OSOAA: a vector radiative transfer model of coupled atmosphere-ocean system for a rough sea surface application to the estimates of the directional variations of the water leaving reflectance to better process multi-angular satellite sensors data over the ocean

Demonstration of a Modular Prototype End-to-End Simulator for Aquatic Remote Sensing Applications

This study introduces a prototype end-to-end Simulator software tool for simulating two-dimensional satellite multispectral imagery for a variety of satellite instrument models in aquatic environments. Using case studies, the impact of variable sensor configurations on the performance of value-added products for challenging applications, such as coral reefs and cyanobacterial algal blooms, is assessed. This demonstrates how decisions regarding satellite sensor design, driven by cost constraints, directly influence the quality of value-added remote sensing products. Furthermore, the Simulator is used to identify situations where retrieval algorithms require further parameterization before application to unsimulated satellite data, where error sources cannot always be identified or isolated. The application of the Simulator can verify whether a given instrument design meets the performance requirements of end-users before build and launch, critically allowing for the justification of the cost and specifications for planned and future sensors. It is hoped that the Simulator will enable engineers and scientists to understand important design trade-offs in phase 0/A studies easily, quickly, reliably, and accurately in future Earth observation satellites and systems.

Impact of blur on 3D laser imaging: Monte-Carlo modelling for underwater applications

3D laser imaging technology could allow visualizing objects hidden in turbid water. Such a technology mainly works at short distances (<50 m) because of the high attenuation of light in water. Therefore, a significant part of the scattering events from the water column is located out of the optical depth of field (DoF), which could induce optical blur on images. In this study, a model is proposed to represent such an optical blur, based on geometric optics. The model is then implemented in a Monte-Carlo scheme. Blur significantly affects the scattered signal from water before the DoF in monostatic conditions, but has less impact in bi-static conditions. Furthermore, it is shown that blur enables a very large variance reduction of 2D images of objects situated within the DoF. Such an effect increases with the extinction coefficient.

Satellite retrieval of the linear polarization components of the water-leaving radiance in open oceans

Atmospheric correction (AC) of polarized radiances acquired by polarization satellite sensors, remains a challenge due to the complex radiative transfer processes of the coupled ocean-atmosphere system. In this study, we proposed an innovative polarized AC algorithm built on the near-infrared band (PACNIR) with an emphasis on the retrieval of the linear polarization components of the water-leaving radiance in clear open oceans. This algorithm was based on the black ocean assumption in the near-infrared band and fitted polarized radiance measurements along multiple observation directions with nonlinear optimized processing. Our retrieval algorithm notably inverted the linearly polarized components of the water-leaving radiance and aerosol parameters. Compared with that of the simulated linear polarization components of the water-leaving radiance via the vector radiative transfer model for the studied sea regions, the mean absolute error of the PACNIR-retrieved linearly polarized components (nQw and nUw) exhibited a magnitude of 10^-4, while the magnitude of that of the simulated nQw and nUw data was 10^-3. Moreover, the PACNIR-retrieved aerosol optical thicknesses at 865 nm exhibited a mean absolute percentage error of approximately 30% relative to in situ values obtained from Aerosol Robotic Network-Ocean Color (AERONET-OC) sites. The PACNIR algorithm could facilitate AC of the polarized data provided by the next generation of multiangle polarization satellite ocean color sensors.

