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A station of AErosol RObotic NETwork Ocean Color (AERONET-OC) has been set on the Ariake Observation Tower of Saga University on April, 2018, for verification of the Second generation Global Imager (SGLI)/Global Change Observation Mission-Climate (GCOM-C). Remote sensing reflectance (Rrs) observed by the AERONET-OC was used for verification of SGLI. SGLI Version 1 data underestimated the shortwave Rrs and Rrs (380) and Rrs(412) were mostly negative, while the estimation was improved by Version 2 with the correction of Rrs(412) to be positive. It was indicated that absorptive aerosol was influenced to SGLI atmospheric correction and caused the underestimation of Rrs. Simple linear correction method to improve shortwave Rrs also worked well for specifically Version 1 data. Water constituents, chlorophyll-a (Chl-a), total suspended matter (TSM) and colored dissolved organic matter (CDOM) of the SGLI were also verified by the ship observation data. All constituents were improved from Version 1 to 2 with the correction of Rrs, although Version 2 underestimated Chl-a and CDOM. Simple regression algorithms were also examined with in situ as well as SGLI Rrs data, and it indicated that more sophisticated algorithms may be required. Time series of water constituents derived from AERONET-OC and SGLI data were compared to river discharge and spring–neap tidal cycle. The results indicated that the behavior, such as the increase of Chl-a after river discharge and interaction of Chl-a and TSM with the spring–neap tidal cycles were observed, although estimations of water constituents were not completely separated by the algorithms.

Seasonal and interannual variations of chlorophyll-a (chl-a) in the upper Gulf of Thailand (uGoT) were obtained using new regionally tuned algorithms applied to Moderate Resolution Imaging Spectroradiometer-Aqua. This long time-series (2003–2017) data were analyzed in the context of variations in environmental conditions associated with the Southeast Asian Monsoon. Chl-a distribution patterns were distinct for the non-monsoon (NOM), southwest-monsoon (SWM), and northeast-monsoon (NEM) seasons. During the SWM/NEM, high/low chl-a concentrations were associated with high/low precipitation and river discharge. During the NOM chl-a concentrations were generally low, because of low precipitation. In general, chl-a variability was tightly coupled to discharge from the Chao Phraya and Tha Chin rivers. Chl-a concentrations were generally higher in the north, but chl-a accumulation in the east/west of the uGoT could be linked to piling of freshwater to the east/west during the SWM/NEM caused by changes in wind direction and the reversal of currents. Interannual changes in chl-a were attributed to El Niño-Southern Oscillation (ENSO) rather than Indian Ocean Dipole (IOD) driven changes in precipitation, river discharge, and wind patterns. During the SWM, positive/negative chl-a anomalies coincided with high/low precipitation and river discharge during La Niña/El Niño. During the NEM, positive/negative chl-a anomaly coincided with high/low river discharge and strong/weak wind during La Niña/El Niño. Meanwhile, during NOM, positive chl-a anomaly could be attributed to anomalous high wind speed and precipitation during El Niño.

This study investigated the seasonal variability of surface chlorophyll-a (chl-a) and the influence of the El Niño Southern Oscillation (ENSO) related to environmental parameters in the Gulf of Thailand (GoT). Monthly chl-a data from MODIS from 2002 to 2020 as well as sea surface temperature (SST), wind, precipitation, and river discharge were used in this analysis. Results from seasonal climatology and Empirical Orthogonal Function (EOF) described high chl-a concentration areas along the western to the southern coasts and near Ca Mau Cape during the northeast monsoon (NEM), and the upper GoT (UGoT), eastern coast, and the GoT mouth during the southwest monsoon (SWM), while low chl-a took place during the non-monsoon (NON). The GoT was divided into six areas based on the EOFs of chl-a, and then the correlation between chl-a variability and environmental parameters was also examined. The results suggested that chl-a in coastal and offshore areas were controlled by different mechanisms. Chl-a in coastal areas responded to precipitation and river discharge as well as the shoreward wind; meanwhile, chl-a in offshore areas correlated with SST and wind magnitude indicating the importance of water mixing and upwelling. The fluctuation of chl-a in each season related to ENSO was captured by EOF based on the seasonal anomaly. The influence of ENSO was strong during NEM and NON but minimal during SWM. El Niño/La Niña generally caused low/high precipitation and high/low SST. Moreover, El Niño/La Niña caused anomalously weak/strong wind during NEM contrary to during NON. Anomalous high/low chl-a were observed in shallow regions during El Niño/La Niña corresponding to strong/weak wind in NON. Abnormal wind under ENSO also created the shifting in the high chl-a area near Ca Mau Cape. These results have improved our understanding of monsoons and ENSO variabilities as the crucial drivers of changes in the tropical marine ecosystem in both seasonal and interannual time scales.

In Mikawa Bay, where hypoxia occurs in the bottom layer during summer, six shipboard observations were conducted from the mouth to the head of the bay from May to August 2014 to investigate the spatiotemporal variation in the bottom layer oxygen consumption rate (OCR). The OCR was determined from the dark incubation of sample waters using an optical oxygen sensor, which showed a range of 5.7-38.3 mmol m

This study develops an ensemble Kalman filter (EnKF)-based regional ocean data assimilation system in which the local ensemble transform Kalman filter (LETKF) is implemented with version 1.0 of the Stony Brook Parallel Ocean Model (sbPOM) to assimilate satellite and in situ observations at a daily frequency. A series of sensitivity experiments are performed with various settings of the incremental analysis update (IAU) and covariance inflation methods, for which the relaxation-to-prior perturbations and spread (RTPP and RTPS, respectively) and multiplicative inflation (MULT) are considered. We evaluate the geostrophic balance and the analysis accuracy compared with the control experiment in which the IAU and covariance inflation are not applied. The results show that the IAU improves the geostrophic balance, degrades the accuracy, and reduces the ensemble spread, and that the RTPP and RTPS have the opposite effect. The experiment using a combination of the IAU and RTPP results in a significant improvement for both balance and analysis accuracy when the RTPP parameter is 0.8–0.9. The combination of the IAU and RTPS improves the balance when the RTPS parameter is ≤0.8 and increases the analysis accuracy for parameter values between 1.0 and 1.1, but the balance and analysis accuracy are not improved significantly at the same time. The experiments with MULT inflating the forecast ensemble spread by 5 % do not demonstrate sufficient skill in maintaining the balance and reproducing the surface flow field regardless of whether the IAU is applied or not. The 11 d ensemble forecast experiments show consistent results. Therefore, the combination of the IAU and RTPP with a parameter value of 0.8–0.9 is found to be the best setting for the EnKF-based ocean data assimilation system.

