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While ecosystem health is improving in many estuaries worldwide following nutrient reductions, inconsistent trends in water clarity often remain. The Chesapeake Bay, a eutrophic estuary with a highly populated watershed, is a crucial testbed for these concerns. Improved efforts are needed to understand why some measurements of downstream estuarine water clarity appear to be uncorrelated with watershed management actions, and multiple metrics of clarity are needed to address this issue. To complement in situ measurements, satellite remote sensing provides an additional tool with which to assess long‐term change in water clarity. In this study, remote sensing reflectance (Rrs) from the Moderate Resolution Imaging Spectroradiometer on satellite Aqua was evaluated from 2003 to 2020 at multiple wavelengths for surface waters of the Chesapeake Bay. Trends show an overall long‐term decrease in Rrs in the upper estuary for all wavelengths, yet an increase in Rrs in the lower estuary for green wavelengths. Trends in band ratios show long‐term decreasing red‐to‐green and red‐to‐blue ratios, yet long‐term increasing green‐to‐blue ratios. Seasonally, trends in band ratios were relatively consistent throughout the year and along‐estuary, whereas single band reflectance trends varied seasonally and along‐estuary. In the lower Bay, Septembers showed the strongest decreasing trends in red reflectance, while early spring and summer had the most pronounced increasing trends in green reflectance. These trends suggest that the system has experienced a long‐term reduction in suspended solids concentration and light attenuation without a systematic reduction in chlorophyll‐a concentration. Plain Language Summary: In many estuaries around the world, waters have become less clear over time because of nutrient and sediment pollution. Watershed management efforts on land have reduced the delivery of nutrient and sediment from specific regions in recent decades. Through these efforts, some estuaries are showing improvements such as more seagrass and higher oxygen levels; however, the water does not always appear clearer. The Chesapeake Bay is one such place where not all measurements of water clarity show improvement, even though the ecosystem is recovering. Satellites provide snapshots of surface water color, covering large areas with frequent repeats in time. From 2003 to 2020, we analyzed long‐term trends in surface water reflectance, or the brightness of the light coming from water at specific colors of visible light. We also analyzed the change over time in ratios between reflectance at different colors, or reflectance ratios. Reflectance ratios are often used to estimate common water quality variables, such as light attenuation, chlorophyll pigment concentration, and particle concentration. Our results show that there has been a decrease in red‐to‐green and red‐to‐blue reflectance ratios, suggesting improving water clarity over time in most of the Bay. However, increasing green‐to‐blue reflectance ratios suggest increasing chlorophyll concentration. Key Points: Since 2003, MODIS‐Aqua red‐to‐green and red‐to‐blue band ratios decreased, suggesting improving water clarity from the early 2000s to 2020Green reflectance and green‐to‐blue band ratios increased in the lower Bay, suggesting larger contribution of phytoplankton since 2003Trends in ratios were more seasonally and spatially (upper vs. lower Bay) consistent than were trends in absolute reflectances [ABSTRACT FROM AUTHOR]

The Andaman Sea has been a classic study region for internal solitary waves (ISWs) for several decades, and extraordinarily large ISWs are characteristic of the Andaman Sea in the Indian Ocean. This paper presents results on the estimation of the propagation velocity of ISWs in the Andaman Sea that were tracked using 195 image pairs acquired by MODIS National Aeronautics and Space Administration (NASA) Terra/Aqua satellites between January 2014 and December 2018. A total of 562 ISWs were identified during the period, and the results of the propagation velocity distribution of ISWs in the Andaman Sea are presented. The estimated propagation velocity of ISWs agrees well with the theoretical results derived from the Korteweg-de Vries (KdV) equation using monthly climatology stratification data and local bathymetry. The ISW propagation velocity decreases as they propagate from deep to shallow water; the maximum propagation velocity of 3.27 m/s was estimated on the western side of the Nicobar Islands and minimum speed of 0.54 m/s occurred in the shallow water region of the southeastern Andaman Sea. The results show that the ISW propagation characteristics differ in the northern, central, and southern regions of the Andaman Sea. In the northern Andaman Sea, the velocity of ISWs propagating westward was greater than that of ISWs propagating eastward at the same water depth. In the central Andaman Sea, the propagation velocity of the ISWs differed over a small area at a depth of 2 500 m, and the velocity of ISWs in the deep mixing layer in winter was higher than that in the shallow mixing layer in spring. Monthly variations in ISW propagation velocity were analyzed in the southern Andaman Sea, and the velocity of ISWs differed greatly in shallow water and was not significantly different in deep water. Water depth and monthly stratification play vital roles in controlling the phase speed of ISWs in the Andaman Sea. This study will provide a basis for the propagation and prediction of ISWs in the Andaman Sea. [ABSTRACT FROM AUTHOR]

Sea ice in the Weddell Sea plays important roles in the albedo, air-sea heat, freshwater, and gas exchanges and the formation of the Antarctic Bottom Water on the continental shelf that regulates global climate through deep thermohaline circulation. Sea ice extent (SIE) in the Weddell Sea does not show any significant trend in the four-decade satellite observation period but does experience large interannual-to-decadal variability. Physical processes underlying this variability are difficult to examine because of a paucity of prolonged observations. Using a coupled general circulation model, we corroborate the observational finding that decadal increases in SIE are preceded by weakening of the mean westerly winds linked to the Southern Annular Mode. Weakening of the westerly winds over the Weddell Sea reduces the northward Ekman current and suppresses upwelling of warm water from the subsurface ocean; this lowers the upper-ocean temperature, causing an increase in sea ice. In a sensitivity experiment where the interannual sea surface temperature variations are suppressed outside the South Atlantic and the Weddell Sea, decadal increase in the SIE over the Weddell Sea is induced by a decrease in the upper-ocean temperature owing to enhanced horizontal advection by the Weddell Gyre. The strengthening of the Weddell Gyre increases the upper-ocean salinity as a result of enhanced evaporation and brine rejection associated with the sea ice increase. These results demonstrate that both the remote atmospheric forcing and local ice-ocean interaction are crucial for generation of decadal sea ice variability in the Weddell Sea. [ABSTRACT FROM AUTHOR]

The operational Potential Fishing Zone (PFZ) advisory generated and disseminated by the ESSO-Indian National Centre for Ocean Information Services has a significant impact on the livelihood of coastal community of India. PFZs are identified as the relatively narrow zones in the ocean where horizontal gradients of physical and/or biological properties are enhanced. The advisories are provided to fishermen on a daily basis using remotely sensed sea surface temperature (SST) and chlorophyll-a (Chl-a) data from NOAA-AVHRR and MODIS-AQUA and/or Oceansat-2 satellites, respectively. Sometimes it becomes a major challenge to retrieve SST/Chl-a data from satellite images, particularly during the extensive cloud coverage. To overcome this operational difficulty, the satellite data is replaced by a coupled physical-biogeochemical model data capable of simulating ocean features leading to PFZs. The use of model data provides an additional advantage towards transforming the existing service from advisories to forecast. The average length of PFZs identified from satellite (model) data (2010–2016) for off Gujarat is 27.80 ± 7.2 km (33.07 ± 3.2 km) whereas for off Andhra Pradesh, it is 28.27 ± 10.9 km (52.48 ± 8.7 km). Considering the capability of the model in identifying PFZs, the existing advisory service can be transitioned into a short term PFZ forecast. [ABSTRACT FROM AUTHOR]

