Temporal and spatial variability of satellite sea surface temperature and ocean colour in the Japan/East Sea

Temporal and spatial variability of Sea Surface Temperature (SST) and ocean colour in the Japan/East Sea (JES) are examined during winter and spring using satellite data from Advanced Very High Resolution Radiometer (AVHRR) and Sea-viewing Wide Field of view Sensor (SeaWiFS). The timing of the spring phytoplankton bloom and the locations of the chlorophyll fronts are related to changes in the thermal fields and the locations of the temperature fronts. Daily images of SST and chlorophyll concentration show both differences and similarities of bio-optical and thermal front location, depending on region and season. Four sub-regions in the JES were defined and SST and chlorophyll values were extracted from weekly and monthly composite images to derive summary statistics. SST at the Subpolar Front increased about 7°C over a 1.5-month period from late April to early June in 1999. During this same period, elevated chlorophyll values near the Korean coast and in the southern basin decreased sharply as the phytoplankton bloom that first developed in the southern basin progressed to the front and northward. The SST/chlorophyll relationship is complex and seasonal. Near the Subpolar Front, SST and chlorophyll were positively related in April. In May, highest chlorophyll values corresponded to mixing regimes (such as areas of convergence and divergence at the edges of meanders) and, by June, SST and chlorophyll near the front were inversely related.     

Ocean colour validation activities at the Acqua Alta Oceanographic Tower in the northern Adriatic Sea

The development and validation of ocean colour products require the availability of in situ atmospheric and marine data. Since 1995, the Coastal Atmosphere and Sea Time Series (CoASTS) Program ensures the collection of an in situ comprehensive set of measurements taken from an oceanographic tower in the northern Adriatic Sea. An example of a validation exercise is presented through the comparison of in situ and satellite-derived aerosol optical thickness at various wavelengths in the 443–865?nm spectral interval.     

Human tracking using 3D surface colour distributions

A likelihood formulation for detailed human tracking in real-world scenes is presented. In this formulation, the appearance, modelled using feature distributions defined over regions on the surface of an articulated 3D model, is estimated and propagated as part of the state. The benefit of such a formulation over currently used techniques is that it provides a dense, highly discriminatory object-based cue that applies in real world scenes. Multi-dimensional histograms are used to represent the feature distributions and an on-line clustering algorithm, driven by prior knowledge of clothing structure, is derived that enhances appearance estimation and computational efficiency. An investigation of the likelihood model shows its profile to be smooth and broad while region grouping is shown to improve localisation and discrimination. These properties of the likelihood model ease pose estimation by allowing coarse, hierarchical sampling and local optimisation.     

Sea surface salinity variability in the tropical Indian Ocean

Argo profiles of temperature and salinity data from the north Indian Ocean have been used to address the seasonal and interannual variability of Sea Surface Salinity (SSS) and SSS Anomaly (SSSA) in 2 boxes from the eastern Equatorial Indian Ocean (EIO: 5°S-5°N, 90°-95°E) and Southeastern Arabian Sea (SEAS: 5°-9°N, 72°-76°E) and to compare with the HYbrid Coordinate Ocean Model (HYCOM) simulated SSS for the period from January 2002 to February 2007. The observational period covered one strong negative Indian Ocean Dipole Zonal Mode (IODZM) event in 2005 and a strong positive IODZM event in 2006. The Argo profiles in each box captured the impact of these IODZM events with a larger impact in the EIO box showing salting (positive SSSA, + 0.9) during negative IODZM (November 2005) and freshening (negative SSSA, − 0.6) during positive IODZM (November 2006). A band of positive (negative) SSSA occurs in the central EIO during negative (positive) IODZM event in 2005 (2006) under the influence of IODZM dynamics. The impact of IODZM event in the SEAS is more evident during boreal winter months. The observed anomalous eastward (westward) surface current contributed to the observed intense salting (freshening) during negative (positive) IODZM event in the EIO. Following the IODZM events, the East India Coastal Current (EICC) gets modulated through the propagation of downwelling/upwelling Kelvin Waves and further lead to the freshening/salting in the SEAS during boreal winter. These are well corroborated with the HYCOM simulations of SSS and currents. This study emphasizes that the HYCOM simulated salinity fields would be useful to provide rapid checks revealing either problems or successes in the satellite retrievals of salinity from the Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions.     

