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Mukherjee S, Hedley JD, Fichot CG, Laliberté J, Bélanger S. Optical closure in highly absorptive coastal waters: significance of inelastic scattering processes. OPTICS EXPRESS 2023; 31:35178-35199. [PMID: 37859255 DOI: 10.1364/oe.501732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 09/11/2023] [Indexed: 10/21/2023]
Abstract
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 situ Rrs(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.
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Small Angle Scattering Intensity Measurement by an Improved Ocean Scheimpflug Lidar System. REMOTE SENSING 2021. [DOI: 10.3390/rs13122390] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Quantification of the horizontal patterns of phytoplankton and the distribution of suspended particles across the sea’s surface has been greatly improved by traditional passive oceanic color remote sensing technology. Lidar technology has already been proven to be effective positive remote sensing technology to construct high-resolution bathymetry models. Lidar technology significantly improves our ability to model biogeochemical processes in the upper ocean and provides advanced concepts regarding the vertical distribution of suspended particles and oceanic optical properties. In this paper, we present a novel optical approach to measuring the scattering intensity and characteristics of suspended particles within small angles backwards and distinguish water medium with different attenuation coefficients by a laboratory demonstration of the ocean Scheimpflug lidar system. The approach allows the direct determination of the scattering intensity over a small angle at the backward direction (175.8~178.8°) with an angular resolution of 0.38. Corrections for the effects of refraction at the air-glass-water interface were demonstrated. The data production (initial width and width attenuation rate of the laser beam) of the ocean Scheimpflug lidar system were utilized to distinguish water with different algae concentrations. Application for the measurement of backward scattering intensity and laser beam width were explored in distances up to several meters with spatial resolutions of millimeter precision.
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Lefering I, Röttgers R, Utschig C, Twardowski MS, McKee D. Measurement uncertainties in PSICAM and reflective tube absorption meters. OPTICS EXPRESS 2018; 26:24384-24402. [PMID: 30469558 DOI: 10.1364/oe.26.024384] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 08/02/2018] [Indexed: 05/26/2023]
Abstract
The nature and magnitude of measurement uncertainties (precision and accuracy) associated with two approaches for measuring absorption by turbid waters (b(532 nm) ranging from 0.20 m-1 to 22.89 m-1) are investigated here: (a) point source integrating cavity absorption meters (PSICAM), and (b) reflective tube absorption meters (AC-9 and AC-s - both WET Labs Inc., USA). Absolute measurement precision at 440 nm was quantified using standard deviations of triplicate measurements for the PSICAM and de-trended, bin averaged time series for the AC-9/s, giving comparable levels (< 0.006 m-1) for both instruments. Using data collected from a wide range of UK coastal waters, PSICAM accuracy was assessed by comparing both total non-water absorption and absorption by coloured dissolved organic material (CDOM) measured on discrete samples by two independent PSICAMs. AC-9/s performance was tested by comparing total non-water absorption measured in situ by an AC-9 and an AC-s mounted on the same frame. Results showed that the PSICAM outperforms AC-9/s instruments with regards to accuracy, with average spread in the PSICAM total absorption data of 0.006 m-1 (RMSE) compared to 0.028 m-1 for the AC-9/s devices. Despite application of a state of the art scattering correction method, the AC-9/s instruments still tend to overestimate absorption compared to PSICAM data by on average 0.014 m-1 RMSE (AC-s) and 0.043 m-1 RMSE (AC-9). This remaining discrepancy can be largely attributed to residual limitations in the correction of AC-9/s data for scattering effects and limitations in the quality of AC-9/s calibration measurements.
