An aerial photography has been used to provide validation data on sea ice near the North Pole where most polar orbiting satellites cannot cover. This kind of data can also be used as a supplement for missing data and for reducing the uncertainty of data interpolation. The aerial photos are analyzed near the North Pole collected during the Chinese national arctic research expedition in the summer of 2010 (CHINARE2010). The result shows that the average fraction of open water increases from the ice camp at approximately 87°N to the North Pole, resulting in the decrease in the sea ice. The average sea ice concentration is only 62.0% for the two flights (16 and 19 August 2010). The average albedo (0.42) estimated from the area ratios among snow-covered ice, melt pond and water is slightly lower than the 0.49 of HOTRAX 2005. The data on 19 August 2010 shows that the albedo decreases from the ice camp at approximately 87°N to the North Pole, primarily due to the decrease in the fraction of snow-covered ice and the increase in fractions of melt-pond and open-water. The ice concentration from the aerial photos and AMSR-E (The Advanced Microwave Scanning Radiometer-Earth Observing System) images at 87.0°-87.5°N exhibits similar spatial patterns, although the AMSR-E concentration is approximately 18.0% (on average) higher than aerial photos. This can be attributed to the 6.25 km resolution of AMSR-E, which cannot separate melt ponds/submerged ice from ice and cannot detect the small leads between floes. Thus, the aerial photos would play an important role in providing high-resolution independent estimates of the ice concentration and the fraction of melt pond cover to validate and/or supplement space-borne remote sensing products near the North Pole.

Sea-ice physical characteristics were investigated in the Arctic section of 143°-180°W during August and early September 2008. Ship-based observations show that both the sea-ice thickness and concentration recorded during southward navigation from 30 August to 6 September were remarkably less than those recorded during northward navigation from 3 to 30 August, especially at low latitudes. Accordingly, the marginal ice zone moved from about 74.0°N to about 79.5°N from mid-August to early September. Melt-pond coverage increased with increasing latitude, peaking at 84.4°N, where about 27% of ice was covered by melt ponds. Above this latitude, melt-pond coverage decreased evidently as the ice at high latitudes experienced a relatively short melt season and commenced its growth stage by the end of August. Regional mean ice thickness increased from 0.8 (±0.5) m at 75.0°N to 1.5 (±0.4) m at 85.0°N along the northward navigation while it decreased rapidly to 0.6 (±0.3) m at 78.0°N along the southward navigation. Because of relatively low ice concentration and thin ice in the investigated Arctic sector, both the short-term ice stations and ice camp could only be set up over multiyear sea ice. Observations of ice properties based on ice cores collected at the short-term ice stations and the ice camp show that all investigated floes were essentially isothermal with high temperature and porosity, and low density and salinity. Most ices had salinity below 2 and mean density of 800-860 kg/m³. Significant ice loss in the investigated Arctic sector during the last 15 a can be identified by comparison with the previous observations.

The algorithms of extracting chlorophyll-a (Chl-a) concentration have been established for Chinese moderate resolution imaging spectrometer (CMODIS) mounted on Shenzhou-3 spaceship launched on 25 March 2002.The CMODIS is an ocean color sensor with 30 visible channels and 4 infrared channels, much different from other ocean color satellites and needs new algorithms to process data.Three models of Chl-a concentration were established based on Chl-a data retrieved from sea-viewing wide field-of-view sensor (SeaWiFS), with the average relative errors of 26.6%, 24%.0% and 33.5%, respectively.This practical and economic approach can be used for developing the algorithms of Chinese ocean color and temperature sensor (COCTS) on the satellite Haiyang-1 to derive the Chl-a concentration concentration distribution.The applicability of the algorithms was analyzed using some in situ measurements.Suspended sediment is the main factor influencing the accuracy of the spectral ratio algorithms of Chl-a concentration.The algorithms are suitable to using in the regions where suspended sediment concentrations (SSC) are less than 5 g/m³ under the condition of relative error of Chl-a concentration retrieval within 35%.High concentration of suspended sediment leads to the overestimate remote sensing retrieval of concentration of Chl-a, while low-middle SSCs lead to the low Chl-a concentration values using the spectral ratio algorithms.Since the accuracy of Chl-a concentration by the spectral ratio algorithms is limited to waters of Case 2, it is necessary to develop semi-analytical models to improve the performance of satellite ocean color remote sensing in turbid coastal waters.

