Southern Ocean sea ice concentration budgets of five ocean-sea ice reanalyses

Abstract

In this study, sea ice concentration (SIC) budgets were calculated for five ocean-sea ice reanalyses (CFSR, C-GLORSv7, GLORYS12v1, NEMO-EnKF and ORAS5), in the Southern Ocean and compared with observations. Benefiting from the assimilation of SIC, the reanalysis products display a realistic representation of sea ice extent as well as sea ice area. However, when applying the SIC budget diagnostics to decompose the changes in SIC into contributions from advection, divergence, thermodynamics, deformation and data assimilation, we find that both atmospheric and oceanic forcings and model configurations are significant contributors on the budget differences. For the CFSR, the primary source of deviation compared to other reanalyses is the stronger northward component of ice velocity, which results in stronger sea ice advection and divergence. Anomalous surface currents in the CFSR are proposed to be the main cause of the ice velocity anomaly. Furthermore, twice the mean ice thickness in the CFSR compared to other reanalyses makes it more susceptible to wind and oceanic stresses under Coriolis forces, exacerbating the northward drift of sea ice. The C-GLORSv7, GLORYS12v1 and NEMO-EnKF have some underestimation of the contribution of advection and divergence to changes in SIC in autumn, winter and spring compared to observations, but are more reasonable in summer. ORAS5, although using the same coupled model and atmospheric forcing as C-GLORSv7 and GLORYS12v1, has a more significant underestimation of advection and divergence to changes in SIC compared to these two reanalyses. The results of the SIC budgets of five ocean-sea ice reanalyses in the Southern Ocean suggest that future reanalyses should focus on improving the modelling of sea ice velocities, for example through assimilation of sea ice drift observations.

Differences Between the CMIP5 and CMIP6 Antarctic Sea Ice Concentration Budgets

“…Notably, the strong relationship between sea ice volume and div is consistent with Nie et al. (2022), who found that the Climate Forecast System Reanalysis (NCEP CFSR) had quite thick sea ice related to excessive divergence. Figure 4 results support their hypothesis of positive feedback between SIT and divergence.…”

Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean

“…Sensitivity experiments with three different atmospheric reanalyses indicated that, at least in winter (April to October), SIC budgets are sensitive to atmospheric forcing, as sea ice models driven by these atmospheric reanalysis products show large errors compared to observations (Barthélemy et al, 2018). This was further validated by the fact that, even when using the same atmospheric reanalysis, the SIC budget in the ice-ocean reanalysis products can vary considerably (Nie et al, 2022). On the other hand, some studies have shown that simulations of the Southern Ocean sea ice area are not sensitive to model parameters (e.g.…”

“…Sea ice simulations in this study were performed using the version 4.0.7 revision 15 731 of the Nucleus for European Modelling of the Ocean (NEMO; NEMO System Team, 2022) coupled with the Sea Ice modelling Integrated Initiative (SI 3 ; NEMO Sea Ice Working Group, 2019), hereafter called NEMO4.0-SI 3 . The model represents the global ocean via a commonly used nominal 2 • tri-polar grid (ORCA2), which has a resolution of about 85 km between 55 and 75 • S. The ORCA2 was chosen because it is already capable of identifying features of the Southern Ocean SIC budget at this resolution (Nie et al, 2022), and considering that hundreds of experiments will be performed, using ORCA2 is computationally comparably cheap. The ORCA2 grid configuration has 31 unevenly spaced vertical layers from 10 m thick (near surface) to 500 m thick (at 5500 m depth).…”

“…The EXP397, which is the best-performing one, has an SIV seasonal cycle that almost overlaps with the ensemble mean, while the second and third best are both close to the CTRL. This evidence again suggests that, even if the realistic SIE is modelled, there is no guarantee of a reasonable SIC budget (Uotila et al, 2014;Nie et al, 2022).…”

Modulation of the seasonal cycle of the Antarctic sea ice extent by sea ice processes and feedbacks with the ocean and the atmosphere

“…At the end of the advance season, the ice edge position is set by the advection of sea ice from the south. Sea ice then melts in regions which are too warm to sustain local production (e.g., Holland and Kimura, 2016;Nie et al, 2022). Neglecting ice transport thus leads to an earlier maximum extent and onset of the retreat (Fig.…”