Search

Particle scattering is a key factor affecting underwater light transport. The diffusion length (zD), defined as 1/[b(1 - g)], where b is the scattering coefficient and g is the asymmetry factor, is obtained from the volume scattering function (VSF) of the particle and plays a vital role in assessing the potential for underwater optical detection, imaging and communication. Owing to the lack of VSF datasets, the variation in zD at different wavelengths in various ocean areas remains unclear. In this study, we used a dual-wavelength (488 & 532 nm) VSFLab to conduct the VSF measurement experiments in the East China Sea (ECS) and the South China Sea (SCS), obtaining VSFs from 1.5° to 178.5° at 51 stations. Seven optical properties, including absorption (a), scattering (b), attenuation (c), diffuse attenuation coefficient (Kd), backscattering (bb), g, andzD, were calculated from the measured VSFs. A comparative analysis of the results was performed, which showed that the laser transmission capability at 532 nm was better than that at 488 nm in terms of the absorption or diffuse attenuation coefficient in the ECS, whereas superior performance was observed at 488 nm in the SCS. However, from the perspective of scattering, zD at 532 nm (zD(532)) demonstrated superior performance in both the ECS and SCS. This superiority was particularly noticeable in regions with exceptionally clear water, such as the eastern side of the Luzon Strait, where zD(532) exceeded zD(488) by approximately 20%. Overall, the findings of this study provide a new perspective for assessing underwater light transmission capabilities. [ABSTRACT FROM AUTHOR]

Automated above-water hyperspectral observations are often subject to inaccuracies caused by instrument malfunction and environmental conditions. This study evaluates the influence of atmospheric and water surface conditions on above-water hyperspectral measurements through statistical methods and Radiative Transfer (RT) modelling. Initially, we developed a general quality control method based on statistical assessment to detect the suspicious spectra. Subsequently, Radiative Transfer (RT) models were used to assess low light conditions, distortions in the spectral shape of above-water solar downwelling irradiance (E S (λ), mW m−2 nm−1) particularly those caused by intense atmospheric scattering and/or reddish hue of dusk or dawn radiation, the effect of atmospheric humidity and precipitation on the intensity and shape of spectra, and the influence of sun glint and surface perturbations on sky (L S (λ), mW m−2 nm−1 sr−1) and water surface (L T (λ), mW m−2 nm−1 sr−1) radiances. The proposed methods were applied to the entire archive of automated above-water hyperspectral measurements collected every ten minutes from 2020 to 2022 at the Royal Netherland Institute for Sea Research (NIOZ) at Jetty Station (NJS) located in the Marsdiep tidal inlet of the Duch Wadden Sea, the Netherlands. The findings demonstrate that low light conditions are characterized by E S (λ) max ≤ 25 mW m−2 nm−1. Red-shifted or distorted spectra are indicated by a ratio of E S (4 8 0)/ E S (6 8 0) ≤ 1.0 and E S (λ max)/ E S (8 6 5) ≤ 1.25. High humidity/precipitation conditions are identified by the ratio of E S (9 4 0)/ E S (8 6 5), which varies with the Solar Zenith Angle (SZA). Furthermore, significant sun glint and surface perturbations, such as whitecaps and foam, are indicated when the minimum ratio of L T (800 nm-950 nm)/ E S (800 nm-950 nm) > 0.025 sr−1, and the ratio of L T (850 nm)/ E S (850 nm) ≥ 0.025 sr−1. [ABSTRACT FROM AUTHOR]

Ocean color satellites require a procedure known as System Vicarious Calibration (SVC) after launch as the pre-launch and on-orbit calibration accuracy is insufficient. The current approach for determination of post-launch SVC uses a single fixed measurement location and may be susceptible to unexpected biases in satellite processing algorithms. Here we describe a novel SVC program which is based on a high resolution and high accuracy radiometric system integrated with an autonomous profiling float (providing a buoyancy engine, physical observations, and communication). This float + radiometer (HyperNav) system can be shipped via air, land, ocean and is deployable from small boats. This SVC program relies on multiple deployment sites with associated facilities to collect a significant amount of SVC quality data in a relatively short time. It has centralized logistics and command-and-control centers ensuring easy access to information regarding the status of each asset and to ensure floats stay within a certain ocean area. The development of the program has been associated with the launch of NASA's PACE satellite and has been executed by academic institutions in collaboration with an industrial partner. Other approaches for a future float-based operational SVC program are discussed. [ABSTRACT FROM AUTHOR]

Hyperspectral optical observations of the Earth's surface oceans from space offer a means to improve our understanding of ocean biology and biogeochemistry. NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission, which includes a hyperspectral ocean color instrument (OCI), will provide radiometric observations of surface ocean with near continuous spectral resolution across the near UV to NIR range. Maintaining sufficient accuracy over the lifetime of satellite ocean color missions requires a robust program for system vicarious calibration (SVC) and product validation. The system vicarious calibration process combines satellite sensor data with in-situ radiometric/optical measurements to remove potential biases due to the combined errors from both satellite radiometric sensor calibration and atmospheric correction. As such, high accuracy, high-spectral resolution insitu radiometric measurements are required to provide a principal source of truth for the satellite-derived products. To meet the requirements, a novel in-situ radiometric system, called HyperNav, has been developed, rigorously characterized and field tested. Key attributes of HyperNav are dual upwelling radiance heads coupled to individual spectrometers, spectral resolution of ~2.2 nm (full width, half-maximum) across 320-900 nm, integrated shutter systems for dark measurements, and integrated tilt and pressure sensors. The HyperNav operational modes include traditional profiling and surface modes, as well as integration with an autonomous profiling float for unattended deployment, offering a new capability for a network of autonomous platforms to support the long-term needs for hyperspectral ocean color remote sensing observations. This paper describes the HyperNav design, in-situ operational modes, and field verification results. [ABSTRACT FROM AUTHOR]

The estimation of depth in optically shallow waters using satellite imagery can be efficient and cost-effective. Active sensors measure the distance traveled by an emitted laser pulse propagating through the water with high precision and accuracy if the bottom peak intensity of the waveform is greater than the noise level. However, passive optical imaging of optically shallow water involves measuring the radiance after the sunlight undergoes downward attenuation on the way to the sea floor, and the reflected light is then attenuated while moving back upward to the water surface. The difficulty of satellite-derived bathymetry (SDB) arises from the fact that the measured radiance is a result of a complex association of physical elements, mainly the optical properties of the water, bottom reflectance, and depth. In this research, we attempt to apply physics-based algorithms to solve this complex problem as accurately as possible to overcome the limitation of having only a few known values from a multispectral sensor. Major analysis components are atmospheric correction, the estimation of water optical properties from optically deep water, and the optimization of bottom reflectance as well as the water depth. Specular reflection of the sky radiance from the water surface is modeled in addition to the typical atmospheric correction. The physical modeling of optically dominant components such as dissolved organic matter, phytoplankton, and suspended particulates allows the inversion of water attenuation coefficients from optically deep pixels. The atmospheric correction and water attenuation results are used in the ocean optical reflectance equation to solve for the bottom reflectance and water depth. At each stage of the solution, physics-based models and a physically valid, constrained Levenberg–Marquardt numerical optimization technique are used. The physics-based algorithm is applied to Landsat Operational Land Imager (OLI) imagery over the shallow coastal zone of Guam, Key West, and Puerto Rico. The SDB depths are compared to airborne lidar depths, and the root mean squared error (RMSE) is mostly less than 2 m over water as deep as 30 m. As the initial choice of bottom reflectance is critical, along with the bottom reflectance library, we describe a pure bottom unmixing method based on eigenvector analysis to estimate unknown site-specific bottom reflectance. [ABSTRACT FROM AUTHOR]