A biooptical modeling, which is based on a radiation transfer model, can be employed to simultaneously retrieve the concentration of various colour factors by multi-spectral remote sensing data, after connecting inherent optical properties (absorption coefficient and backward scattering coefficient) of colour factor with apparent optical properties (remote sensing reflectivity). At present, this method has been used in a relatively wide range of applications in the inversion of a conventional water colour factor concentration in the case II water body: applications such as chlorophyll, suspended sediment, yellow substance. On the basis of extensive field testing data of water quality, correspondingly apparent optical properties, and the full use of the existing parametric model of colour factor inherent optical properties (with the parametrization of petroleum substance inherent optical properties established in the project) the remote recognition model for oil concentration is established by introducing oil as a new water colour factor into a biooptical remote algorithm. The estimated value of the oil concentration was obtained by solving the biooptical model, using the data measured in May 2008 and August 2009 and June 2010 in seawater. The highly accurate inversion result promises to estimate the oil concentration in water for remote sensing.

The chlorophyll-a concentration is generally overestimated for the southern China coastal waters if the default algorithm of the SeaDAS is employed.An algorithm is developed for retrieval of chlorophyll-a concentration in the Zhujiang Estuary,Guangdong Province,China,by using simulated reflectance data.The simulated reflectance is calculated corresponding to the SeaWiFS wavelength bands,via a general model by inputting measured water components,i.e.,the suspended sediment,chlorophyll-a,and yellow substance (DOC) concentration data of 130 samples.Empirical relationships of the chlorophyll-a concentration to 240 different band combinations are investigated based on the simulated reflectance data,and the band combination,R₅R₆/R₃R₄,is found to be the optimum one for the development of an algorithm valid for the Zhujiang Estuary.This algorithm is then employed to determine the chlorophyll-a concentration from SeaWiFS data.The estimated concentrations have a better accuracy than those obtai obtained from the SeaDAS default algorithm when compared with sea truth data.The new algorithm is d}on_strated to work well and is used to derive a series of image maps of the chlorophyll-a concentration distribution for the Zhujiang Estuary and adjacent coastal areas.

According to data obtained in the Bering Sea during the 4th Chinese National Arctic Research Expedition, the distribution of dissolved oxygen (DO) was studied, causes of its maximum concentration were discussed, and the relationships between DO and other parameters, such as salinity, temperature, and chlorophyll a were analyzed. The results showed DO concentration ranged from 0.53 to 12.05 mg/L in the Bering Sea basin. The upper waters contained high concentrations and the maximum occurred at the depth range from 20 to 50 m. The DO concentration decreased rapidly when the depth was deeper than 200 m and reached the minimum at the depth range from 500 to 1 000 m, and then increased slowly with the depth increasing but still kept at a low level. On the shelf, the DO concentration ranged from 6.53 to 16.63 mg/L with a mean value of 10.75 mg/L, and showed a characteristic of decreasing from north to south. The DO concentration was higher in the area between the Bering Sea and Lawrence Island and was lower in the southeast and southwest of Lawrence Island at the latitude of 62°N. The formation of maximum DO concentration was concerned with phytoplankton photosynthesis and formation of the themocline. To the south of Sta. B07 in the Bering Sea basin, the oxygen produced by photosynthesis permeated to the deeper water and the themocline made it difficult to exchange vertically, and to the north of Sta. B07, the maximum DO concentration occurred above the themocline due to phytoplankton activities. On the shelf, the oxygen produced by phytoplankton photosynthesis gathered at the bottom of the thermocline and formed the DO maximum concentration. In the Bering Sea basin, the DO and salinity showed a weak negative correlation (r=0.40) when the salinity was lower than 33.1, a significant negative correlation (r=0.92) when the salinity ranged from 33.1 to 33.7, and an irregular reversed parabola (r=0.95) when the salinity was greater than 33.7.