Evaluation of eight band SuperDove imagery for aquatic applications

Planet's SuperDove constellation is evaluated for remote sensing of water targets. SuperDoves are small satellites with on board eight band PlanetScope imagers that add four new bands compared to the previous generations of Doves. The Yellow (612 nm) and Red Edge (707 nm) bands are of particular interest to aquatic applications, for example in aiding the retrieval of pigment absorption. The dark spectrum fitting (DSF) algorithm is implemented in ACOLITE for processing of SuperDove data, and its outputs are compared to matchup data collected using an autonomous pan-and-tilt hyperspectral radiometer (PANTHYR) installed in the turbid waters of the Belgian Coastal Zone (BCZ). Results for 35 matchups from 32 unique SuperDove satellites indicate on average low differences with PANTHYR observations for the first seven bands (443-707 nm), with mean absolute relative differences (MARD) 15-20%. The mean average differences (MAD) are between -0.01 and 0 for the 492-666 nm bands, i.e. DSF results show a negative bias, while the Coastal Blue (444 nm) and Red Edge (707 nm) show a small positive bias (MAD 0.004 and 0.002). The NIR band (866 nm) shows a larger positive bias (MAD 0.01), and larger relative differences (MARD 60%). Root mean squared differences (RMSD) are rather flat at around 0.01 with peaks in the bands with highest water reflectance of around 0.015. The surface reflectance products as provided by Planet (PSR) show a similar average performance to DSF, with slightly larger and mostly positive biases, except in both Green bands, where the MAD is close to 0. MARD in the two Green bands is a bit lower for PSR (9.5-10.6%) compared to DSF (9.9-13.0%). Higher scatter is found for the PSR (RMSD 0.015-0.020), with some matchups showing large, spectrally mostly flat differences, likely due to the external aerosol optical depth (τ_a) inputs not being representative for these particular images. Chlorophyll a absorption (a_Chl) is retrieved from PANTHYR measurements, and the PANTHYR data are used to calibrate a_Chl retrieval algorithms for SuperDove in the BCZ. Various Red band indices (RBI) and two neural networks are evaluated for a_Chl estimation. The best performing RBI algorithm, i.e. the Red band difference (RBD), showed a MARD of 34% for DSF and 25% for PSR with positive biases of 0.11 and 0.03 m^-1 respectively for 24 PANTHYR a_Chl matchups. The difference in RBD performance between DSF and PSR can be largely explained by their respective average biases in the Red and Red Edge bands, which are opposite signs for DSF (negative bias in the red), and positive for both bands for PSR. Mapping of turbid water a_Chl and hence chlorophyll a concentration (C) using SuperDove is demonstrated for coastal bloom imagery, showing how SuperDove data can supplement monitoring programmes.

Improving the standard protocol for above-water reflectance measurements: 1. Estimating effective wind speed from angular variation of sunglint

The standard above-water protocol for measurement of water reflectance uses a measurement of wind speed to estimate the air-water interface reflectance factor and, thus, remove reflected skylight from upwelling radiance. This aerodynamic wind speed measurement may be a poor proxy for the local wave slope distribution in cases such as fetch-limited coastal and inland waters and/or where there are spatial or temporal differences between the wind speed measurement and the location of reflectance measurements. Here, an improved method is proposed, with a focus on sensors mounted on autonomous pan-tilt units and deployed on fixed platforms, replacing the aerodynamic wind speed measurement by optical measurements of angular variation of upwelling radiance. Using radiative transfer simulations, it is shown that the difference between two upwelling (i.e., water plus air-water interface) reflectances acquired at least 10° apart from each other in the solar principal plane is strongly and monotonically related to effective wind speed. The approach shows good performance in twin experiments using radiative transfer simulations. Limitations of the approach are identified, including difficulties for a very high Sun zenith angle (>60^∘), very low wind speed (<2m s ^-1), and, potentially, cases in which nadir-pointing angles are limited by optical perturbations from the viewing platform.

Continuous Monitoring of Suspended Particulate Matter in Tropical Inland Waters by High-Frequency, Above-Water Radiometry

Water and sediment discharges can change rapidly, and low-frequency measurement devices might not be sufficient to elucidate existing dynamics. As such, above-water radiometry might enhance monitoring of suspended particulate matter (SPM) dynamics in inland waters. However, it has been barely applied for continuous monitoring, especially under partially cloudy sky conditions. In this study, an in situ, high-frequency (30 s timestep), above-water radiometric dataset, collected over 18 days in a tropical reservoir, is analyzed for the purpose of continuous monitoring of SPM concentration. Different modalities to retrieve reflectance spectra, as well as SPM inversion algorithms, were applied and evaluated. We propose a sequence of processing that achieved an average unsigned percent difference (UPD) of 10.4% during cloudy conditions and 4.6% during clear-sky conditions for Rrs (665 nm), compared to the respective UPD values of 88.23% and 13.17% when using a simple calculation approach. SPM retrieval methods were also evaluated and, depending on the methods used, we show that the coefficient of variation (CV) of the SPM concentration varied from 69.5% down to 2.7% when using a semi-analytical approach. As such, the proposed processing approach is effective at reducing unwanted variability in the resulting SPM concentration assessed from above-water radiometry, and our work paves the way towards the use of this noninvasive technique for high-frequency monitoring of SPM concentrations in streams and lakes.

