CHEN Xueen, ZHAN Peng, CHEN Jinrui, QIAN Hongbao. Numerical study of current fields near the Changjiang Estuary and impact of Quick-EnKF assimilation[J]. Acta Oceanologica Sinica, 2011, (5): 33-44. doi: 10.1007/s13131-011-0145-0
Citation:
CHEN Xueen, ZHAN Peng, CHEN Jinrui, QIAN Hongbao. Numerical study of current fields near the Changjiang Estuary and impact of Quick-EnKF assimilation[J]. Acta Oceanologica Sinica, 2011, (5): 33-44. doi: 10.1007/s13131-011-0145-0
CHEN Xueen, ZHAN Peng, CHEN Jinrui, QIAN Hongbao. Numerical study of current fields near the Changjiang Estuary and impact of Quick-EnKF assimilation[J]. Acta Oceanologica Sinica, 2011, (5): 33-44. doi: 10.1007/s13131-011-0145-0
Citation:
CHEN Xueen, ZHAN Peng, CHEN Jinrui, QIAN Hongbao. Numerical study of current fields near the Changjiang Estuary and impact of Quick-EnKF assimilation[J]. Acta Oceanologica Sinica, 2011, (5): 33-44. doi: 10.1007/s13131-011-0145-0
A 30-d current numerical simulation is running for the Yangshan Port, the Changjiang Estuary, the Hangzhou Bay and their adjacent seas using a finite volume coastal ocean model (FVCOM), with Changjiang River runoff and wind effect being considered. At the open boundary, this model is driven by the water level obtained from prediction including eight main partial tides. After the harmonic analysis, the cotidal chart and the iso-amplitude line as well as the current ellipse distribution map are displayed to illustrate the propagation property of a tidal wave. Horizontal velocity of both the U and V components coincides with the actual measurement, which shows that the model result is credible to describe the hydrodynamic pattern in this sea area. On this basis, real-time current data from high-frequency radar is assimilated with the implementation of quick ensemble Kalman filter, which takes the variation tendency of the state vector to compute the analysis field, instead of integrating the field for N (the number of ensemble) times as it used to in the standard EnKF, aiming at raising the efficiency of computation, reducing the error of prediction and at the same time, improving the forecast effect.