Satellites can help monitor harmful algal blooms in coastal regions. Methods have been developed using different satellite missions. However, it is necessary to develop a simple and useful method for discriminating harmful algal species that could be applied to multi-source satellite remote sensing reflectance spectra ($${R}_{\mathrm{rs}}(\lambda ))$$ R rs ( λ ) ) . In this study, based on the bio-optical model, a backscattering indicator, bbp-index (green), was found to be useful for species identification (Karenia mikimotoi and Prorocentrum donghaiense) combined with the red tide index (RI) in water blooms in the East China Sea (ECS). The MODIS, GOCI, and MERIS data collected between 2004 and 2020 were consistent for bloom discrimination, determining that K. mikimotoi exhibited lower bbp-index (green) values than P. donghaiense. The classification of the blooms is based on the following criteria: $${R}_{\mathrm{rs}}(555)$$ R rs ( 555 ) < 0.014 sr−1 and RI > 2.8 and (1) bbp-index (green) > 1.2 $$\times {10}^{-3}$$ × 10 - 3 , classified as P. donghaiense blooms or (2) bbp-index (green) $$\times {10}^{-3}$$ × 10 - 3 , classified as K. mikimotoi blooms. The inclusion of the RI is necessary to directly detect the bloom area. Local bloom reports have confirmed the effectiveness of the bloom discrimination method. In addition, the advantages and limitations of the proposed method are discussed.

Despite the importance of the primary production in coastal Large Marine Ecosystems, the complex bio-optical properties in some coastal waters make the estimation of primary productivity using satellite data quite challenging. Here we critically reviewed the accuracy of parametrization of three core variables, i.e. chlorophyll-a, chlorophyll-specific photosynthetic rate, and euphotic depth, in the Yellow Sea, East China Sea, and Sea of Japan/East Sea Large Marine Ecosystems. We also compared the annual primary productivity estimates of the three Large Marine Ecosystems by a depth-integrated model with those from two other global assessments, which used different primary productivity models: an absorption-based model, and a time and depth-resolved model. Our assessment suggests that 1) accurate parametrization of the core variables is more important than choosing a primary productivity model, and 2) the previous global Large Marine Ecosystem assessments might have overestimated the annual primary productivity in the Yellow Sea by a factor of 2 or so.

There is data for the journal of "Detection and tracking of Chattonella spp. and Skeletonema spp.blooms using Geostationary Ocean Color Imager (GOCI) in Ariake Sea, JapanDetection and tracing of Chattonella spp. and diatom blooms using Geostationary Ocean Color Imager (GOCI) in Ariake Sea, Japan" Excel data for method developement and method verification was uploaded

The surface distribution of the phytoplankton community was investigated in July 2009, 2010, 2011, and 2013 on the mid-shelf of the East China Sea (ECS), which is under the influence of Changjiang River Diluted Water (CDW) and the Kuroshio Current. This study, based on a CHEMTAX analysis of phytoplankton pigments, revealed a predominance of cyanobacteria and prochlorophytes in the eastern ECS, which is perennially under the influence of oligotrophic Kuroshio Surface Water. Towards the west, on the mid-shelf of the ECS, the composition of the phytoplankton community varied from year to year. Diatoms dominated in 2009 and 2013, when dissolved inorganic phosphate (DIP) concentrations were higher than during 2010 and 2011. During the latter two years, characterized as high-nitrate years, a mixed population of cyanobacteria, chlorophytes, and other groups was observed. Cluster analysis based on the phytoplankton community composition together with a PCA of shipboard hydrographic and nutrient data for all four years helped to confirm that the summer phytoplankton community structure of the ECS was regulated by the mixing of water masses and the variability of nutrient ratios within the CDW as it moved offshore. Our results show that elevated DIP concentrations in the CDW favor the growth of diatoms and dinoflagellates. The primary pathway for DIP inputs appears to be the upwelling of high-phosphate subsurface waters along the coast of China.

To confirm the usefulness of optical oxygen sensors in hypoxia-related research in coastal regions, a contactless optical sensor (COS) (FireStingO2, Pyroscience) was used to measure dissolved oxygen concentrations, and the values obtained were compared with those obtained using the traditional Winkler method. During spring and summer seasons, bottom water samples from the Mikawa Bay, where hypoxia frequently occurs, were analyzed. The correlation between the oxygen concentrations obtained using the COS and Winkler methods had a slope of 1.01, an intercept of −6.17 μmol kg−1, and a coefficient of determination of 0.97. Further, when the oxygen consumption rates in the bottom water (OCRbw) were measured using these two methods, the slope, intercept, and coefficient of determination of the correlation between these values were 1.05, −0.08 μmol kg−1 d−1, and 0.63, respectively. These findings indicate that the COS method is suitable for obtaining accurate oxygen concentrations as well as OCRbw values for coastal waters, but it is still difficult to adapt it to small OCRbw values in the open ocean. The highest OCRbw (38.3 μmol kg−1 d−1) was observed at the inner part of the Bay in the end of August. Furthermore, the COS method also allowed the measurement of oxygen concentrations in the water overlaying the sediment core (OCRs + w), which in the Mikawa Bay were 3–5-fold higher than the corresponding OCRbw values. Observations made using the COS method in the Upper Gulf of Thailand (UGoT), which is also characterized by a highly hypoxic bottom layer, showed high OCRbw (>30 μmol kg−1 d−1) and OCRs + w (>40 μmol kg−1 d−1) near the estuarine of large rivers not in the rainy season but also in the dry season. The COS method has potential for use in the collection of OCR data that can significantly contribute to the accuracy of hypoxia prediction models.