Pelagic Sargassum is abundant in the Sargasso Sea, but a recurrent great Atlantic Sargassum belt (GASB) has been observed in satellite imagery since 2011, often extending from West Africa to the Gulf of Mexico. In June 2018, the 8850-kilometer GASB contained >20 million metric tons of Sargassum biomass. The spatial distribution of the GASB is mostly driven by ocean circulation. The bloom of 2011 might be a result of Amazon River discharge in previous years, but recent increases and interannual variability after 2011 appear to be driven by upwelling off West Africa during boreal winter and by Amazon River discharge during spring and summer, indicating a possible regime shift and raising the possibility that recurrent blooms in the tropical Atlantic and Caribbean Sea may become the new norm. [ABSTRACT FROM AUTHOR]

Spectral properties near the dominant wave region influence significantly the surface roughness relevant to ocean remote sensing employing low-frequency microwave sensors. The critical parameters characterizing dominant waves are wind speed and dimensionless spectral peak frequency, which is the inverse wave age. The dimensionless spectral peak frequency can be expressed as an equivalent dimensionless fetch or duration. The connection between dominant waves and surface roughness is the spectral slope. This paper presents a surface wave spectral model designed for low-frequency microwave remote sensing, with special emphasis on tropical cyclone (TC) applications. The key elements of the spectral model are: 1) a general spectral function with coefficients accommodating a variable spectral slope and 2) a parametric function connecting the spectral slope and wind speed, which is established with the mean square slope (MSS) observations obtained inside hurricanes by the global positioning system reflectometry technique. In order to make use of the MSS observations inside hurricanes, parametric models of the spatial distributions of wind speed and dimensionless spectral peak frequency inside TCs are developed. The parametric models are based on the wind and wave similarity relationships derived from analyses of hurricane hunter measurements. [ABSTRACT FROM AUTHOR]

Knowledge of particulate organic carbon export flux (EP) is the key to understanding the marine biological carbon pump. In this study, a satellite remote sensing algorithm based on the food‐web model established by Siegel et al. (2014; https://doi.org/10.1002/2013GB004743) was used to estimate EP in the northern South China Sea (NSCS), which consists of direct sinking flux of large phytoplankton and associated aggregates by gravity and flux of zooplankton feces by grazing. This is the first time that fine spatiotemporal variation of satellite‐derived EP in the NSCS is unveiled. Compared with the results on 1° spatial scale products, the model results based on the satellite products with 1/3° and 1/12° resolutions showed better consistency with the observations. Validation with in situ EP showed that the model exhibited a good performance in the NSCS basin, but the predicted EP in the shelf regions were smaller compared with measurements. The satellite‐derived annual‐mean EP in the shelf areas was 8.47 and 5.56 mmol C·m−2·d−1 in the NSCS basin, on the 1/3° spatial scale, with relative differences from observations were about −50% and −15% for the shelf and basin, respectively. The flux of feces from zooplankton grazing, especially that from microzooplankton grazing, might account for the major fraction of the EP in the NSCS. Accurate products of ocean net primary production and empirical coefficients in the food web (e.g., export efficiency of zooplankton grazing and specific mortality rate of nongrazing phytoplankton) suitable for the NSCS, are essential for performance improvement of the satellite‐based EP model. Plain Language Summary: The ocean has the largest inventory of active cycling carbon in the Earth's system. At present, the global ocean absorbs about 2 billion tons of CO2 from the atmosphere every year, accounting for about one fourth of the world's annual CO2 emissions. By converting inorganic carbon into organic carbon and exporting particulate organic carbon to the deep ocean, where it can be sequestered on time scales ranging from seasons to centuries, the biological carbon pump is essential for carbon sequestration in the ocean. However, the regulatory mechanism of the biological carbon pump is complex, and remains poorly understood, especially in the marginal seas. In this study, a food‐web model established by Siegel et al. (2014; https://doi.org/10.1002/2013GB004743) was used to estimate the particulate organic carbon export flux in the northern South China Sea. This is the first time the fine spatiotemporal variation of satellite‐derived POC export flux in the northern South China Sea is unveiled. In addition, based on the model results, we found that the flux of feces from microzooplankton grazing plays an important role in regulating the particulate organic carbon export in the northern South China Sea. Key Points: Satellite‐based food web model of POC flux shows good performance in the basin of NSCSFine spatiotemporal distribution of satellite‐derived POC export in the NSCS is shown for the first timeOPP and transfer efficiency of microzooplankton grazing to POC export are the most significant factors in regulating POC export in the NSCS [ABSTRACT FROM AUTHOR]

Skillful Arctic Sea ice prediction is becoming increasingly important because of its societal, industrial, and economic impacts over the polar regions and potential influence on lower-latitude weather and climate variability. In this work, we evaluate the multiweek forecast skill of Arctic sea ice using the Climate Forecast System, version 2 (CFSv2). To the authors' knowledge, this is the first effort to diagnose and assess the skill of multiweek Arctic sea ice prediction from a coupled atmosphere–ocean model. Analysis of a suite of retrospective 45-day forecasts spanning 1999–2015 shows that CFSv2 captures general features of sea ice concentration (SIC) variability. Total SIC variability is dominated by interannual variability, which accounts for more than 60% of the total variance. Submonthly variability accounts for 29% of the total variance in December, 20% in March and June, and 12.5% in September. We assess the ability of CFSv2 to predict the pan-Arctic SIC, as well as regional SIC in nine Arctic regions. Results show that the SIC prediction skill is highly region dependent (e.g., higher prediction skill for Kara/Barents Seas and lower for the Canadian Archipelago). Overall, the maximum anomaly correlation coefficient (ACC) of SIC for both melt and freeze-up seasons is near the marginal zones, and their spatial distribution shows a relationship with the distribution of the variance. If the ACC of 0.5 is taken as the critical value for skillful prediction, the predictability of weekly SIC near the marginal zones is about 5–6 weeks. Prediction skill for Arctic sea ice extent is above 0.6 for the entire six target weeks and has a large contribution from interannual variability. [ABSTRACT FROM AUTHOR]