Atmospheric diffuse transmittance of the linear polarization component of water-leaving radiation

The polarization characteristics of water-leaving radiation contain rich information on oceanic constituents. Determining the atmospheric diffuse transmittance is crucial for extracting the polarization information of water-leaving radiation from the radiation acquired by polarimetry satellites at the top of the atmosphere. However, there is still a lack of understanding of the atmospheric diffuse transmittance of the linear polarization component of water-leaving radiation. Here, we first evaluated the difference between the atmospheric diffuse transmittance of the linear polarization component (T_Q, T_U) and the intensity component (T_I) of the water-leaving radiation based on the Ocean Successive Orders with Atmosphere Advanced radiative transfer model. As a consequence, there were apparent differences between T_Q, T_U and T_I. In the case of a large solar zenith angle and a large viewing zenith angle, the difference between T_Q, T_U and T_I will exceed 1. Meanwhile, compared with T_I, the oceanic constituents had a prominent interference with T_Q and T_U, and the sediment concentration had little interference with T_Q and T_U in low- and medium-turbidity water with respect to the aerosol model, optical thickness, observation geometry, and phytoplankton. Moreover, T_Q and T_U lookup tables were generated for medium- and low-turbidity water, which laid the foundation for extracting the water-leaving radiation polarization information from the satellite observation polarization signal.

Exploring the Potential of Optical Polarization Remote Sensing for Oil Spill Detection: A Case Study of Deepwater Horizon

Oil spills lead to catastrophic problems. In most oil spill cases, the spatial and temporal intractability of the detriment cannot be neglected, and problems related to economic, social and environmental factors constantly appear for a long time. Remote sensing has been widely used as a powerful means to conduct oil spill detection. Optical polarization remote sensing, thriving in recent years, shows a novel potential for oil spill detection. This paper provides a demonstration of the use of open-source POLDER/PARASOL polarization time-series data to detect oil spill. The Deepwater Horizon oil spill, one of the largest oil spill disasters, is utilized to explore the potential of optical polarization remote sensing for oil spill detection. A total of 24 feature combinations are organized to quantitatively study the positive effect of adding polarization information and the appropriate way to describe polarization characteristics. Random forest classifier models are trained with different combinations, and the results are assessed by 10-fold cross-validation. The improvement from adding polarization characteristics is remarkable ((average) accuracy: +0.51%; recall: +2.83%; precision: +3.49%; F1 score: +3.01%, (maximum) accuracy: +0.80%; recall: +5.09%; precision: +6.92%; F1 score: +4.72%), and coupling between the degree of polarization and the phase angle of polarization provides the best description of polarization information. This study confirms the potential of optical polarization remote sensing for oil spill detection, and some detailed problems related to model establishment and polarization feature characterization are discussed for the further application of polarization information.

Experimental Study on Bottom-Up Detection of Underwater Targets Based on Polarization Imaging

Previous studies on the polarization imaging of underwater targets mainly focused on top-down detection; however, the capacities of bottom-up detection were poorly known. Based on in situ experiments, the capability of bottom-up detection of underwater targets using polarization imaging was investigated. First, to realize the objective of bottom-up polarization imaging, a SALSA polarization camera was integrated into our Underwater Polarization Imaging System (UPIS), which was integrated with an attitude sensor. At Qiandao Lake, where the water is relatively clear, experiments were conducted to examine the capacity of the UPIS to detect objects from the bottom up. Simultaneously, entropy, clarity, and contrast were adopted to compare the imaging performance with different radiation parameters. The results show that among all the used imaging parameters, the angle of polarization is the optimal parameter for bottom-up detection of underwater targets based on polarization imaging, which may result from the different diffused reflectance of the target surface to the linear polarization components of the Stokes vector.

