZ2ab-derived a and measured a. These results indicate that FZ2ab can bridge the gap between historical measurements and the focus of IOP measurements in modern marine optics, and potentially extend our knowledge on the bio-optical properties of global seas to the past century through the historical measurements of FUI and ZSD.

Ocean Color Analytical Model Explicitly Dependent on the Volume Scattering Function

An analytical radiative transfer (RT) model for remote sensing reflectance that includes the bidirectional reflectance distribution function (BRDF) is described. The model, called ZTT (Zaneveld-Twardowski-Tonizzo), is based on the restatement of the RT equation by Zaneveld (1995) in terms of light field shape factors. Besides remote sensing geometry considerations (solar zenith angle, viewing angle, and relative azimuth), the inputs are Inherent Optical Properties (IOPs) absorption a and backscattering bb coefficients, the shape of the particulate volume scattering function (VSF) in the backward direction, and the particulate backscattering ratio. Model performance (absolute error) is equivalent to full RT simulations for available high quality validation data sets, indicating almost all residual errors are inherent to the data sets themselves, i.e., from the measurements of IOPs and radiometry used as model input and in match up assessments, respectively. Best performance was observed when a constant backward phase function shape based on the findings of Sullivan and Twardowski (2009) was assumed in the model. Critically, using a constant phase function in the backward direction eliminates a key unknown, providing a path toward inversion to solve for a and bb. Performance degraded when using other phase function shapes. With available data sets, the model shows stronger performance than current state-of-the-art look-up table (LUT) based BRDF models used to normalize reflectance data, formulated on simpler first order RT approximations between rrs and bb/a or bb/(a + bb) (Morel et al., 2002; Lee et al., 2011). Stronger performance of ZTT relative to LUT-based models is attributed to using a more representative phase function shape, as well as the additional degrees of freedom achieved with several physically meaningful terms in the model. Since the model is fully described with analytical expressions, errors for terms can be individually assessed, and refinements can be readily made without carrying out the gamut of full RT computations required for LUT-based models. The ZTT model is invertible to solve for a and bb from remote sensing reflectance, and inversion approaches are being pursued in ongoing work. The focus here is with development and testing of the in-water forward model, but current ocean color remote sensing approaches to cope with an air-sea interface and atmospheric effects would appear to be transferable. In summary, this new analytical model shows good potential for future ocean color inversion with low bias, well-constrained uncertainties (including the VSF), and explicit terms that can be readily tuned. Emphasis is put on application to the future NASA Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission.

Forward modeling of inherent optical properties from flow cytometry estimates of particle size and refractive index.

A Mie-based forward modeling procedure was developed to reconstruct bulk inherent optical properties (IOPs) from particle size distributions (PSDs) and real refractive index distributions (PRIDs) obtained using a previously developed flow cytometric (FC) method [Appl. Opt.57, 1705 (2018)APOPAI0003-693510.1364/AO.57.001705]. Given the available PSDs, extrapolations for the particle fraction outside the detection limits of the method and a complex refractive index input (with real part nr directly estimated and imaginary part ni adapted from the literature separately for organic and inorganic components), the model produces volume scattering functions that are integrated to produce scattering and backscattering coefficients, and absorption efficiencies that are used to calculate absorption coefficients. The procedure was applied to PSDs and PRIDs derived from natural samples retrieved in UK coastal waters and analyzed using a CytoSense flow cytometer (CytoBuoy b.v., The Netherlands). Optical closure analysis was carried out between reconstructed IOPs and in situ IOPs measured using an ac-9 spectrophotometer and a BB9 backscattering meter (WET Labs Inc., OR) in the same waters. The procedure is shown to achieve broad agreement with particulate scattering (bp) and backscattering (bbp) [root mean square percentage error (RMS%E): 35.3% and 44.5%, respectively) and to a lesser degree with backscattering ratio (b˜bp) (RMS%E: 77%). The procedure, however, generally overestimated particulate absorption (ap) (RMS%E: 202.3%). This degree of closure was dependent on applying recently developed scattering error corrections to both absorption and attenuation in situ measurements. Not only do these results indirectly validate the FC method as a useful tool for PSD and PRID determination in natural particle populations, they also suggest that Mie theory may be a sufficient model for bulk IOP determination, with previously reported difficulties potentially being caused by inadequately corrected IOP measurements. Finally, in a feature unique to the FC method, the concurrent size and refractive index retrieval enabled assessment of the relative contributions that organic versus inorganic, fluorescent versus non-fluorescent fractions of the particle populations had on the IOPs, and identified which size classes had the largest influence on each of these properties.

