Studies On Ocean Color Remote Sensing In The Bohai Sea Of China

Ocean color remote sensing has become important in the ocean sciences, especially for the coastal oceans. Bohai Sea is a semi-enclosed inland sea with a typical case-2 water environment located at the northernmost end of eastern Chinese mainland. Understandings of its bio-optical properties will be quite important for the improvements of ocean color applications in China. Due to the shallow bottom depths and large amounts of suspended matters transported from some big rivers, however, the optical properties of Bohai Sea become so complicated that the operational chlorophyll algorithms of the world often fail in this area.Based upon the measured data in the coastal areas of Bohai Sea, preliminary results are obtained about the optical properties including the absorption, scattering, and attenuation properties of the water body. Also, this study builds some remote sensing models to predict the inherent optical properties from above surface remote sensing reflectance.Empirical band-ratio algorithms and artificial neural network techniques to retrieve sea surface chlorophyll concentrations are evaluated in the Bohai Sea by using an extensive field observation data set. The comparison results show that these empirical algorithms developed for case-1 and case-2 waters can not be applied directly to the Bohai Sea, because of significant biases. For example, the mean normalized bias (MNB) for OC4V4 product is 1.85 and the root mean square (RMS) error is 2.26. It appears that the Bohai Sea requires new approaches and new parameterizations for both empirical and semi-analytical pigment algorithms.According to the radiative transfer theory, an idealized ocean color model is used to study the effect of nonuniform chlorophyll profile on the ocean color parameters such as penetration depth, the above-surface spectral remote-sensing reflectance, and the optically weighted chlorophyll concentration. The simulations for a vertically nonuniform chlorophyll concentration are compared with reference simulations for a homogeneous ocean whose chlorophyll concentration is identical to the surface chlorophyll concentration of inhomogeneous cases. Due to the influence of the nonuniformity, the maximum relative error at 445 nm for penetration depth is up to 60%, spectral remote-sensing reflectance is about 40% and optically weighted chlorophyll concentration is about 40% within the range of our simulations.Model results show that there is always a spectral band where the value of above-surface remote-sensing reflectance is not influenced by the nonuniformity. Depending on this band, a new model for retrieving sea surface chlorophyll concentration is designed by adding a compensation term into the variable in SeaWiFS OC2V4 algorithm. By using an iterative method with this new model, sea surface chlorophyll concentration can be well retrieved even in the area where the vertical chlorophyll distribution is unknown. This is a new method which is not ever proposed before, and by using this model, people don't need to consider the vertical distributions of chlorophyll.Special characteristics of deep chlorophyll maximum in Bohai Sea of China are examined in this study with four cruises data measured in June and August of 2003 and 2005 respectively. Based on what we measured in 2003, a new blue-to-green ratio method ocean color model to retrieve concentration of deep chlorophyll maximum from the remote sensing reflectance above sea surface is proposed. This model is able to be used in case-2 water areas with depth of deep chlorophyll maximum shallower than 7 meters. This model confirms that satellite sensors can detect deep chlorophyll maximum in most areas of Bohai Sea and the existence of deep chlorophyll maximum also can bring big retrieval errors to ocean color models. The maximum depth from which the radiometer receives significant signal varies as a function of wavelength and of the clarity of the water. Blue or green light can penetrate deeper than red light in sea waters, so satellite sensors in blue and green bands are able to receive the signal of deep chlorophyll maximum. In the shallow seas of case-2 water with shallow depth and high concentration of deep chlorophyll maximum, contribution of deep chlorophyll maximum to remote sensing signals is much larger than that from the sea surface chlorophyll. Therefore, we suggest that we should not focus our attention only in sea surface for study of the ocean color retrieval models, but also should broaden the field of vision.According to Lee's study, a hyperspectral remote-sensing reflectance inversion model is parameterized by using measured data in coastal areas of Bohai Sea. The model only uses remote-sensing reflectance to derive a set of values of absorption, backscattering, water bottom albedo, and bottom depth. The model shows good performances to retrieve phytoplankton absorption and colored detrital matter (detritus plus gelbstoff) absorption. More important, statistical analysis result shows that model derived depths agree well with measured depths of deep chlorophyll maximum, where no significant bias is found, which is primarily due to the existence of water stratification. Therefore, together with the empirical blue-to-green ratio method to retrieve concentration of deep chlorophyll maximum, this study succeed in retrieving the properties of deep chlorophyll maximum (the concentration and the depth) by using remote sensing methods. This work broadens the view of applications of ocean color remote sensing not only just from the surface but also into the oceanic interior, which provides a new method to use ocean color data.