Spatiotemporal Dynamics of Suspended Sediments in the Negro River, Amazon Basin, from In Situ and Sentinel-2 Remote Sensing Data

Monitoring suspended sediments through remote sensing data in black-water rivers is a challenge. Herein, remote sensing reflectance (Rrs) from in situ measurements and Sentinel-2 Multi-Spectral Instrument (MSI) images were used to estimate the suspended sediment concentration (SSC) in the largest black-water river of the Amazon basin. The Negro River exhibits extremely low Rrs values (<0.005 sr−1 at visible and near-infrared bands) due to the elevated absorption of coloured dissolved organic matter (aCDOM at 440 nm > 7 m−1) caused by the high amount of dissolved organic carbon (DOC > 7 mg L−1) and low SSC (<5 mg L−1). Interannual variability of Rrs is primarily controlled by the input of suspended sediments from the Branco River, which is a clear water river that governs the changes in the apparent optical properties of the Negro River, even at distances that are greater than 90 km from its mouth. Better results were obtained using the Sentinel-2 MSI Red band (Band 4 at 665 nm) in order to estimate the SSC, with an R2 value greater than 0.85 and an error less than 20% in the adjusted models. The magnitudes of water reflectance in the Sentinel-2 MSI Red band were consistent with in situ Rrs measurements, indicating the large spatial variability of the lower SSC values (0 to 15 mg L−1) in a complex anabranching reach of the Negro River. The in situ and satellite data analysed in this study indicates sedimentation processes in the lower Negro River near the Amazon River. The results suggest that the radiometric characteristics of sensors, like sentinel-2 MSI, are suitable for monitoring the suspended sediment concentration in large tropical black-water rivers.

Sensitivity analysis of the dark spectrum fitting atmospheric correction for metre- and decametre-scale satellite imagery using autonomous hyperspectral radiometry

The performance of the dark spectrum fitting (DSF) atmospheric correction algorithm is evaluated using matchups between metre- and decametre-scale satellite imagery as processed with ACOLITE and measurements from autonomous PANTHYR hyperspectral radiometer systems deployed in the Adriatic and North Sea. Imagery from the operational land imager (OLI) on Landsat 8, the multispectral instrument (MSI) on Sentinel-2 A and B, and the PlanetScope CubeSat constellation was processed for both sites using a fixed atmospheric path reflectance in a small region of interest around the system's deployment location, using a number of processing settings, including a new sky reflectance correction. The mean absolute relative differences (MARD) between in situ and satellite measured reflectances reach <20% in the Blue and 11% in the Green bands around 490 and 560 nm for the best performing configuration for MSI and OLI. Higher relative errors are found for the shortest Blue bands around 440 nm (30-100% MARD), and in the Red-Edge and near-infrared bands (35-100% MARD), largely influenced by the lower absolute data range in the observations. Root mean squared differences (RMSD) increase from 0.005 in the NIR to about 0.015-0.020 in the Blue band, consistent with increasing atmospheric path reflectance. Validation of the Red-Edge and NIR bands on Sentinel-2 is presented, as well as for the first time, the Panchromatic band (17-26% MARD) on Landsat 8, and the derived Orange contra-band (8-33% MARD for waters in the algorithm domain, and around 40-80% MARD overall). For Sentinel-2, excluding the SWIR bands from the DSF gave better performances, likely due to calibration issues of MSI at longer wavelengths. Excluding the SWIR on Landsat 8 gave good performance as well, indicating robustness of the DSF to the available band set. The DSF performance was found to be rather insensitive to (1) the wavelength spacing in the lookup tables used for the atmospheric correction, (2) the use of default or ancillary information on gas concentration and atmospheric pressure, and (3) the size of the ROI over which the path reflectance is estimated. The performance of the PlanetScope constellation is found to be similar to previously published results, with the standard DSF giving the best results in the visible bands in terms of MARD (24-40% overall, and 18-29% for the turbid site). The new sky reflectance correction gave mixed results, although it reduced the mean biases for certain configurations and improved results for the processing excluding the SWIR bands, giving lower RMSD and MARD especially at longer wavelengths (>600 nm). The results presented in this article should serve as guidelines for general use of ACOLITE and the DSF.