Possibilities of optical remote sensing of dispersed oil in coastal waters

This study is intended to be one of the first steps in assessing the feasibility of remote sensing of dispersed oil in seawater. All optically active seawater constituents, including oil droplets, shape the water-leaving light flux and contribute to a commonly measured apparent optical variable known as remote sensing reflectance (Rrs). Radiative transfer simulations were performed in visible bands for natural seawater in the coastal zone of the Southern Baltic Sea and for a model of seawater polluted by dispersed Petrobaltic crude oil characterised by different droplet size distributions. Our model was supplied by simultaneous in situ measurements of inherent optical properties and the Rrs of natural seawater. The optical description of dispersed oil was based on previous experiments and new application of the Mie solution to the Petrobaltic crude oil of a log-normal size distribution characterised by peak diameters ranging from 0.5 to 500 μm. The results of radiative transfer modelling showed that the typically considered concentration of 1 ppm of oil droplets can locally affect the remote sensing reflectance, causing up to a 6-fold increase or 2-fold decrease, depending on the droplet size distribution. It was demonstrated that the optically significant oil droplet sizes (giving at least 5% contribution to the total scattering coefficient) are <100 μm, as long as oil concentration does not exceed 5 ppm. Moreover, we discussed the influence of dispersed oil droplets on the performance of remote sensing algorithms based on absolute Rrs values or band ratios. Oil dispersion that consists mostly of submicron droplets in a concentration of 1 ppm had the ability to increase blue/green Rrs ratios up to 32%, whereas oil dispersions dominated by micrometre-sized droplets tended to decrease such ratios by up to 18%. Blue/red Rrs ratios were most strongly affected by dispersed Petrobaltic oil, causing a 9%–54% decrease for droplet size distributions characterised by a peak diameter of up to 100 μm. These findings demonstrate why these parameters are considered to be the most useful in the potential remote sensing algorithms.

Optical closure in marine waters from in situ inherent optical property measurements

Optical closure using radiative transfer simulations can be used to determine the consistency of in situ measurements of inherent optical properties (IOPs) and radiometry. Three scattering corrections are applied to in situ absorption and attenuation profile data for a range of coastal and oceanic waters, but are found to have only very limited impact on subsequent closure attempts for these stations. Best-fit regressions on log-transformed measured and modelled downwards irradiance, Ed, and upwards radiance, Lu, profiles have median slopes between 0.92 - 1.24, revealing a tendency to underestimate Ed and Lu with depth. This is only partly explained by non-inclusion of fluorescence emission from CDOM and chlorophyll in the simulations. There are several stations where multiple volume scattering function related data processing steps perform poorly which suggests the potential existence of unresolved features in the modelling of the angular distribution of scattered photons. General optical closure therefore remains problematic, even though there are many cases in the data set where the match between measured and modelled radiometric data is within 25% RMS%E. These results are significant for applications that rely on optical closure e.g. assimilating ocean colour data into coupled physical-ecosystem models.