Arctic sea-ice is declining in extent, leaving coastlines exposed to more storm-wave events. There is an urgent need to understand how these changes affect geomorphic processes along Arctic coasts. Here we describe spatial and temporal patterns of shoreline changes along two geomorphologically distinct, storm-wave dominated reaches of the Chukchi Sea coastline over the last 64 years. One study area encompasses the west- to southwest-facing, coarse-clastic shoreline and ice-rich bluffs of Cape Krusenstern (CAKR). The other covers the north-facing, sandy shorelines on barrier islands, ice-rich bluffs, and the Cape Espenberg spit in the Bering Land Bridge National Park (BELA). Both study areas lie within the zone of continuous permafrost, which exists both on and offshore and outcrops as ice-rich bluffs along the BELA coast. We mapped changes in coastal geomorphology over three observation periods: 1950–1980, 1980–2003, and 2003–2014 using aerial and satellite imagery. We then compared these geomorphic changes to changes in sea-ice coverage, which declined ~10 days per decade between 1979 and 2016 in the southern Chukchi Sea. Changes in coastal geomorphology in both BELA and CAKR exhibited high spatial variability over the study period. Between 2003 and 2014, shorelines of barrier islands in BELA exhibited the highest mean rates of change, −1.5 m yr −1 , while coarse, clastic barrier beaches in CAKR showed only minimal change. Overall, shorelines in both BELA and CAKR became more dynamic (increasing erosion or increasing accumulation) after ca. 2003, with spatial variability in shoreline changes roughly doubling between the first period of observation (1950–1980) and the last (2003–2014). This increase in coastal dynamism may signal a transitional period leading to new state of geomorphic equilibria along these ice-affected coastlines. [ABSTRACT FROM AUTHOR]

The Soil Moisture and Ocean Salinity (SMOS) and Aquarius satellite missions have produced the first sea-surface salinity (SSS) maps from space. The quality of the retrieved SSS must be assessed, in terms of its validation against sparse ground truth, but also in terms of its ability to detect and characterize geophysical processes, such as mesoscale features. Such characterization is sometimes elusive due to the presence of noise and processing artifacts that continue to affect state-of-the-art remote sensing SSS maps. A new method, based on singularity analysis, is proposed to contribute to the assessment of the geophysical characteristics of such maps. Singularity analysis can be used to directly assess the spatial consistency of the SSS fields and to improve the estimation of the wavenumber spectra slope through a new method, the singularity power spectra (SPS). To demonstrate the SPS performance and utility, we applied SPS to different gridded SSS maps, such as SMOS and Aquarius high-level products, the output of a numerical simulation, in situ reanalysis, and climatology, as well as to other sea-surface temperature products for reference. The singularity analysis and SPS methods reveal that both the SMOS level 4 and the Aquarius combined active passive products are both able to describe the geometry of the existing geophysical structures and provide consistent spectral slopes. This paper demonstrates that beyond the remaining sources of uncertainty in remote sensing SSS products, valuable dynamical information on the ocean state can be extracted from these SSS products. [ABSTRACT FROM AUTHOR]

The triple collocation (TC) technique allows the simultaneous calibration of three independent, collocated data sources, while providing an estimate of their accuracy. In this paper, the TC is adapted to validate different salinity data products along the tropical band. The representativeness error (the true variance resolved by the relatively high-resolution systems but not by the relatively low-resolution system) is accounted for in the validation process. A method based on the intercalibration capabilities of TC is used to estimate the representativeness error for each triplet, which is found to impact between 15% and 50% the error estimation of the different products. The method also sorts the different products in terms of their resolving spatiotemporal scales. Six salinity products (sorted from smaller to larger scales) used were: the in situ data from the Global Tropical Moored Buoy Array (TAO), the GLORYS2V3 ocean reanalysis output provided by Copernicus, the satellite-derived Aquarius Level 3 version 4 (AV4) and Soil Moisture and Ocean Salinity (SMOS) objectively analyzed (SOA) maps, and the climatology maps provided by the World Ocean Atlas (WOA). This calibration study is limited to the year 2013, a year when all the products were available. This validation approach aims to assess the quality of the different salinity products at the satellite-resolved spatiotemporal scales. The results show that, at the AV4 resolved scales, the Aquarius product has an error of 0.17, and outperforms TAO, GLORYS2V3, and the SOA maps. However, at the SOA resolved scales (which are coarser than those of the Aquarius product because of the large OA correlation radii used), the SMOS product has an error of 0.20, slightly lower than that of GLORYS2V3, Aquarius, and TAO. The WOA products show the highest errors. Higher order calibration may lead to a more accurate assessment of the quality of the climatological products. [ABSTRACT FROM AUTHOR]

A gray-level co-occurrence matrix (GLCM)-based method was developed for better texture orientation estimation in remote sensing imagery. A GLCM is essentially the joint probability distribution of gray levels at the position pairs satisfying a specific relative position within an image. We first found that when the relative position is aligned with texture orientation, larger elements of the corresponding GLCM are concentrated diagonally. Then, we developed a new texture orientation estimation method. The method uses the GLCMs of relative positions equally spaced in orientation and distance, and three schemes of these GLCMs are calculated. A GLCM-derived parameter is then defined to quantitatively measure the degree of diagonal concentration of the GLCM elements, and its integral over the variable of relative distance is selected as an indicator to find the dominant texture orientation(s). For testing, we applied the method to 44 selected images containing one or multiple aligned textures. The results show that the method is in good agreement with visual inspections from 45 randomly selected people, and is insensitive to large typical noises and illumination change. In addition, using (any) one GLCM calculation scheme over the others does not significantly affect the results. Finally, the method was applied to sea surface wind direction (SSWD) retrieval from 89 synthetic aperture radar images. In the application test, the developed method achieves better SSWD retrieval accuracy than do the commonly used Fourier transform- and gradient-based methods by 8.13° and 16.09° against the European Centre for Medium-Range Weather Forecast ERA-Interim reanalysis data and 10.21° and 17.31° against the cross-calibrated multiplatform data. [ABSTRACT FROM AUTHOR]

Over the Arctic regions, current conventional altimetry products suffer from a lack of coverage or from degraded performance due to the inadequacy of the standard processing applied in the ground segments. This paper presents a set of dedicated algorithms able to process consistently returns from open ocean and from sea-ice leads in the Arctic Ocean (detection of water surfaces and derivation of water levels using returns from these surfaces). This processing extends the area over which a precise sea level can be computed. In the frame of the European Space Agency Sea Level Climate Change Initiative (http://cci.esa.int), we have first developed a new surface identification method combining two complementary solutions, one using a multiple-criteria approach (in particular the backscattering coefficient and the peakiness coefficient of the waveforms) and one based on a supervised neural network approach. Then, a new physical model has been developed (modified from the Brown model to include anisotropy in the scattering from calm protected water surfaces) and has been implemented in a maximum likelihood estimation retracker. This allows us to process both sea-ice lead waveforms (characterized by their peaky shapes) and ocean waveforms (more diffuse returns), guaranteeing, by construction, continuity between open ocean and ice-covered regions. This new processing has been used to produce maps of Arctic sea level anomaly from 18-Hz ENVIronment SATellite/RA-2 data. [ABSTRACT FROM AUTHOR]