Mantis: an all-sky visible-to-near-infrared hyper-angular spectropolarimeter

In this paper, we introduce and present first results from Mantis, a pushbroom type spectropolarimeter recently acquired by the Naval Research Laboratory and built by Polaris Sensor Technologies, Inc. The instrument is designed for high spatial and spectral resolution polarimetric imaging of downwelling skylight. Linear Stokes vectors are acquired over the spectral range of 382-1017 nm, with ≈0.64nm channel spacing, and each line scan consists of 2226 pixels over a 72° field of view (0.75 mrad instantaneous). Measurement of the full sky dome is achieved through the use of a high-precision motorized pan-tilt unit and systematic scanning. An automated Sun shade allows for data collection in the main solar plane without saturation of the focal plane. The uncertainty in the degree of linear polarization varies between 0.07% and 0.5%, depending on incidence angle and wavelength. The total radiometric uncertainty is 2.07% to 2.5%, of which 2% is absolute calibration error. Preliminary data analysis reveals the instrument has a large potential for remote sensing applications.

Potential for nocturnal satellite detection of suspended matter concentrations in coastal waters using a panchromatic band: a feasibility study based on VIIRS (NASA/NOAA) spectral and radiometric specifications

Satellite remote sensing of coastal waters is important for understanding the functioning of these complex ecosystems. High satellite revisit frequency is required to permit a relevant monitoring of the strong dynamical processes involved in such areas, for example rivers discharge or tidal currents. One key parameter that is derived from satellite data is the suspended particulate matter (SPM) concentration. Knowledge of the variability of SPM could be used by sediment transport models for providing accurate predictions. Most of the current satellites that are dedicated to ocean color observations have a sun-synchronous orbit that performs a single daytime observation. The Visible Infrared Imaging Radiometer Suite (VIIRS) ocean color sensor (NASA/NOAA) is the only one that is equipped with a panchromatic spectral band, so-called Day-Night Band, which is able to measure extremely low level signals, typically of the order of magnitude of 10^-5 W m^-2 sr^-1µm^-1. The objective of this paper is to investigate the potential of the panchromatic and radiometric specifications of the VIIRS sensor to detect SPM concentrations from nighttime satellite observations. Realistic radiative transfer simulations are performed to quantitatively determine the amplitude of the top of atmosphere radiances under various conditions such as various moon incident illuminations, observation geometries, atmospheric and oceanic turbidities. The simulations are compared with the minimum detectable radiance as specified for the VIIRS sensor. The results show that the detection of SPM is systematically feasible, including in clear waters, for any observation geometries in the case of a full moon illumination. The sensitivity of the results to the lunar phase (i.e., out of the full moon conditions), which is one of the originalities of the study, shows that the detection should also be feasible for a significant number of nights over the entire lunar cycle, typically from 5 to 15 nights depending on the water turbidity. Therefore, nighttime ocean color panchromatic measurements performed using a VIIRS-like sensor are a highly promising approach, especially if it is combined with daytime observations, for improving the monitoring of ocean dynamics.

Polarization Properties of Reflection and Transmission for Oceanographic Lidar Propagating through Rough Sea Surfaces

Over the past few years, oceanographic lidar was applied to many fields, and polarization lidar could provide extra information for marine particles. To retrieve the water properties, many simulation models and inversion methods were developed. However, few of them account for the depolarization effect of a rough sea surface. In this study, we develop a model to calculate reflection and transmission Mueller matrices, coupled with the lidar observation geometry. Compared with another operational method, our model has a satisfactory performance. This model also considers the shadowing effects of wave facets. Then, we analyze the polarized properties in different azimuth and zenith angles and find that the reflection of sea surface has a crucial effect on the polarization properties of lidar. For unpolarized light, the reflected light tends to be partially polarized. However, for lidar light that is completely polarized, there is an obvious depolarization owing to multiple scattering, and the depolarization is not negligible at small incident angles. The retrieval of properties of ocean constituents can be effectively improved, becoming more accurate by accounting for the depolarization effects of sea surfaces based on our method.

