<p>The satellite-derived sea ice concentration (SIC) from the Special Sensor Microwave Imager/Sounder (SSMIS) over the Antarctic region has been assimilated using a variational data assimilation system at NCMRWF. In this study, daily sea ice analysis produced by NEMOVAR, a variational assimilation system utilizing SSMIS observations (DA), is compared with the free simulation forced without assimilation (noDA) for the 2020–2024 period. The assimilation of SSMIS-derived SIC data has demonstrated notable improvements in model performance, particularly with respect to SIA and its seasonal variability. The root mean square error (RMSE) against SSMIS observation is 0.49 × 10⁶ km² (0.67 × 10⁶ km²) w.r.t. DA (noDA). Compared to noDA, the time evolution of SIC climatology in the DA is more closely aligned with SSMIS observations, highlighting the effectiveness of SIC data assimilation in improving the model fidelity. The climatological differences (DA–noDA) in SIA, Ice Surface Temperature (IST), and near-Infrared (IR) albedo suggest that assimilation not only improves SIC representation but also modulates surface thermodynamics and radiative properties. The SIA exhibits a positive bias over the Antarctic region and a negative bias in IST and near-IR direct albedo, suggesting that in the DA experiment, the higher SIA values are linked to a decrease in IST and reduced near-IR albedo during the period of our study, indicating a consistent thermodynamic adjustment in response to the assimilated sea ice fields.</p>