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 rho 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 r 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 r simulations reduces from similar to 17 to similar to 10% when the wind speed increases from 0 to 14ms(-1). An opposite tendency characterizes the modeling of the sea-surface slope variance, with r differences up to similar to 12% at a wind speed of 10ms(-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 similar to 13 to similar to 18%. The r 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 degrees 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. (C) 2016 Optical Society of Americ

A high-performance computing framework for Monte Carlo ocean color simulations

This paper presents a high-performance computing (HPC) framework for Monte Carlo (MC) simulations in the ocean color (OC) application domain. The objective is to optimize a parallel MC radiative transfer code named MOX, developed by the authors to create a virtual marine environment for investigating the quality of OC data products derived from in situ measurements of in-water radiometric quantities. A consolidated set of solutions for performance modeling, prediction, and optimization is implemented to enhance the efficiency of MC OC simulations on HPC run-time infrastructures. HPC, machine learning, and adaptive computing techniques are applied taking into account a clear separation and systematic treatment of accuracy and precision requirements for large-scale MC OC simulations. The added value of the work is the integration of computational methods and tools for MC OC simulations in the form of an HPC-oriented problem-solving environment specifically tailored to investigate data acquisition and reduction methods for OC field measurements. Study results highlight the benefit of close collaboration between HPC and application domain researchers to improve the efficiency and flexibility of computer simulations in the marine optics application domain. (C) 2016 The Authors. Concurrency and Computation: Practice and Experience Published by John Wiley & Sons Ltd.Portuguese Foundation for Science and Technology (FCT/MEC) [PEst-OE/EEI/UI0527/2011]; ESA [22576/09/I-OL, ARG/003-025/1406/CIMA]; NOVA LINCS [UID/CEC/04516/2013]info:eu-repo/semantics/publishedVersio

Advanced Radiative Transfer Models for the simulation of In situ and Satellite Ocean Color data (ARTEMIS-OC): the Novel Adjacency Perturbation Simulator for Coastal Areas (NAUSICAA) code

oai:publications.jrc.ec.europa.eu:JRC141105This report, the second in a series, leverages JRC extensive experience in developing and applying highly accurate radiative transfer models to simulate in situ and satellite aquatic data, which are integrated into the JRC’s Advanced Radiative Transfer Models for In situ and Satellite Ocean Color data (ARTEMIS-OC) software suite. ARTEMIS-OC includes i) the FEM code for simulating unpolarised solar radiation in open-ocean environments, ii) the PERSEA code to ensure a flexible and comprehensive modelling of the optical properties of realistic atmosphere and water environments, iii) the SkyFEM, FEMrad-OC, and AquaFEM codes, which are tailored FEM-PERSEA configurations to reproduce the radiance detected by sky-looking, satellite and in-water sensors, respectively; and iv) the NAUSICAA code to simulate unpolarised solar radiation in coastal and inland water regions, i.e., in the presence of nearby land perturbations. All algorithms account for multiple scattering and allow varying illumination and observation geometries. The present report focuses on the NAUSICAA code and its applications in investigating and reducing uncertainties in OC data products. The ultimate goal of this report series is to provide a comprehensive description of the ARTEMIS-OC simulation tools in support of the Copernicus Programme launched in 2014 to establish a European capacity for Earth Observation.JRC.D.2 - Ocean and Wate

In-water lidar simulations: the ALADIN ADM-Aeolus backscattered signal at 355 nm

The Lidar Ocean Color (LiOC) Monte Carlo code has been developed to simulate the in-water propagation of the lidar beam emitted by the ALADIN ADM-Aeolus instrument in the ultraviolet (UV) spectral region (∼ 355 nm). To this end, LiOC accounts for reflection/transmission processes at the sea surface, absorption and multiple scattering in the water volume, and reflection from the sea bottom. The water volume components included in the model are pure seawater, Chlorophyll-a concentration (Chl-a), Colored Dissolved Organic Matter (CDOM), and/or a generic absorbing species. By considering the transmission/reception measurement geometry of ALADIN ADM-Aeolus, the study documents the variability of the normalized backscattered signal in different bio-optical conditions. The potential for data product retrieval based on information at 355 nm is considered by developing a demonstrative lookup table to estimate the absorption budget exceeding that explained by Chl-a. Results acknowledge the interest of space programs in exploiting UV bands for ocean color remote sensing, as, for instance, addressed by the PACE mission of NASA

European Radiometry Buoy and Infrastructure (EURYBIA): A Contribution to the Design of the European Copernicus Infrastructure for Ocean Colour System Vicarious Calibration