Atmospheric correction algorithm over coastal and inland waters based on the red and NIR bands: application to Landsat-8/OLI and VNREDSat-1/NAOMI observations

Water pixel extraction and correction of the atmospheric signal represent prerequisite steps prior to applying algorithms dedicated to the assessment of water quality of natural surface water bodies. The recent multiplication of medium spatial resolution sensors (10-60 m) provides the required constellation to monitoring bio-optical and biogeochemical parameters of surface waters at the relevant spatial-temporal scales. Here we present a new approach to identify water pixels and to extract the atmospheric contribution to the top of atmosphere signal measured by the NAOMI sensor on board the first Vietnamese satellite, VNREDSat-1. After verifying the TOA calibration of NAOMI through a vicarious calibration exercise, we adapt a recent water pixel extraction algorithm (WiPE) to NAOMI, and develop a new atmospheric correction algorithm (referred to as red-NIR) based on the use of the red and NIR bands (the only bands available for that purpose on NAOMI) and spectral relationships. The evaluation of red-NIR with a match-up data set gathering remote sensing reflectance, R_rs, measurements performed at the AERONET-OC stations in moderately turbid waters indicates excellent performance in the blue and green part of the spectrum (similar to the performances reached by the SeaDAS NIR-SWIR algorithms) and lower accuracy in the red. Intercomparison of simultaneous images collected by NAOMI and OLI over a more turbid water body shows an excellent agreement between the NAOMI-R_rs estimated by the present processing, and the OLI-R_rs estimated from the ACOLITE algorithm. This approach will allow sensors that do not have SWIR bands, such as SPOT-6 and -7, to be processed, making their data exploitation available for long-term temporal analyses.

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

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−).

Analysis and quantification of seabed adjacency effects in the subsurface upward radiance in shallow waters

The estimation of the bathymetry and the detection of targets located on the seabed of shallow waters using remote sensing techniques is of great interest for many environmental applications in coastal areas such as benthic habitat mapping, monitoring of seabed aquatic plants and the subsequent management of littoral zones. For that purpose, knowledge of the optical effects induced by the neighborhood of a given seabed target and by the water column itself is required to better interpret the subsurface upward radiance measured by satellite or shipborne radiometers. In this paper, the various sources of photons that contribute to the subsurface upward radiance are analyzed. In particular, the adjacency effects caused by the neighborhood of a given seabed target are quantified for three water turbidity conditions, namely clear, moderately turbid and turbid waters. Firstly, an analytical expression of the subsurface radiance is proposed in order to make explicit the radiance terms corresponding to these effects. Secondly, a sensitivity study is performed using radiative transfer modeling to determine the influence of the seabed adjacency effects on the upward signal with respect to various parameters such as the bathymetry or the bottom brightness. The results show that the highest contributions of the adjacency effects induced by the neighborhood of a seabed target to the subsurface radiance could reach 26%, 18% and 9% for clear, moderately turbid and turbid water conditions respectively. Therefore, the detection of a seabed target could be significantly biased if the seabed adjacency effects are ignored in the analysis of remote sensing measurements. Our results could be further used to improve the performance of inverse algorithms dedicated to the retrieval of bottom composition, water optical properties and/or bathymetry.

