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Based on the NASA Bio-Optical Marine Algorithm Dataset and in situ datasets collected from the East China Sea and Lake Qiandaohu, a novel approach was developed to analytically retrieve the absorption coefficient of chromophoric dissolved organic matter (aCDOM) in non-turbid waters. This approach comprised two parts: (1) a green–red band quasi-analytical algorithm, used to accurately derive the total absorption coefficient (a); and (2) the use of the retrievals from (1) are to semi-analytically retrieve aCDOM. This approach for partitioning aCDOM from a was based on the blue band line height at 443 nm, LH(443), which uses the summed absorption coefficients of phytoplankton and CDOM (aphc) at three characteristic wavelengths (412, 443 and 490 nm). This proposed algorithm was then tested and validated using the three datasets. The algorithm was found to perform reasonably well in retrieving aCDOM, with respective mean R2 and mean absolute percentage error (MAPE) values of 0.84 and 42.8%, compared with 0.64 and 72.9% for the empirical model and 0.40 and 66.2% for the extended quasi-analytical algorithm. Furthermore, the algorithm was able to retrieve aCDOM from Medium Resolution Imaging Spectrometer (MERIS) satellite data. One implication for the MERIS satellite data, which exhibit reasonable seasonal variability over the East China Sea, is that it can be used to explore biogeochemical effects on aquatic environments.

Cyclone Nilofar was the third-strongest cyclone in the Arabian Sea. It was a category 4 cyclone that arrived in last week of October 2014. It lingered in the Arabian Sea for 10 days and caused a si...

Marine phytoplankton accounts for roughly half the planetary primary production, and plays significant roles in marine ecosystem functioning, physical and biogeochemical processes, and climate changes. Documenting phytoplankton assemblages' dynamics, particularly their community structure properties, is thus a crucial and also challenging task. A large number of in situ and space-borne observation datasets are collected that cover the marginal seas in the west Pacific, including Bohai Sea, Yellow Sea, and East China Sea. Here, a customized region-specific semi-analytical model is developed in order to detect phytoplankton community structure properties (using phytoplankton size classes, PSCs, as its first-order delegate), and repeatedly tested to assure its reliable performance. Independent in situ validation datasets generate relatively low and acceptable predictive errors (e.g., mean absolute percentage errors, MAPE, are 38.4%, 22.7%, and 34.4% for micro-, nano-, and picophytoplankton estimations, respectively). Satellite synchronization verification also produces comparative predictive errors. By applying this model to long time-series of satellite data, we document the past two-decadal (namely from 1997 to 2017) variation on the PSCs. Satellite-derived records reveal a general spatial distribution rule, namely microphytoplankton accounts for most variation in nearshore regions, when nanophytoplankton dominates offshore water areas, together with a certain high contribution from picophytoplankton. Long time-series of data records indicate a roughly stable tendency during the period of the past twenty years, while there exist periodical changes in a short-term one-year scale. High covariation between marine environment factors and PSCs are further found, with results that underwater light field and sea surface temperature are the two dominant climate variables which exhibit a good ability to multivariate statistically model the PSCs changes in these marginal seas. Specifically, three types of influence induced by underwater light field and sea surface temperature can be generalized to cover different water conditions and regions, and meanwhile a swift response time (approximately 1 month) of phytoplankton to the changing external environment conditions is found by the wavelet analysis. This study concludes that phytoplankton community structures in the marginal seas remain stable and are year-independent over the past two decades, together with a short-term in-year cycle; this change rule need to be considered in future oceanographic studies.

Satellite remote sensing of inland water body requires a high spatial resolution and a multiband narrow spectral resolution, which makes the fusion between panchromatic (PAN) and multi-spectral (MS) images particularly important. Taking the Daquekou section of the Qiantang River as an observation target, four conventional fusion methods widely accepted in satellite image processing, including pan sharpening (PS), principal component analysis (PCA), Gram-Schmidt (GS), and wavelet fusion (WF), are utilized to fuse MS and PAN images of GF-1. The results of subjective and objective evaluation methods application indicate that GS performs the best, followed by the PCA, the WF and the PS in the order of descending. The existence of a large area of the water body is a dominant factor impacting the fusion performance. Meanwhile, the ability of retaining spatial and spectral informations is an important factor affecting the fusion performance of different fusion methods. The fundamental difference of reflectivity information acquisition between water and land is the reason for the failure of conventional fusion methods for land observation such as the PS to be used in the presence of the large water body. It is suggested that the adoption of the conventional fusion methods in the observing water body as the main target should be taken with caution. The performances of the fusion methods need re-assessment when the large-scale water body is present in the remote sensing image or when the research aims for the water body observation.

Qiandao Lake is located in the northern edge of subtropics, and its water body is thermally stratified in summer. It is of great scientific significance to study the vertical physical and chemical indexes and phytoplankton characteristics of the Qiandao Lake to reveal the aquatic ecosystem structure of the thermally stratified lake. Conventional observation uses in-situ profile instruments, which is time consuming and labor intensive. In recent years, lidar has shown increasing oceanic applications; however, it has not yet been extensively applied in inland water. There are no studies using lidar for detecting subsurface plankton layer in Qiandao Lake. In this study, we investigated the applicability of this technology for identifying subsurface plankton layer. A simple and fast phytoplankton layer detection method was introduced. The lidar-detected layer was found to well correspond with that of the in-situ measured subsurface chlorophyll maximum layer (SCML) and phycocyanin maximum layer. Primary results show that lidar and our detection method are effective for subsurface phytoplankton layer detection. They can serve as a good monitoring tool for studying inland water stratification.