Optical closure for remote-sensing reflectance based on accurate radiative transfer approximations: the case of the Changjiang (Yangtze) River Estuary and its adjacent coastal area, China

Optical closure exercises are pivotal for evaluating the accuracy of water quality remote-sensing techniques. The agreement between radiometrically derived and inherent optical property (IOP)-derived above-water spectral remote-sensing reflectance Rrs(λ) is necessary for resolving IOPs, the diffuse attenuation coefficient, and biogeochemical parameters from space. We combined spectral radiometric and IOP measurements to perform an optical closure exercise for two optically contrasting Chinese waters – the Changjiang (Yangtze) River Estuary and its adjacent coastal area in the East China Sea. The final aim of our investigation was to compare two derivations of Rrs(λ): Rrs(λ), derived from radiometric measurements; and Rrs(λ), derived from simultaneous IOP measurements. Five subsequent steps have been taken to achieve this goal, including (1) estimation of the Rrs(λ) from radiometric measurements; (2) scattering correction for the non-water spectral absorption coefficient apd(λ); (3) estimation of the below-water spectral remote-sensing reflectance rrs(λ) from IOPs measurements; (4) the estimation of the Rrs(λ) from the rrs(λ) values; and (5) the comparison between the Rrs(λ) derived from radiometric and IOP measurements. All steps were realized by using both direct measurements and different models based on radiative transfer theory. Results demonstrated that the impact of the errors caused by the scattering correction procedure and conversion of radiometric quantities into Rrs(λ) may be rather significant, especially in the long-wavelength spectrum range. Nevertheless, spectral features were similar between these Rrs(λ) sets for all waters – from relatively clear to very turbid. Exploiting this fact allows use of the spectral reflectance ratios for remote sensing of the estuarine and coastal Chinese waters.

Remote sensing of shelf sea optical properties: Evaluation of a quasi-analytical approach for the Irish Sea

A quasi-analytical approach to deriving the coefficients of absorption, a(λ), backscattering, bb(λ), and the attenuation of planar irradiance, Kd(λ), from sub-surface remote sensing reflectance, rrs(λ), was investigated for the optically complex (Case 2) waters of the Irish Sea. The algorithms of Lee et al. (2005b, Journal of Geophysical Research Oceans, 110, C02017) were tuned for this region using radiative transfer calculations which incorporated locally determined specific inherent optical properties and constituent concentrations. The optimised algorithms were then applied to rrs spectra derived from profiling radiometry for 145 stations in the Irish Sea and adjacent waters, and their outputs compared with inherent optical property measurements for these stations. For the modelled data, recoveries of, a(λ), bb(λ) and Kd(λ) in six wavebands between 412nm and 667nm had mean percentage errors below 3% and standard deviations of around 6%. For in situ data, the algorithms tended to over-estimate a(λ) and under estimate bb(λ) relative to measured values, but a contributing factor could be the difficulty of measuring optical properties accurately in turbid waters. Retrieved values of Kd(λ) were highly correlated with those measured in situ, with regression slopes in the best-performing bands of 1.05 at 442nm (r2=0.91) and 0.92 at 488nm (r2=0.96). Three previously published relationships between satellite-derived optical properties at 490nm and euphotic depth, z1%PAR, produced roughly equivalent results with root mean square percentage errors, relative to in situ measurements, of around 20%. On the logarithmic scales usually employed in remote sensing, values of a(488), bb(488), Kd(488) and z1%PAR recovered using the optimised algorithms bore strong linear relationships to in situ measurements, with least square regression slopes in the range 0.89 to 1.03 and r2 values from 0.87 to 0.94. Application of these algorithms to a MODIS image of the Irish Sea in early summer (25th May 2013) revealed marked spatial variations in optical properties which were well correlated with known patterns of tidal stirring in the region.

Optical characterization of Lake Champlain: Spatial heterogeneity and closure

A robust optical characterization of the underwater and emergent light fields of Lake Champlain was conducted for sites (n=11) throughout the lake in August 2011, based on in situ measurements with modern instrumentation and laboratory measurements of optically active constituents (OACs) and components (ax) of the absorption coefficient (a). Inherent optical property (IOP) measurements included a, ax, and the particulate scattering and backscattering coefficients. Metrics of apparent optical properties (AOPs) included Secchi depth, the diffuse attenuation coefficients for downwelling [Kd(λ)] and scalar (K0) irradiance and remote sensing reflectance [Rrs(λ)]. The credibility of the measurements is demonstrated through: (1) consistency of relationships between OACs and IOPs and AOPs, (2) the approach toward equivalence of laboratory and field measurements, and (3) the extent of closure of predictions of Kd(λ) and Rrs(λ), based on IOP measurements and radiative transfer expressions, with paired observations of these AOPs (average differences of 9.4 and 19.3%). Wide spatial differences in OACs, and the resulting IOPs and AOPs, are documented throughout the bounds of the lake and are the result of its morphologic complexity and differing external loading. The lake is a complex case 2 system, with uncoupled variations in OACs and ax over the bounds of the lake. Both empirical and radiative transfer expressions are used to predict changes in AOPs in response to hypothetical changes in OACs.