Abstract: This study examined links between the variability of coastal front features and composition of fishery landings. Satellite‐derived sea surface temperature data allowed the detection of thermal fronts and calculation of front metrics that account for gradient, persistency, and vicinity. Landings data were clustered by functional group (according to habitat use, size, morphology), and trophic level (TL). Three independent time series analyses, based on two different classes of statistical methodologies, were carried out: (i) correlation analysis performed on species aggregated by functional groups, and (ii) compositional analysis performed on the top five species landed and on species aggregated by trophic level. Analyses were carried out for the Moroccan coast of the Alboran Sea (western Mediterranean Sea). Results of the proposed type of application were discussed with respect to their potential for improving scientific knowledge and management of fisheries in data‐poor areas. Pelagic landings were associated with front indicators in two‐thirds of tested cases. The results demonstrated a markedly different association between landings and front features in the Nador fishing zone, relative to M'diq and Al Hoceima. Improved performance of the front gradient and persistence indicator was detected, with respect to the front gradient only for flatfish and demersal landings. Compositional data regression outlined a different role for Sardina pilchardus and Trachurus trachurus in the Al Hoceima and M'diq landings, and in the latter case the dominance of these two species in the landings seemed to respond to the front density indicator. A decreasing trend in TL > 3.5 landings was detected with increasing front distance. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the author discusses various reports featured at the 13th Biennial Pan Ocean Remote Sensing Conference (PORSEC) including coastal impacts, climate change, and ocean-atmosphere interactions.

Coastal environments are highly dynamic and sensitive to interference and variations caused by the numerous natural and anthropogenic agents. The northern coast of Northeastern Brazil has undergone intense erosion in recent years. However, the construction of the Pecém Port modified the beach and shoreline features differently from the adjacent areas. This article describes using remote-sensing images integrated with a Geographic Information System to evaluate the sedimentary balance and morphological changes observed in the sandy beach area that was affected by the construction of Pecém Port. Two methods were applied to the RapidEye images to quantify the short-time changes that occurred on the coast. The Digital Shoreline Analysis System method showed that the beach width increased west to the port, which was calculated by the Change Polygon Approach determined by intersecting and uniting polygons to estimate the difference between the areas over time. The short-time analysis results showed changing coastal morphology, demonstrating that the anthropic interventions in the region are transforming significantly the natural elements that make up the region landscape. Between 2011 and 2014, the investigated beach stretch of approximately 3 km suffered an accretion process of more than 102,000 m2 over 3 years. The high spatial resolution of satellite images, digital processing imaging techniques and geostatistical methods were effective in this study, allowing understanding the recent changes in the area. [ABSTRACT FROM AUTHOR]

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms. [ABSTRACT FROM AUTHOR]

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

Utility of data from autonomous profiling floats for the validation of satellite ocean colour products from current satellite ocean colour sensors was assessed using radiometric and chlorophyll a fluorescence data from biogeochemical profiling floats (BGC-Argo) deployed in the subtropical gyre of the Indian Ocean. One of the floats was equipped with downward irradiance and upwelling radiance sensors, allowing the remote sensing reflectance, R rs , to be determined. Comparisons between satellite and in situ R rs indicated good agreement for the shorter wavelengths, but weak relationships for both satellites for the 555 nm channel, and showed that radiometers deployed on multipurpose, off-the-shelf BGC-Argo floats can provide validation-quality measurements. About 300 chlorophyll a concentration match-ups were achieved within 18 months, which increased the number of validation data points available for the Indian Ocean as a whole by a factor of ~4 from the previous historical record. Generally, the satellite data agreed with the float-derived chlorophyll concentration within the uncertainty of ±35%, for the band-difference (OCI) and band-ratio (OC3) algorithms, but not for a semianalytical ocean colour model (GSM) that exhibited significantly higher chlorophyll values (>100% mean difference). Our results indicate that autonomous float-based measurements provide substantial potential for improving regional validation of satellite ocean colour products in remote areas. [ABSTRACT FROM AUTHOR]

Direct density measurements of ocean water samples are compared to TEOS10 derived densities. The water sample set includes waters from remote areas as Antarctic waters and the central Arctic, but also waters of regions that resemble closely the reference composition of TEOS10. With few exceptions, the measured densities are smaller than those derived according to TEOS10. The result suggests a potential systematic overestimation of density by TEOS10. For the majority of waters the deviations are about 10 g/m 3 . [ABSTRACT FROM AUTHOR]

Benthopelagic animals are an important component of the deep-sea ecosystem, yet are notoriously difficult to study. Multibeam echosounders (MBES) deployed on autonomous underwater vehicles (AUVs) represent a promising technology for monitoring this elusive fauna at relatively high spatial and temporal resolution. However, application of this remote-sensing technology to the study of small (relative to the sampling resolution), dispersed and mobile animals at depth does not come without significant challenges with respect to data collection, data processing and vessel avoidance. As a proof of concept, we used data from a downward-looking RESON SeaBat 7125 MBES mounted on a Dorado-class AUV to detect and characterise the location and movement of backscattering targets (which were likely to have been individual fish or squid) within 50 m of the seafloor at ~800 m depth in Monterey Bay, California. The targets were detected and tracked, enabling their numerical density and movement to be characterised. The results revealed a consistent movement of targets downwards away from the AUV that we interpreted as an avoidance response. The large volume and complexity of the data presented a computational challenge, while reverberation and noise, spatial confounding and a marginal sampling resolution relative to the size of the targets caused difficulties for reliable and comprehensive target detection and tracking. Nevertheless, the results demonstrate that an AUV-mounted MBES has the potential to provide unique and detailed information on the in situ abundance, distribution, size and behaviour of both individual and aggregated deep-sea benthopelagic animals. We provide detailed data-processing information for those interested in working with MBES water-column data, and a critical appraisal of the data in the context of aquatic ecosystem research. We consider future directions for deep-sea water-column echosounding, and reinforce the importance of measures to mitigate vessel avoidance in studies of aquatic ecosystems. [ABSTRACT FROM AUTHOR]

The present-day ocean remote sensing instruments that operate at low microwave frequencies are limited in spatial resolution and do not allow for monitoring of the coastal waters. This is due to the difficulties of employing a large reflector antenna on a satellite platform, and generating high-quality pencil beams at multiple frequencies. Recent advances in digital beamforming focal-plane arrays (FPAs) have been exploited in this paper to overcome the above problems. A holistic design procedure for such novel multibeam radiometers has been developed, where: 1) the antenna system specifications are derived directly from the requirements to oceanographic surveys for future satellite missions and 2) the numbers of FPA elements/receivers are determined through a dedicated optimum beamforming procedure minimizing the distance to coast. This approach has been applied to synthesize FPAs for two alternative radiometer systems: a conical scanner with an offset parabolic reflector and a stationary wide-scan torus reflector system, each operating at $C$ -, $X$ -, and Ku-bands. Numerical results predict excellent beam performance for both systems with as low as 0.14% total received power over the land. [ABSTRACT FROM PUBLISHER]

