Using ensemble adjustment Kalman filter to assimilate Argo profiles in a global OGCM

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