Sea surface salinity (SSS) in coastal oceans is a direct indicator of riverine plumes and provides essential information about the ocean environment and ecosystem, which affects coastal fisheries, aquaculture, and marine harvests. However, to accurately capture SSS patterns in coastal oceans, high temporal and spatial resolutions are required. This paper introduces a methodology to produce high-resolution (~ 500 m) SSS maps for analysis of river plumes in coastal oceans based on hourly chromophoric dissolved organic matter data collected by the Geostationary Ocean Color Imager. Osaka Bay, located in the eastern Seto Inland Sea, was selected as a pilot region. A comparison between the initial estimates and calibrated SSS data showed a substantial decrease in estimation error, by up to 71%, over a wide range of salinity (20–34) using in situ SSS data collected through an automated observation system. Calculating the salinity anomaly based on the SSS map to identify plume areas, we evaluated the impact of a large runoff event induced by a super typhoon on the river plumes. After the plume formed in the estuary, it extended southward to the bay mouth along the southeastern coast. The plume area during the post-typhoon period covered half of the bay, approximately 1.5 times the area during the pre-typhoon period. The post-typhoon, low-SSS period continued for approximately 2 weeks. Our approach can be of practical use for analyzing the dynamics of river plumes in coastal oceans, leading to the development of coastal ocean prediction models related to operational oceanography., ファイル公開：2019-06-01

Intensive surveys with repeated CTD and microstructure turbulent observations, water and sediments sampling as well as onboard incubation and sediment trap experiments were conducted to reveal the nitrogen budget in the center of the East China Sea (ECS) during July 2010 and 2011. Low salinity water (Changjiang Diluted Water, CDW) covered the study area in 2010, but not in 2011. Higher chlorophyll a (chl. a ) concentration, primary productivity, and downward particle flux in the upper layer were observed in 2010 than those in 2011. Existence of the CDW resulted in a steep pycnocline and an associated subsurface chl. a maximum (SCM) layer directly beneath the CDW. From chemical analyses of particulate carbon and nitrogen contents and isotope ratios, it became apparent that the particles sunk out the euphotic zone in 2010 was primarily originated in the CDW layer and secondly in the SCM layer. Whereas, in 2011, sinking particles were originated in the surface layer but a part of them were decomposed in the bottom of pycnocline. Our findings indicate that the CDW would supply particles into the deep layer and contribute to the downward transport of materials and the efficiency of biological pump in the ECS.

Quantifying the diffuse attenuation coefficient of the photosynthetically available radiation (Kpar) can improve our knowledge of euphotic depth (Zeu) and biomass heating effects in the upper layers of oceans. An algorithm to semi-analytically derive Kpar from remote sensing reflectance (Rrs) is developed for the global open oceans. This algorithm includes the following two portions: (1) a neural network model for deriving the diffuse attention coefficients (Kd) that considers the residual error in satellite Rrs, and (2) a three band depth-dependent Kpar algorithm (TDKA) for describing the spectral selective attenuation mechanism of underwater solar radiation in the open oceans. This algorithm is evaluated with both in situ PAR profile data and satellite images, and the results show that it can produce acceptable PAR profile estimations while clearly removing the impacts of satellite residual errors on Kpar estimations. Furthermore, the performance of the TDKA algorithm is evaluated by its applicability in Zeu derivation and mean temperature within a mixed layer depth (TML) simulation, and the results show that it can significantly decrease the uncertainty in both compared with the classical chlorophyll-a concentration-based Kpar algorithm. Finally, the TDKA algorithm is applied in simulating biomass heating effects in the Sargasso Sea near the Bermuda, with new Kpar data it is found that the biomass heating effects can lead to a 3.4°C maximum warming in the upper layers but could result in a 0.67°C maximum cooling in the deep layers.

Fast repetition rate fluorometry (FRRF) provides a means to examine primary productivity at high resolution across broad scales, but must be coupled with independent knowledge of the electron requirement for carbon uptake (KC) to convert FRRF-measured electron transfer rate (ETR) to an inorganic carbon (C) uptake rate. Previous studies have demonstrated that variability of KC can be explained by key environmental factors (e.g. light, nutrients, temperature). However, how such reconciliation of KC reflects changes of phytoplankton physiological status versus that of community composition has not been well resolved. Therefore, using a dataset of coupled FRRF and C uptake measurements, we examined how the environmental dependency of KC potentially varied with parallel changes in phytoplankton community structure. Data were combined from 14 campaigns conducted during the summer season throughout 2007 to 2014 in the East China Sea (ECS) and Tsushima Strait (TS). KC varied considerably, but this variability was best explained by a linear relationship with light availability (R^2 = 0.66). Co-variability between KC and light availability was slightly improved by considering data as 2 clusters of physico-chemical conditions (R^2 = 0.74), but was best improved as 2 taxonomic clusters: samples dominated by micro-phytoplankton (>20 µm) versus small phytoplankton (nano + pico, ファイル公開：2018-09-29

In summer, Changjiang Diluted Water (CDW) expands over the shelf region of the northern East China Sea. Dilution of the low salinity water could be caused by vertical mixing through the halocline. Vertical mixing through the pycnocline can transport not only saline water, but also high nutrient water from deeper layers to the surface euphotic zone. It is therefore very important to quantitatively evaluate the vertical mixing to understand the process of primary production in the CDW region. We conducted extensive measurements in the region during the period 2009–2011. Detailed investigations of the relative relationship between the subsurface chlorophyll maximum (SCM) and the nitracline suggested that there were two patterns relating to the N/P ratio. Comparing the depths of the nitracline and SCM, it was found that the SCM was usually located from 20 to 40 m and just above the nitracline, where the N/P ratio within the nitracline was below 15, whereas it was located from 10 to 30 m and within the nitracline, where the N/P ratio was above 20. The large value of the N/P ratio in the latter case suggests the influence of CDW. Turbulence measurements showed that the vertical flux of nutrients with vertical mixing was large (small) where the N/P ratio was small (large). A comparison with a time series of primary production revealed a consistency with the pattern of snapshot measurements, suggesting that the nutrient supply from the lower layer contributes considerably to the maintenance of SCM.

GCOM-C/SGLI is a multi-wavelength optical radiometer launched on December 23, 2017. The data provision has started from December 20, 2018. In this research, we briefly introduce standard Level 2 products and their validation results based on in situ data. Mean absolute percentage differences are 16.3 - 69.6% for NLW between 380 - 670 nm, 39 and 64.5% for AOT at 670 nm and 865 nm, 27.9% for CHL and 44.2% for aCDOM. Although the number of in situ validation data are still scare for a few ocean color products, the accuracy of GCOM-C/SGLI data will be improved by our future efforts of calibration/validation activities.

