The “Sea Ice model Calibration for improved Arctic Predictions” project (SICAP) will focus on delivering a modern tuning infrastructure for the Arctic sea ice in Copernicus systems encompassing two main components. Firstly, an updated and standardised sea ice observation catalogue targeting multiple variables (sea ice concentration, thickness, etc.) from different sources (remote sensing and in situ). Secondly, a tuning software to iteratively minimise the mismatch between model simulations and observations. Two alternative automatic calibration methods will be implemented the Green’s function approach and the Dual One-Step-Ahead Smoother approach. SICAP aims at enhancing the sea ice model components of the CMCC Global Ocean Reanalysis System (C-GLORS) and the NERSC Arctic prediction and analysis system TOPAZ. Both model configurations contribute to the Copernicus Marine Service portfolio.

CMCC role
WP1-WP2-WP3-WP4

Activities
SICAP will improve the representation of the Arctic sea ice in Copernicus Marine Service reanalysis and forecast products. We will establish a flexible calibration protocol that, if effective, could be applied to other sea ice models and possibly expanded to include oceanic variables.

Expected results
SICAP outcomes aim to have profound and long-lasting impacts on the Copernicus Marine Service through improved sea ice forecasts and prediction in support of maritime operations in polar regions; advanced knowledge of sea ice prediction skills and forecasts in a range of Copernicus regional and global models. We
will deliver two calibration algorithms (GitHub as a Python package and documentation), including an assessment of their differences and similarities.

Partners
NERSC – Nansen Environmental and Remote Sensing Center