Assessment of SeaWiFS,MODIS, and MERIS ocean colour products in the South China Sea

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Medium Resolution Imaging Spectrometer (MERIS) remote-sensing radiometric and chlorophyll-a (chl-a) concentration products for the South China Sea (SCS) from October 2003 to May 2010 were assessed using in situ data. A strict spatiotemporal match-up method was used to minimize the temporal variability effects of atmosphere and seawater around the measurement site. A comparison of the remote-sensing reflectance (R_rs(λ)) of the three sensors with in situ values from the open waters of the SCS showed that the mean absolute percentage difference varied from 13% to 55% in the 412–560 nm spectral range. Generally, the MERIS radiometric products exhibited higher typical uncertainties and bias than the SeaWiFS and MODIS products. The R_rs(443) to R_rs(555/551/560) band ratios of the satellite data were in good agreement with in situ observations for these sensors. The SeaWiFS, MODIS, and MERIS chl-a products overestimated in situ values by 74%, 42%, and 120%, respectively. MODIS retrieval accuracy was better than those of the other sensors, with MERIS performing the worst. When the match-up criteria were relaxed, the assessment results degraded systematically. Therefore, strict spatiotemporal match-up is recommended to minimize the possible influences of small-scale variation in geophysical properties around the measurement site. Coastal and open-sea areas in the SCS should be assessed separately because their biooptical properties are different and the results suggest different atmospheric correction problems.     

Optimal control of sustainable development in the biological rehabilitation of the Azov Sea

The article is devoted to the application of the concept of sustainable development management to the task of combating the eutrophication of shallow water bodies (by the example of the Azov Sea). To describe the state dynamics of the water body, partial differential equations solved numerically by the finite difference method have been used. The dynamic problem of minimizing costs for the maintenance of the ecosystem of the water body in the defined condition, which is interpreted as the requirement for sustainable development, has been solved. The research and forecast complex, including the mathematical models of the hydrobiology of the shallow water body, environmental databases, and program library used to design scenarios of the ecological situation in the Azov Sea, has been worked out. Changes in the concentration of malicious blue-green algae due to water pollution by biogenic substances causing the rapid growth of these algae have been forecast. The influence of the spatial distribution of the temperature and the salinity on the biological treatment of the Azov Sea though the introduction of green algae, which displaced the toxic blue-green algae, has been studied. Using the designed research and forecast complex based on the materials of expeditions it is possible to investigate the key mechanisms of formation of vertical and horizontal zones in the distribution of biogenic substances, oxygen, and planktonic populations, to set the values of the parameters for management of the amount of hydrogen sulfide and hypoxemic zones, to evaluate the possibility of the biological treatment of the Azov Sea waters with the help of the introduction of the green alga Chlorella vulgaris BIN, followed by displacement of the toxic blue-algae that are most common in shallow water bodies such as Aphanizomenon flosaquae, and to rank the ecological efficiency of the factors for the management of the stability of the composition of the phytoplankton species, including the blooming of microalgae. Examples of the numerical calculations have been provided. The obtained results have been analyzed.     

Correction of bottom influence in ocean colour satellite images of shallow water areas of the Baltic Sea

Ocean colour satellite measurements are mainly disturbed by the atmosphere, the sea surface and the sea bottom in shallow water areas. In such areas special features of bottom topography can be recognized in satellite images of the visible spectrum and the derived concentrations of water constituents are often misinterpreted. The influence of the sea bottom depends on the water depth, the transmission of the water column, the reflectance of the water, the reflectivity of the bottom materials and the used spectral channels of satellite sensors. The influence of the sea bottom on the spectral reflectance at the sea surface is discussed here on the basis of model computations. The calculations are realized for examples of shallow water areas of the Baltic Sea. Furthermore, a technique for the identification of sea bottom disturbed pixels in satellite images and for the elimination of bottom effects is presented. A linear regression analysis between the bottom depth and the spectral reflectance in the different satellite sensor channels is used in order to test the correlation between these two variables. If a relationship exists, the reflectances have to be corrected. This procedure and the elimination of the bottom influence will be explained for specific satellite systems.     