Estimation of chlorophyll concentration in the marine biosphere has been the central topic of ocean color remote sensing since its advent. While various algorithms were proposed in the literature so far and tested for oceanic waters of diverse constituent composition, an independent algorithm evaluation is needed for local ocean waters that have dynamic variation in optically active water constituents such as colored dissolved organic matters (CDOM) and suspended particulate matter (SPM). This paper evaluates the performance of chlorophyll algorithms for Geostationary Ocean Color Imager (GOCI) radiometric data, using in situ measurements collected at 491 stations around Korea Peninsula during 2010–2014 from which there were 130 match-ups with GOCI data. For the evaluation in areas with high variation in SPM, water samples were first classified into three levels of SPM, and then the coefficients of candidate algorithms were newly derived for the turbidity cases using the in situ and GOCI remote sensing reflectance ( R rs ) data. Functional forms of traditional band ratio algorithms ( e.g. OC algorithms (O′Reilly et al., 1998) and Tassan's algorithm (Tassan, 1994)), fluorescence line height algorithm, and near-infrared-to-red band ratio approach were tested. The evaluation results for the coincident in situ pairs of R rs and chlorophyll measurements showed that the mean uncertainty was

The Northwest Pacific region, which includes parts of northeast China, Japan, Korea and southeast Russia, is one of the most densely populated areas of the world. Eutrophication is an emerging environmental problem in this region, where a significant number of red tides and hypoxic conditions have been reported in coastal waters - possibly due to anthropogenic influences such as extensive chemical fertilizer use and sewage effluent. To assess this problem, NOWPAP CEARAC, the Special Monitoring and Coastal Environment Assessment Regional Activity Centre of the Action Plan for the Protection, Management and Development of the Marine and Coastal Environment of the Northwest Pacific Region of the United Nations Environmental Programme, has developed "Procedures for assessment of eutrophication status including the evaluation of land-based sources of nutrients for the NOWPAP region" (NOWPAP Common Procedures). The NOWPAP Common Procedures include the screening procedure to detect symptoms of eutrophication with selected parameters. One of the selected parameters is remotely sensed chlorophyll-a concentration (satellite Chl-a). To prepare a long-term consistent satellite Chl-a from 1998 to 2016, regression analysis was conducted by pixel to pixel using the daily composites of SeaWiFS and MODIS Remote Sensing Reflectance for overlapping period (July 2002 to December 2004). Two different empirical in-water algorithms, a NASA standard and a regionally developed one for turbid water, were applied to estimate Chl-a in the eastern and western parts of the Northwest Pacific region, respectively. The assessment of eutrophication was then conducted by the level and trend of satellite Chl-a.

Riverine nutrients acting in concert with local hydrographic conditions create distinct ecological niches for phytoplankton communities across river-ocean continuums. Here we compare two of the world’s largest river-ocean systems, the Amazon River Plume (ARP) which outflows into the Western Tropical North Atlantic (WTNA) and the Changjiang Diluted Water (CDW) which empties into the East China Sea to show how distinctly different N: P ratios of their source waters, shape phytoplankton communities along the river-ocean continuum. Sampling in the relatively unpolluted surface waters of the ARP during peak river discharge revealed that phytoplankton communities along the river-ocean continuum were strongly controlled by Dissolved Inorganic Nitrogen (DIN, nitrate plus nitrite) concentrations which were low or beyond detectable, while Dissolved Inorganic Phosphorous (DIP, phosphate) was not limiting. Downstream of the plume, nutrient concentrations at the surface were far below the Redfield N:P ratio of 16 : 1, and in this severely nitrogen limited but silica replete mesohaline region, Diatom-Diazotroph Associations (DDA) such as Hemiaulus hauckii-Richelia proliferated, while offshore in nitrate poor oceanic waters, Trichodesmium spp. and Prochlorococcus thrived. In contrast, in the CDW, a system which has witnessed a substantial rise in anthropogenic nitrogen inputs from human pressures within the Changjiang River system, phytoplankton community structure was regulated primarily by DIP which was rapidly consumed in the inner shelf. Data from a series of summer-time cruises in the mid-shelf and offshore regions of the East China Sea, at peak discharge, established that when DIP limitation was ameliorated by on-shelf upwelling of DIP rich Kuroshio Intermediate Waters, diatoms and dinoflagellates dominated. Conversely, during years of heavy discharge, the westward flowing CDW plume was severely DIP limited, probably because water column stratification dampened upwelling of subsurface waters. The consequent phosphate limitation led to the proliferation of small phytoplankton such as Chlorophytes and Cyanobacteria. The absence of diazotrophs in the CDW, leads us to hypothesize that river-ocean continuums, whose source waters are heavily impacted by anthropogenic activities and with nutrient concentrations substantially in excess of Redfield ratios, may not support diatoms on account of DIP limitation nor DDAs and diazotrophs because of excess DIN.

The Japan Sea is a marginal sea surrounded by the Japanese archipelago, Korea Peninsula, Sakhalin Island, mainland China and Russian landmasses which isolate it from the East China Sea, Pacific Ocean, and Okhotsk Sea. In this chapter, studies of phytoplankton and primary production in the Japan Sea using ocean colour satellite data have been summarized. Satellite chlorophyll-a (Chl-a) concentrations were generally well correlated with in situ Chl-a, except in low chlorophyll-a regions within the central region of the Japan Sea, where satellite estimates were higher. A marked seasonality in Chl-a was observed in association with spring and fall blooms over large areas of Japan Sea, with the spring bloom commencing around the subpolar front in the south moving northwards. Overall, interannual variations in Chl-a, appeared to be related to large scale global climate variations. Despite observations of increasing trends in Chl-a, reports of decreases in primary production require that we continue to better understand the role of physical forcing factors in particular, how mesoscale eddies and typhoons that are unique to this region, regulate primary production and phytoplankton biomass distribution. This review also draws attention to the lack of ocean colour algorithms for discriminating phytoplankton functional groups from space. The availability of satellite derived information on phytoplankton functional groups is essential for ocean biogeochemical and fisheries research. This study also emphasizes the need for more bio-optical measurements and algorithm development efforts to fill this gap.

