Climate Feedbacks

September sea-ice cover in the Arctic Ocean projected to vanish by 2100

The Arctic climate is changing rapidly. From 1979 to 2006, September sea-ice extent decreased by almost 25% or about 100,000 km² per year. In September 2007, Arctic sea-ice extent reached its lowest level since satellite observations began and in September 2008, sea-ice cover was still low. This development has raised concerns that the Arctic Ocean could be ice-free in late summer in only a few decades, with important economic and geopolitical implications. Unfortunately, most current climate models significantly underestimate the observed trend in Arctic sea-ice decline, leading to doubts regarding their projections for the timing of ice-free conditions.

In this paper, we analyze the simulated trends in past sea-ice cover in 18 state-of-art-climate models and find a direct relationship between the simulated evolution of September sea-ice extent over the twenty-first century and the magnitude of past trends in sea-ice cover (Figure 1). The reason for this consistently strong relationship is that simulated trends and future changes in September sea ice extent are both determined to a large extent by the baseline sea-ice thickness distribution. This parameter controls most of the intermodel variations in recent trends and continues to have an important role in the evolution of the sea ice extent throughout the twenty-first century period.

Using the relationship between simulated trends and future changes together with observed trends, we project the evolution of September sea-ice cover over the twenty-first century. We find that under a scenario with medium future greenhouse-gas emissions, the Arctic Ocean will probably be ice-free in September before the end of the twenty-first century.

Fig 1. Mean simulated percentage of remaining sea ice in September in the 2021–2040 period as a function of the trend in the 1979–2007 period. Each point corresponds to a CMIP3 model. The vertical bar denotes the observed trend. The 68% confidence prediction interval is estimated using the linear regression model.

Download the publication (Boé et. al. 2009) describing these results in more detail.