Uncovering spatial and temporal patterns of Adriatic Sea colour with self-organizing maps

Fifteen years (1998–2012) of monthly chlorophyll-like pigment concentrations from satellite images (JRC database) were analysed using self-organizing maps (SOMs). The aim was to classify the pigment structures of the Adriatic Sea into a number of patterns present in the data by this novel neural network method. The images are represented by a vector in the multidimensional data-space limited to the Adriatic area. We tried using several predefined patterns, finally selecting an optimal number of 16 spatial structures. Distinct neurons are primarily associated with patterns of different pigment concentration over the whole Adriatic area and with a different extension of the colour front along the west coast. Rare phenomena and variability limited to smaller areas were less represented in the SOM patterns. Although temporal pigment dynamics are synchronous in many areas of the Adriatic Sea, the analysis of their annual course resulted in ten temporal patterns. This representation also demonstrates the ability of the SOM method to connect areas with a particular seasonal variation in chlorophyll.     

Sea surface effects on the sea surface temperature estimation by remote sensing

By using a sea surface temperature profiler buoy, the behaviour of the vertical temperature profile near the sea surface was observed in Mutsu Bay. In the daytime under calm and strong sunshine condition, there occurred a large temperature difference between the uppermost sea surface and the 1 m depth. The difference disappeared when the wind began to blow with a speed greater than 4ms^?1. Besides the atmospheric effects the inhomogeneity of the vertical temperature distribution near the sea surface must be another major error factor in the sea surface temperature estimation by satellite remote sensing.     

Observations of ice surface temperature and thickness in the Baltic Sea

This paper presents the results of an airborne thermal infrared (TIR) experiment. The data were obtained during 6–9 February 1992 period in the Bay of Bothnia, the northern section of the Baltic Sea, in connection with an ERS‐1 field campaign. Two Aegema model 880 TIR cameras were used with nominal wavelengths at 5 and 10 µm, attached to the front of the helicopter with a Tyler mount. The camera's thermal resolution is 0.2 K; after corrections for atmosphere effects, the surface temperature accuracy is 0.5 K. The spatial resolution of individual images is 70 cm at the 300‐m flight altitude. The measurement programme was successful, producing high‐quality TIR data over ice for two different days, even under difficult weather conditions. Ice temperatures ranged from open water temperatures to 261 K for fast ice conditions on the day on the first flight. The standard deviation of the surface temperature, generally, increased with ice thickness with a value of ～0.4 K for maximum thickness, and autocorrelation length scales not exceeding a value of 5 m. Generally, all the higher values of standard deviation (>0.7) of surface temperatures were for scenes with mixed ice/open water. The results show that TIR has a substantial ability to classify ice type and thickness when the air temperature is less than 269 K, from open water at the freezing point to thin nilas and thicknesses up to 20–45 cm in the fast ice zone. In addition, a quasi‐steady sea‐ice model is used to provide a physical interpretation of the sea‐ice surface temperatures. The use of the model requires information on the atmospheric surface layer and snow thickness data, together with calibration points. The model worked well when the air temperature was around 260 K or less.     

The effect of VDU colour on visual fatigue in the fovea and periphery of the visual field

The effect of the display of a visual display unit (VDU) on visual fatigue was investigated using the critical flicker frequency (CFF) paradigm. The results indicate that fatigue, as measured by CFF, varied as the VDU colour and eccentricity changed in the visual field. It was found that blue and red, that is, both extremes of the visible spectrum, strongly caused visual fatigue in the visual field when compared to green and yellow, that is, the middle range of the visible spectrum. Furthermore, for yellow and blue, VDU signal fatigue tended to decrease as the distance from the fovea increased. whereas for red and green, it increased by up to 10° in the periphery and then tended to decrease. The results indicate that yellow and green cause less fatigue in the periphery and fovea, respectively.     

Sea surface temperature simulation and forecast

Unconventional computing of sea surface temperature (SST) was once featured by NASA as a unique merger of science and art. Our approach led to a discovery that just one geographical point could be sufficient to track global anomalies of SST based on El Niño Southern Oscillation (ENSO). Such single point in the Pacific Ocean off of the island of Isabella in the Galapagos Islands was named the Galapagos indicator. Now we show that a single point in the Baltic Sea off of the coast of Göteborg could be also sufficient to track ENSO. We propose to name it the Baltic indicator. We also demonstrate that two crisis falls of oil price in 2008 and 2014 followed just after the local maximums of Baltic indicator. However, Baltic and Galapagos indicators do not show any evident trend in settling the global warming from the beginning of this century.     

