Assimilation of ice compactness data in a strong coupling regime in the ocean – sea ice coupled model

• Main Authors: Kaurkin, Maxim N., Kalnitski, Leonid Y., Ushakov, Konstantin V., Ibrayev, Rashit A.
• Format: Text
• Language: English
• Published: 2021
• Subjects: Arctic; Arctic Ocean; Sea ice
• Online Access: https://doi.org/10.5194/os-2021-65; https://os.copernicus.org/preprints/os-2021-65/

The Arctic Ocean plays an important role in the global climate system, where sea ice regulates the exchange of heat, moisture and momentum between the atmosphere and the ocean. A comprehensive analysis and forecast of the Arctic ocean system requires a detailed numerical ocean and sea ice coupled model supplemented by assimilation of observational data at appropriate time scales. A new operative ocean – ice state forecast system was developed and implemented. It consists of the INMIO4.1 ocean general circulation model and the CICE5.1 sea ice dynamics and thermodynamics model with common spatial resolution of 0.25°. For the exchange of boundary conditions and service actions (data storage, time synchronization, etc.), the coupled model uses the Compact Modeling Framework (CMF3.0). Data assimilation is implemented in the form of the Data Assimilation Service (DAS) based on the Ensemble Optimal Interpolation (EnOI) method. This technique allows to simultaneously correct the ocean (temperature, salinity, surface level) and ice (concentration) model fields in the DAS service, so they are coordinated not only through the exchange of boundary conditions, but already at the stage of data assimilation (i.e. strong coupling data assimilation). Experiments with the INMIO – CICE model show that the developed algorithm provides a significant improvement in the accuracy of forecasting the state of the ice field in the Arctic Ocean.