The Arctic sea ice decline and the Arctic warming amplification have been identified by the observations and modeling; however, how the sea ice affects the wintertime air-sea turbulent heat flux and contributes to the Arctic atmosphere heat budget is still less understood. Previous studies have demonstrated the spatial coherence between the trends of turbulent heat flux and sea ice concentration and proposed that the ice-temperature feedback can be another cause of the Arctic amplification. However, how much of the air-sea turbulent heat flux increase resulted from the Arctic ice retreat in the past 30 years is not quantitatively known. In this paper, the increased air-sea turbulent heat flux (sensible and latent heat flux) is identified by combining the Optimal Interpolation SST (OISST) and Objectively Analyzed Air-sea Fluxes (OAFlux) Project. It is expected such a study can provide research evidence for the profound understandings of the Arctic climate changes and validation for the model results.
Figure 1 shows that the standard deviations (STDs) of seasonal wintertime mean sensible and latent heat flux (SHF+LHF) are most significant in the vicinity between the climatological multi-year sea ice edge (gray shaded) and the most equatorward sea ice edge (magenta). A physical assumption was applied that the SHF+LHF is zero with sea ice cover. The most equatorward sea ice edges are set as the starting line, any sea ice retreat from this line can induce extra SHF+LHF to the above atmosphere. The accumulated energy is divided by the polar cap surface area (north of 60oN). The results show that the SHF+LHF increase from 3 Wm-2 to 10 Wm-2 from 1981 to 2011, about 0.26 Wm-2 per year.
The increased SHF+LHF can contribute to the heat budget anomaly for the above atmosphere. A one-dimensional linear heat budget analysis of the vertical integrated column is employed to build the physical relationship for air-sea-ice interactions. The heat budget can be expressed as Eq. (1) which was commonly used by previous studies.
where is the atmospheric energy storage for the column, the convergence of atmospheric energy transport, the net radiation at the top of the atmosphere (TOA), and the net heat flux at the Earth's surface.
The four contributions to the energy storage in Eq. (2) are heat state, kinetic energy, energy associated with the freshwater transport, and the surface geopotential. Here, it is assumed that the energy storage anomaly is primarily induced by the temperature changes. The other three terms on the R.H.S of Eq. (1) are in balanced state except for the SHF+LHF for the term . Therefore, the energy storage anomaly associated with the temperature changes for the polar cap, is triggered by the anomaly of the increased heat loss from the ocean. It can be expressed as:
The previous studies show that the extreme warming for the polar cap mainly concentrates in the lowermost layer from 1000 to 900 hpa. Equation (3) is used to see the effect of the changing air-sea heat flux on the heat storage changes in the lower troposphere. The linear air temperature trend by the 1-D model prediction is about 0.03ºC/yr, which is consistent with the increases from the polar temperature observations of GISS and HadCRUT3 (Fig. 2). The results from the newly updated reanalysis (CFSR, ERA-Interim and CFSR) also show similar trend but with slightly difference (not shown here) magnitude.
FIG. 1. (a): The STD of the seasonal wintertime mean SHF superimposed with the mean sea ice extent location, the black line represents the mean concentration of 15%, which is defined as the mean sea ice extent, while the magenta line represents the most equatorward shift of the sea ice extent in the past three decades. The gray shading color represents the climatological multi-year wintertime sea ice in the Arctic Ocean; (b) and (c): the same as (a), but for LHF and SHF+LHF.
FIG. 2. Surface air temperature anomaly from GISS (green) and HadCRUT3 (black) from 1981 to 2005 compared to 1981. The dashed curve is the continuous anomaly for HadCRUT3 from 2005 to present. Mean air temperature from 1000 hpa to 900 hpa is predicted by the 1-D linear model (red, SHF+LHF only; navy, SHF+LHF and net longwave radiation).