Ocean color satellites require a procedure known as System Vicarious Calibration (SVC) after launch as the pre-launch and on-orbit calibration accuracy is insufficient. The current approach for determination of post-launch SVC uses a single fixed measurement location and may be susceptible to unexpected biases in satellite processing algorithms. Here we describe a novel SVC program which is based on a high resolution and high accuracy radiometric system integrated with an autonomous profiling float (providing a buoyancy engine, physical observations, and communication). This float + radiometer (HyperNav) system can be shipped via air, land, ocean and is deployable from small boats. This SVC program relies on multiple deployment sites with associated facilities to collect a significant amount of SVC quality data in a relatively short time. It has centralized logistics and command-and-control centers ensuring easy access to information regarding the status of each asset and to ensure floats stay within a certain ocean area. The development of the program has been associated with the launch of NASA’s PACE satellite and has been executed by academic institutions in collaboration with an industrial partner. Other approaches for a future float-based operational SVC program are discussed.

Hyperspectral optical observations of the Earth’s surface oceans from space offer a means to improve our understanding of ocean biology and biogeochemistry. NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission, which includes a hyperspectral ocean color instrument (OCI), will provide radiometric observations of surface ocean with near continuous spectral resolution across the near UV to NIR range. Maintaining sufficient accuracy over the lifetime of satellite ocean color missions requires a robust program for system vicarious calibration (SVC) and product validation. The system vicarious calibration process combines satellite sensor data with in-situ radiometric/optical measurements to remove potential biases due to the combined errors from both satellite radiometric sensor calibration and atmospheric correction. As such, high accuracy, high-spectral resolution in-situ radiometric measurements are required to provide a principal source of truth for the satellite-derived products. To meet the requirements, a novel in-situ radiometric system, called HyperNav, has been developed, rigorously characterized and field tested. Key attributes of HyperNav are dual upwelling radiance heads coupled to individual spectrometers, spectral resolution of ∼2.2 nm (full width, half-maximum) across 320–900 nm, integrated shutter systems for dark measurements, and integrated tilt and pressure sensors. The HyperNav operational modes include traditional profiling and surface modes, as well as integration with an autonomous profiling float for unattended deployment, offering a new capability for a network of autonomous platforms to support the long-term needs for hyperspectral ocean color remote sensing observations. This paper describes the HyperNav design, in-situ operational modes, and field verification results.

The Southern Ocean (SO) is known for its atypical bio‐optical regime. This complicates the interpretation of proxies measured from satellite and in situ platforms equipped with optical sensors, which occupy an important niche for monitoring the vast and remote SO. A ship‐based field study in concert with time series observations from BioGeoChemical‐Argo (BGC‐Argo) profiling floats were used to investigate spatial and temporal variations in bio‐optical relationships in the open ocean waters surrounding the Kerguelen Plateau in the Indian sector of the SO. Compared to other regions with similar chlorophyll concentrations, chlorophyll‐specific phytoplankton absorption in the blue waveband presented a consistent negative anomaly. The anomaly was uniform over deep mixed layers and correlated with phytoplankton size, photoacclimation and atypically high concentrations of fucoxanthin. The BGC‐Argo observation‐based proxies revealed that the blue absorption anomaly increased with chlorophyll concentration both spatially and temporally and, while particularly pronounced in the naturally iron‐fertilized waters, was also found in the High Nutrient Low Chlorophyll region. While phytoplankton size was an important driver of the anomaly, photoacclimation associated with self‐shading of phytoplankton cells was also involved during intense booms. The backscattering coefficient exhibited negative and positive anomalies in the low and high biomass regimes, respectively. The large positive anomaly in high biomass regimes was attributed to the variable non‐algal particles characteristics associated with a relatively high production of bloom by‐products. With clear understanding of the bio‐optical anomalies, BGC‐Argo floats stand as unique tools for monitoring the bio‐optical spatio‐temporal complexity of the SO. Plain Language Summary: The Southern Ocean (SO) plays a key role in Earth's climate. However, its remoteness and harsh climate necessitate remote sensing approaches such as optical sensors on profiling floats and satellites. These require optical measurements and shipboard samples to relate optical signals to biological properties, called optical proxies. The SO optical proxies have been found to be very different from those measured in other oceanic regions. Here the proxies in the Kerguelen region are investigated along a ship's track crossing from subtropical to subpolar latitudes. The Kerguelen Plateau impedes both wind and currents such that deep waters upwell to the surface providing nutrients to primary producers. This region in the Indian sector of the SO provides a tremendous range in ecosystem properties from nutrient‐starved to nutrient‐rich, making these results applicable to other SO areas. The authors find that the differences in optical proxies can be explained by the presence of different phytoplankton communities and their responses to being mixed to depths where light is limited. This explains why the proxies vary so significantly across this region and change over the seasons. This knowledge makes the observations obtained by floats and satellites invaluable for understanding the entire SO. Key Points: Contribution by large diatoms and photoacclimation are major drivers of a negative anomaly in the blue chlorophyll‐specific phytoplankton absorption coefficientBioGeoChemical‐Argo observations indicate a bio‐optical anomaly exists over the entire year with maximal values associated with seasonal bloomsThe Indian Southern Ocean shows a large seasonal and regional variability in bio‐optical regimes that lie outside the global means [ABSTRACT FROM AUTHOR]

Understanding the transmission of light in ocean turbulence is of great significance for underwater communication, underwater detection, and other fields. The properties of ocean turbulence can affect the transmission characteristics of light beams, therefore it is essential to estimate the ocean turbulence intensity (OTI). In this study, we propose a deep learning-based method for predicting the OTI. Using phase screens to simulate ocean turbulence, we constructed a database of distorted Gaussian beams generated by Gaussian beams passing through ocean turbulence with varying intensities. We built a convolutional neural network and trained it using this database. For the trained network, inputting a distorted beam can accurately predict the corresponding intensity of ocean turbulence. We also compared our designed network with traditional network models such as AlexNet, VGG16, and Xception, and the results showed that our designed network had higher accuracy.