Variability of the reflectance coefficient of skylight from the ocean surface and its implications to ocean color

The value and spectral dependence of the reflectance coefficient (ρ) of skylight from wind-roughened ocean surfaces is critical for determining accurate water leaving radiance and remote sensing reflectances from shipborne, AERONET-Ocean Color and satellite observations. Using a vector radiative transfer code, spectra of the reflectance coefficient and corresponding radiances near the ocean surface and at the top of the atmosphere (TOA) are simulated for a broad range of parameters including flat and windy ocean surfaces with wind speeds up to 15 m/s, aerosol optical thicknesses of 0-1 at 440nm, wavelengths of 400-900 nm, and variable Sun and viewing zenith angles. Results revealed a profound impact of the aerosol load and type on the spectral values of ρ. Such impacts, not included yet in standard processing, may produce significant inaccuracies in the reflectance spectra retrieved from above-water radiometry and satellite observations. Implications for satellite cal/val activities as well as potential changes in measurement and data processing schemes are discussed.

Water-leaving contribution to polarized radiation field over ocean

The top-of-atmosphere (TOA) radiation field from a coupled atmosphere-ocean system (CAOS) includes contributions from the atmosphere, surface, and water body. Atmospheric correction of ocean color imagery is to retrieve water-leaving radiance from the TOA measurement, from which ocean bio-optical properties can be obtained. Knowledge of the absolute and relative magnitudes of water-leaving signal in the TOA radiation field is important for designing new atmospheric correction algorithms and developing retrieval algorithms for new ocean biogeochemical parameters. In this paper we present a systematic sensitivity study of water-leaving contribution to the TOA radiation field, from 340 nm to 865 nm, with polarization included. Ocean water inherent optical properties are derived from bio-optical models for two kinds of waters, one dominated by phytoplankton (PDW) and the other by non-algae particles (NDW). In addition to elastic scattering, Raman scattering and fluorescence from dissolved organic matter in ocean waters are included. Our sensitivity study shows that the polarized reflectance is minimized for both CAOS and ocean signals in the backscattering half plane, which leads to numerical instability when calculating water leaving relative contribution, the ratio between polarized water leaving and CAOS signals. If the backscattering plane is excluded, the water-leaving polarized signal contributes less than 9% to the TOA polarized reflectance for PDW in the whole spectra. For NDW, the polarized water leaving contribution can be as much as 20% in the wavelength range from 470 to 670 nm. For wavelengths shorter than 452 nm or longer than 865 nm, the water leaving contribution to the TOA polarized reflectance is in general smaller than 5% for NDW. For the TOA total reflectance, the water-leaving contribution has maximum values ranging from 7% to 16% at variable wavelengths from 400 nm to 550 nm from PDW. The water leaving contribution to the TOA total reflectance can be as large as 35% for NDW, which is in general peaked at 550 nm. Both the total and polarized reflectances from water-leaving contributions approach zero in the ultraviolet and near infrared bands. These facts can be used as constraints or guidelines when estimating the water leaving contribution to the TOA reflectance for new atmospheric correction algorithms for ocean color imagery.

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

Inelastic scattering plays an important role in ocean optics. The main inelastic scattering mechanisms include Raman scattering, fluorescence by colored dissolved organic matter (FDOM), and fluorescence by chlorophyll. This paper reports an implementation of all three inelastic scattering mechanisms in the exact vector radiative transfer model for coupled atmosphere and ocean Systems (CAOS). Simulation shows that FDOM contributes to the water radiation field in the broad visible spectral region, while chlorophyll fluorescence is limited in a narrow band centered at 685 nm. This is consistent with previous findings in the literature. The fluorescence distribution as a function of depth and viewing angle is presented. The impacts of fluorescence to the degree of linear polarization (DoLP) and orientation of the polarization ellipse (OPE) are studied. The DoLP is strongly influenced by inelastic scattering at wavelengths with strong inelastic scattering contribution. The OPE is less affected by inelastic scattering but it has a noticeable impact, in terms of the angular region of positive polarization, in the backward direction. This effect is more apparent for deeper water depth.

