Sky Reflections Research Articles

Robust ocean color from drones: Viewing geometry, sky reflection removal, uncertainty analysis, and a survey of the Gulf Stream front

AbstractAccurate and robust retrieval of ocean color from remote sensing enables critical observations of aquatic natural systems, from open ocean biological oceanography, coastal biodiversity, and water quality for human health. In the last decade, studies have increasingly highlighted the important role of small‐scale processes in coastal and marine ecology and biogeochemistry, but observation and modeling at these scales remains technologically limited. Unoccupied aircraft systems (UAS, aka drones) can rapidly sample large areas with high spatial and temporal resolution; but the challenge of accurately retrieving ocean color, particularly with common wide field‐of‐view multispectral imagers, has limited the adoption of this technology. As UAS endurance, autonomy, and sensor capabilities continue to increase, so does this technology's potential to observe the ocean at fine scales, but only if proper protocols are followed. The present study provides a guide for achieving (1) ideal viewing geometry of UAS‐borne ocean color sensors, (2) techniques for the removal of sun glint and reflected skylight to derive water‐leaving radiances, (3) characterization of uncertainty in these measurements, and (4) converting water‐leaving radiances to remote‐sensing reflectance for analytic end products such as chlorophyll a estimates. Documented open‐source code facilitates replication of this emerging technique. Using this methodology, we briefly describing fine‐scale variability of the Gulf Stream front off North Carolina alongside synoptic satellite data and in situ measurements for comparison. These results demonstrate how UAS‐based ocean color measurements complement and enhance conventional ocean observations and modeling to resolve fine‐scale variability and close the lacuna between satellite and in situ methods.

A Bird's-Eye View: Novel Use of Drone Images to Quantify Differences in Altitudinal Reflections in Bird-window Collision Studies

Bird-window collisions (BWCs) constitute a significant source of mortality for both resident and migratory birds. Because windows reflect surrounding landscape components, such as vegetation or sky, birds do not always perceive glass as a barrier. Here we demonstrate a novel technique to classify and quantify reflections in windows on the Radford University campus in southwest Virginia, U.S.A. We deployed a consumer-grade Unmanned Aerial Vehicle, i.e., drone, to photograph 14 contiguous or near-contiguous window columns across five campus buildings in August 2020. For each study aspect, the drone (equipped with an RGB camera) captured images at ca. 5 m altitudinal increments from the ground floor to the roof of each building (three to six images/vertical column). We then manually classified each image in ImageJ to calculate approximate proportions of reflected: (1) vegetation, (2) sky, (3) and artificial structures or impervious surfaces, plus (4) nonreflective glass. We used a generalized linear model to determine how proportional reflections of vegetation, sky, buildings, and nonreflective glass varied across vertical increments. We found the proportion of sky significantly decreased with increasing photo heights, whereas proportion of nonreflective glass significantly increased with increasing heights. This supports previous findings that because birds are drawn to sky reflections, they may collide at relatively lower positions on buildings. Inconsistency in landscape design and building positioning on the campus precluded trends in vegetative or building reflections by height. Our pilot study demonstrates the applicability of a consumer-grade drone for investigating visual characteristics of reflections that influence BWCs from variable observation angles. We suggest the expanded use of drone images as a straightforward technique to measure changes in reflection characteristics from varying degrees of observation. They are a novel method in developing a BWC risk assessment as well as potential mitigation strategies in a suburban or campus environment with buildings of intermediate heights.

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.

Evaluation of Global Solar Irradiance Estimates from GL1.2 Satellite-Based Model over Brazil Using an Extended Radiometric Network