High computational burden and low accuracy in non-uniform textures are the two main challenges of coral reef classification frameworks. To overcome these drawbacks, two novel forms of mapping approaches are proposed to enable Local Binary Patterns (LBP) scheme to extract discriminative features from textures. The mapping approach is a way to map the extracted features into a histogram (features vector) efficiently. In other words, the mapping method can merge some features into a feature and provides lower number of features efficiently. The proposed mapping techniques can be used for various types of LBPs; consequently, the extended LBPs can be applied to all types of textures. Benthic texture datasets are employed to assess the proposed method compared to the traditional ones. Regarding the multimodal distribution of the elicited features, K-Nearest Neighbor (KNN) is employed for classifying the extracted features. Here, the proposed mapping methods are tested on a special form of completed local binary patterns (CLBP). From the accuracy point of view, the extended CLBPs demonstrate higher accuracy compared to CLBP and also other state-of-the-art LBPs. Moreover, the proposed mapping approaches enhance the accuracy of rotation invariant LBPs, especially for large neighborhood. The proposed methods improve the classification accuracy for both noisy and noise-free images. From the computational complexity point of view, the extended CLBPs provide lower number of features compared to the others which leads to a faster recall time in KNN classifier. [ABSTRACT FROM AUTHOR]

Deriving inherent optical properties (IOPs) and other water quality parameters from satellite remote sensing data covering optically shallow environments has historically been problematic due to difficulties in separating the benthic signal from that of the water column. While recent advances have improved such retrievals, most methods have high uncertainties for very shallow (< 5 m) or very bright (e.g., carbonate sand) targets. Here, we present a two-stage process to improve IOP derivations from satellite-derived reflectance data, termed the Shallow Water Optimization with Resolved Depth (SWORD). Within this process, a raster bathymetry is first derived through multiple pixel-wise implementations of a spectral matching algorithm on mapped reflectance data. This bathymetry is then used as a fixed input in subsequent implementations of the algorithm, leading to improved IOP retrievals. The SWORD approach was developed and tested using a dataset of simulated reflectance spectra as well as MERIS reflectance data covering two optically shallow water environments. Bathymetries derived using this process showed strong agreement with those determined from soundings and coastal relief models. Although SWORD-derived raster albedo maps showed general concordance to benthic habitat surveys, we found limited benefit of fixing this parameter in spectral matching routines. IOP derivations from SWORD show expected spatiotemporal patterns in the Florida Keys region, consistent with local hydrodynamic processes, seasonal fluctuations, and known anomalous events. This approach is portable to multispectral reflectance data from similar satellite instruments, allowing regular and ongoing assessment and monitoring of optical water quality for ecologically and economically important marine systems. [ABSTRACT FROM AUTHOR]

Rastrelliger kanagurta is among the pelagic fish of commercial value caught in the archipelagic waters of Spermonde, Indonesia. The dynamic oceanographic pattern in this area influences the distribution of this pelagic fish. Understanding the relationship between the distribution of fish and environmental factors is important in exploring fisheries resources. This study used Rastrelliger kanagurta fishing-catch data during the high-catch season in the second quarter, which was from April to June (2008 and 2009), and satellite data of chlorophyll- a (chl- a ), and sea surface temperature (SST) from MODIS-Aqua. The study aimed to identify the relationship between fish distribution with chl- a and SST constructed using the Generalized Additive Model (GAM), detect the potential fishing grounds, and determine the impact of climate change on fish distribution based on temperature projection of IPCC-AR5-RCPs. The distribution of Rastrelliger kanagurta was significantly associated ( p < 0.0001) with the preferred range of chl- a at 0.30–0.40 mg/m 3 and SST at 30.00–31.00 °C. The potential fishing ground maps showed that areas with high potential catch were located near the coast to offshore (3–20 M), with acceptable level of map accuracy at 83.34%; with kappa value at 0.70. Increased temperature of 1.80 °C resulted in movement of potential fishing grounds to the southern part of Makassar Straits leading to the archipelagic waters of Spermonde. In contrast, increased temperature of 2.60 °C and 3.30 °C resulted in lesser potential fishing grounds area which shifted further to the south. The results of this study indicated applicability of remote sensing in contributing to optimal fishing effort and decision making for long-term management of Rastrelliger kanagurta resources. [ABSTRACT FROM AUTHOR]

Carbonate production on coral reefs is responsible for the provision of beach sands, for the maintenance of seawater chemical balances and for the growth of reef structure and associated habitat complexity. Key carbonate producers including hard coral, crustose coralline algae, foraminiferal sand and Halimeda were mapped from satellite imagery (spatial resolution 2.5 m, mean overall accuracy = 81%) and an upscaling model was applied to estimate carbonate production. A sensitivity analysis was conducted to evaluate the influence of employing different calcification rates for live coral on the upscaling model. Contemporary coral reef carbonate production for the 21 reef platforms of the Capricorn-Bunker Group (southern Great Barrier Reef) is estimated to be between 489,000 and 659,000 t per year based on seawater chemistry, community composition, calcification rates and reef structural complexity (rugosity). The upscaling model was relatively insensitive to different parameterisations of live coral calcification employed, probably due to live coral being a relatively minor contributor by area (approximately 18% of total reef area throughout the study region). This suggests regional scale seafloor characteristics, such as percentage of area dominated by substrates prone to dissolution (e.g. coral rubble), have a strong bearing on calcium carbonate production and need to be given greater consideration The upscaling framework presented provides a new method for quantifying regional carbonate production that could be applied globally, and provides a valuable baseline against which future changes to carbonate production in this region can be assessed. [ABSTRACT FROM AUTHOR]

