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.     

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.     

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.     

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.     

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.     

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     

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.     

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.     

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).     

Interannual variability of the chlorophyll-a and sea surface temperature of the Black Sea

A comparative analysis of the Black Sea surface temperature and chlorophyll-a concentration was based on the satellite data (PODAAC JPL AVHRR Pathfinder and SeaWiFS) for 1998–2005. The fields of dispersion and spatial gradient were analysed as well. On the interannual scale, no statistical relationship was found between the field of sea surface temperature and chlorophyll-a. The mesoscale variability (which masked the statistical assessments of interannual coupling) was well pronounced in the fields of both parameters. For the deep part of the sea, a sign of the wave-type origin of the variability of chlorophyll-a and sea surface temperature was evaluated.     

Sea surface temperature GOES-8 estimation approach for the Brazilian coast

This work presents a quite consistent procedure for estimation of sea surface temperature (SST) using data from the new generation of the Geostationary Operational Environmental Satellite (GOES). The SST methodology is based on the classical split-window equation. The regional split-window coefficients (A ₀, A ₁, A ₂ and A ₃) are estimated by an algorithm regression taking as dependent variable three datasets, i.e. the SST derived from National Oceanic and Atmospheric Administration (NOAA)-14 polar-orbiting satellite and from buoys of Pilot Research Moored Array in Tropical Atlantic (PIRATA) and National Programme of Buoys (PNBOIA). This work shows that the main advantage of the GOES-8 SST algorithm, in comparison with the multi-channel sea surface temperature (MCSST) procedure using Advanced Very High Resolution Radiometer (AVHRR) data, is the high frequency sampling imagery (each half-hour) which permits a daily image with much less quantity of cloud contamination. The algorithm results using AVHRR/NOAA-14 as input dataset for the regression show that the accuracy of the GOES-8 SST algorithm is better than 1.0°C for all Brazilian coast. For regional estimation, the accuracy has been improved to around 0.5°C. Also, the accuracy of GOES-8 SST is better than 0.7°C using in situ SST collected from moored and drifting buoys.     

Sea surface motion over an anticyclonic eddy on the Oyashio Front

NOAA-6 AVHRR (11-μm band) satellite images for 20 and 21 May 1981 have been used with an interactive computer algorithm to calculate surface flow components from displacement of surface pattern features and elapsed time. The results give estimates of speed and direction for motion along the Oyashio Front and over an anticyclonic eddy between the First and Second Oyashio Intrusions. Speeds of 54 cm/s were detected along the Oyashio thermal ridge. On the periphery of the eddy, speeds in the order of 25 cm/s were present while, nearer the center, motion at 14 cm/s was indicated. A composite picture of flow vectors overlayed on the image for 20 May infers streamline flow characteristics for the surface motion and shows surface isolation of the eddy from the Tohoku area to the south.     

Establishing an objective basis for image compositing in satellite oceanography

This study strives to establish an objective basis for image compositing in satellite oceanography. Image compositing is a powerful technique for cloud filtering that often emphasizes cloud clearing at the expense of obtaining synoptic coverage. Although incomplete cloud removal in image compositing is readily apparent, the loss of synopticity, often, is not. Consequently, the primary goal of image compositing should be to obtain the greatest amount of cloud-free coverage or clarity in a period short enough that synopticity, to a significant degree, is preserved.To illustrate the process of image compositing and the problems associated with it, we selected a region off the coast of California and constructed two 16-day image composites, one, during the spring, and the second, during the summer of 2006, using Advanced Very High Resolution Radiometer (AVHRR) InfraRed (IR) satellite imagery. Based on the results of cloud clearing for these two 16-day sequences, rapid cloud clearing occurred up to day 4 or 5, followed by much slower cloud clearing out to day 16, suggesting an explicit basis for the growth in cloud clearing. By day 16, the cloud clearing had, in most cases, exceeded 95%. Based on these results, a shorter compositing period could have been employed without a significant loss in clarity.A method for establishing an objective basis for selecting the period for image compositing is illustrated using observed data. The loss in synopticity, which, in principle, could be estimated from pattern correlations between the images in the composite, was estimated from a separate time series of SST since the loss of synopticity, in our approach, is only a function of time. The autocorrelation function of the detrended residuals provided the decorrelation time scale and the basis for the decay process, which, together, define the loss of synopticity. The results show that (1) the loss of synopticity and the gain in clarity are inversely related, (2) an objective basis for selecting a compositing period corresponds to the day number where the decay and growth curves for synopticity and clarity intersect, and (3), in this case, the point of intersection occurred 3.2 days into the compositing period. By applying simple mathematics it was shown that the intersection time for the loss in synopticity and the growth in clarity is directly proportional to the initial conditions required to specify the clarity at the beginning of the compositing period, and inversely proportional to the sum of the rates of growth for clarity and the loss in synopticity. Finally, we consider these results to be preliminary in nature, and, as a result, hope that future work will bring forth significant improvements in the approach outlined in this study.     