Background: The coastal ocean's environment has changed owing to human activity, with eutrophication becoming a global concern. However, oligotrophication occurs locally and decreases fish production. Historically, the Secchi depth has been used as an index of primary productivity. We analyzed the results of over-a-half-century routine observations conducted in Sagami Bay and Tokyo Bay to verify the eutrophication/oligotrophication trend based on Secchi depth observations in a temperate coastal region near the Greater Tokyo area, which is highly affected by human activities. Methods: Data recorded in the Kanagawa Prefecture from 1963 to 2018 were used in this study. After quality control, the observation area was divided into Tokyo Bay, the Uraga Channel (outer part of Tokyo Bay), Sagami Bay (northern part), and Sagami Nada (southern part of Sagami Bay) based on temperature and salinity at a depth of 10 m. Because the environmental parameters showed autocorrelation, time-series and correlation analyses were conducted using generalized least squares (GLS) models with a Prais-Winsten estimator. Results: The Secchi depth was the shallowest in Tokyo Bay, followed by the Uraga Channel, Sagami Bay, and Sagami Nada, and was deep in winter (December and January), and shallow in summer (July) in all regions. The correlated analyses using the GLS model indicated that the shallowing of Secchi depth was significantly associated with decreases in temperature, salinity, and phosphate concentration. However, time-series analyses using GLS models indicated that the Secchi depth was significantly shallower, except in Tokyo Bay, where the surface temperature was significantly warming and the surface phosphate and nitrite concentrations decreased everywhere. A significant shallowing trend of the Secchi depth was mostly observed during the light-limiting season (January-March). Discussion: Correlation analyses suggested the importance of horizontal advective transport, particularly from Tokyo Bay, which has cold and less saline eutrophic water. However, long-term shallowing of the Secchi depth was associated with warming, and changes in salinity were not significant in most months when the Secchi depth trend was significant. Thus, horizontal advection is not the primary cause of long-term eutrophication. Because the eutrophication trend was primarily observed in winter, when light is the major limiting factor of primary production, we concluded that warming provides a better photoenvironment for phytoplankton growth and induces eutrophication. As a decline in anthropogenic nutrient input after 1990s was reported in the investigated area, the long-term eutrophication trend was most likely caused due to global warming, which is another alarming impact resulting from human activities. [ABSTRACT FROM AUTHOR]

Introduction: Space-borne lidar measurements from sensors such as CALIOP were recently used to retrieve the particulate back-scattering coefficient, bbp, in the upper ocean layers at a global scale and those observations have a strong potential for the future of ocean color with depth-resolved observations thereby complementing the conventional ocean color remote sensed observations as well as overcoming for some of its limitations. It is critical to evaluate and validate the space-borne lidar measurements for ocean applications as CALIOP was not originally designed for ocean applications. Few validation exercises of CALIOP were published and each exercise designed its own validation protocol. We propose here an objective validation protocol that could be applied to any current and future space-borne lidars for ocean applications.Methods: We, first, evaluated published validation protocols for CALIOP bbp product. Two published validation schemes were evaluated in our study, by using in-situ measurements from the BGC-Argo floats. These studies were either limited to day- or nighttime, or by the years used or by the geographical extent. We extended the match-up exercise to day-and nighttime observations and for the period 2010–2017 globally. We studied the impact of the time and distance differences between the in-situ measurements and the CALIOP footprint through a sensitivities study. Twenty combinations of distance (from 9-km to 50-km) and time (from 9 h to 16 days) differences were tested.Results & Discussion: A statistical score was used to objectively selecting the best optimal timedistance windows, leading to the best compromise in term of number of matchups and low errors in the CALIOP product. We propose to use either a 24 h/9 km or 24 h/15 km window for the evaluation of space-borne lidar oceanic products.

The estimation of depth in optically shallow waters using satellite imagery can be efficient and cost-effective. Active sensors measure the distance traveled by an emitted laser pulse propagating through the water with high precision and accuracy if the bottom peak intensity of the waveform is greater than the noise level. However, passive optical imaging of optically shallow water involves measuring the radiance after the sunlight undergoes downward attenuation on the way to the sea floor, and the reflected light is then attenuated while moving back upward to the water surface. The difficulty of satellite-derived bathymetry (SDB) arises from the fact that the measured radiance is a result of a complex association of physical elements, mainly the optical properties of the water, bottom reflectance, and depth. In this research, we attempt to apply physics-based algorithms to solve this complex problem as accurately as possible to overcome the limitation of having only a few known values from a multispectral sensor. Major analysis components are atmospheric correction, the estimation of water optical properties from optically deep water, and the optimization of bottom reflectance as well as the water depth. Specular reflection of the sky radiance from the water surface is modeled in addition to the typical atmospheric correction. The physical modeling of optically dominant components such as dissolved organic matter, phytoplankton, and suspended particulates allows the inversion of water attenuation coefficients from optically deep pixels. The atmospheric correction and water attenuation results are used in the ocean optical reflectance equation to solve for the bottom reflectance and water depth. At each stage of the solution, physics-based models and a physically valid, constrained Levenberg–Marquardt numerical optimization technique are used. The physics-based algorithm is applied to Landsat Operational Land Imager (OLI) imagery over the shallow coastal zone of Guam, Key West, and Puerto Rico. The SDB depths are compared to airborne lidar depths, and the root mean squared error (RMSE) is mostly less than 2 m over water as deep as 30 m. As the initial choice of bottom reflectance is critical, along with the bottom reflectance library, we describe a pure bottom unmixing method based on eigenvector analysis to estimate unknown site-specific bottom reflectance.

In the days following the passage of Hurricane Ian over the West Florida Shelf, a large plume of calcium carbonate (CaCO3) mud slurry was observed extending from west of the Dry Tortugas and curving to the east into the Straits of Florida. This discreet target offered a unique opportunity to quantify the suspended mass of CaCO3 in the slurry. Estimating the concentration of sediment in a plume of suspended CaCO3 by satellite sensor observations has been stymied up to now owing to a lack of in situ suspended sediment measurements during storm events, as “sea truth” data for such events is difficult to acquire. However, the Particulate Inorganic Carbon (PIC) standard product provided by the NASA Ocean Biology Distributed Active Archive Center (OBDAAC) is based on Moderate Resolution Imaging Spectroradiometer (MODIS) observations of a plume of coccolith chalk released from a ship in the “Chalk-Ex” experiment. Due to the similarities (particle size, mineralogy, and reflectance properties) of the suspended chalk features and the Ian-induced slurry, we utilized this data product to make initial estimates of the concentration of suspended sediment in the plume.