Sea surface salinity (SSS) is an important parameter to characterize physical and biogeochemical processes, yet its remote estimation in coastal waters has been difficult because satellite sensors designed to “measure” SSS lack sufficient resolution and coverage, and higher-resolution ocean color measurements suffer from optical and biogeochemical complexity when used to estimate SSS. In the northern Gulf of Mexico (GOM), this challenge is addressed through modeling, validation, and extensive tests in contrasting environments. Specifically, using extensive SSS datasets collected by many groups spanning > 10 years and MODIS (Moderate Resolution Imaging Spectroradiometer) and SeaWiFS (Sea-Viewing Wide Field-of-View Sensor) estimated remote sensing reflectance (Rrs) at 412, 443, 488 (490), 555, and 667 (670) nm and sea surface temperature (SST), a multilayer perceptron neural network-based (MPNN) SSS model has been developed and validated with a spatial resolution of ~ 1 km. The MPNN was selected over many other empirical approaches such as principle component analysis (PCA), multi-nonlinear regression (MNR), decision tree, random forest, and supporting vector machines (SVMs) after extensive evaluations. The MPNN was trained by a back-propagation learning technique with Levenberg-Marquardt optimization and Bayesian regularization. The model showed an overall performance of root mean square error (RMSE) = 1.2, with coefficient of determination (R 2 ) = 0.86, mean bias (MB) = 0.0, and mean ratio (MR) = 1.0 for SSS ranging between ~ 1 and ~ 37 ( N = 3640). Validation using an independent dataset showed a RMSE of 1.1, MB of 0.0, and MR of 1.0 for SSS ranging between ~ 27 and ~ 37 ( N = 412). The model with its original parameterization has been tested in the Mississippi-Atchafalaya coastal region, Florida's Big Bend region, and in the offshore Mississippi River plume, with satisfactory performance obtained in each case. Comparison with concurrent Aquarius-derived SSS maps (110-km resolution) showed similar agreement in offshore waters as indicated above, but the new 1-km resolution SSS maps revealed more finer-scale features as well as salinity gradients in coastal waters. The sensitivity of the model to realistic model input errors in satellite-derived SST and Rrs was also thoroughly examined, with uncertainties in the model-derived SSS being always < 1 for SSS > 30. The extensive validation, evaluation, and sensitivity test all indicated the robustness of the MPNN model in estimating SSS in most, if not all, coastal waters and offshore plumes in the northern GOM. Thus, the model provided a basis for generating near real-time 1-km resolution SSS maps from satellite measurements. However, the model showed limitations when applied to regions with known algal blooms or upwelling as they both led to low Rrs in the blue bands that may be falsely recognized as caused by low SSS. [ABSTRACT FROM AUTHOR]

Remote sensing of chlorophyll- a concentration, [Chl- a ], has been difficult in coastal waters like the Chesapeake Bay owing largely to terrestrial substances (such as minerals and humus) that are optically significant but do not covary with phytoplankton. Here we revisit the semi-analytical pathway of deriving [Chl- a ] based on the light absorption coefficient of phytoplankton by introducing the generalized stacked-constraints model (GSCM) to partition satellite-derived total light absorption coefficient of water (with pure-water contribution subtracted), a nw (λ), into phytoplankton, a ph (λ), and non-phytoplankton components, where a nw (λ) is derived from satellite remote-sensing reflectance, R rs (λ), using the Quasi-Analytical Algorithm. The GSCM-derived a ph (λ) was compared with field matchups of [Chl- a ]. We show that semi-analytical approaches can provide superior [Chl- a ] product compared with reflectance-band-ratio algorithms when the accuracy of satellite-derived a ph (λ) is sufficiently improved, in this case with the GSCM. However, the improvement is at the cost of significantly reduced data availability because the GSCM may provide no feasible solutions when input a nw (λ) data are subject to large errors. This in turn highlights the needs for improved atmospheric correction and upstream models capable of preserving actual spectral shapes of R rs (λ) and a nw (λ), respectively. [ABSTRACT FROM AUTHOR]

This study presents an empirical approach for estimating sea surface salinity (SSS) from remote sensing of ocean colour. The analysis is based on two important empirical relationships of in-water optical properties. The first involves the behaviour of the optical properties of coloured dissolved organic matter (CDOM) under conservative mixing along the salinity gradient. The second is the tight relationship between CDOM and water-leaving radiance. Our results showed that CDOM absorption coefficients in ultra-violet wavelengths (350 and 380 nm) can be best estimated using the blue-green band ratio Rrs(412/547) with a R² value of 0.87. It was also found that the absorption coefficient of CDOM in the study area was tightly correlated with the salinity (R²≈0.83); however, the data indicate that this relationship may be dependent on freshwater flow and the intensity of vertical mixing. During the wet and well-mixed season (Northeast monsoon), CDOM was almost conservative with salinity but tended to behave non-conservatively during the dry and stratified season (Southwest monsoon). These resulting empirical relationships allow CDOM and salinity in the study area to be estimated from satellite ocean colour data. Validation using independent datasets showed that the algorithms for CDOM and salinity perform relatively well with the RMS error of 0.04 m-1 and 0.30', respectively, over a range of salinity from 30' to 33'. The ability of the algorithm to predict salinity as those presented in this study can be further improved using more independent tests with in-situ and satellite bio-optical measurements. [ABSTRACT FROM AUTHOR]

Underwater topography can be imaged using remote sensing methods. Numerous studies have been conducted to understand the imaging mechanism of shallow water topography. However, current-topography interaction constitutes the weakest link in the remote sensing imaging mechanism of underwater topography. In addition, few studies focused on different topography patterns. Current velocity is highly correlated with bathymetry, and velocity gradient is used as an indicator of sea surface roughness. In this research, we analyzed the distribution characteristics of current velocity and velocity gradient in different cases using a 3-dimensional (3-D) hydrodynamic model to discuss the current-topography interaction part of the remote sensing imaging mechanism, especially the modulation by current parallel or normal to the underwater topography, both positive and negative. Results showed remarkable agreement between 3-D current analysis and surface velocity analysis. Parallel and normal currents had different responses to different topography types. The distribution of surface current gradient showed opposite features over negative and positive topography in parallel and normal current fields. This can be used to distinguish negative topography from positive topography with different current directions to a certain extent. [ABSTRACT FROM AUTHOR]

Using remote sensing data for marine monitoring, marine rescue, marine pollution monitoring which has a broad monitoring area and fast response time, so in the last 10 years, satellite borne or airborne optical and SAR sensor data have been increasingly used in the field of ocean monitoring. However, based on the dynamic video to carry out the study of the detection of irregular debris blocks from the wrecked ship, aircraft is less. To a great extent, it affects the efficiency of maritime rescue. This paper, based on the dynamic objects detection, Color Space Quantization and property of Human Vision System, takes the irregular wreckage patches as research. And a detection algorithm for dynamic objects is developed with the foundation of Lab channels. To verify that, the calculation of the Euclidean distance between the characteristic parameters of irregular wreckage patches and regular floating ones, and the average Euclidean distance is 0.8245 between the irregular1 and the regular while that between irregular2 and the regular is 4.3645. At the same time, the Hausdorff distance was calculated and verified, and the average distance between the irregular block 1 and the regular block was 2.5975. The average distance between the block 2 and the rule block was 13.8962. Experimental results show that the method is consistent with the results of the second methods, which proves that the first method is scientific and operational. Therefore, it can be found that some parameters including divergence, elongation and eccentricity fluctuate dramatically from those in irregular ones to the regular one, which could be extracted to recognize or distinguish the patches. That is why this paper is of importance in marine rescue and detection of objects on the sea surface. [ABSTRACT FROM AUTHOR]