Coupled nitrogen cycling processes can alleviate the negative effects of eutrophication caused by excessive nitrogen load in estuarine ecosystems. The abundance and diversity of nitrifiers and denitrifiers across different environmental gradients were examined in the sediment of Hangzhou Bay. Quantitative PCR and Pearson's correlation analyses suggested that the bacterial ammonia-oxidizers (AOB) were the dominant phylotypes capable of ammonia oxidation, while the nirS-encoding denitrifiers predominated in the denitrification process. Simultaneously, nitrite and pH were found to be the two major factors influencing amoA and nir gene abundances, and the distribution of bacterial communities. Moreover, the ratio of nirS/AOB amoA gene abundance showed negative correlation with nitrite concentration. Fluorescence in situ hybridization further demonstrated that AOB and acetate-denitrifying cells were closely connected and formed obvious aggregates in the sediment. Together, all these results provided us a preliminary insight for coupled nitrification-denitrification processes in the sediment of Hangzhou Bay.

The critical angle at which the brightness of oil slicks and oil-free seawater is reversed occurs under sunglint and is often shown as an area of uncertainty due to different roughness and surface Fresnel reflection parameters. Consequently, differentiating oil slicks from the seawater in these areas using optical sensors is a challenge. Polarized optical remote sensing techniques provide complementary information for intensity imagery with different physical properties and, thus, possess the ability to resolve this difficult problem. In the polarized reflectance model, the degree of linear polarization (DOLP) of sunglint depends on accurately knowing the Stokes parameter for the reflected light, and varies with the refractive index of the surface layer and the viewing angles. For the polarized detection of oil slicks, the highest sensitivity of the DOLP to the refractive index is located within the specular reflection direction where the sum of the solar and sensor zenith angles is 82.6°. The modeled results clearly indicate that the DOLP of oil slicks is weaker in comparison with oil-free seawater under sunglint. Using measurements from the space-borne Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) over the Deepwater Horizon oil spill in the Gulf of Mexico, we illustrate that the PARASOL-derived DOLP difference between the oil spill and seawater is obvious and is in accordance with the modeled results. These preliminary results suggest that the potential of multi-angle measurement and feasibility of deriving refractive index of ocean surface from space-borne sensors need further researches.

The potential for a ship-mounted laser fluorometer to provide rapid, non-intrusively measurements in both coastal and lake conditions are investigated. The instrument consists of a high pulse repetition frequency (10-kHz) microchip laser for fluorescence excitation, a broadband hyperspectral micro spectrometer for spectral detection, and a confocal reflective fluorescent probe for signal collection; it weighs only about 1.7kg. Chlorophyll a (chl-a) and colored dissolved organic matter (CDOM) measured by the new instrument were observed to agree well with those measured by traditional time-consuming laboratory methods in Hangzhou Bay seawater and Qiandao Lake inland water. Subsequently, laser fluorescence distribution and characteristics of chl-a and CDOM in these regions were analyzed, which will improve our understanding of biogeochemical processes in these optically complex aquatic systems. The portable system is promising for water environment monitoring, especially in coastal and inland water.

Off the Yangtze River Estuary and its adjacent waters (the YRE) are one of the fastest changing regions in the world in terms of the effects of anthropogenic disturbance. Here we address quantitative analysis whether reducing river to sea sediment may cause declining water turbidity then a better light available condition for the algal growth, therefor increasing phytoplankton bloom magnitude in the YRE in the bloom season. An area of high phytoplankton productivity zone is estimated by theoretical and satellite data analysis, which matches well with the spatial distribution of accumulative times of the reported algal bloom events at the decadal time scale. We present 17-year (1998–2014) satellite and hydrological data to reveal an increasing trend in Chlorophyll-a concentration (Chl-a) in the spring bloom season (May to June), which has strong correlation with the decreasing in the sediment discharge from the Yangtze river to the East China Sea. Changes in Chl-a and the sediment load are inversely related in terms of both temporal variation and their corresponding magnitudes (R 2 =0.38, p=0.008, n=17). Furtherly, this relationship is not sensitivity to one-year time lag analysis. On the other hand, euphotic depth in the bloom period shows no significant change, which reflects a balance between the increasing phytoplankton biomass enhancing water turbidity and declining riverine sediment decreasing turbidity. Finally, a stepwise multiple linear regression is used to determine which of the five relatively independent environmental variables most significantly contribute to the interannual variability of the bloom magnitude. The most significant effect (p=0.00007) is also found in the riverine sediment load. Therefor, our results suggest that anthropogenic derived riverine sediment change has been significantly impacted spring phytoplankton production in the YRE.

A new bio-optical algorithm based on the green and red bands of the Medium Resolution Imaging Spectrometer (MERIS) is developed to differentiate the harmful algal blooms of Prorocentrum donghaiense Lu (P. donghaiense) from diatom blooms in the East China Sea (ECS). Specifically, a novel green-red index (GRI), actually an indicator for a(510) of bloom waters, is retrieved from a semi-analytical bio-optical model based on the green and red bands of phytoplankton-absorption and backscattering spectra. In addition, a MERIS-based diatom index (DIMERIS) is derived by adjusting a Moderate Resolution Imaging Spectroradiometer (MODIS) diatom index algorithm to the MERIS bands. Finally, bloom types are effectively differentiated in the feature spaces of the green-red index and DIMERIS. Compared with three previous MERIS-based quasi-analytical algorithm (QAA) algorithms and three existing classification methods, the proposed GRI and classification method have the best discrimination performance when using the MERIS data. Further validations of the algorithm by using several MERIS image series and near-concurrent in-situ observations indicate that our algorithm yields the best classification accuracy and thus can be used to reliably detect and classify P. donghaiense and diatom blooms in the ECS. This is the first time that the MERIS data have been used to identify bloom types in the ECS. Our algorithm can also be used for the successor of the MERIS, the Ocean and Land Color Instrument, which will aid the long-term observation of species succession in the ECS. This article is protected by copyright. All rights reserved.