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Werdell PJ, McKinna LI, Boss E, Ackleson SG, Craig SE, Gregg WW, Lee Z, Maritorena S, Roesler CS, Rousseaux CS, Stramski D, Sullivan JM, Twardowski MS, Tzortziou M, Zhang X. An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing. PROGRESS IN OCEANOGRAPHY 2018; 160:186-212. [PMID: 30573929 PMCID: PMC6296493 DOI: 10.1016/j.pocean.2018.01.001] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
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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Affiliation(s)
| | - Lachlan I.W. McKinna
- NASA Goddard Space Flight Center, Code 616, Greenbelt, MD, USA
- Go2Q Pty Ltd, Sunshine Coast, QLD, Australia
| | - Emmanuel Boss
- School of Marine Sciences, University of Maine, Orono, Maine, USA
| | | | - Susanne E. Craig
- NASA Goddard Space Flight Center, Code 616, Greenbelt, MD, USA
- Universities Space Research Association, Columbia, MD, USA
| | - Watson W. Gregg
- NASA Global Modeling and Assimilation Office, Greenbelt, MD, USA
| | - Zhongping Lee
- School for the Environment, University of Massachusetts Boston, Boston, MA, USA
| | | | - Collin S. Roesler
- Department of Earth and Oceanographic Science, Bowdoin College, Brunswick, ME, USA
| | - Cécile S. Rousseaux
- Universities Space Research Association, Columbia, MD, USA
- NASA Global Modeling and Assimilation Office, Greenbelt, MD, USA
| | - Dariusz Stramski
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
| | - James M. Sullivan
- Harbor Branch Oceanographic Institute, Florida Atlantic University, Fort Pierce, FL, USA
| | - Michael S. Twardowski
- Harbor Branch Oceanographic Institute, Florida Atlantic University, Fort Pierce, FL, USA
| | - Maria Tzortziou
- Department of Earth and Atmospheric Science, The City College of New York, New York, NY, USA
- NASA Goddard Space Flight Center, Code 614, Greenbelt, MD, USA
| | - Xiaodong Zhang
- Department of Earth System Science and Policy, University of North Dakota, Grand Forks, ND, USA
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Xiong Y, Zhang X, He S, Gray DJ. Re-examining the effect of particle phase functions on the remote-sensing reflectance. APPLIED OPTICS 2017; 56:6881-6888. [PMID: 29048028 DOI: 10.1364/ao.56.006881] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Accepted: 07/21/2017] [Indexed: 06/07/2023]
Abstract
Even though it is well known that both the magnitude and detailed angular shape of scattering (phase function, PF), particularly in the backward angles, affect the color of the ocean, the current remote-sensing reflectance (Rrs) models typically account for the effect of its magnitude only through the backscattering coefficient (bb). Using 116 volume scattering function (VSF) measurements previously collected in three coastal waters around the U.S. and in the water of the North Atlantic Ocean, we re-examined the effect of particle PF on Rrs in four scenarios. In each scenario, the magnitude of particle backscattering (i.e., bbp) is known, but the knowledge on the angular shape of particle backscattering is assumed to increase from knowing nothing about the shape of particle PFs to partially knowing the particle backscattering ratio (Bp), the exact backscattering shape as defined by β˜p(γ≥90°) (particle VSF normalized by the particle total scattering coefficient), and the exact backscattering shape as defined by the χp factor (particle VSF normalized by the particle backscattering coefficient). At sun zenith angle=30°, the nadir-viewed Rrs would vary up to 65%, 35%, 20%, and 10%, respectively, as the constraints on the shape of particle backscattering become increasingly stringent from scenarios 1 to 4. In all four scenarios, the Rrs variations increase with both viewing and sun angles and are most prominent in the direction opposite the sun. Our results show a greater impact of the measured particle PFs on Rrs than previously found, mainly because our VSF data show a much greater variability in Bp, β˜p(γ≥90°), and χp than previously known. Among the uncertainties in Rrs due to the particle PFs, about 97% can be explained by χp, 90% by β˜p(γ≥90°), and 27% by Bp. The results indicate that the uncertainty in ocean color remote sensing can be significantly constrained by accounting for χp of the VSFs.
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Lain LR, Bernard S, Matthews MW. Understanding the contribution of phytoplankton phase functions to uncertainties in the water colour signal. OPTICS EXPRESS 2017; 25:A151-A165. [PMID: 28241532 DOI: 10.1364/oe.25.00a151] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The accurate description of a water body's volume scattering function (VSF), and hence its phase functions, is critical to the determination of the constituent inherent optical properties (IOPs), the associated spectral water-leaving reflectance, and consequently the retrieval of phytoplankton functional type (PFT) information. The equivalent algal populations (EAP) model has previously been evaluated for phytoplankton-dominated waters, and offers the ability to provide phytoplankton population-specific phase functions, unveiling a new opportunity to further understanding of the causality of the PFT signal. This study presents and evaluates the wavelength dependent, spectrally variable EAP particle phase functions and the subsequent effects on water-leaving reflectance. Comparisons are made with frequently used phase function approximations e.g. the Fournier Forand formulation, as well as with phase functions inferred from measured VSFs in coastal waters. Relative differences in shape and magnitude are quantified. Reflectance modelled with the EAP phase functions is then compared against measured reflectance data from phytoplankton-dominated waters. Further examples of modelled phytoplankton-dominated waters are discussed with reference to choice of phase function for two PFTs (eukaryote and prokaryote) across a range of biomass. Finally a demonstration of the sensitivity of reflectance due to the choice of phase function is presented. The EAP model phase functions account for both spectral and angular variability in phytoplankton backscattering i.e. they display variability which is both spectral and shape-related. It is concluded that phase functions modelled in this way are necessary for investigating the effects of assemblage variability on the ocean colour signal, and should be considered for model closure even in relatively low scattering conditions where phytoplankton dominate the IOPs.
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