The identification and tracking of ships can be achieved by analyzing laser echo signals from their wakes. A new method for the laser detection of bubble wakes based on multi-timescale hierarchical processing is presented in this paper. It contributes to amplifying the strength of the wake echo while mitigating its nonstationary characteristics. The applicability of the algorithm for bubble wake detection under strong and weak shading effects is verified through combining the bubble cluster distribution with a Monte Carlo simulation. Additionally, the method is tested in a real wake crossing and following detection experiments. The experimental results demonstrate that the signal-to-backscatter ratio and detection rate trends are consistent with the simulation findings. Specifically, the algorithm improves the signal-to-backscatter ratio by an average of 17.35%, and increases the detection rate to an impressive 90.74%. Applying this algorithm enhances the system's effectiveness in detecting bubble wakes. • A new laser detection method for ship bubble wakes based on multi-timescale hierarchical processing is presented in this paper. • The applicability of the method to both single- and multi-cycle echoes is demonstrated by simulations and experiments on the lake. • It contributes to amplifying the strength of the wake echo while mitigating its nonstationary characteristics. • The method can effectively improve the signal-to-backscatter ratio and detection rate under strong and weak shading effects. [ABSTRACT FROM AUTHOR]

Arctic marine ecosystems are strongly influenced by the extreme seasonality of light in the region. Accurate determination of light is essential for building a comprehensive understanding of the dynamics of animal and aquatic algae populations. Current approaches to underwater light field parameterisations rely upon shortwave radiation (300–3000 nm) estimates from satellites or surface radiometry measurements to populate full radiative transfer software. Due to the inaccessibility of many regions in the Arctic, measured data is not widely available. This study presents a model of spectrally resolved underwater light in ice‐free conditions in the Barents Sea. Given a location and time, the model accounts for downwelling spectral irradiance in the photosynthetically active radiation (PAR, 400–700 nm) range (EDPAR) at the ocean surface from solar, lunar, and galactic light sources, modulated by local cloud cover. We demonstrate the ability to extend over the full year into the period of Polar Night, validated in both broadband PAR and spectral domains. Using a bio‐optical model of diffuse attenuation developed for the Barents Sea, we show accurate calculations to depth for inhomogeneous water columns over a spatial‐temporal range, validated against time series irradiance data from the ArcLight observatory in Ny‐Ålesund, Svalbard and in‐situ irradiance sensors deployed in the Barents Sea. Finally, in comparison to state‐of‐the‐art radiative transfer models, averaged over the water column we demonstrate a typical mean absolute error of <1 μmol m−2 s−1 in EDPAR for overcast conditions (<6 μmol m−2 s−1 for clear‐sky) and reduced execution time of factor 20. Plain Language Summary: Marine organisms in the Arctic experience large variations in underwater light levels due to prolonged periods of 24‐hr darkness and 24‐hr light. Since light is a key driver in many ecosystem dynamics, accurate modeling of Arctic marine populations can be challenging due to difficulties in determining light levels. The harsh conditions of the region can make many areas inaccessible, and often light levels fall below the sensitivity limits of widely available commercial radiometers. Additionally, most existing light field models can only predict light when the sun is above the horizon. We present a light field model that operates uninterrupted throughout the full year, able to calculate light fields from the sun above and below the horizon as well as light from the moon. The model determines spectrally resolved underwater light levels in the wavelength range that is important for biological processes. Modeled outputs have been compared and show good agreement with above surface light measurements taken in Ny‐Ålesund as well as underwater measurements recorded in the Barents Sea. Key Points: A fully seasonal model of underwater hyperspectral light in the Barents Sea, able to operate through Polar NightThe model captures below horizon solar irradiance, the magnitude and timing of lunar irradiance, and is validated by in situ dataThe model can be used globally with the provision of an appropriate bio‐optical model for the region of interest [ABSTRACT FROM AUTHOR]

Estimates of the diffuse attenuation coefficient ( K d ) at two different wavelengths and band-integrated (PAR) were obtained using different published algorithms developed for open ocean waters spanning in type from explicit-empirical, semi-analytical and implicit-empirical and applied to data from spectral radiometers on board six different satellites (MODIS-Aqua, MODIS-Terra, VIIRS–SNPP, VIIRS-JPSS, OLCI-Sentinel 3A and OLCI-Sentinel 3B). The resultant K d s were compared to those inferred from measurements of radiometry from sensors on board autonomous profiling floats (BGC-Argo). Advantages of BGC-Argo measurements compared to ship-based ones include: 1. uniform sampling in time throughout the year, 2. large spatial coverage, and 3. lack of shading by platform. Over 5000 quality-controlled matchups between K d s derived from float and from satellite sensors were found with values ranging from 0.01 to 0.67 m − 1 . Our results show that although all three algorithm types provided similarly ranging values of K d to those of the floats, for most sensors, a given algorithm produced statistically different K d distributions from the two others. Algorithm results diverged the most for low K d (clearest waters). Algorithm biases were traced to the limitations of the datasets the algorithms were developed and trained with, as well as the neglect of sun angle in some algorithms. This study highlights: 1. the importance of using comprehensive field-based datasets (such as BGC-Argo) for algorithm development, 2. the limitation of using radiative-transfer model simulations only for algorithm development, and 3. the potential for improvement if sun angle is taken into account explicitly to improve empirical K d algorithms. Recent augmentation of profiling floats with hyper-spectral radiometers should be encouraged as they will provide additional constraints to develop algorithms for upcoming missions such as NASA's PACE and SBG and ESA's CHIME, all of which will include a hyper-spectral radiometer. [ABSTRACT FROM AUTHOR]

Atmospheric correction of remote sensing imagery over optically complex waters is still a challenging task. Even algorithms showing a good accuracy for moderate and extremely turbid waters need to be tested when being used for eutrophic inland basins. Such a test was carried out in this study on the example of a Sentinel-3/OLCI image of the productive waters of the Gorky Reservoir during the period of intense blue-green algal bloom using data on the concentration of chlorophyll a and remote sensing reflectance measured from the motorboat at many points of the reservoir. The accuracy of four common atmospheric correction (AC) algorithms was examined. All of them showed unsatisfactory accuracy due to incorrect determination of atmospheric aerosol parameters and aerosol radiance. The calculated aerosol optical depth (AOD) spectra varied widely (AOD(865) = 0.005 − 0.692) even over a small area (up to 10 × 10 km) and correlated with the measured chlorophyll a. As a result, a part of the high water-leaving signal caused by phytoplankton bloom was taken as an atmosphere signal. A significant overestimation of atmospheric aerosol parameters, as a consequence, led to a strong underestimation of the remote sensing reflectance and low accuracy of the considered AC algorithms. To solve this problem, an algorithm with a fixed AOD was proposed. The fixed AOD spectrum was determined in the area with relatively "clean" water as 5 percentiles of AOD in all water pixels. The proposed algorithm made it possible to obtain the remote sensing reflectance with high accuracy. The slopes of linear regression are close to 1 and the intercepts tend to zero in almost all spectral bands. The determination coefficients are more than 0.9; the bias, mean absolute percentage error, and root-mean-square error are notably lower than for other AC algorithms. [ABSTRACT FROM AUTHOR]