Estimation of hyperspectral inherent optical properties from in-water radiometry: error analysis and application to in situ data

An inverse algorithm is developed to retrieve hyperspectral absorption and backscattering coefficients from measurements of hyperspectral upwelling radiance and downwelling irradiance in vertically homogeneous waters. The forward model is the azimuthally averaged radiative transfer equation, efficiently solved by the EcoLight radiative transfer model, which includes the effects of inelastic scattering. Although this inversion problem is ill posed (the solution is ambiguous for retrieval of total scattering coefficients), unique and stable solutions can be found for absorption and backscattering coefficients. The inversion uses the attenuation coefficient at one wavelength to constrain the inversion, increasing the algorithm's stability and accuracy. Two complementary methods, Monte Carlo simulation and first-order error propagation, are used to develop uncertainty estimates for the retrieved absorption and backscattering coefficients. The algorithm is tested using both simulated light fields from a chlorophyll-based case I bio-optical model and radiometric field data from the 2008 North Atlantic Bloom Experiment. The influence of uncertainty in the radiometric quantities and additional model parameters on the inverse solution for absorption and backscattering is studied using a Monte Carlo approach, and an uncertainty budget is developed for retrievals. All of the required radiometric and inherent optical property measurements can be made from power-limited autonomous platforms. We conclude that hyperspectral measurements of downwelling irradiance and upwelling radiance, with a single-wavelength measurement of attenuation, can be used to estimate hyperspectral absorption to an accuracy of ±0.01 m(-1) and hyperspectral backscattering to an accuracy of ±0.0005 m(-1) from 350 to 575 nm.

MEASURING THE PARTICULATE BACKSCATTERING OF INLAND WATERS: A COMPARISON OF TECHNIQUES

Abstract. The objective of this work was to examine whether the standard particulate backscattering IOP (Inherent Optical Properties) measurement method could be simplified. IOP measurements are essential for parameterising several forms of algorithms used to estimate water quality parameters from airborne and satellite images. Field measurements of the backscattering IOPs are more difficult to make than absorption measurements as correction of the raw Hydroscat-6 backscattering sensor observations is required to allow for the systematic errors associated with the water and water quality parameter absorption. The standard approach involves making simultaneous measurement of the absorption and attenuation of the water with an absorption and attenuation meter (ac-9) or making assumptions about the particulate backscattering probability. Recently, a number of papers have been published that use an alternative method to retrieve the particulate backscattering spectrum by using laboratory measured absorption values and in situ spectroradiometric observations. The alternative method inverts a model of reflectance iteratively using non-linear least squares fitting to solve for the particulate backscattering at 532 nm (bbp0(532)) and the particulate backscattering spectral slope (γ). In this paper, eleven observations made at Burdekin Falls Dam, Australia are used to compare the alternative reflectance method to the conventional corrected Hydroscat-6 observations. Assessment of the alternative reflectance method showed that the result of the inversions were highly dependent on the starting conditions. To overcome this limitation, Particle Swarm Optimisation, a stochastic search technique which includes a random element in the search approach, was used. It was found that when compared to the conventionally corrected Hydroscat-6 observations, the alternative reflectance method underestimated bbp0(532) by approximately 50% and overestimated γ by approximately 40%. Differences of this scale in specific backscattering spectra will have a pronounced effect on the parameterisation and subsequent performance of semi-analytical water quality parameter retrieval algorithms. This has implications for any water quality monitoring regimes that rely on semi-analytical algorithms.

