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The sea-surface reflectance factor ρ required for the determination of the water- leaving radiance from above-water radiometric measurements is derived from radiative transfer simulations relying on models of the sky-radiance distribution and sea-surface statistics. This work primarily investigates the impact on ρ of various sky-radiance and sea-surface models. A specific replicability analysis, restricted to the 550 nm wavelength, has been performed with the Monte Carlo code for Ocean Color Simulations (so-called MOX) accounting for the measurement geometry recommended in protocols for the validation of satellite ocean color data and commonly applied for operational measurements. Results indicate that the variability of ρ increases with wind speed and reaches the largest values for sun elevations close to the zenith or approaching the horizon. In particular, a variability up to about 2% is observed for wind speeds below 4 ms−1 and sun zenith angles larger than 20°. Finally, the benchmark of the ρ values from this study with those formally determined with the Hydrolight code and widely utilized by the ocean color community, exhibits systematic differences. The source of these differences is discussed and the implications for field measurements are addressed.

The adjacency radiance field surrounding a small island (i.e., the Lampedusa Island in the Central Mediterranean Sea) was theoretically analyzed to address implications on a hypothetical nearby system vicarious calibration (SVC) infrastructure for satellite ocean color sensors. Simulations, performed in the visible and near-infrared regions for the Ocean Land Color Instrument (OLCI) operated onboard Sentinel-3 satellites, show different patterns of adjacency effects (AE) around the island. In the direction of the reflected sunbeam (i.e., in the north-western region), AE mainly originate by missing glint contributions from the sea surface masked by the island. These AE are mainly negative, decrease with wavelength, and strongly depend on sea surface anisotropy (i.e., sea state) and illumination conditions; this hinders the capability to provide a general unique description of their features. In the remaining marine regions, AE are positive and do not exceed the radiometric sensitivity of OLCI data beyond approximately 14 km from the coast. At shorter distances, uncertainties in satellite radiance due to AE would hence not allow fulfilling requirements for SVC.

This publisher’s note corrects an equation in Appl. Opt. 59, C63 (2020).APOPAI0003-693510.1364/AO.378512

The detectability of adjacency effects (AE) in ocean color remote sensing by SeaWiFS, MODIS-A, MERIS, OLCI, OLI and MSI is theoretically assessed for typical observation conditions up to 36 km offshore (20 km for MSI). The methodology detailed in Bulgarelli et al. (2014) is applied to expand previous investigations to the wide range of terrestrial land covers and water types usually encountered in mid-latitude coastal environments. Simulations fully account for multiple scattering within a stratified atmosphere bounded by a non-uniform reflecting surface, sea surface roughness, sun position and off-nadir sensor view. A harmonized comparison of AE is ensured by adjusting the radiometric sensitivity of each sensor to the same input radiance. Results show that average AE in data from MODIS-A, and from MERIS and OLCI in reduced spatial resolution, are still above the sensor noise level (NL) at 36 km offshore, except for AE caused by green vegetation at the red wavelengths. Conversely, in data from the less sensitive SeaWiFS, OLI and MSI sensors, as well as from MERIS and OLCI in full spatial resolution, sole AE caused by highly reflecting land covers (such as snow, dry vegetation, white sand and concrete) are above the sensor NL throughout the transect, while AE originated from green vegetation and bare soil at visible wavelengths may become lower than NL at close distance from the coast. Such a distance increases with the radiometric resolution of the sensor. It is finally observed that AE are slightly sensitive to the water type only at the blue wavelengths. Notably, for an atmospheric correction scheme inferring the aerosol properties from NIR data, perturbations induced by AE at NIR and visible wavelengths might compensate each other. As a consequence, biases induced by AE on radiometric products (e.g., the water-leaving radiance) are not strictly correlated to the intensity of the reflectance of the nearby land., Highlights • Quantification of adjacency effects for a wide range of coastal environments • Comparison of adjacency effects for data from various ocean color sensors • Relevance of adjacency effects as a function of the SNR of satellite sensors

The presented adjacency correction algorithm is based on the use of the point spread function (PSF) which allows calculating the contribution of reflections from the nearby pixels to the apparent radiance of the target. The analytical expression of the PSF for an arbitrary stratified atmosphere is obtained in the approximation of primary scattering, whereas the full equation of radiative transfer is used for the estimation of the radiance reflected from the surface. The algorithm is sensor independent and can be applied for processing images of water basins with arbitrary shape of the shore line and under different geometries of observation. The program using this algorithm is included in Modular Inversion Program — MIP (Heege et al., 2014) for processing of satellite images on a routine basis. Examples of processing results are presented in the paper.

