Zhaohua Sun

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.

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.

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.

A bio-optical inversion model to retrieve absorption contributions and phytoplankton size structure from total minus water spectral absorption using genetic algorithm

We propose a bio-optical inversion model that retrieves the absorption contributions of phytoplankton and colored detrital matter (CDM), as well as the phytoplankton size classes (PSCs), from total minus water absorption spectra. The model is based on three-component separation of phytoplankton size structure and a genetic algorithm. The model performance was tested on two independent datasets (the NASA bio-Optical Marine Algorithm Dataset (NOMAD) and the northern South China Sea (NSCS) dataset). The relationships between the estimated and measured values were strongly linear, especially for aCDM (412), and the Root Mean Square Error (RMSE) of the CDM exponential slope (SCDM) was relatively low. Next, the inversion model was directly applied to in-situ total minus water absorption spectra determined by an underwater meter during a cruise in September 2008, to retrieve the phytoplankton size structure in the seawater. By comparing the measured and retrieved chlorophyll a concentrations, we demonstrated that total and size-specific chlorophyll a concentrations could be retrieved by the model with relatively high accuracy. Finally, we applied the bio-optical inversion model to investigate changes in phytoplankton size structure induced by an anti-cyclonic eddy in the NSCS.

Estimating the Augmented Reflectance Ratio of the Ocean Surface When Whitecaps Appear

The presence of foam influences the accuracy of satellite-derived water-leaving radiance. A model has been developed to estimate the augmented reflectance ratio (A(λ,U)) due to differences in the fraction of whitecap coverage (w) on the ocean surface. A(λ,U) can be calculated from the product of w and ρ(λ,U), where ρ(λ,U) is the augmented ratio of the reflectance of background water (Rb(λ)) caused by the presence of whitecaps. Our results showed that the average A(400~700,U) in the visible region was approximately 1.3% at U = 9 m∙s−1, 2.2% at U = 10 m∙s−1, 4.4% at U = 12 m∙s−1, 7.4% at U = 14 m∙s−1, 19% at U = 19 m∙s−1 and 37.9% at U = 24 m∙s−1, making it is necessary to consider the augmented reflectance ratio for remote sensing applications. By estimating remote sensing augmented reflectance using A(λ,U), it was found that the result was in good agreement with previous studies conducted in other areas with U from 9 to 12 m∙s−1. Since Rb(λ) is temporally and spatially variable, our model considered the variation of Rb(λ), whereas existing models have assumed that Rb(λ) is constant. Therefore, the proposed model is more suitable for estimating the augmented reflectance ratio due to whitecaps.

Remote sensing assessment of sediment variation in the Pearl River Estuary induced by Typhoon Vicente

A MODIS-based algorithm was developed to investigate the impact of Typhoon Vicente on the total suspended solid concentration in the Pearl River Estuary. This algorithm used two high resolution bands at 645 nm and 555 nm to map the concentrations. Regression between the remote sensing reflectance and in situ total suspended solid concentration showed good correlation (R2 = 0.91), indicating that the algorithm was valid for the high turbid waters in the Pearl River Estuary. MODIS-derived maps showed different total suspended solid concentration anomalies in different sub-regions of the estuary during the passage of Typhoon Vicente. In western inlets, the increase of total suspended solids (maximum values of 22.20 g m−3 before and 55.71 g m−3 after the typhoon) was possibly related to the larger rainfall discharge from the Pearl River. In Lingdingyang, the increase of total suspended solids (maximum values of 19.60 g m−3 before and 44.59 g m−3 after the typhoon) might be the result of typhoon-induced resuspension. In the southeastern portion of the Estuary, due to the typhoon-induced current, a significant decrease of total suspended solid area (decreased by 10 g m−3) was observed. Different changes were observed in different sub-regions under the influence of the typhoon, implying the complicated hydrological environment is an important feature in the Pearl River Estuary.