The downwelling irradiance is a crucial part of the air‐sea heat flux and a major energy source for the photosynthesis processes in the upper ocean. The modeling of the irradiance field is often time‐consuming in conventional Monte Carlo (MC) simulations. We propose an accelerated model based on machine learning to significantly reduce the computational cost. By introducing a generalized beam spreading function, we transform the raw data generated with the MC simulation into training data of reduced dimensions, which is then used to develop an artificial neural network. To validate the machine learning model, we use the MC model to simulate the irradiance field under a broadband wave field. For both clear and turbid seawater, the irradiance field predicted by the machine learning model agrees well with the MC simulation result. Compared with the MC simulation that is computationally expensive, our machine learning model is O(1,000) times faster. Plain Language Summary: Sunlight is an important source of energy for aquatic creatures. When sunlight enters the water, it changes the propagating direction and may be absorbed or spread by small particles in the water. While we can reproduce these physical phenomena virtually on computers nowadays, the simulations cost a substantial amount of computing resources and often require a supercomputer. In this study, we develop a method to accelerate the tracking of sunlight propagation in the upper ocean using machine learning. Our deep neural network takes the wave shape information as the input and exports the information needed for constructing the underwater light field. Compared with the traditional technique, our method is over one thousand times faster and may be used on desktop computers. Key Points: A machine‐learning‐based method is proposed to accelerate the Monte Carlo (MC) simulation of oceanic downwelling irradianceThe surface wave modulation effect on the irradiance field is captured by the neural network predictionThe computational speed of the new method is O(1,000) times faster than the conventional MC simulation [ABSTRACT FROM AUTHOR]

The scattering by suspended particles is being measured with increasing frequency in the global oceans. Yet, little is known of size fractioned contribution, particularly from submicron particles and to the polarized scattering. In this study, three Mueller scattering matrix elements, P11, P12, and P22, for the bulk particles and for size fractions

In the past several years, the capabilities of optical tools and in situ imaging devices have greatly expanded and are now revolutionizing the field of plankton research. These tools have facilitated the discovery of new plankton and enhanced the understanding of populations of fragile and gelatinous zooplankton. Imaging devices are becoming more accessible and regularly deployed on oceanographic studies and monitoring efforts. However, despite the increasing use of these tools, there are few studies which offer direct comparisons between in situ imaging devices and traditional-net based methods, especially in open-ocean, oligotrophic systems where plankton are sparser and less intensively sampled. This study compares estimates of mesozooplankton abundance calculated by net-tows and an Underwater Vision Profiler 5 (UVP5HD-DEEP) imaging system. Net tows were conducted with a Multiple Opening and Closing Nets with Environmental Sensing System (MOCNESS) device equipped with 153µm mesh. In total, four tows, each sampling eight distinct depth bins, were conducted aboard two cruises in the Sargasso Sea. Along each cruise, in situ images were collected using an Underwater Vison Profiler 5 (UVP5HD-DEEP). Using these methods, we estimated abundance of different mesozooplankton groups (>0.5 mm). Using established biovolume-biomass conversions, we also estimated the dry mass of certain zooplankton taxa. Furthermore, we address two methods for calculating density and biomass concentration from UVP data. Estimates of mesozooplankton abundance and biomass concentration were generally higher from MOCNESS methods than the UVP estimates across all taxa. It was found that there is not a reliable relationship between UVP estimates and MOCNESS estimates when directly comparing similar depth bins. Nonetheless, when integrating density and biomass concentrations throughout the water column, estimates are not significantly different between the methodology. This study addresses several important considerations for using in situ imaging tools and how to reconcile findings with traditional net-based methods.

Particulate volume scattering function (VSF), especially at angles larger than 170°, is of particular importance for interpreting ocean optical remote sensing signals and underwater imagery. In this study, a laboratory-based VSF instrument (VSFlab) adopting the periscopic optical system was developed to obtain VSF measurements from 1°–178.5°. In the VSFlab, a new prism design that simply combines a single prism and a neutral density filter was proposed to more efficiently reduce the stray light in the backward direction, while a detailed calibration procedure was given. A full validation based on standard beads of various sizes and a comparison with the results from LISST-VSF and POLVSM indicated that the VSFlab can provide reliable results from 1° to 178.5°. VSFlab measurements in the East China Sea (ECS) exhibited a moderate increase (not more than 5 times) in VSF from 170° to 178.5° rather than a sharp increase of more than one order of magnitude presented in other instrument results measured in other coastal regions. The estimates of the particulate backscattering coefficient using single angle scattering measurements near 120° or 140° and suitable χp were justified. Two types of the VSFs with different size distribution and shape parameters in the ECS can be distinguished based on the variability of χp after 155°. The measured VSF could provide a basis for the parameterization of VSF in the radiative transfer model and the variability of χp in the backward direction had the potential to be used to characterize the particles in the coastal region of the ECS. [ABSTRACT FROM AUTHOR]

The Preisendorfer and Mobley Monte Carlo model is a classical photon-rough sea surface interaction model that is used to study the reflectance and transmittance properties of the wind-driven sea surface. In this paper, we develop a computational framework and the implementation for parallel processing of this model by using Message Passing Interface. We then analyze the correspondence between serial and parallel results and the speedup of the proposed algorithm on a single personal computer and computers cluster. The results indicate that achieved speedup is slightly lower than the linear speedup, and the parallel efficiency is slowly decreased by increasing the number of processes. Compared to a serial code, the relative differences of irradiance are all lower than 2.5%, and the relative differences of radiance are below 2.5% for air-incident source and below 10% for underwater source. [ABSTRACT FROM AUTHOR]

Summary: Data from MERIS onboard Envisat and MODIS onboard Terra and Aqua for 15–16 May 2010 were used to study powerful imprints of atmospheric gravity waves (AGWs) on the western part the Black Sea surface. Two cold fronts crossed the sea following the warm front and caused the AGWs which modulated the sea surface. Imprints of AGWs appeared as stripes of alternating brightness, they had crest length more than a hundred kilometers and wavelength of units of kilometers. Wave amplitude of AGWs imprints, evaluated by a 90%-depth of light penetration into the sea at 490 nm z90, the value inverse to the diffuse attenuation coefficient Kd_490, was units of decimeterxs. MODIS 250-m data of remote sensing reflectance, wind components and atmospheric pressure near the sea surface were obtained by processing the top of atmosphere data with the SeaDAS software package. Negative correlations of fluctuations of z90 with fluctuations of wind stress and atmospheric pressure were found on the transects of more than ten kilometers. The impact of wind stress on the origination of AGW imprints was found to be determinant, while the impact of atmospheric pressure was not more than units of percent.

