Wenxi Cao

Variations in the optical scattering properties of phytoplankton cultures.

The scattering and backscattering coefficients of 15 phytoplankton species were determined in the laboratory using the acs and BB9 instruments. The spectral variability of scattering properties was investigated and the homogenous sphere model based on Mie theory was also evaluated. The scattering efficiencies at 510 nm varied from 1.42 to 2.26, and the backscattering efficiencies varied from 0.003 to 0.020. The backscattering ratios at 510 nm varied from 0.17% to 0.97%, with a mean value of 0.58%. The scattering properties were influenced by algal cell size and cellular particulate organic carbon content rather than the chlorophyll a concentration. Comparison of the measured results to the values estimated using the homogenous sphere model showed that: (1) The model could well reproduce the spectral scattering coefficient with relative deviations of 5-39%, which indicates that cell shape and internal structure have no significant effects on predicting the scattering spectra; (2) Although the homogenous sphere model generally reflected the spectral trend of backscattering spectra for most species, it severely underestimated the backscattering coefficients by 1.4-48.6 folds at 510 nm. The deviations for Chaetoceros sp. and Microcystis aeruginosa were large and might be due to algal cell chain links and intracellular gas vacuoles, respectively.

Measuring natural phytoplankton fluorescence and biomass: a case study of algal bloom in the Pearl River estuary.

A moored optical buoy was deployed in the Pearl River estuarine waters for a 15-day period. A four-day algal bloom event occurred during this study period. Both chlorophyll a concentration and algal cell density (a proxy for biomass) changed dramatically before and after the event. The chlorophyll concentration at a 2.3m depth rose from 5.15 mg/m(-3) at 15:00 h on August 19 to 23.62 mg/m(-3) at 9:00 h on August 21, and then decreased to 3.24 mg/m(-3) at 15:00 h on August 24. The corresponding cell density ranged from 1.57 x 10(5) to 1.76 x 10(6)cells/L. We used normalized fluorescence line height (NFLH) and normalized fluorescence intensity (NFI) in order to determine fluorescence activity. Combined with the in situ sampling dataset, we were able to correlate natural fluorescence (NFLH and NFI) with chlorophyll a concentrations, and found correlation coefficients of 0.72 and 0.75, respectively. We also found correlations between natural fluorescence and cell density, with correlation coefficients of 0.71 and 0.65, respectively. These results indicate that applying continuous time series of natural fluorescence can reflect changes in biomass. This technique will prove extremely useful for in situ and real-time observations using an optical buoy. Although there are still problems to solve in the real-time observation of natural fluorescence in algal bloom events, we discuss the primary factors affecting fluorescence signals and suggest possible methods for mitigating these issues.

Variation of particulate organic carbon and its relationship with bio-optical properties during a phytoplankton bloom in the Pearl River estuary.

In this study, variations in the particulate organic carbon (POC) were monitored during a phytoplankton bloom event, and the corresponding changes in bio-optical properties were tracked at one station (114.29°E, 22.06°N) located in the Pearl River estuary. A greater than 10-fold increase in POC (112.29-1173.36 mg m⁻³) was observed during the bloom, with the chlorophyll a concentration (Chl-a) varying from 0.984 to 25.941 mg m⁻³. A power law function is used to describe the relationship between POC and Chl-a, and the POC:Chl-a ratio tends to change inversely with Chl-a. Phytoplankton carbon concentration is indirectly estimated using the conceptual model proposed by Sathyendranath et al. (2009), and this carbon is found to contribute 47.21% (±10.65%) to total POC. The estimated carbon-to-chlorophyll ratio of phytoplankton in diatom-dominated waters is found to be comparable with results reported in the literature. Empirical algorithms for determining the concentrations of Chl-a and POC were developed based on the relationships of these variables with the blue-to-green reflectance ratio. With these bio-optical models, the levels of particulate organic carbon and Chl-a could be predicted from the radiometric data measured by a marine optical buoy, which showed much more detailed information about the variability in biogeochemical parameters during this bloom event.

Analysis of seagrass reflectivity by using a water column correction algorithm

Seagrass in optically shallow water can generate optical signals that can be tracked remotely. Unfortunately the signals from the bottom are relatively weak and can be affected by the water column when concentrations of suspended particles, chlorophyll and coloured dissolved organic matter are high. An optical model simulating the propagation of light for retrieving the bottom reflectance was developed. Implementation of the method was found to be effective for improving the accuracy of coastal habitat maps, and essential for deriving empirical relationships between remotely sensed data and interesting features in the marine environment. The appropriate wavebands for seagrass mapping, which generally lay between 500 and 630 nm and 680 and 710 nm, were obtained by means of full visual inspection and analysis of the correct spectra. Additionally, a strong relationship between the reflectance value at 715 nm and Leaf Area Index was found, with a correlation coefficient of 0.99.