Using ten years (2003–2012) of satellite Chlorophyll-a data, we report that annual phytoplankton bloom climax in the Northwest Pacific marginal seas (17°–58°N) delays northward at a rate of 22.98 ± 2.86 km day−1. The spring bloom is a dominant feature of the phytoplankton seasonal cycle in this region, except for the northern South China Sea, which features a winter bloom. The sea surface hourly Photosynthetically Available Radiation (PAR) intensity averaged over the bloom peak duration is nearly uniform (1.04 ± 0.10 W m−2 h−1) among the four sub-regions (i.e. the northern South China Sea, the Kuroshio waters, the Sea of Japan and the Sea of Okhotsk), although different algal species in these four distinct ecological provinces could adapt to a much larger change in other environmental parameters (including total daily PAR, day length, sea surface temperature, net surface heat flux, mixed layer depth, wind speed and euphotic depth). The differences of the hourly PAR intensity between the four provinces during their bloom periods are smaller than those during non-bloom seasons. In contrast, an increasing total daily PAR (W m−2 day−1), due to the longer day length at higher latitudes, may balance decreasing sea surface temperature and induce algal flowering. Our results point to an optimal hourly light intensity for the annual phytoplankton bloom peak timing in this entire region, which could potentially become an indicator for the requirement of these annual bloom peaks.

Sea surface salinity of ocean waters has been obtained from L-band microwave radiometer on satellite, such SMOS, Aquarius and SMAP. It provides a new technology and way to observe the salinity over large region from space. However, it is still difficult to get the sea surface salinity of the coastal waters due to that the effect on satellite-observed microwave radiance of radio frequency interference over near-shore regions. Fortunately, the colored dissolved organic matter (CDOM) has conservative or semi-conservative property in the freshwater areas of coastal rivers and it has a good linear correlation between the absorption coefficient of CDOM and salinity. Based on those, a conservative mixing relationship between the fresh water from the Pearl River and the sea water from the South China Sea are established and the distribution of sea surface salinity from MODIS-retrieved absorption coefficient of CDOM (aCDOM) at 355nm wavelength in this study. The linear relationship between salinity and aCDOM at 355 nm under conservative mixing conditions can be established from the in-situ observed salinity and MODIS-retrieved aCDOM at 355 nm at the central water mass in the Pearl River Estuary and the northern basin region of South China Sea. By comparing daily observed MODIS-retrieved sea surface salinity with the in-site observed salinity, it shows that the salinity retrieved from satellite-based aCDOM has good agreement with observations, and it can better capture the location of low salinity fresh water in the Pearl River. For the summer averaged satellite-based salinity from 2002 to 2018, sea surface salinity are gradually increases from the vertical coastline to the sea in the Pearl River Estuary region. The salinity in coastal region is low by the effect of the Pearl River diluted water, and the salinity in offshore region is high. On average, the distribution of salinity shows that the diffusion of fresh water from the Pearl River generally spread along the coastline to the east and west in summer, while the runoff on the westward is larger and on the eastward it is affected by some flushing water of other rivers. In the future, MODIS-retrieved salinity can be as a supplement to salinity inversion of Microwave radiometer in the coastal region.

Knowledge about the spatiotemporal distribution of sea surface salinity (SSS) provides valuable and important information for understanding various marine biogeochemical processes and ecosystems, especially for those coastal waters significantly affected by human activities. Remote-sensing techniques have been used to monitor salinity in the open ocean with their advantages of wide-area surveys and real-time monitoring. However, potential challenges remain when using satellite data with coarse spatiotemporal resolutions, leading to a loss of valuable information. In the current study, based on the local dataset collected over the southern Yellow Sea (SYS), a region-customized algorithm was developed to estimate SSS by using the remote sensing reflectance. The model evaluations indicated that our algorithm yielded good SSS estimation, with a root-mean-square error (RMSE) of 0.29 psu and a mean absolute percentage error (MAPE) of 0.75%. Satellite-derived SSS results compared well with those derived from in situ observations, further suggesting the good performance of our developed algorithm for the study regions. We applied this algorithm to Geostationary Ocean Color Imager (GOCI) data for the month of August from 2011 to 2018 in the SYS, and produced the spatial distribution patterns of the SSS for August of each year. The SSS values were high in offshore waters and lower in coastal waters, especially in the Yangtze River estuary. The negative correlation between the monthly Changjiang River discharge (CRD) and SSS (R = −0.71, p < 0.001) near the Yangtze River estuary was observed, suggesting that the SSS distribution in the Yangtze River estuary was potentially influenced by the CRD. In offshore waters, the correlation between SSS and CRD was weak (R < 0.2), suggesting that the riverine discharge’s effect might be weak.