The potential interactions between the bloom-forming dinoflagellates and other phytoplankton during the algal bloom cycle are interesting, while the causes for the phytoplankton community changes were not fully understood. We hypothesized that phytoplankton community structure and photosynthetic activities of total phytoplankton have their special characteristics in different phases of the algal blooms. To test this hypothesis, a survey covering the process of a Prorocentrum donghaiense bloom in coastal waters between Dongtou and Nanji Islands was carried out from 9 to 20 May 2016, and the changes in the phytoplankton community and photosynthetic activities of total phytoplankton were determined. Surface seawater was sampled for microscopic analysis of phytoplankton composition and pulse amplitude modulated (PAM) chlorophyll fluorescence analysis of photosynthetic activities of the total phytoplankton species. A total of 25, 31, and 19 phytoplankton species were identified in its growth (9-12 May), maintenance (13-18 May) and dissipation phases (19-20 May), respectively. Diatoms were dominant in terms of species number while dinoflagellates were predominant at cell abundance. Dinoflagellates were the major dominant species during three phases of the bloom based on the dominance (Y) value, whereas the dominant species extended to dinoflagellates and diatoms including P. donghaiense, Coscinodiscus argus, Gonyaulax spinifera, Cyclotella sp. and Scrippsiella trochoidea in the dissipation phase. In the maintenance phase, the average cell abundances of the total phytoplankton and P. donghaiense were consistent with the chlorophyll a (Chla) concentration in the seawater; for the diversity indices of total phytoplankton species, Simpson index (C) was the highest while Shannon index (H') and Pielou evenness index (J') were the lowest. Furthermore, photosynthetic activities of the total phytoplankton species represented by the effective quantum yield (Fq'/Fm') and the maximum relative electron transport rate (rETRmax) in the maintenance phase were higher than those in the growth and dissipation phases. The results indicated that the characteristics of phytoplankton community structure and photosynthetic activities could be regarded as criteria in predicting the phases of algal blooms.

Accurate estimates of primary production from satellite-derived data on both regional and global scales are one of the most important goals of international ocean color remote-sensing programs. This manuscript presents surface concentrations and vertical distributions of chlorophyll-a (Chl-a) data as a proxy for phytoplankton biomass, and calculated photosynthesis–irradiance (P–E) curve parameters, which were used to estimate integrated monthly primary production in the Sargasso Sea euphotic zone from 2004 to 2009. The measured surface Chl-a in the Sargasso Sea was low but exhibited strong seasonal variation, and correlated well with satellite estimates of Chl-a. Underwater light transmission was modeled using a shifted Gaussian model from 69 vertical Chl-a profiles, which were collected in the Sargasso Sea. The P–E curve parameters were experimentally derived; the maximum photosynthetic rate, P m B ranged from 1.51 to 3.05 (mgC(mgChl-a) −1 h −1 ) and the maximum light utilization coefficient, α B , ranged from 0.017 to 0.806 (mgC(mgChl−a) −1 (Wm −2 ) −1 h −1 ). These data and previously published P–E curve parameter estimates were used in a spectrally varying model to estimate integrated primary production in the Sargasso Sea euphotic zone. Output from two of the four primary production models agreed well with in-situ measurements (±20%) and captured the strong seasonal variation.

A total of 13 cruises were performed in different seasons between July 2010 and July 2012, and in various subsystems of the Changjiang (Yangtze River) Estuary and the adjacent East China Sea (ECS). Multiple vessels were deployed to conduct transect sampling, simultaneous and consecutive sampling, sampling with buoys, and sampling during phytoplankton bloom events, which allowed us to track detached patches of water masses and to collect discrete and time-series samples in different patches. We found that the river-derived nutrients from the Changjiang could be transported through the western ECS and reach as far as the northeastern ECS during summer, but in the form of isolated patches rather than continuous plumes. The concentrations of NO3−, SiO32−, and PO43− decreased with increasing seaward distance of these patches, showing largely nonconservative mixing behavior and the ECS being a sink for nutrients. During winter, conversely, all nutrient species showed mostly conservative behavior, with correlative coefficients (R2) even reaching > 0.97 in the salinity-nutrient correlations for both NO3− and SiO32− during the western ECS cruise in February 2012 and during the Changjiang mouth cruise in March 2012. In addition, a large variability in nutrient concentrations was observed within the Changjiang freshwaters and could be partly attributed to inputs from local tributaries. This study highlights the importance of simultaneous field sampling with multiple vessels for investigating the biogeochemical behavior of nutrients in highly dynamic ocean margin areas such as the Changjiang Estuary-ECS region.

Satellite Chlorophyll a (CHL) data was used to investigate the influence of mesoscale anticyclonic eddies (AEs) and cyclonic eddies (CEs) on the timing of spring phytoplankton bloom initiation around the Yamato Basin (133-139° E and 35-39.5° N) in the Japan Sea, for the period 2002-2011. The results showed significant differences between AEs and CEs in the timing and initiation mechanism of the spring phytoplankton bloom. Blooms were initiated earlier in CEs which were characterized by shallow mixed-layer depths ( 100 m) but close to the commencement of positive Q0. This suggests that the relaxation of turbulent mixing is crucial for the bloom initiation in AEs.

The paper “A neural network model for remote sensing of diffuse attenuation coefficient in global oceanic and coastal waters: Exemplifying the applicability of the model to the coastal regions in Eastern China Seas” uses the ratio of water-leaving radiance to downward irradiance multiple by π as the remote sensing reflectance for NOMAD dataset and the implement routine of diffuse attenuation coefficient retrieval models. Our results indicate that the quasi-analytical algorithm-based semi-analytical model (QSM) and spectrum-based neural network model (SNNM) produce a superior performance to these mentioned in the original paper, but these results do not affect the main conclusions in the original paper.

Seven cruises were conducted in the Changjiang (Yangtze River) Estuary and the adjacent western East China Sea (ECS) from 2010 to 2012 to study the seasonal variations of δ13C and δ15N in suspended organic matter. In addition, two cruises in the northeastern ECS in July 2011 and in Tsushima Strait in July 2012 were conducted to evaluate the distribution patterns of these isotopes over the entire Changjiang transport pathway. In summer, the surface δ13C was lowest in the Changjiang Channel, increasing from land to sea, reaching highest values in the central ECS, and then decreasing and remaining relatively constant. In winter, the surface δ13C in the western ECS showed lower values with less variation in general. At most stations, δ13C increased from the sea surface to the seabed, reflecting the degradation of sinking organic matter; however, these trends could be changed in the summer by surface phytoplankton accumulation. Combining data from all the Changjiang Estuary and western ECS cruises revealed that when the suspended particulate matter (SPM) was > 135 mg/L, the δ13C values were fairly constant (−24.5‰ to −20.5‰); when the SPM was

For global oceanic and coastal waters, a multilayer back propagation neural network (MBPNN) is developed to retrieve the diffuse attenuation coefficient for the downwelling spectral irradiance at the wavelength 490 nm (Kd(490)). The applicability of Lee's quasi-analytical algorithm-based semi-analytical model, Wang's switching model, Chen's semi-analytical model, Jamet's neural network model, and the MBPNN model is evaluated using the NASA bio-optical marine algorithm dataset (NOMAD) and the Eastern China Seas dataset. Based on the comparison of Kd(490) predicted by these five models, with field measurements taken in global oceanic and coastal waters, it is found that the MBPNN model provides a stronger performance than the Lee, Wang, Chen, and Jamet's models. The atmospheric effects on the MODIS data are eliminated using near-infrared band-based and shortwave infrared band-based combined models, and the Kd(490) is quantified from the MODIS data after atmospheric correction using the MBPNN model. The study results indicate that the MBPNN model produces ~ 28% uncertainty in estimating Kd(490) from the MODIS data. Finally, an exemplification of the applicability of the model to the coastal regions in the Eastern China Seas is carried out. Our results suggest that the Kd(490) shows a large variation in the Eastern China Seas, ranging from 0.02 to 4.0 m− 1, with an average value of ~ 0.17 m− 1.

