naa a22 4500 510753809 CHVBK 20180411083115.0 cr unu---uuuuu 180411e20130701xx s 000 0 eng 10.1007/s13131-013-0328-y doi (NATIONALLICENCE)springer-10.1007/s13131-013-0328-y Assimilation of surface currents into a regional model over Qingdao coastal waters of China [Elektronische Daten] [Jian Zhao, Xueen Chen, Jiangling Xu, Wei Hu, Jinrui Chen, Thomas Pohlmann] Surface currents measured by high frequency (HF) radar arrays are assimilated into a regional ocean model over Qingdao coastal waters based on Kalman filter method. A series of numerical experiments are performed to evaluate the performance of the data assimilation schemes. In order to optimize the analysis procedure in the traditional ensemble Kalman filter (ENKF), a different analysis scheme called quasiensemble Kaman filter (QENKF) is proposed. The comparisons between the ENKF and the QENKF suggest that both them can improve the simulated error and the spatial structure. The estimations of the background error covariance (BEC) are also assessed by comparing three different methods: Monte Carlo method; Canadian quick covariance (CQC) method and data uncertainty engine (DUE) method. A significant reduction of the root-mean-square (RMS) errors between model results and the observations shows that the CQC method is able to better reproduce the error statistics for this coastal ocean model and the corresponding external forcing. In addition, the sensibility of the data assimilation system to the ensemble size is also analyzed by means of different scales of the ensemble size used in the experiments. It is found that given the balance of the computational cost and the forecasting accuracy, the ensemble size of 50 will be an appropriate choice in the Qingdao coastal waters. The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg, 2013 Qingdao coastal waters nationallicence surface currents nationallicence Ensemble Kalman filter nationallicence Finite Volume Coastal Ocean Model (FVCOM) nationallicence Zhao Jian College of Physical and Environmental Oceanography, Ocean University of China, 266100, Qingdao, China aut Chen Xueen College of Physical and Environmental Oceanography, Ocean University of China, 266100, Qingdao, China aut Xu Jiangling North China Sea Brach, State Oceanic Administration, 266003, Qingdao, China aut Hu Wei North China Sea Brach, State Oceanic Administration, 266003, Qingdao, China aut Chen Jinrui College of Physical and Environmental Oceanography, Ocean University of China, 266100, Qingdao, China aut Pohlmann Thomas University of Hamburg, D-20146, Hamburg, Germany aut Acta Oceanologica Sinica Springer Berlin Heidelberg 32/7(2013-07-01), 21-28 0253-505X 32:7<21 2013 32 13131 https://doi.org/10.1007/s13131-013-0328-y text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s13131-013-0328-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhao Jian College of Physical and Environmental Oceanography, Ocean University of China, 266100, Qingdao, China aut NATIONALLICENCE 700 1- Chen Xueen College of Physical and Environmental Oceanography, Ocean University of China, 266100, Qingdao, China aut NATIONALLICENCE 700 1- Xu Jiangling North China Sea Brach, State Oceanic Administration, 266003, Qingdao, China aut NATIONALLICENCE 700 1- Hu Wei North China Sea Brach, State Oceanic Administration, 266003, Qingdao, China aut NATIONALLICENCE 700 1- Chen Jinrui College of Physical and Environmental Oceanography, Ocean University of China, 266100, Qingdao, China aut NATIONALLICENCE 700 1- Pohlmann Thomas University of Hamburg, D-20146, Hamburg, Germany aut NATIONALLICENCE 773 0- Acta Oceanologica Sinica Springer Berlin Heidelberg 32/7(2013-07-01), 21-28 0253-505X 32:7<21 2013 32 13131 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer