Using MITgcm, researchers uncover how storm-driven mixing and ice motion combined to trigger exceptional sea ice retreat missed by operational forecasts.

Reporting by Helen Hill for MITgcm

Extreme weather events are becoming an increasingly important driver of Arctic sea ice variability, but accurately representing their impacts remains a challenge for both operational forecasting systems and climate models. A striking example occurred in January 2022, when a record-breaking Arctic cyclone swept across the Barents Sea and the region surrounding Svalbard, producing an unprecedented loss of sea ice. Despite the event’s magnitude, both the ECMWF operational forecast and the CESM1 climate model significantly underestimated the observed retreat, raising an important scientific question: what processes were missing or poorly represented in existing simulations?

To address this question, Ivana Cerovečki (Scripps Institution of Oceanography, University of California San Diego) and colleagues developed a regional ocean-sea-ice configuration of MITgcm covering the European Arctic. The model was forced with ERA5 atmospheric reanalysis and evaluated against multiple observational datasets, including satellite estimates of sea ice concentration and thickness as well as Argo float measurements of upper-ocean structure. The researchers also explored the sensitivity of the simulations to different ocean initial conditions and to the parameterization of air-sea-ice momentum transfer.

MITgcm was a particularly powerful tool for this investigation because it can simultaneously represent sea ice dynamics, ocean circulation, vertical mixing, and air-ocean-ice interactions. Capturing these coupled processes was essential, since the storm’s impact depended not only on the strength of the winds but also on how those winds altered the structure of the upper ocean and transferred momentum to the ice cover.

The simulations revealed that different physical mechanisms dominated in different parts of the region. North of Svalbard, strong cyclone winds generated intense vertical mixing that eroded the usual stratification between cold, fresh polar surface waters and the warmer, saltier Atlantic Water lying below. This mixing transported heat upward, allowing Atlantic-origin water to reach the surface and rapidly melt thin seasonal ice from beneath. Evidence for this process was clearly visible in Argo observations, yet it was largely absent from the operational forecast and global climate model simulations examined by the authors.

In contrast, sea ice loss south of Svalbard was controlled primarily by ice dynamics rather than oceanic heat. There, strong winds mechanically dispersed the ice cover, pushing ice away from the region and creating areas of open water. The study further demonstrated that the partitioning between thermodynamic ice loss (melting) and mechanical ice loss (divergence) was highly sensitive to the choice of air-ice drag coefficient. Increasing the drag coefficient substantially improved agreement between the MITgcm simulations and the observed evolution of sea ice area.

Want to find out more? Email Ivana

Story image: Envisat image capturing sea ice and cloud streets in the Svalbard Archipelago

About the Researcher

Ivana Cerovečki is a physical oceanographer and Project Scientist at Scripps Institution of Oceanography, UC San Diego. Her research investigates ocean circulation, water-mass transformation, air-sea-ice interactions, and climate variability, with a particular focus on polar oceans and the role of ocean mixing in climate processes. She has been using MITgcm since 2003.

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