The Relation among Sea Ice, Surface Temperature, and Atmospheric Circulation in Simulations of Future Climate

Observations document substantial 20-40 year trends in the past several decades in the Arctic. Studies show sea ice thickness and extent have declined, air temperature has increased, and the temperature and salinity of the upper ocean have increased (e.g., see Serreze et al., 2000). At the same time, we have seen a weakening of the tropospheric anticyclone over the Beaufort Sea that can be associated with trends in a large-scale pattern of atmospheric variability (Walsh et al, 1996; Thompson and Wallace, 1998). The fluctuations of Arctic surface temperatures, sea ice, and the upper ocean are coherent with this pattern of atmospheric variability (Rigor et al., 2000, 2001; Zhang et al., 1998) on a range of time scales. Most evidence indicates the Arctic surface climate is responding to the atmospheric circulation. If we knew what was causing variability and trends in the atmospheric circulation, we could better predict the future of Arctic climate. However, the source of the recently observed trends and the decadal variability remains a matter of debate. The dominant relation between observed surface temperature trends and the atmospheric circulation in the Arctic may seem to contradict the commonly held wisdom, based on model studies, that Arctic warming induced by greenhouse gases (GHGs) is amplified by ice-albedo feedback primarily over sea ice. Although sea ice has receded in much of the eastern Arctic, the observed peak warming is over Eurasia. In contrast, most climate models have a warming maximum over the ocean (Raisanen, 2001). Figure 1 shows the warming in GHG forced experiments from a selection of climate models participating in the IPCC 2001 report. Climate change simulations with the sea ice held fixed to its present day extent indicate that changes in the ice extent account for 20-40 of the global warming, depending on the model (Ingram et al, 1989; Rind et al., 1995). The strength of the ice-albedo feedback in a model depends on parameterizations and the mean state. For example, a relatively strong amplification is seen in CGCM2, whose present day sea ice is arguably too thin, at less than 2 m in the central Arctic.