Combined studies of latitudinal and interannual variations of annual phytoplankton bloom peak in East Asian marginal seas (17°–58°N, including the northern South China Sea (SCS), Kuroshio waters, the Sea of Japan and the Okhotsk Sea) are rarely. Based on satellite-retrieved ten-year (2003–2012) median timing of the annual Chlorophyll a concentration (Chl a) climax, here we report that this annual spring bloom peak generally delays from the SCS in January to the Okhotsk Sea in June at a rate of (21.20±2.86) km/d (decadal median±SD). Spring bloom is dominant feature of the phytoplankton annual cycle over these regions, except for the SCS which features winter bloom. The fluctuation of the annual peak timing is mainly within ±48 d departured from the decadal median peak date, therefore this period (the decadal median peak date ±48 d) is defined as annual spring bloom period. As sea surface temperature rises, earlier spring bloom peak timing but decreasing averaged Chl a biomass in the spring bloom period due to insufficient light is evident in the Okhotsk Sea from 2003 to 2012. For the rest of three study domains, there are no significant interannual variance trend of the peak timing and the averaged Chl a biomass. Furthermore this change of spring phytoplankton bloom timing and magnitude in the Okhotsk Sea challenges previous prediction that ocean warming would enhance algal productivity at high latitudes.

The concentration of total suspended matter (TSM) at the sea surface is derived from satellite data using a complex proxy TSM model in East China Sea from 1997 to 2008. The structure of the mean TSM image is similar to that of the topography, indicating that the distribution of the surface concentration is strongly related to the water depth. A dynamic sediment model (DSM) is constructed to relate the TSM concentration at the sea surface with suspended sediment at the benthic boundary layer, the Rouse number, and the water depth. The DSM model is improved through iteration with a convergence identified by the mean relative difference between two adjacent bottom TSM images which becomes smaller with the more iterations and the value is less than 1% after 50 iterations. The performance of the DSM model is validated by satellite-measured concentration with a mean relative error of 5.2% for the monthly mean images. The DSM model is used to deduce the bottom TSM concentration at the benthic boundary layer and the distribution of the Rouse number. The spatial distribution of the sea surface TSM concentration is determined predominately by both the bottom suspended sediment concentration and water depth. The temporal variation of the sea surface concentration mainly depends upon the Rouse number in the water column. Our result shows that the discharge of the Changjiang River can change the distribution of the Rouse number to form a band-shaped region in the Changjiang Estuary. The DSM model provides a framework for understanding some of the mechanisms of the formation and variation of the primary TSM plume and the secondary plume in the ECS. The primary TSM plume corresponds approximately to the region with depth shallower than 20 m and the secondary plume corresponds to the region with depths between 20 and 50 m.

In recent years, airborne lidar has been used in a wide range of oceanic applications, including detection of bathymetry, bubbles, internal waves, and schools of fish. However, it has not yet been extensively applied in Chinese seas. For example, there have been no studies to detect subsurface plankton layers in the South China Sea (SCS) by airborne lidar. In this study, we investigated this technology’s applicability for identifying subsurface plankton layers in Sanya Bay, SCS. Three airborne lidar flight experiments were carried out in March 2018 and in September 2017. Shipboard synchronous measurements were carried out in March 2018 to validate the lidar measurements. The method that is presented here can be used to detect a subsurface plankton layer, which is characterized by depth, thickness, and intensity. Compared with chlorophyll-a profile synchronously measured by shipborne fluorometer, there was a consistent relationship. The subsurface plankton layer depth error was less than 0.7 m. Next, the spatial distribution and seasonal variation of lidar measured subsurface plankton layers in Sanya Bay, SCS, was analyzed. The results showed that airborne lidar can potentially detect subsurface plankton layer within 50 meters deep in relatively clear water. This will enhance our understanding of biogeochemical processes in these optically complex aquatic systems.

A field, light-weight laser fluorometer based on the method of laser induced fluorescence was developed for water quality monitoring. The basic instrument configuration uses a high pulse repetition frequency microchip laser, a confocal reflective fluorescent probe and a broadband hyperspectral micro spectrometer; it weights only about 1.7 kg. Simultaneous estimates of three important water quality parameters, namely, chlorophyll a (chl-a), colored dissolved organic matter (CDOM), and total suspended matter (TSM) measured by the laser fluorometer were observed to agree well with those measured by traditional methods (0.27–0.84 μg L−3 chl-a, R2 = 0.88; 0.104–0.295 m−1 CDOM absorption, R2 = 0.90; and 59.8–994.9 mg L−3 TSM, R2 = 0.86) in Hangzhou Bay water. Subsequently, distribution and characteristics of CDOM and chl-a laser fluorescence in Hangzhou Bay were analyzed, which will enhance our understanding of biogeochemical processes in this complex estuarine system at high-resolution, high-frequency and long-term scale.

The dinoflagellate Prorocentrum donghaiense (P. donghaiense) is one of the most common species making up harmful algal blooms in the Yangtze River Estuary and the adjacent area of the East China Sea. Based on the differences between the absorption characteristics of P. donghaiense and diatoms from the East China Sea and an extensive in-situ remote sensing reflectance (Rrs) dataset, a multispectral approach for discriminating P. donghaiense blooms from other water types was developed based on MODIS Rrs spectral shape discrimination. The procedure is separated into two steps. First, the bloom waters are identified by the low Rrs(555) and high RAB owing to their relatively low reflectance and high spectral slope in the green bands. Second, two new indices of P. donghaiense index (PDI) and diatom index (DI) are developed for discriminating P. donghaiense from diatom blooms, based on the distinct spectral differences found in the green and red spectral ranges of phytoplankton absorption between the two algal groups. The validation using observations collected during near-con-current field surveys showed that the application of our practical method to MODIS imagery can provide reliable information on the inferred pattern and spatial distribution of the algal bloom, and that the classification technique for P. donghaiense bloom is considered successful, which may allow coastal mangers to better mitigate the harmful effects of P. donghaiense blooms in the East China Sea.

