Using ensemble adjustment Kalman filter to assimilate Argo profiles in a global OGCM |
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| Authors: | Xunqiang Yin Fangli Qiao Qi Shu |
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| Institution: | (1) The First Institute of Oceanography, State Oceanic Administration, 6 Xian-Xia-Ling Road, Hi-Tech Industry Park, Qingdao, China, 266061;(2) Key Laboratory of Marine Science and Numerical Modeling (MASNUM), State Oceanic Administration, Qingdao, China; |
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| Abstract: | An ensemble adjustment Kalman filter (EAKF) is used to assimilate Argo profiles of 2008 in a global version of the Modular
Ocean Model version 4. Four assimilation experiments are carried out to compare with the simulation without data assimilation,
which serves as the control experiment. All experiment results are compared with dataset of Global Temperature–Salinity Profile
Program and satellite sea surface temperature (SST). The first experiment (Exp 1) is implemented by perturbing temperature
of upper layers in the initial conditions (ICs) with an amplitude of 1.0°C and no ensemble inflation. The results from Exp
1 show that the simulated temperature (salinity) deviation in the upper 400 m (500 m) is reduced through Argo data assimilation;
however, these deviations are increased in deeper layers. The error reduction in SST is much greater during January to June
than during the rest of the year. Three more experiments are designed to understand the responses in different layers and
months. Two of them test model sensitivities to ICs by perturbing them vertically: one over the vertical extent of the whole
water column (Exp 2) and the other employs smaller perturbation amplitude of 0.1°C (Exp 3). Exp 2 shows that the simulated
temperature and salinity deviations are systematically improved in the whole water column. Comparison between Exps 2 and 3
suggests that perturbation amplitude is important. Exp 4 tests the influence of the optimal inflation factor of 5%, which
is determined by other set of numerical tests. Exp 4 improves assimilation performance much more than the other three experiments
without inflation. Therefore, we conclude that the perturbation should be introduced to all model layers, proper perturbation
amplitude is important for Ocean data assimilation using EAKF, and the ensemble inflation by an optimal inflation is critical
to improve the skill of the EAKF analysis. |
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