The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates

In this paper, uncertainties in the retrieval of satellite surface chlorophyll concentrations in the Mediterranean Sea have been evaluated using both regional and global ocean colour algorithms. The rationale for this effort was to define the most suitable ocean colour algorithm for the reprocessing of the entire SeaWiFS archive over the Mediterranean region where standard algorithms were demonstrated to be inappropriate. Using a large dataset of coincident in situ chlorophyll and optical measurements, covering most of the trophic regimes of the basin, we validated two existing regional algorithms [Bricaud, A., E. Bosc, and D. Antoine, 2002. Algal biomass and sea surface temperature in the Mediterranean Basin — Intercomparison of data from various satellite sensors, and implications for primary production estimates. Remote Sensing of Environment, 81(2-3), 163-178.; D'Ortenzio, F., S. Marullo, M. Ragni, M. R. d'Alcala and R. Santoleri, 2002. Validation of empirical SeaWiFS algorithms for chlorophyll-alpha retrieval in the Mediterranean Sea — A case study for oligotrophic seas. Remote Sensing of Environment, 82(1), 79-94.] and the global algorithm OC4v4 used for standard NASA SeaWiFS products. The results of our analysis confirmed that the OC4v4 performs worse than the two existing regional algorithms. Nonetheless, these two regional algorithms do show uncertainties dependent on chlorophyll values. Then, we introduced a better tuned algorithm, the MedOC4. Using an independent set of in situ chlorophyll data, we quantified the uncertainties in SeaWiFS chlorophyll estimates using the existing and new regional algorithms. The results confirmed that MedOC4 is the best algorithm matching the requirement of unbiased satellite chlorophyll estimates and improving the percentage of the satellite uncertainty, and that the NASA standard chlorophyll products are affected by an uncertainty of the order of 100%. Moreover, the analysis suggests that the poor quality of the SeaWiFS chlorophyll in the Mediterranean is not due to the atmospheric correction term but to peculiarities in the optical properties of the water column. Finally the observed discrepancy between the global and the regional bio-optical algorithms has been discussed analysing the differences between the two in situ datasets used for tuning the algorithms (SeaBASS versus ours). The main results are that methodological differences in the two datasets cannot play a major role and the inherent bio-optical properties of the basin can explain the observed discrepancy. In particular the oligotrophic water of the Mediterranean Sea is less blue (30%) and greener (15%) than the global ocean.     

Sea ice surface features in Arctic summer 2008: Aerial observations

Eight helicopter flights were conducted, and more than 9000 aerial images were obtained during the Third Chinese National Arctic Research Expedition in 2008 in the Pacific Arctic Sector (PAS). Along the cruise tracks between 77°N and 86°N, area fractions of open water and ice cover varied from 0.96 to 0.12 and from 0.03 to 0.81, respectively, while the melt pond fraction varied between 0 and 0.2. The ice concentrations derived from aerial images and the AMSR-E/ASI products were comparable to each other, especially in the range of 50-90%. However, the satellite-derived data overestimated the aerial observations by 14 ± 9% in areas with large ice concentrations (> 90%), and nearly ignored those with very low ice concentrations (< 20%). In addition, a significantly higher amount of melt ponds was observed in the PAS in the summer of 2008 as compared to five years ago. The areally averaged albedo increased from 0.09 in the marginal ice zone at 77°N to 0.63 in the far north zone at 86°N, where the ice concentration was 90%. The albedo was significantly smaller than those reported in earlier studies in the PAS for the same region because of an overall decrease in ice concentration. Compared with 2007 data, the lower ice concentration in 2008 may yield a smaller total ice-covered area, although the Arctic ice extent in 2008 was slightly larger than the record minimum in 2007.