Over recent decades the Arctic has warmed approximately twice as fast as the rest of the Northern Hemisphere. At the same time, Arctic sea-ice concentration has decreased rapidly, especially in September when sea ice in the Arctic reaches its lowest extent of the year. Interannual variability in the minimum sea ice extent is enormous, especially over the past decade that includes several years of record minimum coverage interspersed with other less extreme years. Satellite observations of sea ice concentrations go back to 1979.
This vast interannual variability is mostly driven by extratropical atmospheric dynamical processes both directly and indirectly, and modulated by slower ocean processes. Wind represents an important forcing of sea ice distribution that qualifies as direct forcing. Thermodynamical consequences of extratropical dynamical variability such as changes to the radiative surface fluxes due to increased moisture in the Arctic can in turn lead to important feedback processes that can quickly amplify the change. A recent study indicates that in years when there is a low Arctic sea-ice minimum in September there is an increase in moisture transport into the Arctic in the preceding spring. The increase in moisture leads to increased greenhouse effect that is thought to play an important role in initiating the melt in spring that will become an extensive area of melt in September. We hypothesize that the extreme moisture transport into the Arctic in the form of atmospheric rivers (ARs) during certain key parts of the year plays an important role in the extent of the sea-ice minimum that is reached each year, and overall in interannual variability of sea ice concentrations.
We propose to analyze the frequency and moisture flux of ARs in certain key areas of the Arctic in 35 years of reanalysis data, the time period of which overlaps with observations of sea-ice concentration. We will examine sea-ice concentration and surface fluxes following episodes of extreme moisture flux, as well as the large-scale flow because of the close association of ARs to Rossby wave breaking, a process that drives major climate patterns. We will carry out similar analysis for the archive of CMIP5 climate simulations, both historical runs and projections for the coming century under projected increases in greenhouse gases. We will test hypothesis regarding the role of ARs for Arctic sea ice concentration by running idealized Global Climate Model simulations.
The work is directly relevant to the opportunity in that it examines climate mechanisms that affect Arctic temperatures and variability in sea-ice concentration in observations and model simulations. This will lead to an improved scientific understanding of the changing climate system, which is a stated goal of NOAA’s Next Generation Strategic Plan.