A soil circulation occurs in the south of Cheju Island in the spring. Nutrients and its influence on chlorophyll a (Chl a) around the circulations were studied from April 9 to May 6, 2007. Spring bloom with elevated concentrations of Chl a was observed during the investigation. High concentrations of phosphate, nitrate and silicate at 0.6, 12, and 8 mmol/m3, respectively, were detected. A low water temperature prevented the growth of phytoplankton. Chl a concentrations in the study area might be strongly associated with the high silicate concentration.

Bottom water hypoxia occurs frequently during the summer off the Changjiang Estuary. To estimate its spatial extent and investigate how climatic variations and extreme events may affect its occurrence, we developed a regional statistical model that combines satellite and buoy observations via empirical and statistical relationships. The estimated results were validated using cruise data off the Changjiang Estuary and its adjacent areas. First, we quantified the linkage between the observed dissolved oxygen (DO) concentrations in the bottom water and the chlorophyll-a (Chl-a) concentrations at the surface. With the help of the model, the bottom layer DO concentrations in the region lacking in situ measurements were estimated using the observations near the buoys and the satellite-derived Chl-a concentrations. Comparisons between the modeled results and surveys conducted between 2006 and 2011 indicate that the error of the estimated extent of low-oxygen bottom water was less than 26% and that the bias in the estimated minimum DO concentration was less than 0.5 mg L−1. Both buoy observations and modeled results indicate that the strength of water stratification and the amount of labile organic matter added to the bottom water are the two main factors that control the occurrence and the magnitude of seasonal low-oxygen events off the Changjiang Estuary.

The colored fraction of dissolved organic matter, CDOM, directly influences water optical properties and spectral quality, playing an important role in aquatic ecosystems, optical remote sensing and carbon circulation in the sea. Measuring in situ CDOM absorption coefficient, however, is difficult because it requires prefiltration of water samples. A field-portable laser fluorometer for fast acquisition of in situ CDOM fluorescence data without sample filtering was developed. Using the instrument in the Yangtze River estuary, the East China Sea coast, the West Lake, and the Qiandao Lake, good estimates of CDOM absorption were obtained from in situ fluorescence measurements. High correlation ( r = 0.94) was observed between CDOM absorption coefficient and fluorescence normalized to Raman scattering in diverse water types. Comparison of different methods for measuring CDOM fluorescence was carried out. Fluorescence measured by in situ laser fluorometer compared very well to the values obtained using more sophisticated laboratory spectrophotofluorometer; a significant relationship ( r = 0.95) was identified between the two methods. Spatial distributions of CDOM in the Yangtze River estuary and its adjacent sea compiled from discrete samples analyses were presented. A linear relationship was identified between CDOM fluorescence and salinity in surface water, reflecting the potential of CDOM fluorescence to be used as a passive tracer of freshwater input. The in situ measurement results demonstrated the utility of the laser fluorometer for rapid acquisition of high-resolution profiles, and that the work resulting from sample filtration or storage can be avoided.

Prorocentrum donghaiense is one of the most common red tide causative dinoflagellates in the Changjiang (Yangtze) River Estuary and the adjacent area of the East China Sea. It causes large-scale blooms in late spring and early summer that lead to widespread ecologic and economic damage. A means for distinguishing dinoflagellate blooms from diatom(Skeletonema costatum) blooms is desired. On the basis of measurements of remote sensing reflectance [R rs(λ)] and inherent optical parameters, the potential of using a multispectral approach is assessed for discriminating the algal blooms due to P. donghaiense from those due to S. costatum. The behavior of two reflectance ratios [R 1 = R rs(560)/R rs (532) and R 2 = R rs(708)/R rs(665)], suggests that differentiation of P. donghaiense blooms from diatom bloom types is possible from the current band setup of ocean color sensors. It is found that there are two reflectance ratio regimes that indicate a bloom is dominated by P. donghaiense: (1) R 1 > 1.55 and R 2 < 1.0 or (2) R 1 > 1.75 and R 2 ⩾ 1.0. Various sensitivity analyses are conducted to investigate the effects of the variation in varying levels of chlorophyll concentration and colored dissolved organicmatter (CDOM) as well as changes in the backscattering ratio (b bp/b p) on the efficacy of this multispectral approach. Results indicate that the intensity and inherent optical properties of the algal species explain much of the behavior of the two ratios. Although backscattering influences the amplitude of R rs(λ), especially in the 530 and 560 nm bands, the discrimination between P. donghaiense and diatoms is not significantly affected by the variation of b bp/b p. Since a CDOM(440) in coastal areas of the ECS is typically lower than 1.0 m−1 in most situations, the presence of CDOM does not interfere with this discrimination, even as S CDOM varies from 0.01 to 0.026 nm−1. Despite all of these effects, the discrimination of P. donghaiense blooms from diatom blooms based on multispectral measurements of R rs(λ) is feasible.