An algorithm for the retrieval of suspended sediment concentrations in the Irish Sea from SeaWiFS ocean colour satellite imagery

A study was conducted in the Irish Sea with the aim of deriving an algorithm for the retrieval of suspended sediment concentrations from ocean colour imagery obtained from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). In situ observations of the diffuse attenuation coefficient, K_d , and irradiance reflectance, R, were obtained at wavelengths coincident with the SeaWiFS visible wavebands using a Profiling Reflectance Radiometer (PRR600, Biospherical Instruments Inc., San Diego). Results showed that surface reflectance at 665 nm (R₆₆₅ ), rather than variations in the intrinsic colour of the ocean (using colour ratios), was the most widely applicable method of obtaining suspended sediment concentrations from ocean colour imagery in this region. The derived algorithm enabled the estimation of mineral suspended sediment (MSS) concentrations from ocean colour in the Irish Sea, accurate to within 1 mg l^?1 (see equation below). Furthermore, the application of this algorithm to a SeaWiFS image of the Irish Sea accurately reproduced known regions of high turbidity with realistic MSS concentrations.

MSS=0.0441R ² ₆₆₅ + 1.1392R ₆₆₅ + 1.7459

(R ²=0.9105, n=124, RMS error=0.907)

Specific absorption and scattering coefficients were derived for all optically active in-water constituents, namely yellow substance (YS), mineral suspended sediments (MSS) and phytoplankton pigments (C). An optical model based on the empirically derived absorption and scattering coefficients reproduced the observed relationship between MSS and R ₆₆₅. Model results highlighted the relative insensitivity of reflectance at 665 nm to variations in the concentrations of other in-water constituents, suggesting that the algorithm may be applicable to the Irish Sea throughout the year.     

Learning and surface boundary feedbacks for colour natural scene perception

Boundary detection and segmentation are essential stages in object recognition and scene understanding. In this paper, we present a bio-inspired neural model of the ventral pathway for colour contour and surface perception, called LPREEN (Learning and Perceptual boundaRy rEcurrent dEtection Neural architecture). LPREEN models colour opponent processes and feedback interactions between cortical areas V1, V2, V4, and IT, which produce top-down and bottom-up information fusion. We suggest three feedback interactions that enhance and complete boundaries. Our proposed neural model contains a contour learning feedback that enhances the most probable contour positions in V1 according to a previous experience, and generates a surface perception in V4 through diffusion processes. We compared the proposed model with another bio-inspired model and two well-known contour extraction methods, using the Berkeley Segmentation Benchmark. LPREEN showed better performance than two methods and slightly worse performance than another one.     

基于医学图像的复杂曲面重建

为了更准确地重建复杂的三维医学数据模型,把二维医学图像轮廓线上的像素点转化为三维点云,引入经典的泊松点云重建技术。由于泊松重建的效果依赖于点云法向的准确性,针对轮廓线数据的特点,结合图像二维梯度方向,给出了点云法向的一致定向及基于已知定向进一步精确估计法向的方法。泊松重建方法作为一种隐式重建技术,可以很好地处理医学图像数据中经常存在的噪声、拓扑复杂等问题。鼻咽喉模型重建的结果说明,一致定向方法改进了传统的一致定向方法,得到了更为准确的医学重建模型。     

Distance field manipulation of surface models

A surface manipulation technique that uses distance fields-scalar fields derived geometrically from surface models-to combine, modify, and analyze surfaces is presented. It is intended for application to complex models arising in scientific visualization. Computing distance from single triangles is discussed, and an optimized algorithm for computing the distance field from an entire closed surface is built. The use of the fields for surface removal, interpolation and blending is examined. The strength of the approach is that it lets simple 3D algorithms substitute for potentially very complex 2D methods     

Estimation of sea surface currents based on ocean colour remote-sensing image analysis

Accurate quantification of the sea surface current speeds with high spatial resolution and in near real-time is beneficial for many applications of physical oceanography, and can be implemented by processing ocean colour remote-sensing imagery data. The robust optical flow (ROF) approach applied to sub-image processing is described in detail in this article, and compared with a conventional maximum cross-correlation (MCC) block matching algorithm with sub-pixel operation. ROF results obtained from Geostationary Ocean Colour Imager (GOCI) imagery are shown to be in good agreement with sea surface currents derived from Ocean Surface Current Analyses-Real time (OSCAR) data, providing a validation of the ROF method.     

