Vector radiative transfer model for coupled atmosphere and ocean systems including inelastic sources in ocean waters

Zhai, Peng-Wang; Hu, Yongxiang; Winker, David M.; Franz, Bryan A.; Werdell, Jeremy; Boss, Emmanuel

doi:10.1364/oe.25.00a223

Cited by 26 publications

(33 citation statements)

References 72 publications

(104 reference statements)

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“…To model the radiative transfer in the atmosphere and ocean system, simple methods use the Fresnel-Snell law to combine the two non-uniformly refracting layered media for a flat ocean surface. However, better modeling schemes are required with respect to wind speed for the rough ocean surface (Cox and Munk, 1954;Nakajima and Tanaka, 1983;Fischer and Grassl, 1984;Mobley, 1994;Fell and Fischer, 2001;Jin et al, 2006;Chowdhary et al, 2006;Ota et al, 2010;He et al, 2010;Zhai et al, 2010Zhai et al, , 2017Chami et al, 2015), particularly in the sunglint conditions. Sunglint is a major issue for the remote sensing of aerosols or ocean color.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous determination of aerosol optical thickness and water-leaving radiance from multispectral measurements in coastal waters

Shi

Nakajima

2018

Atmos. Chem. Phys.

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Abstract. Retrieval of aerosol optical properties and water-leaving radiance over ocean is challenging since the latter mostly accounts for ∼  10 % of the satellite-observed signal and can be easily influenced by the atmospheric scattering. Such an effort would be more difficult in turbid coastal waters due to the existence of optically complex oceanic substances or high aerosol loading. In an effort to solve such problems, we present an optimization approach for the simultaneous determination of aerosol optical thickness (AOT) and normalized water-leaving radiance (nLw) from multispectral satellite measurements. In this algorithm, a coupled atmosphere–ocean radiative transfer model combined with a comprehensive bio-optical oceanic module is used to jointly simulate the satellite-observed reflectance at the top of atmosphere and water-leaving radiance just above the ocean surface. Then, an optimal estimation method is adopted to retrieve AOT and nLw iteratively. The algorithm is validated using Aerosol Robotic Network – Ocean Color (AERONET-OC) products selected from eight OC sites distributed over different waters, consisting of observations that covered glint and non-glint conditions from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Results show a good consistency between retrieved and in situ measurements at each site. It is demonstrated that more accurate AOTs are determined based on the simultaneous retrieval method, particularly in shorter wavelengths and sunglint conditions, where the averaged percentage difference (APD) of retrieved AOT is generally reduced by approximate 10 % in visible bands compared with those derived from the standard atmospheric correction (AC) scheme, since all the spectral measurements can be used jointly to increase the information content in the inversion of AOT, and the wind speed is also simultaneously retrieved to compensate the specular reflectance error estimated from the rough ocean surface model. For the retrieval of nLw, atmospheric overcorrection can be avoided in order to have a significant improvement of the inversion of nLw at 412 nm. Furthermore, generally better estimates of band ratios of nLw(443) / nLw(554) and nLw(488) / nLw(554) are obtained using the simultaneous retrieval approach with lower root mean square errors and relative differences than those derived from the standard AC approach in comparison to the AERONET-OC products, as well as the APD values of retrieved Chl which decreased by about 5 %. On the other hand, the standard AC scheme yields a more accurate retrieval of nLw at 488 nm, prompting a further optimization of the oceanic bio-optical module of the current model.

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Section: Introductionmentioning

confidence: 99%

Simultaneous determination of aerosol optical thickness and water-leaving radiance from multispectral measurements in coastal waters

Shi

Nakajima

2018

Atmos. Chem. Phys.