The GL (GLobal radiation) physical model was developed to compute global solar irradiance at ground level from (VIS) visible channel imagery of geostationary satellites. Currently, its version 1.2 (GL1.2) runs at Brazilian Center for Weather Forecast and Climate Studies/National Institute for Space Research (CPTEC/INPE) based on GOES-East VIS imagery. This study presents an extensive validation of GL1.2 global solar irradiance estimates using ground-based measurements from 409 stations belonging to the Brazilian National Institute of Meteorology (INMET) over Brazil for the year 2016. The INMET reasonably dense network allows characterizing the spatial distribution of GL1.2 data uncertainties. It is found that the GL1.2 estimates have a tendency to overestimate the ground data, but the magnitude varies according to region. On a daily basis, the best performances are observed for the Northeast, Southeast, and South regions, with a mean bias error (MBE) between 2.5 and 4.9 W m−2 (1.2% and 2.1%) and a root mean square error (RMSE) between 21.1 and 26.7 W m−2 (10.8% and 11.8%). However, larger differences occur in the North and Midwest regions, with MBE between 12.7 and 23.5 W m−2 (5.9% and 11.7%) and RMSE between 27 and 33.4 W m−2 (12.7% and 16.7%). These errors are most likely due to the simplified assumptions adopted by the GL1.2 algorithm for clear sky reflectance (Rmin) and aerosols as well as the uncertainty of the water vapor data. Further improvements in determining these parameters are needed. Additionally, the results also indicate that the GL1.2 operational product can help to improve the quality control of radiometric data from a large network, such as INMET's. Overall, the GL1.2 data are suitable for use in various regional applications.

On the role of the seawater absorption-to-attenuation ratio in the radiance polarization above the southern Baltic surface

Abstract. Information about polarization of light leaving the ocean surface has the potential to improve the quality of bio-optical parameter retrieval from ocean color remote sensing (OCRS). This improvement can be applied in numerous ways, such as limiting of Sun glints and obtaining information about atmospheric aerosol properties for atmospheric correction as well as increasing the accuracy of the algorithms based on the water-leaving signal. Polarization signals at the top of the atmosphere (ToA) that include the water-leaving signal are strongly influenced by atmospheric molecular scattering and by direct Sun and sky reflections from the sea surface. For these reasons, it is necessary to better understand the factors that change the polarization of light in the atmosphere–ocean system, especially in coastal zones affected by dynamic changes. In this paper, the influence of seasonal variability of light absorption and scattering coefficients (inherent optical properties; IOPs) of seawater, wind speed and solar zenith angle (SZA) on the polarization of upwelling radiance over the sea surface in the visible light bands is discussed. The results come from a polarized radiative transfer model based on the Monte Carlo code and applied to the atmosphere–ocean system using averaged IOPs as input data. The results, presented in the form of polar plots of the total upwelling radiance degree of polarization (DoP), indicate that regardless of the wavelength of light and type of water, the highest value of the above-water DoP is strongly correlated with the absorption-to-attenuation ratio. The correlation is a power function that depends on both the SZA and the wind speed. The correlation versatility for different wavelengths of light is very unusual in optics of the sea and is therefore worth emphasizing.

Removal of water‐surface reflection effects with a temporal minimum filter for UAV‐based shallow‐water photogrammetry

AbstractThe recent development of structure‐from‐motion (SfM) and multi‐view stereo (MVS) photogrammetry techniques has enabled semi‐automatic high‐resolution bathymetry using aerial images taken by consumer‐grade digital cameras mounted on unmanned aerial vehicles (UAVs). However, the applicability of these techniques is sometimes limited by sun and sky reflections at the water surface, which render the point‐cloud density and accuracy insufficient. In this research, we present a new imaging technique to suppress the effect of these water‐surface reflections. In this technique, we order a drone to take a short video instead of a still picture at each waypoint. We then apply a temporal minimum filter to the video. This filter extracts the smallest RGB values in all the video frames for each pixel, and composes an image with greatly reduced reflection effects. To assess the performance of this technique, we applied it at three small shallow‐water sites. Specifically, we evaluated the effect of the technique on the point cloud density and the accuracy and precision of the photogrammetry. The results showed that the proposed technique achieved a far denser point cloud than the case in which a randomly chosen frame was used for each waypoint, and also showed better overall accuracy and precision in estimating water‐bottom elevation. The effectiveness of this new technique should depend on the surface wave state and sky radiance distribution, and this dependence, as well as the applicability to large areas, should be investigated in future research. Copyright © 2018 John Wiley &amp; Sons, Ltd.

Variability of adjacency effects in sky reflectance measurements.

