Arctic sea ice decline erratic as expected
Figure 1: Observations (black) of Arctic sea-ice extent in September. The dashed black line represents the long-term linear trend and various deliberately chosen 8-year linear trends are shown in colours.
The most recent 8-year trend, starting from the extreme low of 2007, happens to show an upward trend. Does this mean the Arctic sea-ice is recovering? No – it is a bounce within a long-term downward trajectory. Similarly, the 2000-2007 trend could have been partly due to a bounce in the opposite direction. Kay et al. (2011) suggested that up to half of the sea-ice trend up to 2005 was due to natural variability, and Day et al. (2012) concluded that 5-30% of the recent trend could be due to variations in the Atlantic Ocean.
But what about the climate models? Stroeve et al. (2007) suggested that the CMIP3 global climate models (GCMs) were showing less dramatic reductions in sea-ice than the observations. The latest generation of GCMs (CMIP5) have some simulations which do reproduce the observed trend.
And, what do these GCMs say about the likelihood of the observed ‘bounces’ in Arctic sea-ice? Figure 2 shows the probability distribution of all 7-year trends from the CMIP5 historical simulations from 1979-2013. Short periods with no apparent sea-ice decline occur regularly in this period. Swart et al. demonstrate that periods of more than a decade with zero trend are not unusual and that they occur in the simulated future also.
Figure 2: Distribution of 7-year linear trends in September Arctic sea-ice extent, for CMIP5 (grey), CESM Large Ensemble (cyan) and observations (red). The observed 2001-2007 and 2007-2013 trends are highlighted in green and blue respectively. Note that the Swart et al. analysis was done before the 2014 minimum so the paper uses 7-year trends and examines 2007-2013 and 2001-2007 as the two extreme cases.
The analysis was also repeated with a large (30 member) ensemble of simulations with the CESM GCM. In this case, the difference between the simulations is solely due to the experienced weather which varies from case to case. Interestingly, the range of trends seen in this single model is very similar to the entire range of CMIP5 GCMs, suggesting that a large fraction of this range is due to internal climate variability and not due to differences between the GCMs themselves.
When will the ball reach the bottom of the hill? The IPCC AR5 took the unusual step of only using five GCMs for its overall assessment of future Arctic sea-ice because many of the simulations were not deemed adequate. The IPCC concluded that it was likely that the Arctic would be reliably ice-free in September by 2050 (where ‘reliably ice-free’ means 5 consecutive years with less than 1 million km2 of sea-ice), assuming high future emissions.
The expected outcome is that the long-term decline in Arctic sea-ice will continue as global temperatures increase. There will be further bounces, both up and down. Individual years will become ice-free sometime in the 2020s, 2030s or 2040s, depending on future greenhouse gas emissions and the natural variations. But, even at the bottom of the hill the ball will continue to bounce – not every year will have zero ice in summer. The bounces will become smaller if global temperatures continue to increase, and other summer and autumn months will also become ice-free. However, in future scenarios with sharp reductions in greenhouse emissions, the Arctic sea-ice recovers slightly as global temperatures decline.
Main image: Frozen sea.
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Thanks to Richard Betts who I first saw use the bouncing ball analogy for climate.