We exhibit a proof-of-concept laboratory study for inversion of the partial Mueller scattering matrix of hydrosols from polarimetric observations across a smooth Fresnel boundary. The method is able to derive the 9 Mueller matrix elements relating to linear polarization for scattering angles between 70 and 110°. Unlike prior studies of this nature, we utilize measurements from a hyper-angular polarimeter designed for passive remote sensing applications to derive the Mueller matrix, and tailor the polarimetric data reduction approach accordingly. We show agreement between the inversion results and theoretical Mueller matrices for Rayleigh scattering and Mie theory. The method is corroborated by measurements made with a commercial LISST-VSF instrument. Challenges and opportunities for use of the technique are discussed.

Light penetration through the ocean creates underwater light color niches and photosynthetic organisms use specific strategies to capture light in these niches. The selection pressure for some cyanobacteria strains in the genus Synechococcus that change color to absorb either blue or green light (chromatic acclimaters, or generalists) is not well understood. Here, we tested the hypothesis that changes in ocean spectra brought about by mixing preferentially selects for generalists within a Synechococcus population. We investigated ocean conditions that led to high proportions of Synechococcus generalists versus specialists in a model ocean column, and compared simulations with in situ metagenomic and physical oceanographic data from major Bio‐GO‐SHIP cruises, supplemented with GEOTRACES and TARA Oceans, as well as the GOOS Argo Program and sea surface height from AVISO. We found that greater mixed layer depths selected for generalists in simulated Synechococcus populations, but did not account for much of the variance in the partitioning of light‐harvesting strategies in situ. Rather, oceanographic signatures for upwelling areas and ocean fronts explained more of the variation between Synechococcus generalists and specialists in the ocean. Our results motivate further study of the in situ light environments of upwelling zones and ocean fronts, which are currently understudied as potential light‐driven niche habitats. Plain Language Summary: The variety of pigments used by cyanobacteria to capture light for photosynthesis increases the colors of light available for use in the ocean. Some members of the cyanobacterial genus, Synechococcus, can change color to absorb either blue or green light (generalists), adding to the variety of light‐harvesting strategies. Though the reason for this color change is believed to be fluctuations in the underwater blue/green light field, this has not been tested directly. Using a mathematical model of the ocean column, we find the highest percentages of generalists in the Synechococcus population in deep ocean mixed layers. Comparison of model results to actual distributions of generalists indicate that deep mixing plays a smaller role than our model suggested, and that upwelling zones, where water is vertically moved to the surface, and ocean fronts, where major ocean currents meet, are also important habitats for Synechococcus generalists in the ocean. Key Points: Despite high correlation with modeled deep mixing, Synechococcus blue‐green acclimaters do not correlate with open ocean mixed layer depthsA high percentage of Synechococcus chromatic acclimaters correlate with low surface temperatures and low sea surface heightA high percentage of Synechococcus chromatic acclimaters are observed along paths of major ocean fronts, and upwelling zones [ABSTRACT FROM AUTHOR]

Internal waves generated by the movement of surface and subsurface vehicles in the ocean have specific importance in maritime applications. These types of waves are categorized as forced internal waves. In this article, an attempt using a novel optical method is made to study the forced internal waves that are generated by a large surface vehicle in a controlled sea exercise. The optical method uses a diode laser operating at 635 nm and a lateral-effect position-sensitive photodetector. The laser beam undergoes modulation in both its intensity and beam positions with respect to the density variations that are caused in the stratified ocean by the forced internal waves. The experimental scheme, the system aspect of the optical method, and supporting theoretical aspects are detailed with corroborating experimental results. It is observed that the frequency of the forced internal waves also remains within the band of naturally occurring ambient oscillations in the ocean. The obtained results indicate that the forced internal waves detected by the optical method can be used for detecting the movement of maritime vehicles in the ocean. [ABSTRACT FROM AUTHOR]

Estimates of the diffuse attenuation coefficient (Kd) at two different wavelengths and band-integrated (PAR) were obtained using different published algorithms developed for open ocean waters spanning in type from explicit-empirical, semi-analytical and implicit-empirical and applied to data from spectral radiometers on board six different satellites (MODIS-Aqua, MODIS-Terra, VIIRS–SNPP, VIIRS-JPSS, OLCI-Sentinel 3A and OLCI-Sentinel 3B). The resultant Kds were compared to those inferred from measurements of radiometry from sensors on board autonomous profiling floats (BGC-Argo). Advantages of BGC-Argo measurements compared to ship-based ones include: 1. uniform sampling in time throughout the year, 2. large spatial coverage, and 3. lack of shading by platform. Over 5000 quality-controlled matchups between Kds derived from float and from satellite sensors were found with values ranging from 0.01 to 0.67 m−1. Our results show that although all three algorithm types provided similarly ranging values of Kd to those of the floats, for most sensors, a given algorithm produced statistically different Kd distributions from the two others. Algorithm results diverged the most for low Kd (clearest waters). Algorithm biases were traced to the limitations of the datasets the algorithms were developed and trained with, as well as the neglect of sun angle in some algorithms. This study highlights: 1. the importance of using comprehensive field-based datasets (such as BGC-Argo) for algorithm development, 2. the limitation of using radiative-transfer model simulations only for algorithm development, and 3. the potential for improvement if sun angle is taken into account explicitly to improve empirical Kd algorithms. Recent augmentation of profiling floats with hyper-spectral radiometers should be encouraged as they will provide additional constraints to develop algorithms for upcoming missions such as NASA’s PACE and SBG and ESA’s CHIME, all of which will include a hyper-spectral radiometer.

While recent research has provided increasing insight into ocean ecosystem functions and rapidly improving predictive ability, it has become clear that for some key processes, including grazing by zooplankton, there simply is no currently available instrumentation to quantify relevant stocks and rates, remotely or in situ. When measurement capacity is lacking, collaborative research between instrument manufacturers and researchers can bring us closer to addressing key knowledge gaps. By necessity, this high risk, high rewards research will require iterative steps from best case scenarios under highly controlled and often artificial laboratory conditions to empirical verification in complex in situ conditions with diverse biota. To illustrate our point, we highlight the example of zooplankton grazing in marine planktonic food webs. Grazing by single-celled zooplankton accounts for the majority of organic carbon loss from marine primary production but is still measured with logistically demanding, point-sample incubation methods that result in reproducible results but at insufficient resolution to adequately describe temporal and spatial dynamics of grazer induced impacts on primary production, export production and the annual cycle of marine plankton. We advance a collaborative research and development agenda to eliminate this knowledge gap. Resolving primary production losses through grazing is fundamental to a predictive understanding of the transfer of matter and energy through marine ecosystems, major reservoirs of the global carbon cycle.