Sky reflectance Rsky(λ) is used to correct in situ reflectance measurements in the remote detection of water color. We analyzed the directional and spectral variability in Rsky(λ) due to adjacency effects against an atmospheric radiance model. The analysis is based on one year of semi-continuous Rsky(λ) observations that were recorded in two azimuth directions. Adjacency effects contributed to Rsky(λ) dependence on season and viewing angle and predominantly in the near-infrared (NIR). For our test area, adjacency effects spectrally resembled a generic vegetation spectrum. The adjacency effect was weakly dependent on the magnitude of Rayleigh- and aerosol-scattered radiance. The reflectance differed between viewing directions 5.4±6.3% for adjacency effects and 21.0±19.8% for Rayleigh- and aerosol-scattered Rsky(λ) in the NIR. Under which conditions in situ water reflectance observations require dedicated correction for adjacency effects is discussed. We provide an open source implementation of our method to aid identification of such conditions.

Validation of a spectral correction procedure for sun and sky reflections in above-water reflectance measurements.

A three-component reflectance model (3C) is applied to above-water radiometric measurements to derive remote-sensing reflectance Rrs (λ). 3C provides a spectrally resolved offset Δ(λ) to correct for residual sun and sky radiance (Rayleigh- and aerosol-scattered) reflections on the water surface that were not represented by sky radiance measurements. 3C is validated with a data set of matching above- and below-water radiometric measurements collected in the Baltic Sea, and compared against a scalar offset correction Δ. Correction with Δ(λ) instead of Δ consistently reduced the (mean normalized root-mean-square) deviation between Rrs (λ) and reference reflectances to comparable levels for clear (Δ: 14.3 ± 2.5 %, Δ(λ): 8.2 ± 1.7 %), partly clouded (Δ: 15.4 ± 2.1 %, Δ(λ): 6.5 ± 1.4 %), and completely overcast (Δ: 10.8 ± 1.7 %, Δ(λ): 6.3 ± 1.8 %) sky conditions. The improvement was most pronounced under inhomogeneous sky conditions when measurements of sky radiance tend to be less representative of surface-reflected radiance. Accounting for both sun glint and sky reflections also relaxes constraints on measurement geometry, which was demonstrated based on a semi-continuous daytime data set recorded in a eutrophic freshwater lake in the Netherlands. Rrs (λ) that were derived throughout the day varied spectrally by less than 2 % relative standard deviation. Implications on measurement protocols are discussed. An open source software library for processing reflectance measurements was developed and is made publicly available.

INTRODUCTION TO THE SYMBOL-IDENTIFICATION OF THE PRESENCE OF WATER IN IRAN'S MOSQUES ARCHITECTURE

Water element in Iranian architecture in terms of symbolic meanings and concepts has been manifested in different forms.Water in the body of Iranian mosques due to both the mystical and practical loads had also carried more symbolic messages. The presence of water in Iranian mosques architecture In addition to having image-creations associated with the prayers, ablution, purification and refreshing ritual had also carried reflection of semantic load, transparency, and being-like-mirror.Water in terms of presence in running and still water forms and in terms of symbolism system in the methods of allusion, symbol, sign, indication, secret, mystery, point, appearance, riddle, analogy has found objective appearancein the body of Iranian mosques. The present research has been conducted with descriptive-analytical method.The presence of water is in a variety of ordering elements of kinetic and stillness, and signs of relaxation, peace, reconciliation, stable sign of life, sky reflection, and survival continuation in ideas derived from symbolic concepts. The most important elements related to the presence of water in Iranian mosques architecture are place of ablution, trough, pool, patio, and fountain.This appearance and manifestation of water's form and character in Iranian architecture have had a special position and even sacred. A corner of these appearances can be observed in symbols used in Iranian mosques objectively. Symbol, its types and the manner of advent and display of the symbolic elements of water in Iran's mosque architecture have been investigated in this study. Achievements of this research will lead to the initial symbol-identifier conception of the presence and manifestation and appearance of water in the area of the architectural body of Iranian mosques.