Phytoplankton light absorption properties were investigated at the surface and subsurface chlorophyll a maximum (SCM) layer in the East China Sea (ECS), a marginal sea which is strongly influenced by the Changjiang discharge in summer. Results from ECS were compared with those from the Tsushima Strait (TS) where the influence of Changjiang discharge is less. The probable controlling factors, packaging effect (cell size) and pigment composition of total chlorophyll a (Tchl a)-specific absorption coefficient (aph&ast;(λ)) were examined by the corresponding measurements of pigments identified by high-performance liquid chromatography. We observed distinct phytoplankton size structure and thereby absorption properties between ECS and TS. At the surface, mixed populations of micro-, nano- and pico-phytoplankton were recorded in ECS while pico-phytoplankton dominated in TS, generating a lower average aph&ast;(λ) in ECS than in TS. Within SCM, average aph&ast;(λ) was higher in ECS than in TS because of the dominance of nano- and micro-phytoplankton in ECS and TS, respectively. By pooling surface and SCM samples, we found regular trends in phytoplankton size-fraction versus Tchl a; and correlations between aph&ast;(λ) and Tchl a consistent with previous observations for the global ocean in TS but not in ECS. In ECS phytoplankton size-fraction was not correlated with Tchl a, which consequently caused poor relationships between aph&ast;(λ) and Tchl a. The abnormal values mainly originated from the surface low-salinity waters and SCM waters beneath them. At high Tchl a, aph&ast;(λ) of these samples was substantially higher compared to the values in TS and from the global regressions, which was attributable to the lower micro-phytoplankton fraction, and higher nano- and/or pico-phytoplankton fractions in ECS. These observations indicated that the distinct light absorption properties of phytoplankton in ECS were possibly influenced by the Changjiang discharge. Our findings imply that general bio-optical algorithms proposed based on the correlations between aph&ast;(λ) and Tchl a or the patterns in size-fraction versus Tchl a are not applicable in ECS, and need to be carefully considered when using these general algorithms in river-influenced regions.

Time series of the chlorophyll-a concentration (Chl-a) observed by ocean color satellites from 1998 to 2009 were used to assess eutrophication in Toyama Bay, the Sea of Japan. An overall mean of Chl-a during the 12-year period was used to divide the study area into “high” or “low” Chl-a areas based on a reference condition of 5 mg m−3. The annual maximum monthly mean Chl-a trend was estimated pixel-wise and its significance examined by the Sen slope test at a 90 % confidence level. By combining the level and trend of remotely sensed Chl-a, Toyama Bay was then classified into six eutrophication states: high-increasing, high-no trend, high-decreasing, low-increasing, low-no trend and low-increasing. Our study indicates that the combined use of both the level and trend of remotely sensed Chl-a can be an efficient method to preliminarily assess eutrophication of coastal waters after a quality screening process with level 2 flags and validation with in situ Chl-a data.

In recent decades, human-driven environmental change caused by the modification of river discharges, the exploitation of marine resources, the burning of fossil fuels, and various shoreline developments and engineering activities, has accelerated; and evidence of this is seen around the world. Linking continents with open oceans, coastal seas trap most land-based discharge and consequently face varying degrees of anthropogenic change.

Giant jellyfish (Nemopilema nomurai) outbreaks in relation to satellite sea surface temperature (SST) and chlorophyll-a concentrations (Chl-a) were investigated in the Yellow Sea and East China Sea (YECS) from 1998 to 2010. Temperature, eutrophication, and match–mismatch hypotheses were examined to explain long-term increases and recent reductions of N. nomurai outbreaks. We focused on the timing of SST reaching 15 °C, a critical temperature enabling polyps to induce strobilation and enabling released ephyra to grow. We analyzed the relationship of the timing with interannual variability of SST, Chl-a, and the timing of phytoplankton blooms. Different environmental characteristics among pre-jellyfish years (1998–2001), jellyfish years (2002–2007, 2009), and non-jellyfish years (2008, 2010) were assessed on this basis. The SST during late spring and early summer increased significantly from 1985 to 2007. This indicated that high SST is beneficial to the long-term increases in jellyfish outbreaks. SST was significantly lower in non-jellyfish years than in jellyfish years, suggesting that low SST might reduce the proliferation of N. nomurai. We identified three (winter, spring, and summer) major phytoplankton bloom regions and one summer decline region. Both Chl-a during non-blooming periods and the peak increased significantly from 1998 to 2010 in most of the YECS. This result indicates that eutrophication is beneficial to the long-term increases in jellyfish outbreaks. Timing of phytoplankton blooms varied interannually and spatially, and their match and mismatch to the timing of SST reaching 15 °C did not correspond to long-term increases in N. nomurai outbreaks and the recent absence.

Seasonal and spring interannual variations in chlorophyll- a (Chl) and total suspended matter (TSM) in the Yellow and East China Seas through a 10-year period were examined by using new datasets from Yellow Sea Large Marine Ecosystem Ocean Color Project (YOC) algorithms. YOC SCHL calculations are based on a combination of the SeaWiFS standard algorithm and a local empirical algorithm for areas of low and high normalized water-leaving radiance 555 nm, respectively. YOC SCHL was lower than the standard SCHL in areas with high concentrations of resuspended sediment, especially along the Chinese and Korean coasts and around the Changjiang Bank from fall to spring. YOC SCHL was high in areas of low TSM in the middle of the Yellow Sea, and offshore of the Changjiang Bank in April, indicating the occurrence of spring blooms. In these areas, TSM was dominated by phytoplankton cells and phytoplankton-related organic particles. Offshore from the Changjiang River mouth and around the Changjiang Bank, YOC SCHL and TSM in March were low and high, respectively, with maximum YOC SCHL values occurring around the Changjiang Bank in May. Spring bloom started with decrease in resuspended sediment concentrations in these areas. During summer, YOC SCHL values were high and TSM concentrations were low; TSM was dominated by organic particles related to phytoplankton activity when Changjiang River diluted water moved from the river mouth to east of the bank. YOC SCHL in spring offshore from the Changjiang River mouth increased significantly during the 10 years, and correspond to an increase in red tide events. In the middle of the Yellow Sea, maximum YOC SCHL in spring increased gradually and significantly during the 10 years. Many of the spatial and temporal variations in YOC SCHL were consistent with a range of earlier in situ descriptions. Our results indicate that the satellite ocean data with proper algorithms is a powerful tool to analyze phytoplankton dynamics in moderate-high suspended sediment area.