Satellite observations of optical and biological properties in the Korean dump site of the Yellow Sea

With the standard near-infrared (NIR) atmospheric correction algorithm for ocean color data processing, a high chlorophyll-a concentration patch was consistently observed from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua platform in the middle of the Yellow Sea during the spring (end of March to early May). This prominent patch was not observed in the historical ocean color satellite imageries in late 1970s to early 1980s, and a location corresponding to this patch has been used as a Korean dump site since 1988. At the same time, MODIS chlorophyll-a concentrations derived using the shortwave infrared (SWIR) atmospheric correction algorithm developed for the ocean color satellite data in turbid coastal or high-productive ocean waters were significantly reduced.Comparison between in situ and MODIS chlorophyll-a measurements shows that the chlorophyll-a from the MODIS-Aqua products using the standard-NIR atmospheric correction algorithm is significantly overestimated. The images of the MODIS-derived normalized water-leaving radiance spectra and water diffuse attenuation coefficient data using the NIR-SWIR-based atmospheric correction approach show that absorption and scattering by organic and inorganic matter dumped in the Korean dump site have strongly influenced the satellite-derived chlorophyll-a data. Therefore, the biased high chlorophyll-a patch in the region is in fact an overestimation of chlorophyll-a values due to large errors from the standard-NIR atmospheric correction algorithm. Using the NIR-SWIR algorithm for MODIS-Aqua ocean color data processing, ocean color products from 2002 to 2008 for the Korean dump site region have been generated and used for characterizing the ocean optical and biological properties. Results show that there have been some important changes in the seasonal and interannual variations of phytoplankton biomass and other water optical and biological properties induced by colored dissolved organic matters, as well as suspended sediments.     

Spatial and temporal variability of satellite-derived sea surface temperature in the Barents Sea

The Barents Sea (BS) is an important region for studying climate change. This sea is located on the main pathway of the heat transported from low to high latitudes. Since oceanic conditions in the BS may influence vast areas of the Arctic Ocean, it is important to continue to monitor this region and analyse the available oceanographic data sets. One of the important quantities that can be used to track climate change is the sea surface temperature (SST). In this study, we have analysed the 32 years, (1982–2013) National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation SST Version 2 data for the BS. Our results indicate that the regionally averaged SST trend in the BS (about 0.03°C year^–1) is greater than the global trend. This trend varies spatially with the lowest values north from 76° N and the highest values (about 0.06°C year^–1) in proximity of Svalbard and in coastal regions near the White Sea. The SST and 2 m air temperature (AT) trends are high in winter months in the open BS region located west from Novaya Zemlya. Such trends can be linked to a significant retreat of sea ice in this area in recent years. In this article, we also documented spatial patterns in the annual cycle of SST in the BS. We have shown that the interannual variability of SST is similar in different regions of the BS and well correlated with the interannual patterns in AT variability.     

MEMS_DSC: a new device for microcalorimetric analysis in the biological field

The metabolism of cells is studied by scientists using a number of cells high enough to have a signal in the regular differential scanning calorimetry (DSC). Currently the number of cells necessary for thermal analysis is on the order of hundreds of thousands. The cell metabolism researchers have been trying to reduce this number with an eye on the final prize of sample size of one. In this paper, we report a novel MEMS_DSC (Micro Electro Mechanical System-Differential Scanning Calorimetry), which reduces the number of cells needed for analysis by about two orders of magnitude. It uses the Seebeck effect generated by a polysilicon n-gold junction to convert the temperature measured from cells directly into a voltage signal. To characterize the device a laser was used to heat the sensor; a lock-in amplifier, coupled with an optical chopper, allowed us to measure a very low heat power (25.5 nW).