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“…All terms are a function of depth z and wavelength λ. The Zaneveld expression does not account for any inelastic processes, such as molecular Raman scattering or fluorescence [30][31][32][33]. Using physically reasoned approximations for f b including the assumption of single scattering, the following was obtained by Zaneveld ([28]; his Equation 14):…”

Section: Forward Model Developmentmentioning

confidence: 99%

“…Lastly, potential uncertainties in the full RT computations must be considered, as this was used to parameterize several ZTT terms. Polarization is not considered in the ZTT model or in Hydrolight, which is likely important [29,33]. There is a need in the research community for commercially available RT code with a focus on the ocean that includes full polarization, along with concomitant measurements of polarized radiance in the field.…”

Section: Assessing Residual Bias In the Modelmentioning

confidence: 99%

“…There is a need in the research community for commercially available RT code with a focus on the ocean that includes full polarization, along with concomitant measurements of polarized radiance in the field. Neither the Hydrolight simulations or ZTT model included inelastic effects from DOM fluorescence, which could lead to bias errors as high as about 10% in the mid-visible [33]. Another potential source of uncertainty is the water Raman estimation [60], where bias errors as high as 10% can be typical.…”

Section: Assessing Residual Bias In the Modelmentioning

confidence: 99%

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Ocean Color Analytical Model Explicitly Dependent on the Volume Scattering Function

Twardowski

Tonizzo²

2018

Applied Sciences

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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.

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“…Several approaches, including Monte Carlo simulation [25][26][27][28], the invariant imbedding method [23], and the discrete ordinate method [29], have been used to obtain numerical solutions for the RTE of water via the necessary boundary conditions. Several vector radiative transfer models of coupled ocean-atmosphere system (e.g., studies in References [30][31][32][33][34][35][36]) were developed to predict the radiance and degree of polarization of the light using various numerical methods.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Weighting Average Functions as a Simplification of the Radiative Transfer Simulation in Vertically Inhomogeneous Eutrophic Waters

Xue

2019

Applied Sciences

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Current water color remote sensing algorithms typically do not consider the vertical variations of phytoplankton. Ecolight with a radiative transfer program was used to simulate the underwater light field of vertical inhomogeneous waters based on the optical properties of a eutrophic lake (i.e., Lake Chaohu, China). Results showed that the vertical distribution of chlorophyll-a (Chla(z)) can considerably affect spectrum shape and magnitude of apparent optical properties (AOPs), including subsurface remote sensing reflectance in water (rrs(λ, z)) and the diffuse attenuation coefficient (Kx(λ, z)). The vertical variations of Chla(z) changed the spectrum shapes of rrs(λ, z) at the green and red wavelengths with a maximum value at approximately 590 nm, and changed the Kx(λ, z) from blue to red wavelength range with no obvious spectral variation. The difference between rrs(λ, z) at depth z m and its asymptotic value (Δrrs(λ, z)) could reach to ~78% in highly stratified waters. Diffuse attenuation coefficient of downwelling plane irradiance (Kd(λ, z)) had larger vertical variations, especially near water surface, in highly stratified waters. Three weighting average functions performed well in less stratified waters, and the weighting average function proposed by Zaneveld et al., (2005) performed best in highly stratified waters. The total contribution of the first three layers to rrs(λ, 0−) was approximately 90%, but the contribution of each layer in the water column to rrs(λ, 0−) varied with wavelength, vertical distribution of Chla(z) profiles, concentration of suspended particulate inorganic matter (SPIM), and colored dissolved organic matter (CDOM). A simple stratified remote sensing reflectance model considering the vertical distribution of phytoplankton was built based on the contribution of each layer to rrs(λ, 0−).

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Vector radiative transfer model for coupled atmosphere and ocean systems including inelastic sources in ocean waters

Cited by 26 publications

References 72 publications

Simultaneous determination of aerosol optical thickness and water-leaving radiance from multispectral measurements in coastal waters

Simultaneous determination of aerosol optical thickness and water-leaving radiance from multispectral measurements in coastal waters

Ocean Color Analytical Model Explicitly Dependent on the Volume Scattering Function

Evaluation of Weighting Average Functions as a Simplification of the Radiative Transfer Simulation in Vertically Inhomogeneous Eutrophic Waters

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