An extensive comparison between radiative transfer codes in the atmosphere–ocean system is proposed and performed. The full angular radiance distribution at several optical depths in atmosphere and water is intercompared on a set of idealized problems designed to study codes’ accuracy in modeling separate, specific system features. In-water profiles of upwelling nadir radiance, upwelling and downwelling irradiance are intercompared for a realistic case extracted from an experimental data set. Two models are involved: the FEM numerical algorithm, based on the finite element method, and the P HO-TRAN 3D backward Monte Carlo code. The results show an optimal agreement between the codes under any condition. Codes’ relative differences are always lower than the estimated statistical error on the P HO-TRAN results.

Biases induced by land perturbations in satellite-derived water-leaving radiance are theoretically estimated for typical observation conditions in a coastal area of the northern Adriatic Sea hosting the Aqua Alta Oceanographic Tower (AAOT) validation site. Two different correction procedures are considered: not deriving (AC-1) or alternatively deriving (AC-2) the atmospheric properties from the remote sensing data. In both cases, biases due to adjacency effects largely increase by approaching the coast and with the satellite viewing angle. Conversely, the seasonal and spectral dependence of biases significantly differ between AC-1 and AC-2 schemes. For AC-1 schemes average biases are within ±5% throughout the transect at yellow-green wavelengths, but at the coast they can reach -21% and 34% at 412 and 670 nm, respectively, and exceed 100% at 865 nm. For AC-2 schemes, adjacency effects at those wavelengths from which atmospheric properties are inferred add significant perturbations. For the specific case of a correction scheme determining the atmospheric properties from the near-infrared region and by adopting a power-law spectral extrapolation of adjacency perturbations on the derived atmospheric radiance, average biases become all negative with values up to -60% and -74% at 412 and 670 nm at the coast, respectively. The seasonal trend of estimated biases at the AAOT is consistent with intra-annual variation of biases from match-ups between in situ and satellite products derived with SeaDAS from SeaWiFS and MODIS data. Nevertheless, estimated biases at blue wavelengths exceed systematic differences determined from match-up analysis. This may be explained by uncertainties and approximations in the simulation procedure, and by mechanisms of compensation introduced by the turbid water correction algorithm implemented in SeaDAS.

A methodology is presented to quantify the adjacency effects induced in satellite ocean color radiometric data by the presence of land in coastal regions. Specifically, the adjacency radiance, defined as the difference in top-ofatmosphere (TOA) signal when accounting for and when neglecting nearby mainland, is parameterized to decouple the dependence on the optical properties of land and water from those of atmosphere and sea surface, and from measurement geometry. The methodology is applied for a set of realistic satellite observation conditions, along a transect in the Northern Adriatic Sea crossing the Acqua Alta Oceanographic Tower (AAOT, 45.31N, 12.51E) ocean color validation site. The newly developed Novel Adjacency pert Urbation Simulator for Coast Al Areas (NAUSICAA) 3D backward Monte Carlo code and the well established highly accurate plane-parallel FEM radiative transfer code, are used to simulate signal contributions at TOA. Results at relevant ocean color center-wavelengths for the AAOT site i...

Accurate radiative transfer modeling in the coupled atmosphere-sea system is increasing in importance for the development of advanced remote-sensing applications. Aiming to quantify the uncertainties in the modeling of coastal water radiometric quantities, we performed a closure experiment to intercompare theoretical and experimental data as a function of wavelength lambda and water depth z. Specifically, the study focused on above-water downward irradiance E(d)(lambda, 0+) and in-water spectral profiles of upward nadir radiance L(u)(lambda, z), upward irradiance E(u)(lambda, z), downward irradiance E(d)(lambda, z), the E(u)(lambda, z)/L(u)(lambda, z) ratio (the nadir Q factor), and the E(u)(lambda, z)/E(d)(lambda, z) ratio (the irradiance reflectance). The theoretical data were produced with the finite-element method radiative transfer code ingesting in situ atmospheric and marine inherent optical properties. The experimental data were taken from a comprehensive coastal shallow-water data set collected in the northern Adriatic Sea. Under various measurement conditions, differences between theoretical and experimental data for the above-water E(d)(lambda, 0+) and subsurface E(d)(lambda, 0-) as well as for the in-water profiles of the nadir Q factor were generally less than 15%. In contrast, the in-water profiles of L(u)(lambda, z), E(d)(lambda, z), E(u)(lambda, z) and of the irradiance reflectance exhibited larger differences [to approximately 60% for L(u)(lambda, z) and E(u)(lambda, z), 30% for E(d)(lambda, z), and 50% for the irradiance reflectance]. These differences showed a high sensitivity to experimental uncertainties in a few input quantities used for the simulations: the seawater absorption coefficient; the hydrosol phase function backscattering probability; and, mainly for clear water, the bottom reflectance.