Three years of L-band brightness temperature measurements in a mountainous area: Topography, vegetation and snowmelt issues

L-band passive measurements (1.4 GHz) over continental areas are known to be related to surface soil moisture. Two satellite missions were recently launched to measure land surface emissions at this frequency band (SMOS-Soil Moisture and Ocean Salinity in 2009 and SMAP-Soil Moisture Active/Passive in 2015). In order to improve soil moisture retrievals from satellite data, ground-based radiometer systems operating at the same frequency were deployed over specified areas to investigate the L-band emission of various land covers under various climatological conditions. In this study, three years of L-band passive measurements from a radiometer installed on top of a steep mountain in the French Alps were analyzed and compared to L-band passive simulations. The innovative radiometer location led to large footprints due to the distance between the radiometer and the area under study. This experiment also produced microwave measurements affected by various potential difficulties typically encountered in SMOS/SMAP satellite missions: topography, heterogeneous footprints, dry/wet snow events, dew and vegetation litter. Based on in situ and modeling data, this paper investigates the potential of a radiative transfer model (L-band Microwave Emission of the Biosphere, L-MEB) to simulate L-band measurements and analyzes the differences with ELBARA observations. First, it was found that the topography generated a mixing of the horizontal and vertical polarizations. In addition, a large positive bias was found on ELBARA measurements (31 K and 12 K in horizontal and vertical polarizations respectively). Investigations showed that the sky reflection measured by the radiometer was partially substituted by land reflection coming from the surrounding topography. Second, the low-vegetation emission was investigated and highlighted the inability of the MODIS NDVI product to correctly represent the vegetation dynamics. Finally, dry snow conditions were found to have non-negligible impact at L-band and a particular signature was found during snow melting periods, with potential applications at the SMOS/SMAP spatial scales (~ 40 km).

Time-lapse thermography for building defect detection

Building thermography traditionally captures the thermal condition of building fabric at one single point in time, rather than changes in state over a sustained period. Buildings, materials and the environment are, however, rarely in a thermal equilibrium, which therefore risks the misinterpretation of building defects by employing this standard methodology. This paper tests the premise that time-lapse thermography can better capture building defects and dynamic thermal behaviour. Results investigating the temporal resolution required for time-lapse thermography over two case study houses found that under typical conditions small temperature differences (approximately 0.2K) between thermal areas could be expected for 30-min image intervals. Results also demonstrate that thermal patterns vary significantly from day-to-day, with a 2.0K surface temperature difference experienced from one day to the next. Temporal resolutions needed adjusting for different types of construction. Time-lapse experiments raised practical limitations for the methodology that included problems with the distance to target and foreground obstructions. At the same time, these experiments show that time-lapse thermography could greatly improve our understanding of building transient behaviour and possible building defects. Time-lapse thermography also enables enhanced differentiation between environmental conditions (such as clear sky reflections), actual behaviour and construction defects, thereby mitigating the risk of misinterpretation.

Dispatches

Dispatches

Extending 3D near-cloud corrections from shorter to longer wavelengths

Satellite observations have shown a positive correlation between cloud amount and aerosol optical thickness (AOT) that can be explained by the humidification of aerosols near clouds, and/or by cloud contamination by sub-pixel size clouds and the cloud adjacency effect. The last effect may substantially increase reflected radiation in cloud-free columns, leading to overestimates in the retrieved AOT. For clear-sky areas near boundary layer clouds the main contribution to the enhancement of clear sky reflectance at shorter wavelengths comes from the radiation scattered into clear areas by clouds and then scattered to the sensor by air molecules. Because of the wavelength dependence of air molecule scattering, this process leads to a larger reflectance increase at shorter wavelengths, and can be corrected using a simple two-layer model [18]. However, correcting only for molecular scattering skews spectral properties of the retrieved AOT. Kassianov and Ovtchinnikov [9] proposed a technique that uses spectral reflectance ratios to retrieve AOT in the vicinity of clouds; they assumed that the cloud adjacency effect influences the spectral ratio between reflectances at two wavelengths less than it influences the reflectances themselves. This paper combines the two approaches: It assumes that the 3D correction for the shortest wavelength is known with some uncertainties, and then it estimates the 3D correction for longer wavelengths using a modified ratio method. The new approach is tested with 3D radiances simulated for 26 cumulus fields from Large-Eddy Simulations, supplemented with 40 aerosol profiles. The results showed that (i) for a variety of cumulus cloud scenes and aerosol profiles over ocean the 3D correction due to cloud adjacency effect can be extended from shorter to longer wavelengths and (ii) the 3D corrections for longer wavelengths are not very sensitive to unbiased random uncertainties in the 3D corrections at shorter wavelengths.