The monitoring of coastal areas is becoming an urgent necessity in the context of increased pressure over these ecosystems due to climate change and human activities. Long term evaluation of specific parameters regarding water quality can now be achieved, thanks to the increased number of archived Earth Observation satellite data, now covering decades. Within this study, 12 years of MODIS information were used to compute surface water turbidity products that were further temporal binned into composite datasets (e.g. monthly, annual). A regional algorithm, based on local in situ measurements, was used in order to inverse remote sensing reflectance values into turbidity units. The interpretation of the final maps revealed important characteristics of the processes that play a major role in the regional turbidity dynamics. Observations were made regarding the relation between surface water turbidity and Danube River's discharge rates, winds, currents and also the bottom sedimentary characteristics of the shelf area. We discuss how different regions are affected by various external factors, depending on their geographical location, and we reinforce the idea that the river solid input is not the only parameter controlling water clarity in the Danube Delta coastal area, resuspension processes playing also an important role. [ABSTRACT FROM AUTHOR]

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Shore-based remote sensing platforms are increasingly used to frequently (~daily) obtain bathymetric information of large (~km ^2 ) nearshore regions over many years. With recorded wave frequency \Omega and wavenumber k (and hence wave phase speed c = \Omega /k ), bed elevation can be derived using a model that relates \Omega and k to water depth. However, the accuracy of as a function of the sensor and the method of \Omega -k retrieval is not well known, especially not under low-period waves. Here, we assess the accuracy of zb , based on two sensors with their own method of phase speed retrieval, in a dynamic, kilometer-scale environment (Sand Engine, The Netherlands). Bias in zb is systematic. A fast Fourier transform (FFT) method on X -band radar imagery produced zb too shallow by 1.0 m for -15~\text m \leq zb \leq -9 m, and too deep by 2.3 m for zb\geq -6 m. A cross-spectral method on optical video imagery produced zb too shallow by 0.59 m for -10~\text m \leq zb \leq -5 m, and too deep by 0.92 m for zb\geq -1 m. Intermediate depths had negligible bias, −0.02 m for the radar-FFT approach and −0.01 m for the video-CS approach. The collapse of the FFT method in shallow water may be explained by the inhomogeneity of the wave field in the 960 m $\times960$ m analysis windows. A shoreward limit of the FFT method is proposed that depends on zb in the analysis windows. [ABSTRACT FROM PUBLISHER]

We investigate some temporal properties of the microwave backscattered field from the sea surface at low incidence, namely, the decorrelation time and the Doppler shift distribution. These quantities may have an important impact on the performances of the altimeter and synthetic aperture radar systems in Ku- and Ka-bands and must be accurately evaluated. In the framework of classical analytical scattering models and for realistic sea spectra, we obtain a simple expression for the decorrelation time with respect to the main sea state parameters and the scattering geometry. We further propose an original approach based on a time-domain estimator to evaluate the distribution of instantaneous Doppler shifts and the Doppler centroid. The evolution of the latter with the sea state and scattering angles is calculated and discussed. A procedure is proposed to recover the full two-sided Doppler spectrum. We discuss the use of the Doppler shift in view of the geophysical parameter retrieval at low incidence. We find that the surface wind vector can, in principle, be well estimated from the azimuthal variation of the Doppler shift, whereas the signature of the surface current is not sufficient to allow for its estimation. [ABSTRACT FROM PUBLISHER]

The article proposes parallel implementation of the Ensemble Optimal Interpolation (EnOI) data assimilation (DA) method in eddy-resolving World Ocean circulation model. The results of DA experiments in North Atlantic with ARGO drifters are compared with the multivariate optimal interpolation (MVOI) DA scheme. The sensitivity of the model error, i.e., the difference between the model and observations depending on the number of ensemble elements, is also assessed and presented. The effectiveness of this method over the MVOI scheme is confirmed. The model outputs with and without assimilation are also compared with independent sea surface temperature data from ARMOR 3d. [ABSTRACT FROM AUTHOR]

The Barents Sea is particularly vulnerable to large-scale hydro-climatic changes associated with the polar amplification of climate change. Key oceanographical variables in this region are the seasonal development of sea-ice and the location and strength of physico-chemical gradients in the surface and subsurface water layers induced by the convergence of Arctic- and Atlantic-derived water masses. Remote sensing imagery have highlighted the increasing success of calcifying haptophytes (coccolithophores) in the summer phytoplankton production of the Barents Sea over the last 20 years, as a response to an overall larger contribution of Atlantic waters to surface and sub-surface waters, as well as to enhanced sea-ice melt-induced summer stratification of the photic layer. The present study provides a first thorough description of coccolithophore standing stocks and diversity over the shelf and slope of the western Barents Sea from two sets of surface and water column samples collected during August–September 2014 from northern Norway to southern Svalbard. The abundance and composition of coccolithophore cells and skeletal remains (coccoliths) are discussed in view of the physical–chemical–biological status of the surface waters and water column based on in-situ (temperature, salinity, fluorescence) and shore-based (microscope enumerations, chemotaxonomy) measurements, as well as satellite-derived data (Chl a and particulate inorganic carbon contents). The coccolithophore population is characterized by a low species diversity and the overwhelming dominance of Emiliania huxleyi . Coccolithophores are abundant both within the well stratified, Norwegian coastal water — influenced shallow mixed layer off northern Norway, as well as within well-mixed cool Atlantic water in close vicinity of the Polar Front. Bloom concentrations with standing stocks larger than 4 million cells/l are recorded in the latter area north of 75°N. Our limited set of chemotaxonomic data suggests that coccolithophores contribute substantially (ca. 20% of the total Chl a ) to the summer phytoplankton community which is made essentially of small-sized algal groups. Excluding the bloom area, coccolith calcite accounts for an average of 20% to the bulk particulate inorganic carbon content in the surface waters, and explains to some extent the satellite-derived spatial distribution of this parameter. Deep water living coccolithophore species thriving below the pycnocline as well as populations present in well-mixed cool Atlantic water are rapidly transferred to depth in the form of intact coccospheres down to at least 200 m. High amplitude internal waves which, according to our observations, affect a wide range of water depth up to the lower photic zone, might strengthen the vertical transfer of this sinking population. [ABSTRACT FROM AUTHOR]

It has become a routine to automatically identify mesoscale ocean eddies in the world's oceans and reconstruct their trajectories from remote sensing data. However, the major migration pathways along which eddies mainly propagate are not clear, particularly in the South China Sea (SCS). This study utilized a trajectory partition-and-group method to quantitatively measure and group trajectories of eddies in the SCS from 1992 to 2012 to extract their major migration corridors. The trajectories were first simplified into segments using the minimum description length (MDL) principle, their origin and destination (OD) points, and their trajectory partitions (TP) between two consecutive tracking times, respectively. The MDL-, OD-, and TP-based segments were then respectively grouped into clusters using the density-based spatial clustering of applications with noise (DBSCAN) algorithm. Representative trajectories, i.e., the major migration corridors, were then extracted from different clusters. Results show that the MDL-based corridors are the most tenable in revealing the migration corridors of eddies in the SCS. The major MDL-based migration corridors of both anticyclonic and cyclonic eddy in the SCS mainly extend westward and show a meridional propagation toward the equator. The different major migration corridors in the northern, central, and southern SCS could be attributed to the various influences of seabed topography and/or background currents in these regions. [ABSTRACT FROM AUTHOR]