In the context of the Copernicus Program, EUMETSAT prioritizes the creation of an ocean color infrastructure for system vicarious calibration (OC-SVC). This work aims to reply to this need by proposing the European Radiometry Buoy and Infrastructure (EURYBIA). EURYBIA is designed as an autonomous European infrastructure operating within the Marine Optical Network (MarONet) established by University of Miami (Miami, FL, USA) based on the Marine Optical Buoy (MOBY) experience and NASA support. MarONet addresses SVC requirements in different sites, consistently and in a traceable way. The selected EURYBIA installation is close to the Lampedusa Island in the central Mediterranean Sea. This area is widely studied and hosts an Atmospheric and Oceanographic Observatory for long-term climate monitoring. The EURYBIA field segment comprises off-shore and on-shore infrastructures to manage the observation system and perform routine sensors calibrations. The ground segment includes the telemetry center for data communication and the processing center to compute data products and uncertainty budgets. The study shows that the overall uncertainty of EURYBIA SVC gains computed for the Sentinel-3 OLCI mission under EUMETSAT protocols is of about 0.05% in the blue-green wavelengths after a decade of measurements, similar to that of the reference site in Hawaii and in compliance with requirements for climate studies

Comparison of correction methods for bidirectional effects in ocean colour remote sensing

31 pages, 20 figures, 13 tables, supplementary data https://doi.org/10.1016/j.rse.2025.114606.-- Data availability: Data will be made available on request.Several methods were developed in Ocean Colour remote sensing over the last 25 years to model the anisotropy of the upwelling radiant field with respect to observation and solar-illumination geometries, also denoted as bidirectional reflectance distribution function (BRDF). These methods are necessary to produce normalized, or “BRDF-corrected,” marine reflectance representative of the seawater's inherent optical properties (IOPs) independently of the measurement conditions. Each scheme relies on specific modeling assumptions and implementation solutions, which can lead to different results depending on the actual combination of the seawater IOPs with the illumination and viewing geometry. The first aim of this study is to analyze the principles and methods of the reference BRDF schemes presented by Morel et al. (denoted as M02), Park and Ruddick (P05), Lee et al. (L11), He et al. (H17), and Twardowski and Tonizzo (T18). Acknowledging the direct applicability of M02, P05, and L11, their performance has been verified under a variety of conditions, including in situ measurements, matchup observations, and space-borne images. Comparisons between non-corrected and normalized data clearly confirm the need to account for the BRDF effect. In particular, the analysis of the results indicates 1) a substantial equivalence of M02, P05, and L11 in clear waters and 2) the tendency to obtain better results with M02 and L11 as the optical complexity increases. Although M02 was conceived for Case 1 waters, the underlying Chlorophyll-a overestimation tendency in some optically complex conditions is likely the reason for its extended applicability. Since L11 is based on a more comprehensive and flexible framework for all water types, the design of this method is suggested for revisions and BRDF correction improvementsThis study was done in the frame of the European Commission's Copernicus study “BRDF correction of S3 OLCI water reflectance products” (contract No. RB_EUM-CO-21-4600002626-JIG), conducted by EUMETSAT. The work also acknowledges the support of the Ocean Colour Thematic Assembly Centre of the Copernicus Marine Environment and Monitoring Service (contract: 21001 L02-COP-TAC OC-2200–Lot 2: Provision of Ocean Colour Observation Products (OC-TAC)) and the Spanish “Severo Ochoa Center of Excellence” Accreditation Grant CEX2019–000928-S. J. P. acknowledges partial funding by the European Union through the NextGenerationEU Program, ITINERIS Project (Italian Integrated Environmental Research Infrastructures System)Peer reviewe

BRDF correction of S3 OLCI water reflectance products

Ocean Optics XXV, 2-7 October 2022, Quy Nhon, Binh Dinh, Vietnam.-- 1 page, figuresOngoing study to minimize the effects of the Bidirectional Reflectance Distribution Function (BRDF) and deliver Sentine3 OLCI fully normalized water reflectancesEUMETSAT Contract Ref.: RB_EUM-CO-21-4600002626-JIGPeer reviewe

Multi layer perceptron neural network algorithms for ocean colour applications in coastal waters

This work focuses on the development, performance assessment and identification of the range of applicability of ocean color algorithms for the retrieval of seawater constituents in optically complex coastal regions.  Multi Layer Perception neural network algorithms were implemented using a set of experimental data collected in the northern Adriatic Sea (CoASTS data set).  The following quantities were modelled as a function of the remote sensing reflectance:  i)  Chlorophyll-a concentration (Chl-a);  ii)  Absorption of the pigmented particulate matter at 443 nm (αph (443);  iii)  Absorption spectra of the coloured dissolved organic matter (αys) and of the non pigmented particulate matter (adp).  The range of applicability of two MLP algorithms developed for the retrieval of the Chl-a in coastal and open sea regions, were compared using SeaWiFS images of European Seas.  A method for algorithms blending was also formulated and applied to case studies.</p

Multi layer perceptron neural network algorithms for ocean colour applications in coastal waters

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