A coordinated retrieval method for sea surface salinity based on SMOS and ocean color data was developed. The method retrieved sea surface salinity in open sea based on SMOS data, and those with much RFIs in the coastal area using ocean color data, aCDOM. Tight relationships between surface water salinity and in situ aCDOM were found during the cruises in the Yangtze River estuary on April 2013 and Hangzhou Bay in May 2014, distributions of aCDOM revealed gradual downward trends of magnitudes, as water flowed down the Yangtze River estuary into the ECS coast. A dilution process was detected as water flowed down the Yangtze River and into the ECS coast. Thus, a salinity inversion model from the negative relationship between salinity and aCDOM was developed firstly. Then we matched the SSS products with different spatial resolution retrieved based on SMOS and ocean color and combined them. In the end, we compared the SSS measurements between those based on only SMOS data and those based on method in this paper, and found that the method can make up the phenomenon of lack of data effectively.

The diurnal variation of the suspended sediment concentration (SSC) in Hangzhou Bay, China has been investigated using remotely-sensed SSC derived from the Geostationary Ocean Color Imager (GOCI) in combination with a coupled hydrodynamic-ecological model for regional and shelf seas (COHERENS). The SSC maps were inferred through a UV-AC atmospheric correction algorithm and an empirical inversion algorithm from the GOCI Level-1B data. The sediment transport model was initialized from maps of the GOCI-derived SSC and the model results were validated through a comparison with remotely-sensed data. The comparison demonstrated that the model results agreed well with the observations. The relationship between SSC distribution and hydrodynamic conditions was analyzed to investigate the sediment transport dynamics. The model’s results indicate that the action of tidal currents dominate the sediment deposition and re-suspension in the coastal waters of the East China Sea. This is especially the case in Hangzhou Bay where the tidal currents are strongest. The satellite-derived sediment data product can not only dramatically improve the specification of the initial conditions for the sediment model, but can also provide valuable information for the model validation, thereby improving the model’s overall performance.

This paper proposes the retrieval method of ocean wave spectrum for airborne radar observations at small incidence angles, which is slightly modified from the method developed by Hauser. Firstly, it makes use of integration method to estimate total mean square slope instead of fitting method, which aims to reduce the affects of fluctuations superposed on normalized radar cross-section by integration. Secondly, for eliminating the noise spectrum contained in signal spectrum, the method considers the signal spectrum in certain look direction without any long wave components as the assumed noise spectrum, which would be subtracted from signal spectrum in any look direction for linear wave spectrum retrieval. Estimated ν from the integration method are lower than the one from fitting method and have a standard deviation of 0.004 between them approximately. The assumed noise spectrum energy almost has no big variations along with the wave number and is slightly lower to the high wave number part of signal spectrum in any look direction, which follows that the assumption makes sense. The retrieved directional spectra are compared with the buoy records in terms of peak wavelength, peak direction and the significant wave height. Comparisons show that the retrieved peak wavelength and significant wave height are slightly higher than the buoy records but don’t differs significantly (error less than 10%). For peak direction, the swell waves in first case basically propagate in the wind direction 6 hours ago and the wind-generated waves in second case also propagate in the wind direction, but the 180° ambiguity remains. Results show that the modified method can carry out the retrieval of directional wave spectrum.

Some missions have been carried out to measure wave directional spectrum by synthetic aperture radar (SAR) and airborne real aperture radar (RAR) at a low incidence. Both them have their own advantages and limitations. Scientists hope that SAR and satellite-based RAR can complement each other for the research on wave properties in the future. For this study, the authors aim to simulate the satellite-based RAR system to validate performance for measuring the directional wave spectrum. The principal measurements are introduced and the simulation methods based on the one developed by Hauser are adopted and slightly modified. To enhance the authenticity of input spectrum and the wave spectrum measuring consistency for SAR and satellite-based RAR, the wave height spectrum inversed from Envisat ASAR data by cross spectrum technology is used as the input spectrum of the simulation system. In the process of simulation, the sea surface, backscattering signal, modulation spectrum and the estimated wave height spectrum are simulated in each look direction. Directional wave spectrum are measured based on the simulated observations from 0° to 360°. From the estimated wave spectrum, it has an 180° ambiguity like SAR, but it has no special high wave number cut off in all the direction. Finally, the estimated spectrum is compared with the input one in terms of the dominant wave wavelength, direction and SWH and the results are promising. The simulation shows that satellite-based RAR should be capable of measuring the directional wave properties. Moreover, it indicates satellite-based RAR basically can measure waves that SAR can measure.

A Lagrangian tracer model is set up for Hangzhou Bay based on Coupled Hydrodynamical Ecological model for Regional Shelf Sea (COHERENS). The study area is divided into eight subdomains to identify the dominant physical processes, and the studied periods are March (the dry season) and July (the wet season). The model performance has been first verified by sea-surface elevation and tidal current observations at several stations. Eight tracer experiments are designed and Lagrangian particle tracking is simulated to examine the impact of physical processes (tide, wind and river runoff) on the transport of passive tracer released within the surface layer. Numerical simulations and analysis indicate that: (1) wind does not change the tracer distribution after 30 days except for those released from the south area of the bay during the wet season; (2) the tide and the Qiantang River runoff are important for particle transport in the head area of the bay; (3) the Changjiang River runoff affects the tracer transport at the mouth of the bay, and its impact is smaller in the dry season than in the wet season.