Spatial and Temporal Homogeneity of Solar Surface Irradiance across Satellite Generations

Solar surface irradiance (SIS) is an essential variable in the radiation budget of the Earth. Climate data records (CDR’s) of SIS are required for climate monitoring, for climate model evaluation and for solar energy applications. A 23 year long (1983–2005) continuous and validated SIS CDR based on the visible channel (0.45–1 μm) of the MVIRI instruments onboard the first generation of Meteosat satellites has recently been generated using a climate version of the well established Heliosat method. This version of the Heliosat method includes a newly developed self-calibration algorithm and an improved algorithm to determine the clear sky reflection. The climate Heliosat version is also applied to the visible narrow-band channels of SEVIRI onboard the Meteosat Second Generation Satellites (2004–present). The respective channels are observing the Earth in the wavelength region at about 0.6 μm and 0.8 μm. SIS values of the overlapping time period are used to analyse whether a homogeneous extension of the MVIRI CDR is possible with the SEVIRI narrowband channels. It is demonstrated that the spectral differences between the used visible channels leads to significant differences in the solar surface irradiance in specific regions. Especially, over vegetated areas the reflectance exhibits a high spectral dependency resulting in large differences in the retrieved SIS. The applied self-calibration method alone is not able to compensate the spectral differences of the channels. Furthermore, the extended range of the input values (satellite counts) enhances the cloud detection of the SEVIRI instruments resulting in lower values for SIS, on average. Our findings have implications for the application of the Heliosat method to data from other geostationary satellites (e.g., GOES, GMS). They demonstrate the need for a careful analysis of the effect of spectral and technological differences in visible channels on the retrieved solar irradiance.

Establishment of a hyperspectral evaluation model of ocean color satellite-measured reflectance

The accuracy of the satellite-measured reflectance is a key question for data processing and oceanographic applications. A hyperspectral satellite remote sensing reflectance evaluation model (HRSREM) was developed to evaluate the accuracy of the satellite measured reflectance. The model can compute the total reflectance at the top of the atmosphere (TOA) according to observation conditions of satellites, based on a radiative transfer model with the consideration of multiple scattering effects and atmospheric absorption effects. The performance of the HRSREM model was examined by Gordon’s algorithms, showing that the relative errors of the Rayleigh scattering reflectance and the aerosol scattering reflectance are less than 2%. The model can also compute the sky reflectance which can be validated by in-situ measurements. The two sky reflectances match well with a spectral average error of 5.4%. The relative error of the total reflectance of the model, verified by sea-viewing wide field-of-view sensor (SeaWiFS) data, is about 3.5%. Therefore, the total reflectances at TOA, computed by the model, can be taken as reference values to evaluate the accuracy of satellite reflectances. The model was used to evaluate the accuracy of the hypersptral satellite (Hyperion) remote sensing data. The Hyperion reflectance matches the total reflectance of HRSREM very well at visible and near-infrared bands with an average error of 7.3%, while the status of calibration coefficients at shortwave infrared bands are not stable with a large spectral average error of 63.5%. The reflectance evaluation of a moderate resolution imaging spectrometer (CMODIS) data indicated that relative errors are large, especially at near-infrared bands with relative errors more than 100%. The calibration coefficients of CMODIS, obtained from laboratory measurements, are not reliable. The CMODIS data should be recalibrated for oceanographic applications. The performance of the HRSREM model is effective in evaluating satellite data and its algorithms can be easily modified in order to evaluate the accuracy of other ocean color satellite sensors.