The suspended particulate matter (SPM) concentration (unit: mg l-1) in surface waters is an essential measure of water quality and clarity. Satellite remote sensing provides a powerful tool to derive the SPM with synoptic and repeat coverage. In this study, we developed a new global SPM algorithm utilizing the remote sensing reflectance (Rrs(λ)) at near-infrared (NIR), red, green, and blue bands (NIR-RGB) as input. The evaluations showed that the NIR-RGB algorithm could predict SPM with the median absolute percentage difference of ~35%-39% over a wide range from ~0.01 to >2,000 mg l-1. The uncertainty is smaller (29%-37%) for turbid waters where Rrs(671) ≥ 0.0012 sr-1 and slightly higher (41%-44%) for clear waters where Rrs(671) < 0.0012 mg l-1. The algorithm was implemented with the global Rrs(λ) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. We provided a brief characterization of the spatial distribution and temporal trends of the SPM products in global waters based on the monthly SPM composites. Case studies of the SPM time series in coastal and inland waters suggest that the satellite SPM estimations registered spatial and seasonal variation and episodic events in regional scales as well. The VIIRS-generated global SPM maps provide a valuable addition to the existing ocean color products for environmental and climate applications. [ABSTRACT FROM AUTHOR]

This study investigated how ocean optical properties and solar attenuation may affect the upper ocean temperature structure and ocean heat content (OHC). We employed a realistic three‐dimensional ocean circulation model for the northwestern Atlantic to simulate ocean states during the active Atlantic hurricane season of 2017. Sensitivity experiments were performed by coupling the ocean circulation prediction with either a conventional water type‐based solar attenuation model or an inherent optical properties (IOP)‐based model. Validations against in‐situ ocean temperature observations and remote sensing‐derived OHC showed that ocean simulations using the IOP‐based model outperformed simulations using the conventional water type‐based model in predicting sea surface temperature, upper ocean thermal structure, and OHC. An OHC‐hurricane intensity relationship derived for five major hurricanes in 2017 suggests that the ocean optical properties and the application of an appropriate solar attenuation model are important for the forecast of hurricane intensity. Plain Language Summary: In this study, we examined how solar attenuation affects the upper ocean temperature structure and ocean heat content. We employed a realistic three‐dimensional ocean circulation model for the northwestern Atlantic to simulate ocean conditions during the active Atlantic hurricane season of 2017. Model experiments were performed by coupling the circulation simulation with either the conventional water type‐based solar attenuation model or an inherent optical properties (IOP)‐based model. We found that the type of solar attenuation scheme used has a significant effect on the model's ability to predict sea surface temperature, upper thermal structure, ocean heat content, and hurricane intensity. The experiments using the IOP‐based model outperformed those using water type‐based model. Our study highlights the importance of adopting IOP products from ocean color satellites and the IOP‐based solar attenuation model in ocean prediction and storm forecasting. Key Points: The selection of solar attenuation scheme has a significant effect on predictions of ocean heat content and hurricane intensityModel experiments using the IOP‐based solar attenuation scheme along with satellite observations significantly improve model performanceOur study highlights the importance of adopting the IOP‐based solar attenuation scheme and IOP products in storm forecasting [ABSTRACT FROM AUTHOR]

Aiming at the problem of image distortion caused by light refraction during underwater imaging, and the conversion error caused by existing image conversion algorithms due to neglecting the secondary refraction of light, an underwater image conversion algorithm based on the light refraction model is proposed in this paper. The algorithm firstly obtains the pixel information of the underwater image, then calculates the corresponding coordinate information of the pixel points in the equivalent air image through the mapping relationship, and finally obtains the equivalent air image through image interpolation. Experimental results shows, compared with the existing image conversion algorithms, the proposed algorithm reduces the average error of u direction from 2.289 5 to 1.213 3, which is a decrease of 47.01%. The average error of v direction is reduced from 3.252 5 to 1.526 3, which is a decrease of 53.07%. At the same time, the mean value of ranging error was reduced from 58.83 mm to 28.88 mm, a decrease of 50.91%。

The spectra of sea reflectance coefficients, measured remotely from a ship in the region of the Urals oil spill, in the form of emulsion and individual films, have been analyzed. The pollution was detected in the Bering Sea near Cape Navarin on August 4, 2013, during the voyage of the Professor Khlyustin training ship. In situ flow-through fluorometric measurements of concentrations of the chlorophyll a and colored dissolved organic matter at a depth of 4 m, where the contamination effect was not detected, were used. The regression relations between remote and in situ measurements in clear and oil-polluted waters are analyzed. The preliminary technique is developed for detecting sea surface oil pollution, which is in emulsified form and in the form of small films about 1 m2 in area, using remote measurements of the seawater reflectance spectra. [ABSTRACT FROM AUTHOR]

Satellite ocean color remote sensing is the primary method to retrieve synoptic measurements of the optical properties of the ocean on large spatial and regular time scales. Through bio-optical modeling, changes in ocean color spectra can be linked to changes in marine ecosystem and biogeochemical properties. Bio-optical algorithms rely on assumptions about the covariance of marine constituents as well as the relationships among their inherent and apparent optical properties. Validation with in situ measurements of in-water constituents and their optical properties is required to extrapolate local knowledge about ocean color variations to global scales. Here, we evaluate seasonal and spatial relationships between optical constituents and their inherent and apparent optical properties throughout the annual cycle of the North Atlantic plankton bloom using bio-optical data from four cruises conducted as part of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). Our results show ocean color variability, quantified using field observations of the remote sensing reflectance spectrum at each NAAMES station, is driven by colored dissolved organic matter (CDOM) absorption in the ultraviolet wavelengths, phytoplankton absorption in the blue wavelengths, and total particulate backscattering in the green wavelengths. Results from a recently storm-mixed station at the height of the spring bloom demonstrate that significant changes in bio-optical properties can occur on daily scales. By testing the effects of variations in lighting conditions and solar geometries, we also demonstrate that, for this data set, remote sensing reflectance should be considered a quasi-inherent optical property. We find that the temporal and spatial chlorophyll concentrations and the magnitudes of inherent optical properties can be accurately assessed using previously published ocean color algorithms. However, changes in the spectral slopes of the inherent optical properties are often poorly retrieved, indicating the need for improvements in the retrieval of optical constituent composition. The characterization of such a dynamic environment provides beneficial insights for future bio-optical algorithms.

Particulate volume scattering function (VSF), especially at angles larger than 170°, is of particular importance for interpreting ocean optical remote sensing signals and underwater imagery. In this study, a laboratory-based VSF instrument (VSFlab) adopting the periscopic optical system was developed to obtain VSF measurements from 1°–178.5°. In the VSFlab, a new prism design that simply combines a single prism and a neutral density filter was proposed to more efficiently reduce the stray light in the backward direction, while a detailed calibration procedure was given. A full validation based on standard beads of various sizes and a comparison with the results from LISST-VSF and POLVSM indicated that the VSFlab can provide reliable results from 1° to 178.5°. VSFlab measurements in the East China Sea (ECS) exhibited a moderate increase (not more than 5 times) in VSF from 170° to 178.5° rather than a sharp increase of more than one order of magnitude presented in other instrument results measured in other coastal regions. The estimates of the particulate backscattering coefficient using single angle scattering measurements near 120° or 140° and suitable χp were justified. Two types of the VSFs with different size distribution and shape parameters in the ECS can be distinguished based on the variability of χp after 155°. The measured VSF could provide a basis for the parameterization of VSF in the radiative transfer model and the variability of χp in the backward direction had the potential to be used to characterize the particles in the coastal region of the ECS.