Light absorption by phytoplankton, non-algal particles (NAP) and chromophoric dissolved organic matter (CDOM) was investigated at 90 sites of a clear, deep artificial lake (Lake Qiandaohu) to study natural variability of absorption coefficients. Our study shows that CDOM absorption is a major contributor to the total absorption signal in Lake Qiandaohu during all seasons, except autumn when it has an equivalent contribution as total particle absorption. The exponential slope of CDOM absorption varies within a narrow range around a mean value of 0.0164 nm−1 ( s d = 0.00176 nm−1). Our study finds some evidence for thIS autochthonous production of CDOM in winter and spring. Absorption by phytoplankton, and therefore its contribution to total absorption, is generally greatest in spring, suggesting that phytoplankton growth in Lake Qiandaohu occurs predominantly in the spring. Phytoplankton absorption in freshwater lakes generally has a direct relationship with chlorophyll-a concentration, similar to the one established for open ocean waters. The NAP absorption, whose relative contribution to total absorption is highest in summer, has a spectral shape that can be well fitted by an exponential function with an average slope of 0.0065 nm−1 ( s d = 0.00076 nm−1). There is significant spatial variability present in the summer of Lake Qiandaohu, especially in the northwestern and southwestern extremes where the optical properties of the water column are strongly affected by the presence of allochthonous matter. Variations in the properties of the particle absorption spectra with depths provides evidence that the water column was vertically inhomogeneous and can be monitored with an optical measurement program. Moreover, the optical inhomogeneity in winter is less obvious. Our study will support the parameterization of the Bio-optical model for Lake Qiandaohu from in situ or remotely sensing aquatic color signals.

Red tide not only destroys marine fishery production and deteriorates the marine environment, it also causes human health problems. In China, the East China Sea has a high incidence of red tide disasters. Remote sensing technology has been proven an effective means of monitoring red tides. Spectral information of red tide water is an important basis for establishing red tide remote sensing monitoring models. This paper analyzes and compares the differences between red tide event spectral curves and multiyear monthly averaged spectral curves of MODIS data from July 2002 to June 2012, and develops a red tide monitoring algorithm based on the background field, to extract red tide information of the East China Sea. With the application of the algorithm in the East China Sea, it reveals that it can effectively determine the location of red tide and extract red tide information.

Chromophoric dissolved organic matter (CDOM) exists in all natural waters. Researches on optical properties of CDOM play an important role in ocean color remote sensing retrieval. The optical properties of CDOM in Zhejiang coastal waters were investigated from August 18, 2009 to June 9, 2011 covering four seasons. Based on the measured data, the distribution of the absorption coefficient of CDOM was analyzed. The results showed that absorption coefficient at 440 nm (a(440)) decreased with the offshore direction, and the relatively high value of a(440) was observed generally in the coastal waters and low value in the adjacent waters. The distribution reflected the terrigenous origin characteristics of CDOM. The relationship between salinity and a(440) of the four seasons was discussed. The results demonstrated that a(440) had a significant negative linear relationship with the salinity. That is to say, CDOM took on the conservative behavior in the research region.

The variations of Dissolved Oxygen (DO) in the near-bottom waters off the Changjiang (Yangtze River) Estuary before and after the passage of typhoons are investigated using both remotely sensed and in situ data sets. The Ekman pumping velocity during and after Typhoon was calculated. From buoys observation, typhoon passed by cause the water exchange between upper and lower layer. The mixture made the Dissolved Oxygen (DO) level changed to high level in short time. The level of DO at 50 m increased from 3.2 to 6.2 during the period of strong winds (< 30 knots) of Typhoon Muifa. The mixing process occurred in a short time, about 1-2 hours. The raise and resume result also has been verified from cruise observations. Typhoon effects hypoxia in many aspects. Typhoon can affect hypoxia in many ways. SST decreases as typhoon passes directly over the water. The concentrations of surface Chl a increase gradually due to mixing triggered by the typhoon. The affected area and time of change of hypoxia depend on the wind speed and the movement of the typhoon as well as the water depth.

Red tide not only destroys marine fishery production, deteriorates the marine environment, affects coastal tourist industry, but also causes human poison, even death by eating toxic seafood contaminated by red tide organisms. Remote sensing technology has the characteristics of large-scale, synchronized, rapid monitoring, so it is one of the most important and most effective means of red tide monitoring. This paper selects the high frequency red tides areas of the East China Sea as study area, MODIS/Aqua L2 data as the data source, analysis and compares the spectral differences in the red tide water bodies and non-red tide water bodies of many historical events. Based on the spectral differences, this paper develops the algorithm of Rrs555/Rrs488> 1.5 to extract the red tide information. Apply the algorithm on red tide event happened in the East China Sea on May 28, 2009 to extract the information of red tide, and found that the method can determine effectively the location of the occurrence of red tide; there is a good corresponding relationship between red tide extraction result and chlorophyll a concentration extracted by remote sensing, shows that these algorithm can determine effectively the location and extract the red tide information.

At the beginning of 2008, the south area of China suffered a rare heavy snow and low temperature weather, which brought enormous economic lose and broke the environment. The abnormal weather also influenced the ocean color environment. Through analysis of MODIS remote sensing 3A data during 2 months before and after the snowstorm and low temperature weather, the author finds that, on the one hand,compared with same period of last year, the sea surface temperature (SST) from the East China Sea to the South China Sea (18°N-32°N 108°E-126°E descended 2.57°C; the average chlorophyll-a concentration(CHL-a)rose from 1.198 mg. m -3 to 1.75 mg. m -3 in the snowstorm and low temperature weather period from January 11 to 31 of 2008 which was 1.46 times more than that of the same period of last year. On the other hand, compared with the period before snowstorm,the SST decreased from 22.42°C to 18.34°C but the CHL-a rose from 1.32 mg. m -3 to 1.60 mg. m -3 after the snowstorm. In addition,the sea water transparency(SDD) had a certain increase in the open sea of South China Sea, but the suspended sediment concentration(SSC) increased significantly near the seashore, the Yangtse River Estuary and the Pearl River Estuary, which increased 200% compared with the period before the snowstorm 2008. Through researching and indicating, the main reason of increase of the CHL-a in the near seashore area(the I water) was more probably due to the increase of the SSC, and the CHL-a by remote sensing has greater error, which rising from the high SSC led to the increase of CHL-a; but in the open sea the increase of CHL-a is that the SDD improved and then the euphotic increased. As a result,this could promote the growth of primary productivity. Therefore, it faces the better applied foreground to monitor the influence on the ocean ecosystem environment caused by the snowstorm and low temperature weather through remote sensing.