Evaluation and Normalization of Cloud Obscuration Related BRDF Effects in Field Spectroscopy

The impact of target bidirectional reflectance in dual field of view spectroscopy was described and quantified using field measurements and ray-tracing simulations. A data-driven normalization method was developed to convert reflectance factors under cloud obscured conditions into clear sky reflectance by decomposing the target bidirectional reflectance into an isotropic target-specific component and a group-specific bidirectional component. An evaluation on tree, grass and gravel targets suggests a reduction in relative reflectance error obtained by normalization from 15% to less than 5% between 400 and 1800 nm. At higher wavelengths a decreased signal-to-noise ratio increases the errors.

MODIS observations of enhanced clear sky reflectance near clouds

Several recent studies have found that the brightness of clear sky systematically increases near clouds. Understanding this increase is important both for a correct interpretation of observations and for improving our knowledge of aerosol‐cloud interactions. However, while the studies suggested several processes to explain the increase, the significance of each process is yet to be determined. This study examines one of the suggested processes—three‐dimensional (3‐D) radiative interactions between clouds and their surroundings—by analyzing a large dataset of MODIS (Moderate Resolution Imaging Spectroradiometer) observations over the Northeast Atlantic Ocean. The results indicate that 3‐D effects are responsible for a large portion of the observed increase, which extends to about 15 km away from clouds and is stronger (i) at shorter wavelengths (ii) near optically thicker clouds and (iii) near illuminated cloud sides. This implies that it is important to account for 3‐D radiative effects in the interpretation of solar reflectance measurements over clear regions in the vicinity of clouds.

Modeling the infrared radiance of rough sea surface in the infrared windows: 3–5 μm and 8–12 μm

The general formulations for spectral directional emissivity and spectral bi-directional reflectivity are analyzed by using Fresnel's formula and Snell's law in rough sea surface which is simulated by wave facets, whose slopes are changing according to the isotropic Gaussian distribution with respect to surface wind. Then, shadowing effect is taken into account in both emission and reflection of sea surface. On this basis, the mathematic expression is obtained for spectral radiance of rough sea surface, in which the radiance of rough sea surface is considered as a composition of self-emission, reflection of sky and reflection of sun. Finally, calculations for infrared radiance of rough sea surface in bands of 3–5 μm and 8–12 μm are given to illustrate their significant different, which are caused mostly by the dispersion of sun radiation.

Introducing a mini-catamaran to perform reflectance measurements above and below the water surface

An innovative platform is tested to perform reflectance measurements at sea. This platform is a mini-catamaran with two hulls 1m long and set 0.7m apart, fitted with optical sensors. It can be used far away from an oceanographic ship to avoid its hull influencing the measurement. Reflectance measurements were performed with a TriOS radiance sensor placed +2cm or -2cm from the water surface and a TriOS irradiance sensor. Tests were carried out in calm seas and with cloud cover. The processing to derive marine radiances from raw measurements is detailed. When the radiance sensor is above the interface, it limits the sky reflections on the targeted surface and the radiance is identical to that deduced from measurements below the surface. When the sensor is placed at +3cm abovewater or higher, glint affects the measurements. The mini-catamaran shows a good ability to measure marine reflectance with an adapted measurement protocol. Except for very turbid waters, it seems preferable to perform upwelling radiance measurements below the surface.

The influence of neighbouring clouds on the clear sky reflectance studied with the 3-D transport code RADUGA

Operational remote sensing of terrestrial atmosphere is heavily based on the 1-D radiative transfer equation. However, cloudy scenes are influenced by 3-D effects (e.g., illumination from cloud sides, etc.). This leads to biases in aerosol/cloud/land/ocean retrieval schemes for scenes with clouds. These biases can be understood and quantified only with the use of the 3-D radiative transfer theory, which allows to account for arbitrary spatial variation of atmospheric parameters. The task of this paper is twofold. First of all we introduce a novel technique for the solution of the 3-D radiative transfer equation based on the grid approximations and the straightforward iteration procedure realised on supercomputers with parallel architecture. We study the performance of our technique comparing with the solutions obtained by the Monte-Carlo code. A close correspondence is found. Secondly, we quantify the influence of neighbouring clouds on the clear sky reflection function at the nadir observation depending on the solar illumination conditions. We find that the influence of cloud on the clear sky reflectance function is not negligible (even outside the cloud geometrical shadow). Thus, the peculiar inner boundary layer arises in the sky reflectance function with shadowing and brightening effects.