The end of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission makes harmful algal bloom (HAB) detection with moderate resolution satellite data now relies on Moderate Resolution Imaging Spectroradiometer (MODIS). Based on MODIS and in situ data collected in the coastal region of the western part of Seto-Inland Sea, Japan with HAB-forming algae Karenia mikimotoi, a simpler new satellite remote sensing-based HAB detection method was developed. The strength of this method is, although it does not require indigenous atmospheric correction scheme, it is expected to be able to classify K. mikimotoi blooms, diatom blooms, TSM-dominated waters, gelbstoff-dominated waters, and mixed waters in the optically complex coastal waters. We anticipate that our satellite remote sensing-based HAB detection method can operate as a valuable complementary tool assisting in situ HAB monitoring and as an integrated part of HAB early warning systems to mitigate HAB negative impacts not only in the coastal waters of the western part of Seto-Inland Sea, Japan, but also in the other coastal waters with different HAB-forming algae, providing that backscattering signature and pigment packaging of other HAB-forming algae are similar to those of K. mikimotoi.

Knowledge of phytoplankton community structures is important to the understanding of various marine biogeochemical processes and ecosystem. Fluorescence excitation spectra (F(λ)) provide great potential for studying phytoplankton communities because their spectral variability depends on changes in the pigment compositions related to distinct phytoplankton groups. Commercial spectrofluorometers have been developed to analyze phytoplankton communities by measuring the field F(λ), but estimations using the default methods are not always accurate because of their strong dependence on norm spectra, which are obtained by culturing pure algae of a given group and are assumed to be constant. In this study, we proposed a novel approach for estimating the chlorophyll a (Chl a) fractions of brown algae, cyanobacteria, green algae and cryptophytes based on a data set collected in the East China Sea (ECS) and the Tsushima Strait (TS), with concurrent measurements of in vivo F(λ) and phytoplankton communities derived from pigments analysis. The new approach blends various statistical features by computing the band ratios and continuum-removed spectra of F(λ) without requiring a priori knowledge of the norm spectra. The model evaluations indicate that our approach yields good estimations of the Chl a fractions, with root-mean-square errors of 0.117, 0.078, 0.072 and 0.060 for brown algae, cyanobacteria, green algae and cryptophytes, respectively. The statistical analysis shows that the models are generally robust to uncertainty in F(λ). We recommend using a site-specific model for more accurate estimations. To develop a site-specific model in the ECS and TS, approximately 26 samples are sufficient for using our approach, but this conclusion needs to be validated in additional regions. Overall, our approach provides a useful technical basis for estimating phytoplankton communities from measurements of F(λ).

Fast repetition rate fluorometry (FRRf) provides a potential means to examine marine primary productivity; however, FRRf-based productivity estimations require knowledge of the electron requirement (K) for carbon (C) uptake (K C) to scale an electron transfer rate (ETR) to the CO2 uptake rate. Most previous studies have derived K C from parallel measurements of ETR and CO2 uptake over relatively short incubations, with few from longer-term daily-integrated periods. Here we determined K C by comparing depth-specific, daily ETRs and CO2-uptake rates obtained from 24-h on-deck incubation experiments undertaken on seven cruises in Ariake Bay, Japan, from 2008 to 2010. The purpose of this study was to determine the extent of variability of K C and to what extent this variability could be reconciled with the prevailing environmental conditions and ultimately to develop a method for determining net primary productivity (NPP) based on FRRf measurements. Both daily ETR and K C of the upper layer varied considerably, from 0.5 to 115.7 mmol e− mg Chl-a −1 day−1 and 4.1–26.6 mol e− (mol C)−1, respectively, throughout the entire data set. Multivariate analysis revealed a strong correlation between daily photosynthetically active radiation (PAR) and K C (r 2 = 0.94). A simple PAR-dependent relationship derived from the data set was used for generating K C, and this relationship was validated by comparing the FRRf-predicted NPP with the 13C uptake measured in 2007. These new observations demonstrate the potential application of FRRf for estimating regional NPP from ETR.

To trace offshore surface low-salinity water (LSW) in the northeastern Gulf of Mexico, a proxy was developed using the surface water beam attenuation coefficient (c p), and salinity matched with synchronous Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite data from three annual summer cruises (July 1998–August 2000) using a two-step empirical approach. First, a relationship between in-situ salinity and c p was obtained. Second, in-situ c p was matched with SeaWiFS radiance ratios of all available blue-to-green wavelengths. Finally, satellite-derived surface salinity was determined directly by combining the two empirical relationships, providing a robust estimate over a range of salinities (26–36). This significantly improves the limited spatial and temporal resolution of surface salinity distribution obtained by shipboard sampling. The resulting correlation is best explained as mixing between low-salinity plume waters and normal salinity Gulf waters. The empirical relationships were used to map satellite-derived salinity using the average of SeaWiFS images during each summer cruise. As expected for summer, spatial patterns of LSW plumes with high c p, particulate matter (PM), particulate organic carbon (POC), and chlorophyll-a (Chl-a) were connected to the mouth of the Mississippi River Delta and extended to the east-southeast. Normal salinity Gulf water with lower c p, PM, POC, and Chl-a was confined to the shelf and upper slope in the eastern part of the study area, outside the plumes. This proxy approach can be applied throughout the region of shipboard sampling for more detailed coverage and analysis.