The Colored Dissolved Organic Materials (CDOM) and the de-pigmented particles are the main components affecting the ocean colors in China coastal waters (which are commonly considered as the Case II waters). Understanding of their spectral characteristics is very important to develop the regional bio-optical algorithms for ocean color remote sensing. The coastal water in East China Sea (ECS) is influenced by the terrestrial materials especially the Yangtze River outflow, which has high dissolved organic and suspended materials concentration and complex particles composition. In this paper, we analyze the in situ datasets collected in four seasons between 2006 and 2007 in ECS, and get the spectral absorption models of CDOM and de-pigmented particles. The distributions of absorption coefficients of CDOM ( ) and de-pigmented particles ( ) show a decreasing trend from coastal water to the off-shore waters, which is influenced mainly by the Yangtze River outflow and coastal currents with remarkable seasonal variation in ESC. The maxima of a dp CDOM a dp a dp is very high and even up to 90 m-1 level in estuary waters that it will apparently influence the retrieval of CDOM. The frequency of slops of the exponential spectrum of de-pigmented particles obeys the Gaussian distribution and it has good relationships with the absorption coefficient especially in the near-shore areas. The optical characteristics in ECS will give feasible reference to the further development of regional bio-optical algorithms.

The marine waters of the Yellow Sea and East China Sea cover a large area and represent an important fishing ground. Monitoring changes in their biological productivity is an important goal that can hopefully be reached using satellite remote-sensing. Operational ocean color satellite algorithms are generally successful over the open ocean. These algorithms are based upon simple band ratios, assuming that the only optically active component of any significance in the water is phytoplankton. While this assumption generally holds for the open ocean waters, it may not always be the case for coastal ecosystems (in what are commonly referred to as Case II waters). This problem is particularly evident in the study site. For the high concentration of SPM, it make the failure of the atmospheric correction algorithm and decrease the accuracy of the products of ocean color remote sensing, such as the SeaWiFS and MODIS. In order to develop the high accuracy regional algorithm, the inherent optical properties in Yellow Sea and East China Sea must study previously. In this paper, the absorption and scattering properties of the optically significant biogeochemical variables and the composition of SPM are studied use the in situ dataset of the inherent optical properties in the Yellow Sea and East China Sea.

Light absorption, chlorophyll-specific absorption and package effect of phytoplankton in Zhujiang River mouth was studied on the two cruises of "Shiyan 2". The vertical distribution of phytoplankton in waters can be simulated by Gaussian equation; light absorption of phytoplankton was made on 25 mm GF/F filter, maximum light absorption of phytoplankton was at the depth 5-10m underwater. The value of chlorophyll-specific absorption was negatively correlated with chlorophyll a concentration. Package effect index also had a negative relationship with chlorophyll concentration. These results indicated that the characteristics of light absorption by phytoplankton varied in different waters were properly related to the phytoplankton concentration.

Coral reefs are complex marine ecosystems and environment-sensitive that are constructed and maintained by biological communities that thrive in the warm tropical ocean. Remote sensing provides a more efficient way to observe and monitor shallow coral reefs than alternative field survey. Dong-Sha Atoll is located at the northern continental margin of the South China Sea. The area of the atoll is more than 300 km2 with an average depth of 10 m, and has being abused by destructive fishing during recent decades. In this paper, three satellite broadband multi-spectral imageries (Quickbird2, ETM+, and SPOT5) are used to survey this area. In the preprocessing, low-resolution images are geometrically corrected to high-resolution imagery. For information extraction, unsupervised classification functions are adopted for ETM+ and SPOT5 data, and supervised classification method for Quickbird2. The classification results are (or not) merged into coral reef, and operated by vectorization, simplification, and topological analysis. There are 1331 coral reefs larger than 100 m2 with the detection limitation of 3×3 pixels at multi-band data of Quickbird2. The results extracted from SPOT5 data are better than that of ETM data at silty lagoon due to its higher resolution, and less at atoll reef bodies in the absence of blue waveband.

An operational fisheries oceanography system was established to help fishermen analyze the situations of fishery in North Pacific. The system composes of three sub-systems which are a ship-boarding satellite telemetry receiving station, a ship-boarding satellite communication system and a land-based fishery charts producing system. The system can provide some oceanic environmental charts such as sea surface temperature (SST) and relevant derived products which are the most popular use in fishery industry. The accuracy of SST is the most important and affects the performance of the operational system, which is found to be dissatisfactory. Many factors affect the accuracy of SST and it is difficult to increase the accuracy by SST retrieval algorithms and clouds detection techniques. A new technique of temperature error control is developed to detect the abnormity of satellite SST. The performance is evaluated to change the temperature bias from -3.04 to 0.05°C and the root mean square (RMS) from 5.71 to 1.75°C. It is suitable to be employed in an operational satellite-measured SST system and improves the performance of the system in fishery applications.