The Monte Carlo method is used to solve the nonstationary laser sensing equation for a multicomponent optically dense water medium taking into account the influence of the water-air interface and the contributions of multiple radiation scattering by sea water and of the signal reflection from the sea bottom. Dependences of the signal power recorded with a monostatic lidar equipped with a time-of-flight matrix single-photon avalanche diode (SPAD) photodetector on the water depth and surface microwaves for different field-of-view angles of the receiver are obtained. Results of investigations have shown that the maximum depth of sea bottom detection is 40–50 m given that the optical water thickness does not exceed 3.5–4 m. The dynamic range of lidar signals from water reaches 7–9 orders of magnitude for lidar sensing of sea bottom at limiting depths of 40–50 m in very transparent water in the presence of the Fresnel reflection from the water surface. Results of statistical simulation have shown that the lidar system with the matrix receiver intended for sea water sensing can be realized at the modern technical level. Under favorable conditions, the lidar return signal power provides sensing of sea bottom to depths of 40–50 m. [ABSTRACT FROM AUTHOR]

Copyright of Dokuz Eylul University Muhendislik Faculty of Engineering Journal of Science & Engineering / Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi is the property of Dokuz Eylul Universitesi Muhendislik Fakultesi Fen ve Muhendislik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modeling of radiation characteristics of semitransparent media containing particles or bubbles in the independent scattering limit is examined. The existing radiative properties models of a single particle in an absorbing medium using the approaches based on (1) the classical Mie theory neglecting absorption by the matrix, (2) the far field approximation, and (3) the near field approximation are reviewed. Comparison between models and experimental measurements are carried out not only for the radiation characteristics but also for hemispherical transmittance and reflectance of porous fused quartz. Large differences are found among the three models predicting the bubble radiative properties when the matrix is strongly absorbing and/or the bubbles are optically large. However, these disagreements are masked by the matrix absorption during calculation of radiation characteristics of the participating medium. It is shown that all three approaches can be used for radiative transfer calculations in an absorbing matrix containing bubbles.

The Biogeochemical-Argo program (BGC-Argo) is a new profiling-float-based, ocean wide, and distributed ocean monitoring program which is tightly linked to, and has benefited significantly from, the Argo program. The community has recommended for BGC-Argo to measure six additional properties in addition to pressure, temperature and salinity measured by Argo, to include oxygen, pH, nitrate, downwelling light, chlorophyll fluorescence and the optical backscattering coefficient. The purpose of this addition is to enable the monitoring of ocean biogeochemistry and health, and in particular, monitor major processes such as ocean deoxygenation, acidification and warming and their effect on phytoplankton, the main source of energy of marine ecosystems. Here we describe the salient issues associated with the operation of the BGC-Argo network, with information useful for those interested in deploying floats and using the data they produce. The topics include float testing, deployment and increasingly, recovery. Aspects of data management, processing and quality control are covered as well as specific issues associated with each of the six BGC-Argo sensors. In particular, it is recommended that water samples be collected during float deployment to be used for validation of sensor output.

In ocean remote sensing, the backscattered light received by optical remote sensor carries the light information of the ocean itself. Ocean optical remote sensing is closely related to the spectral characteristics of water body. Ocean spectral characteristics are the basic research and application of ocean remote sensing. The two sensors have a small bandwidth and a bandwidth of 50 to 100 nanometres. In this paper, the spectral structure of the ocean is studied by measurements means and ocean hyperspectral characteristics. It can be found that the changes of offshore body optical parameters can be understood by the spectral characteristic components experiments with different materials in sea water. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A high degree of consistency and comparability among chlorophyll algorithms is necessary to meet the goals of merging data from concurrent overlapping ocean color missions for increased coverage of the global ocean and to extend existing time series to encompass data from recently launched missions and those planned for the near future, such as PACE, OLCI, HawkEye, EnMAP and SABIA-MAR. To accomplish these goals, we developed 65 empirical ocean color (OC) chlorophyll algorithms for 25 satellite instruments using the largest available and most globally representative database of coincident in situ chlorophyll a and remote sensing reflectances. Excellent internal consistency was achieved across these OC 'Version -7' algorithms, as demonstrated by a median regression slope and coefficient of determination (R2) of 0.985 and 0.859, respectively, among 903 pairwise comparisons of OC-modeled chlorophyll. SeaWiFS and MODIS-Aqua satellite-to- in situ match-up results indicated equivalent, and sometimes superior, performance to current heritage chlorophyll algorithms. During the past forty years of ocean color research the violet band (412 nm) has rarely been used in empirical algorithms to estimate chlorophyll concentrations in oceanic surface water. While the peak in chlorophyll-specific absorption coincides with the 443 nm band present on most ocean color sensors, the magnitude of chlorophyll-specific absorption at 412 nm can reach upwards of ~70% of that at 443 nm. Nearly one third of total chlorophyll-specific absorption between 400 and 700 nm occurs below 443 nm, suggesting that bands below 443 nm, such as the 412 nm band present on most ocean color sensors, may also be useful in detecting chlorophyll under certain conditions and assumptions. The 412 nm band is also the brightest band (that is, with the most dominant magnitude) in remotely sensed reflectances retrieved by heritage passive ocean color instruments when chlorophyll is less than ~0.1 mg m−3, which encompasses ~24% of the global ocean. To attempt to exploit this additional spectral information, we developed two new families of OC algorithms, the OC5 and OC6 algorithms, which include the 412 nm band in the MBR. By using this brightest band in MBR empirical chlorophyll algorithms, the highest possible dynamic range of MBR may be achieved in these oligotrophic areas. The terms oligotrophic, mesotrophic, and eutrophic get frequent use in the scientific literature to designate trophic status; however, quantitative definitions in terms of chlorophyll levels are arbitrarily defined. We developed a new, reproducible, bio-optically based index for trophic status based on the frequency of the brightest, maximum band in the MBR for the OC6_SEAWIFS algorithm, along with remote sensing reflectances from the entire SeaWiFS mission. This index defines oligotrophic water as chlorophyll less than ~0.1 mg m−3, eutrophic water as chlorophyll a bove 1.67 mg m−3 and mesotrophic water as chlorophyll between 0.1 and 1.67 mg m−3. Applying these criteria to the 40-year mean global ocean chlorophyll data set revealed that oligotrophic, mesotrophic, and eutrophic water occupy ~24%, 67%, and 9%, respectively, of the area of the global ocean on average. • 65 empirical chlorophyll algorithms for 25 ocean color satellites were developed. • All algorithms achieved excellent internal consistency across satellite instruments. • Additional spectral information improves chlorophyll algorithm signal-to-noise. • Ocean color radiometry provides a reproducible bio-optical index for trophic status. [ABSTRACT FROM AUTHOR]