A one-dimensional photochemical model with parameterized vertical eddy diffusion is used to simulate the dimethyl sulfide (DMS) in the marine atmospheric boundary layer near the equator.The boundary condition of the DMS flux over sea surface is assigned from gas exchange models that depend on sea surface wind speed and DMS concentration in surface water.Photolysis rates at various altitudes are calculated as a function of solar zenith angle, and the radiation calculation includes ozone absorption, surface reflection and molecular scattering.
The simulated results of the DMS diurnal cycle are in good agreement with the observations.Sensitivity tests of the model indicate that the concentration of the DMS in the marine surface layer appears to be affected by a combination of chemical processes and meteorological conditions.In addition, photochemical processes are rather important.The reaction of the DMS with.OH radical, the heterogeneous conversion of SO₂ and the deposition of NSS-SO₄^- and the methanesulfonic acid (MSA) are critical factors of controlling the DMS, SO₂, NSS-SO₄^- and the MSA concentrations and distributions in the atmosphere.The DMS concentration in air is directly proportional to surface wind speed, but it is inversely proportional to boundary layer height in the convective boundary layer.The distributions of the DMS concentrations in sir are strongly influenced by atmospheric stratification in stable conditions.

The sea ice concentration observation from satellite remote sensing includes the spatial multi-scale information. However, traditional data assimilation methods cannot better extract the valuable information due to the complicated variability of the sea ice concentration in the marginal ice zone. A successive corrections analysis using variational optimization method, called spatial multi-scale recursive filter (SMRF), has been designed in this paper to extract multi-scale information resolved by sea ice observations. It is a combination of successive correction methods (SCM) and minimization algorithms, in which various observational scales, from longer to shorter wavelengths, can be extracted successively. As a variational objective analysis scheme, it gains the advantage over the conventional approaches that analyze all scales resolved by observations at one time, and also, the specification of parameters is more convenient. Results of single-observation experiment demonstrate that the SMRF scheme possesses a good ability in propagating observational signals. Further, it shows a superior performance in extracting multi-scale information in a two-dimensional sea ice concentration (SIC) experiment with the real observations from Special Sensor Microwave/Imager SIC (SSMI).

The general features of the Great Whirl (GW) off the Somali Coast in 2017 and its influences on chlorophyll a (Chl a) concentration were studied by using satellite data and model outputs. Results show that GW, which initiated at 7°N, 53°E on June 13, had a lifetime of 153 d with an average amplitude of 16 cm and an average radius of 205 km. After the formation of GW, the concentration of Chl a in the interior of GW showed a downward trend throughout its life cycle, except in early July and mid-October. In early July, the Chl a blooms in the interior of GW were attributed to the combined effect of three processes. They are eddy horizontal transportation, the deepening of the mixed layer caused by the monsoon and eddy pumping, and the upward transportation of nutrients caused by eddy-induced Ekman pumping. In October, the Chl a blooms were probably due to the weakening of GW. During the period, water exchange occurred more frequently across the eddy, thus phytoplanktons were imported into the interior of GW.

The effects of biological heating on the upper-ocean temperature of the global ocean are investigated using two ocean-only experiments forced by prescribed atmospheric fields during 1990–2007, on with fixed constant chlorophyll concentration, and the other with seasonally varying chlorophyll concentration. Although the existence of high chlorophyll concentrations can trap solar radiation in the upper layer and warm the surface, cooling sea surface temperature (SST) can be seen in some regions and seasons. Seventeen regions are selected and classified according to their dynamic processes, and the cooling mechanisms are investigated through heat budget analysis. The chlorophyll-induced SST variation is dependent on the variation in chlorophyll concentration and net surface heat flux and on such dynamic ocean processes as mixing, upwelling and advection. The mixed layer depth is also an important factor determining the effect. The chlorophyll-induced SST warming appears in most regions during the local spring to autumn when the mixed layer is shallow, e.g., low latitudes without upwelling and the mid-latitudes. Chlorophyll-induced SST cooling appears in regions experiencing strong upwelling, e.g., the western Arabian Sea, west coast of North Africa, South Africa and South America, the eastern tropical Pacific Ocean and the Atlantic Ocean, and strong mixing (with deep mixed layer depth), e.g., the mid-latitudes in winter.