The sensitivity of parameterization schemes in thermodynamic modeling of the landfast sea ice in Prydz Bay, East Antarctica

Abstract

Based on the measurements conducted over the landfast sea ice in Prydz Bay, East Antarctica during the sea-ice growth season in 2016, various parameterization schemes in the high-resolution thermodynamic snow/ice model HIGHTSI are evaluated. The parameterization scheme of turbulent fluxes produces the largest errors compared with the parameterization schemes for other surface heat fluxes. However, the sea-ice thickness simulation is most sensitive to the differences in upward longwave radiation at the surface. In addition, the sea-ice thickness simulation during the growth season is highly sensitive to the oceanic heat flux, and a new oceanic heat flux parameterization scheme based on the bulk method is proposed. The new parameterization scheme is tested in a second year, and it significantly improves the model performance relative to the standard configuration when compared against observations. Finally, the seasonal variation in the heat budget and its influence on the sea-ice thickness variation are analyzed. The net shortwave radiation, sensible heat flux and conductive heat flux (the net longwave radiation and latent heat flux) are found to be the surface heat sources (heat sinks) during the growth season. The larger conductive heat flux and the smaller oceanic heat flux can intensify the growth of sea ice.

Combining a New Parameterization Scheme of Oceanic Heat Flux with Thickness Assimilation to Improve Sea Ice Forecast Accuracy in Liaodong Bay

“…It considers various processes, including surface heat balance, internal heat conservation in ice and snow, and heat conduction at the ice bottom. The model has been successfully applied for sea ice forecast purposes in the Baltic Sea, Kara Sea, Polynya, Zhongshan Station, and Prydz Bay [12][13][14][15][16][17][18]. This application shows a promising future for the HIGHTSI model in the sea ice forecast of local regions.…”

Antarctic Sea Ice Concentration in the Brazilian Earth System Model Simulations

“…The need for advances in sea ice modeling includes more accurate physical processes, more realistic ocean circulation representation, including mesoscale eddies, and the development of higher-resolution models (Hofmann & Maqueda, 2011;Langlais et al, 2015;Smith et al, 2022;Rackow et al, 2022). Many uncertainties in sea ice modeling are related to parameterizations, the representation of sub-grid-scale processes, and the sparse and short historical observational data (Michaelis et al, 2020;Liu et al, 2022;Meredith et al, 2019;Casagrande et al, 2023). Luo et al (2023) used a new multivariate balanced atmospheric ensemble forcing that was able to suppress model errors of SIC and produce improvements in the accuracy of simulation and better estimates of simulation uncertainties.…”