Based on long-term satellite-derived ocean data sets and methods of empirical orthogonal function and singular value decomposition, we investigated the spatiotemporal variability of the chlorophyll- a concentration (CHL) on seasonal and interannual timescales in the western tropical Pacific associated with physical ocean variables of sea surface temperature (SST), sea level anomaly (SLA) and sea surface wind (SSW), and the El Niño Southern Oscillation (ENSO) index. The bio-physical synchronous variation on interannual timescale was also confirmed in terms of the scales of variability and oscillation periods in the time-frequency space using the methods of Fourier transform, Morlet wavelet transform, and wavelet coherence analysis. On a seasonal timescale, the first two modes of the monthly mean CHL fields described the consecutive spatiotemporal variation in CHL in the western tropical Pacific. CHL reached the maximum during late winter–early spring and minimum during summer–early autumn with the exception of the northeast of Papua New Guinea and the Solomon Islands. The CHL bloom in boreal winter–spring was closely associated with cold SST, high sea level along the North Equatorial Countercurrent meanders, and strong wind. On an interannual timescale, the variability of CHL exhibited a close correlation with SST, SLA, SSW, and ENSO. During El Niño, CHL increased in the oligotrophic western basin of the warm pool associated with cold SST, low SLA, and strong westerly winds but decreased in the mesotrophic eastern basin of the warm pool in association with warm SST, high SLA, and weak easterly trade winds. There may exist time-lag for the bio-physical covariation, i.e., CHL and SST varied simultaneously within 1 month, and CHL variations led SLA by approximately 0–3 months but lagged wind speed by about 1 month. In the time-frequency domain, the interannual variability in CHL and physical ocean variables had high common power, indicating that the variability scales and oscillation periods of CHL were significantly related to these of SST, SLA, and ENSO index. The significant anti-phase relationships were also shown between CHL and SST, CHL and SLA, and CHL and multivariate ENSO index through the wavelet coherence analysis. [ABSTRACT FROM AUTHOR]

Remote sensing observations show optical signatures to conform to the physical oceanographic patterns in the Tasman Sea. To test the link between physical oceanographic processes and bio-optical properties we investigated an in situ bio-optical dataset collected in the Tasman Sea. Analysis of in situ observations showed the presence of four different water masses in the Tasman Sea, formed by the relatively warm and saline East Australia Current (EAC) water, a mesoscale cold core eddy on the continental slope, cooler Tasman Sea water on the shelf and river plume water. The distribution of suspended substances and their inherent optical properties in these water masses were distinctly different. Light absorption and attenuation budgets indicate varying optical complexity between the water masses. Specific inherent optical properties of suspended particulate and dissolved substances in each group were different as they were influenced by physical and biogeochemical processes specific to that water mass. Remote sensing reflectance signature varied in response to changing bio-optical properties between the water masses; thus providing the link between physical oceanographic processes, bio-optical properties and the optical signature. Findings presented here extend our knowledge of the Tasman Sea, its optical environment and the role of physical oceanographic processes in influencing the inherent optical properties and remote sensing signature in this complex oceanographic region. [ABSTRACT FROM AUTHOR]

Most oceanographic instruments on the seafloor have no connections with the surface and therefore have to run on batteries and store data until recovery. To demonstrate a developing technology, sensors and acoustic modems were powered with energy harvested from the seafloor, and data were relayed acoustically in near-real time to the Monterey Accelerated Research System (MARS) observatory in Monterey Bay, California, and to surface research vessels. MARS is a cabled observatory in deep water (~890 m) at the edge of Monterey Canyon. An acoustic modem was attached to the MARS node and configured to send out commands to, and relay data received from, remote modems. Two benthic microbial fuel cells (BMFCs) positioned approximately 0.5 km away from MARS supplied power to the remote modems and sensors. At their peak performance, these BMFCs produced continuous power densities of ~35 mW m−2 (footprint area). The modems utilized in this study contained an integrated power management platform (PMP) designed to manage and store the electrical energy generated by each BMFC and to record BMFC performance parameters and sensor data on an hourly basis. Temperature and either oxygen or conductivity sensors were chosen because of their common use and environmental relevance. Acoustically transmitted data records show that the BMFCs renewed energy stores and that the oceanographic sensors measured dissolved oxygen, temperature, and conductivity reliably throughout the operational life of each BMFC system (~6 months). These systems remained in place for more than 12 months. [ABSTRACT FROM AUTHOR]

High-frequency radars (HFRs) measure ocean surface currents remotely through the Bragg scattering of radio waves by surface gravity waves with wavelengths shorter than 50 m. HFR range is affected by sea ice, which dampens surface gravity waves and limits wind fetch for adjacent open waters. HFR range sensitivity to sea ice concentration was empirically determined for two types of HFR-Coastal Ocean Dynamics Applications Radar (CODAR) and Wellen Radar (WERA)-installed on the shores of the lower St. Lawrence estuary, Canada, during winter 2013. One CODAR was operating at 13.5 MHz on the southern shore, and one WERA was operating at 16.15 MHz on the northern shore. Ranges were determined using a signal-to-noise ratio threshold of 6 dB for first-order Bragg scattering measured by the receive antenna elements. Ranges were normalized for expected ranges in ice-free conditions, using empirical relationships determined during summer 2013 between the range and surface gravity wave energy at the Bragg frequencies. Normalized ranges Γ decrease approximately linearly with increasing sea ice concentration C (averaged over the ice-free observational domain) with a slope close to −1 for both HFR types, that is, Γ = 1 − C. However, for a given sea ice concentration, range can vary significantly depending on the sea ice spatial distribution. [ABSTRACT FROM AUTHOR]

Based on synthetic aperture radar (SAR) images, this study illustrates the characteristics of oceanic eddies in the Luzon Strait and its adjacent seas. An eddy detection method is applied to 426 SAR frames (including the European Remote Sensing satellite, ERS-2, and the Environmental Satellite, ENVISAT) from 2005 to 2011, and 60 eddies are identified. About 78% of these eddies have sizes smaller than 12 km, which is smaller than the local first baroclinic deformation radius, and thus can be categorized as submesoscale eddies. Their polarities are dominated by cyclonic features. Our results indicate that oceanic eddy activity may be largely underestimated by observational techniques that only resolve mesoscale features, and that SAR is an effective tool for detecting and studying submesoscale eddies. [ABSTRACT FROM PUBLISHER]

In contrast to traditional ocean observation systems such as research vessels and moorings, gliders, a specific category of autonomous underwater vehicles, can be operated individually or as fleets. These devices are designed to allow for continuously and remotely commanded ocean observation from the surface down to at least 1 km depth and deliver data with high horizontal and temporal resolution. This article assesses the legal framework and identifies the legal conditions that ought to be fulfilled in order to deploy and operate gliders in conformity with the international law of the sea. [ABSTRACT FROM AUTHOR]