Optical characterization and tests of closure for Oneida Lake, New York, USA

Optical characteristics are a central feature of water quality and are increasingly used as a basis for monitoring concentrations of optically active constituents (OACs) through satellite-based remote sensing. This study presents a robust optical characterization of the near-surface waters of eutrophic Oneida Lake, New York, USA, that features in situ spectral measurements of inherent optical properties (IOPs) and remote sensing reflectance (Rrs(λ)), an apparent optical property (AOP) critical to remote sensing initiatives. The IOP measurements included the absorption coefficient, (a(λ)), and particulate scattering (bp(λ)) and backscattering (bbp(λ)) coefficients. Supporting measurements included Secchi depth (SD), the OACs, chlorophyll a, phycocyanin, suspended particulate material, and laboratory determinations of components of a(λ) (ax(λ)), including colored dissolved organic matter, nonalgal particles, and phytoplankton. The strong spectral patterns of a, ax, and Rrs, and more modest wavelength dependencies of bp and bbp, are documented. The credibility of the optical characterizations is demonstrated through (1) the consistency of relationships between SD−1 and bp, and ax and the OACs; (2) the extent of closure between in situ and laboratory measurements of a and ax; and (3) the extent of closure between predicted Rrs spectra, based on the observed IOP (a and bbp) spectra and application of a widely used radiative transfer relationship, and observations. Major temporal and substantial spatial variations in OACs, IOPs, SD, and Rrs(λ) are documented. Much of the variability in the OACs and SD were well predicted by system-specific empirical relationships that used Rrs values at specified wavelengths (consistent with the Medium Resolution Imaging Spectrophotometer [MERIS]) as the independent variables, supporting the potential for effective monitoring of these features through remote sensing in the future.

Evaluation of a compact sensor for backscattering and absorption

Seawater inherent optical properties (IOPs) are key parameters in a wide range of applications in environmental studies and oceanographic research. In particular, the absorption coefficient (a) is the typical IOP used to obtain the concentration of chlorophyll-a in the water-a critical parameter in biological oceanography studies and the backscattering coefficient (b(b)) is used as a measure of turbidity. In this study, we test a novel instrument concept designed to obtain both the absorption and backscattering coefficients. The instrument would emit a collimated monochromatic light beam into the water retrieving the backscattered light intensity as a function of distance from the center of illumination. We use Monte Carlo modeling of light propagation to create an inversion algorithm that translates the signal from such an instrument into values of a and b(b). Our results, based on simulations spanning the bulk of natural values of seawater IOP combinations, indicate that a 6.2 cm diameter instrument with a radial resolution of 1 cm would be capable of predicting b(b) within less than 13.4% relative difference and a within less than 57% relative difference (for 90% of the inverted a values, the relative errors fall below 29.7%). Additionally, these errors could be further reduced by constraining the inversion algorithm with information from concurrent measurements of other IOPs. Such a compact and relatively simple device could have multiple applications for in situ optical measurements, including a and b(b) retrievals from instrumentation mounted on autonomous underwater vehicles. Furthermore, the same methodology could possibly be used for an out-of-water sensor.

Ocean color patterns help to predict depth of optical layers in stratified coastal waters

Subsurface optical layers distributed at two different depths were investigated in Monterrey Bay, East Sound, and the Black Sea based on spatial statistics of remote sensing reflectance (Rrs). The main objective of this study was to evaluate the use of Rrs(443)/Rrs(490) (hereafter R1) skewness (ψ) as an indicator of vertical optical structure in different marine regions. Measurements of inherent optical properties were obtained using a remotely op- erated towed vehicle and R1 was theoretically derived from optical profiles. Although the broad range of trophic status and water stratification, a common statistical pattern consist- ing of lower ψR1—a deeper optical layer was found in all study cases. This variation was attributed to optical changes above the opticline and related to horizontal variability of par- ticulates and spectral variations with depth. We recommend more comparisons in stratified coastal waters with different phytoplankton communities before the use of ψR1 can be gener- alized as a noninvasive optical proxy for screening depth changes on subsurface optical layers.