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Son, Y.B.; Kim, Y.H.; Choi, B.-J., and Park, Y.-G., 2016. Lagrangian Coherence Structures and the dispersion of green algal bloom in the Yellow and East China Sea. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 1237 - `1241. Coconut Creek (Florida), ISSN 0749-0208. During the summer 2011, the Geostationary Ocean Colour Imager (GOCI) detected patches of the recurrent massive floating green algae in the central part of the Yellow Sea (YS) and East China Sea (ECS). This study utilizes the Lagrangian Coherent Structures (LCSs) analysis to demonstrate the horizontal dispersion pattern of algal bloom patches. This approach is based on the assumption that unstable manifolds such as ridges in the finite-time Lyapunov exponent (FTLE) fields coincide with material transport barriers. To calculate the FTLE fields, flow fields derived from the Regional Ocean Modeling System (ROMS) and wind fields were utilized. The combined effects of winds and currents in material transport in coastal and ocean environments were investigated. Comparison of LCSs derived by current only and current-wind combined flow showed that the results of current-wind combined flow cases match better the observation results from GOCI than those of current only cases. This implies that the distribution pattern of green algae patches would be controlled by the combined effect of the surface current and wind that was included LCS in terms of leeway effect. [ABSTRACT FROM AUTHOR]

To increase the accuracy of ocean predictions in the Yellow and East China Sea (YES), the satellite-borne sea surface temperature (SST) data have been assimilated to an operational ocean modeling system by applying an ensemble Kalman filter (EnKF). As the observed SST was assimilated continuously into the model with time, the ensemble spread decreased and the efficiency of data assimilation degenerated. To increase liability of the system and the ensemble spread, model uncertainties were represented stochastically by perturbing the model tendency parameters such as eddy viscosity, bottom drag coefficient, light attenuation depth, as well as atmospheric forcing. Data assimilation experiments were performed with forcing from a regional atmospheric model from September 2011 to February 2012. The assimilation results with and without the stochastically perturbed model parameters and atmospheric forcing were compared. The ensemble with the perturbations has larger spread and smaller root-mean-square deviation (RMSD) in temperature compared with the ensemble without the perturbations. The SST RMSD relative to anther supplementary SST dataset was reduced from 0.91 to 0.81 °C over the YES. The assimilation of the SST data improved the simulated SST compared with the observation at the ocean buoy stations, and also made the subsurface temperature profiles closer to the observed ones. The assimilation experiments showed that a stochastic representation of the model errors by the perturbations of the model parameters and atmospheric forcing increases the spread of the ensemble and improves the structure of background error covariance, which enhances the performance of the ensemble modeling system in the YES. [ABSTRACT FROM AUTHOR]

In an image from the Geostationary Ocean Color Imager (GOCI) taken on 13 June 2011, a recurrent floating green algae bloom was detected around Qingdao. To detect the bloom an index based on multi-spectral band ratios using three wavelengths (555, 660, 745 nm) was utilized. One month later, the GOCI images detected widespread floating green algae patches (east–west elongated) across the Yellow Sea and East China Sea (YS, ECS). The presence of the patches was confirmed from various oceanic observation cruises. Lagrangian particle tracking experiments were conducted to understand the pathway of the floating green algae patches and interpret the physical forcing factors that affect the distribution and advection of the floating green algae. The numerical simulation results indicated that dominant southerly winds during June and July 2011 were related to offshore movement of the floating green algae, especially their eastward extension in the YS/ECS. An infrequent and unusual event occurred in June 2011: a typhoon MEARI, caused the green algae to detach from the coast and initiated movement to the east. After the typhoon event, sea surface temperature recovered rapidly enough to grow the floating green algae, and wind and local current controlled the movement of the massive floating algae patches (coastal accumulation or offshore advection in the YS/ECS). Analysis of the floating green algae pixels' movement during passage of Typhoon MAON in July 2011 revealed that the floating green algae patches were significantly controlled by both ocean currents and enhanced winds. These findings suggest that the floating green algae bloom off Qingdao and in the middle of the YS and ECS in the summer of 2011 occurred due to the combined effects of recent rapid expansion of seaweed aquaculture, strong winds, and the wind patterns in blooming regions. Our combined approach, using satellite data and numerical simulations, provides a robust estimate for tracing and monitoring changes in green algae blooms on a regional scale. [ABSTRACT FROM AUTHOR]