The vertically generalized production model (VGPM), which was designed for open ocean waters ( Behrenfeld and Falkowski, 1997a ; henceforth BF), was evaluated using in situ measurements of primary productivity (PP) in the characteristically turbid coastal waters of Ariake Bay, southwestern Japan, to develop a regionally modified version of the model. The euphotic depth (Zeu)-integrated PP (IPP) calculated from the VGPM using in situ chlorophyll a (Chl a) and sea surface temperature (SST) was significantly overestimated (by factors of 2–3), but 52% of the observed variability was explained. The weak correlation could have partially resulted from overestimations by the sub-models embedded in the original VGPM model for estimation of Zeu ( Morel and Berthon, 1989 ; henceforth MB) and the optimal Chl a-normalized PP ( p opt B ). The sub-model estimates of p opt B and Zeu with in situ p opt B and Zeu showed significant improvement, accounting for 84% of the variability and causing less overestimation. Zeu was the most important parameter influencing the modeled IPP variation in Ariake Bay. Previous research suggested that the Zeu model, which was based on surface Chl a, overestimated in situ Zeu by a factor of 2–3, resulting in weak correlation between the modeled and in situ IPP. The Zeu sub-model was not accurate in the present study area because it was basically developed for clear (case 1) waters. A better estimation of Zeu could be obtained from the in situ remote sensing reflectance (Rrs) using a quasi-analytical algorithm (QAA) in this turbid water ecosystem. Among the parameters of PP models, p opt B is conventionally considered the most important. However, in this study p opt B was of secondary importance because the contribution of p opt B to the variation in modeled IPP was less than the contribution of Zeu. The modeled and in situ p opt B were weakly correlated with 50% of the data points that overestimated the in situ values. The estimation of Chl a was improved by optimizing the Chl a algorithm with in situ Rrs data. Incorporating the QAA-based Zeu and the optimized Chl a and constant (median) p opt B value led to improved performance of the VGPM for the study area. Thus, even though the VGPM is a global open ocean model, when coupled with turbid water algorithms for Zeu and Chl a and constant (median) p opt B , it provided realistic estimates of IPP in the turbid water ecosystem of Ariake Bay.

To distinguish true red tide water (particularly Cochlodinium polykrikoides blooms) from non-red tide water (false satellite high chlorophyll water) in the South Sea of Korea, we developed a systematic classification method using spectral information from MODIS level products and applied it to five different harmful algal bloom events. Red tide and nonred tide waters were classified based on four different criteria. The first step revealed that the radiance peaks of potential red tide water occurred at 555 and 678 nm. The second step separated optically different waters that were influenced by relatively low and high contributions of colored dissolved organic matter (CDOM) (including detritus) to chlorophyll. The third and fourth steps discriminated red tide water from non-red tide water based on the blue-to-green ratio in areas with lower and higher contributions of CDOM to chlorophyll, respectively. After applying the red tide classification (using the four criteria), the spectral response of the red tide water, which is influenced by pigment concentration, showed different slopes for the blue and green bands (lower slope at blue bands and higher slope at green bands). The opposite result was found for non-red tide water, due to decreasing phytoplankton absorption and increasing detritus/CDOM absorption at blue bands. The results were well matched with the discoloration of water (blue to dark red/brown) and delineated the areal coverage of C. polykrikoides blooms, revealing the nature of spatial and temporal variations in red tides. This simple spectral classification method led to increase user accuracy for C. polykrikoides and non-red tide blooms (>46% and >97%) and provided a more reliable and robust identification of red tides over a wide range of oceanic environments than was possible using chlorophyll a concentration, chlorophyll anomaly, fluorescence analysis, or proposed red tide detection algorithms.

Underwater light environment and photosynthetic accessory pigments were investigated in Ariake Bay in order to understand how change of the pigments occurs in response to the tidal-induced changes in underwater light conditions. We hypothesize that phytoplankton increases photo-protective pigments and decreases light-harvesting pigments under higher light condition in the mixed layer caused by tidal cycle. Contribution rates of non-phytoplankton particles (a nph (400‐700)) for light attenuation coefficient (K d ) was highest (32‐85%), and those of phytoplankton particles (a ph (400‐700)), dissolved organic matter (a g (400‐700)) and water were 6‐32, 6‐21 and 5‐23%, respectively. Mean K d was higher during the spring tide (0.55 ± 0.23 m ‐1 ) than the neap tide (0.44 ± 0.16 m ‐1 ), and the K d difference was caused by the substances resuspension due to the tidal current. In contrast, ratios of photo-protective pigments (diadinoxanthin and diatoxanthin) per chlorophyll a ((DD+DT)/Chl a) were higher during the neap tide (0.10 ± 0.03 mg mg-Chl a ‐1 ) than the spring tide (0.08 ± 0.03 mg mg-Chl a ‐1 ). And there was significant positive correlation between (DD+DT)/ Chl a and mean relative PAR in the mixed layer ( Imix ). Moreover, there was significant negative correlation between ratios of light-harvesting pigments (fucoxanthin) per Chl a (Fuco/Chl a) and Imix . These results suggested that phytoplankton in Ariake Bay increase photo-protective pigments and decrease light-harvesting pigments in the higher light condition of less turbid, shallower mixed layer during neap tide than spring tide.

The accurate retrieval of chlorophyll-a concentration (Chl-a) from ocean color satellite data is extremely challenging in turbid, optically complex coastal waters. Ariake Bay in Japan is a turbid semi-enclosed bay of great socio-economic significance, but it suffers from serious water quality problems, particularly due to red tide events. Chl-a derived from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor on satellite Aqua in Ariake Bay was investigated, and it was determined that the causes of the errors were from inaccurate atmospheric correction and inappropriate in-water algorithms. To improve the accuracy of MODIS remote sensing reflectance (Rrs) in the blue and green bands, a simple method was adopted using in situ Rrs data. This method assumes that the error in MODIS Rrs(547) is small, and MODIS Rrs(412) can be estimated from MODIS Rrs(547) using a linear relation between in situ Rrs(412) and Rrs(547). We also showed that the standard MODIS Chl-a algorithm, OC3M, underestimated Chl-a, which was mostly due to water column turbidity. A new empirical switching algorithm was generated based on the relationship between in situ Chl-a and the blue-to-green band ratio, max(Rrs(443), Rrs(448)/Rrs(547), which was the same as the OC3M algorithm. The criterion of Rrs(667) of 0.005 sr−1 was used to evaluate the extent of turbidity for the switching algorithm. The results showed that the switching algorithm performed better than OC3M, and the root mean square error (RMSE) of estimated Chl-a decreased from 0.414 to 0.326. The RMSE for MODIS Chl-a using the recalculated Rrs and the switching algorithm was 0.287, which was a significant improvement from the RMSE of 0.610, which was obtained using standard MODIS Chl-a. Finally, the accuracy of our method was tested with an independent dataset collected by the local Fisheries Research Institute, and the results revealed that the switching algorithm with the recalculated Rrs reduced the RMSE of MODIS Chl-a from 0.412 of the standard to 0.335.