Estimation of daily photosynthetically active radiation (PAR) in presence of low to high aerosol loads: application to OLCI-like satellite data

Estimation of daily photosynthetically active radiation (PAR) is of primary importance for monitoring the ocean primary production and the subsequent production of carbon by phytoplankton at global scale from remote sensing ocean color sensors. On the other hand, aerosol abundance and composition play a critical role in the modulation of PAR. In this study, an original algorithm, so-called OLCIPAR, is proposed for routinely determining the daily PAR from optical satellite sensors such as the OLCI sensor aboard Sentinel-3 (ESA). The OLCIPAR algorithm has been developed to overcome some of the limitations of the current existing methods. In particular, multiple scattering effects induced by the atmospheric layer are taken into account based on exact radiative transfer calculations. Another advantage of OLCIPAR method is to consider a great variety of aerosol models to better account for their optical variability as observed in real world conditions. The OLCIPAR algorithm was applied to the archive of MERIS data, whose sensor is similar to OLCI. The validation of the retrieved daily PAR was carried out based on comparison with the time series acquired by the BOUSSOLE oceanographic buoy moored in the Mediterranean Sea. Results show a regression slope of 1% and an accuracy within 10% which confirms the robustness of the algorithm. The comparison of OLCIPAR retrievals with the products routinely distributed by NASA shows that estimates of PAR differ by up to 20% in the subtropical Atlantic Ocean where important amounts of dust aerosols are present. The improvements brought by OLCIPAR method for deriving the daily PAR could thus permit to better assess the impact of aerosols on reduction of PAR with implications on the estimation of oceanic primary production.

Polarized reflectance and transmittance distribution functions of the ocean surface

Two aspects of ocean modelling are treated: representation of ocean waves considering all size-classes of waves and tracing of light-interactions at the wavy sea surface. Nonlinear wave profiles are realized accounting for a wide range of climatologically relevant sea states and wind speeds. Polarized ray tracing is used to investigate air-incident and whitecap-free reflectance and transmittance distributions with high angular resolution subject to sea-characterizing parameters, such as significant wave height, peak wave period, wind speed, and surface roughness. Wave-shadowing effects of incident and multiple reflected rays are fully considered. Their influence mostly starts with incidence angles greater than 60°, i.e., when the sun is near the horizon, and is especially pronounced for steep sea states. The net effect of multiple reflections is a redistribution of reflectance and transmittance fractions in their respective hemispheres and a slight increase of the net transmission of light into the sea. Revised reflectance and transmittance distribution functions, RDF and TDF, are provided depending on surface roughness in terms of the mean-square slope; reference is made to other sea state parameters. In comparison with the slope statistics approach, uncertainties related to sun near the horizon are reduced and on average this study yields somewhat higher reflectance values with some variability related to the sea state. By means of provided data, irradiance and radiance reflectances can be computed using desired sky radiance distributions, e.g., clear sky, overcast or partly cloudy sky, as well as wind or sea state information including wave propagation direction.

Effects of light polarization and waves slope statistics on the reflectance factor of the sea surface

Above-water radiometry depends on estimates of the reflectance factor ρ of the sea surface to compute the in situ water-leaving radiance. The Monte Carlo code for ocean color simulations MOX is used in this study to analyze the effect of different environmental components on ρ values. A first aspect is examining the reflectance factor without and by accounting for the sky-radiance polarization. The influence of the sea-surface statistics at discrete grid points is then considered by presenting a new scheme to define the variance of the waves slope. Results at different sun elevations and sensor orientations indicate that the light polarization effect on ρ simulations reduces from ∼17 to ∼10% when the wind speed increases from 0 to 14m s^-1. An opposite tendency characterizes the modeling of the sea-surface slope variance, with ρ differences up to ∼12% at a wind speed of 10m s^-1. The joint effect of polarization and the the sea-surface statistics displays a less systematic dependence on the wind speed, with differences in the range ∼13 to ∼18%. The ρ changes due to the light polarization and the variance of the waves slope become more relevant at sky-viewing geometries respectively lower and higher than 40° with respect to the zenith. An overall compensation of positive and negative offsets due to light polarization is finally documented when considering different sun elevations. These results address additional investigations which, by combining the modeling and experimental components of marine optics, better evaluate specific measurement protocols for collecting above-water radiometric data in the field.