Satellite-observed variability of phytoplankton size classes associated with a cold eddy in the South China Sea

Ocean-color remote sensing has been used as a tool to detect phytoplankton size classes (PSCs). In this study, a three-component model of PSC was reparameterized using seven years of pigment measurements acquired in the South China Sea (SCS). The model was then used to infer PSC in a cyclonic eddy which was observed west of Luzon Island from SeaWiFS chlorophyll-a (chla) and sea-surface height anomaly (SSHA) products. Enhanced productivity and a shift in the PSC were observed, which were likely due to upwelling of nutrient-rich water into the euphotic zone. The supply of nutrients promoted the growth of larger cells (micro- and nanoplankton), and the PSC shifted to greater sizes. However, the picoplankton were still important and contributed ∼48% to total chla concentration. In addition, PSC time series revealed a lag period of about three weeks between maximum eddy intensity and maximum chlorophyll, which may have been related to phytoplankton growth rate and duration of eddy intensity.

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

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

Modelling the influence of mineral particles and phytoplankton on chlorophyll estimation from ocean colour remote sensing

The absorption and backscattering properties of phytoplankton were calculated from Mie theory for different slopes of Junge‐type size distribution and different complex refractive indices of particles. The ratio of the spectral backscattering coefficient to the sum of the spectral absorption and backscattering coefficients of seawater was analysed as a proxy for reflectance of various concentrations of phytoplankton and mineral particles in seawater. The results indicate that the chlorophyll‐specific absorption and backscattering are very sensitive to variations in size distribution and refractive index. Therefore, phytoplankton with a steeper slope of size distribution or stronger absorption ability could cause higher OC4v4‐derived chlorophyll concentrations than those with a gentler slope of size distribution or lower absorption properties. Mineral particles also have a strong effect on the determination of chlorophyll concentration. With a gradual increase in mineral concentration, an overall increase in the magnitude of the whole reflectance spectrum is observed, and the spectral maximum tends to shift towards longer wavelengths. The mineral particles may cause an overestimation of OC4v4‐derived chlorophyll at low chlorophyll concentrations and an underestimation at high chlorophyll concentrations compared to that in seawater without mineral particles.

Novel method for quantifying the cell size of marine phytoplankton based on optical measurements.

Phytoplankton size is important for the pelagic food web and oceanic ecosystems. However, the size of phytoplankton is difficult to quantify because of methodological constraints. To address this limitation, we have exploited the phytoplankton package effect to develop a new method for estimating the mean cell size of individual phytoplankton populations. This method was validated using a data set that contained simultaneous measurements of phytoplankton absorption and cell size distributions from 13 phytoplankton species. Comparing with existing methods, our method is more efficient with good accuracy, and it could potentially be applied in current in situ optical instruments.

Diurnal variability of ocean optical properties during a coastal algal bloom: implications for ocean colour remote sensing

Understanding the diurnal variability of ocean optical properties is critical for better interpretation of satellite ocean colour data and characterizing biogeochemical processes. The daytime variability of ocean optical properties throughout an algal bloom event is analysed in this article based on in situ observations from dawn to dusk at a fixed coastal site in the South China Sea. Diurnal variability during the sunlit period of the ocean optical properties is found to be significant. During the 6 hours around noon, the temporal variability (defined by the coefficient of variation) of phytoplankton absorption, coloured dissolved organic matter and non-algal particle absorption, and particle backscattering at 443 nm can reach 21% ± 15%, 12% ± 9%, and 17% ± 9%, respectively. The diurnal variability during the bloom is much more pronounced than that of the non-bloom phase. With atmospheric radiative transfer modelling, it is further demonstrated that the geostationary satellite detection of within-day optical variability in algae-dominated waters depends on the reliability of the aerosol retrieval. The implications of the diurnal bio-optical variability for the retrieval, validation, and interpretation of satellite ocean colour products are also discussed.

Empirical ocean color algorithm for estimating particulate organic carbon in the South China Sea

We examined regional empirical equations for estimating the surface concentration of particulate organic carbon (POC) in the South China Sea. These algorithms are based on the direct relationships between POC and the blue-to-green band ratios of spectral remotely sensed reflectance, Rrs (λB)/Rrs(555). The best error statistics among the considered formulas were produced using the power function POC (mg/m3)=262.173 [Rrs(443)/Rrs(555)]−0.940. This formula resulted in a small mean bias of approximately −2.52%, a normalized root mean square error of 31.1%, and a determination coefficient of 0.91. This regional empirical equation is different to the results of similar studies in other oceanic regions. Our validation results suggest that our regional empirical formula performs better than the global algorithm, in the South China Sea. The feasibility of this band ratio algorithm is primarily due to the relationship between POC and the green-toblue ratio of the particle absorption coefficient. Colored dissolved organic matter can be an important source of noise in the band ratio formula. Finally, we applied the empirical algorithm to investigate POC changes in the southwest of Luzon Strait.