Abstract
Reanalysis data are known to have relatively large uncertainties in the polar region than at lower latitudes. In this study, we used a single sea-ice model (Los Alamos’ CICE5) and three sets of reanalysis data to quantify the sensitivities of simulated Arctic sea ice area and volume to perturbed atmospheric forcings. The simulated sea ice area and thickness thus volume were clearly sensitive to the selection of atmospheric reanalysis data. Among the forcing variables, changes in radiative and sensible/latent heat fluxes caused significant amounts of sensitivities. Differences in sea-ice concentration and thickness were primarily caused by differences in downward shortwave and longwave radiations. 2-m air temperature also has a significant influence on year-to-year variability of the sea ice volume. Differences in precipitation affected the sea ice volume by causing changes in the insulation effect of snow-cover on sea ice. The diversity of sea ice extent and thickness responses due to uncertainties in atmospheric variables highlights the need to carefully evaluate reanalysis data over the Arctic region.
Highlights
There has been a dramatic change in the Arctic sea ice in recent years [1,2,3,4,5]
Atmospheric and oceanic variables are required for sea ice models, yet atmospheric observational data are very limited in the Arctic, especially in the open ocean where observations were scarce in time and place
As sea ice models are sensitive to surface forcings, uncertainties within the reanalysis data could lead to errors and biases in estimated sea ice variables such as concentration, thickness and volume and reduce the reliability of simulated results [10,14,15]
Summary
There has been a dramatic change in the Arctic sea ice in recent years [1,2,3,4,5]. The extents of Arctic sea ice between 2007 and 2016 are all ranked within the top 10 for minimum sea ice; September 2012 had the smallest summer sea ice extent on record (3.63 × 106 km2 ) while Autumn (October and November). Atmospheric reanalysis data, which assimilate both in-situ and remote sensed observations, are often used to force sea ice models [9]. As sea ice models are sensitive to surface forcings, uncertainties within the reanalysis data could lead to errors and biases in estimated sea ice variables such as concentration, thickness and volume and reduce the reliability of simulated results [10,14,15]. In an attempt to isolate the role of atmospheric forcing as much as possible, we focused on uncertainties in sea ice thickness to different atmospheric forcings while fixing sea surface temperature (SST) to observations. Uncertainty related to different reanalysis datasets has been investigated in previous research, few studies have quantified how uncertainty in reanalysis data affects simulated sea ice volumes when used as atmospheric forcing. We assess the large impact on sea ice volume examining variables such as heat flux and sea ice growth to understand the processes producing volume discrepancies (Section 4)
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