Estimation of transport at open boundaries with an ensemble Kalman filter in a coastal ocean model

被引:6
|
作者
Jordi, Antoni [1 ]
Wang, Dong-Ping [2 ]
机构
[1] IMEDEA UIB CSIC, Inst Mediterrani Estudis Avancats, Esporles 07190, Illes Balears, Spain
[2] SUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11794 USA
关键词
Boundary conditions; Kalman filters; Shelf dynamics; Modeling; Mediterranean Sea; GENERAL-CIRCULATION MODEL; 2-WAY NESTED MODEL; DATA-ASSIMILATION; FORECAST ERROR; IMPLEMENTATION; ALGORITHMS; BAY;
D O I
10.1016/j.ocemod.2013.01.002
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The performance of the ensemble adjustment Kalman filter (EAKF) to estimating volume transports at open boundaries was investigated for a coastal ocean model of the Palma Bay, Mallorca Island, Mediterranean Sea. The circulation in the Palma Bay is mainly driven by the remotely wind-generated island trapped waves (ITWs) propagating around Mallorca and by a local wind response. Thus, for a model of the bay proper only, the large-scale ITWs must be incorporated into the open ocean boundary conditions. To take into account the effect of ITWs, an EAKF was used to assimilate the moored Acoustic Doppler Current Profiler (ADCP) velocity time series collected in the inner part of the Bay through a simultaneous state and parameter estimation. In this approach, flows at open boundaries were included in the model state as time-dependent parameters and were updated in each assimilation step. The simulation was validated with moored ADCP data as well as with independent towed ADCP spatial velocity survey data. The new results are markedly improved over the model experiments without data assimilation or with state estimation only. In particular, simulation using the estimated values at open boundaries significantly outperforms simulation with 'a priori' prescribed values at boundaries. The error reduction is about 45% when ITWs dominate the circulation. Our results present a promising approach in dealing with the open boundary conditions in a coastal ocean model. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:56 / 66
页数:11
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