3.1. Climatology and Variability of Summer Storm Activity
The model ensemble simulations principally capture the spatial structures of storm count derived from their forcing dataset, the NCEP–NCAR reanalysis [8
], including the across-subregion variation (Figure 2
). As was previously found [41
], the total number of storms in HIRHAM–NAOSIM is higher than that in the NCEP–NCAR reanalysis. The higher storm count in the regional model could be attributed to its higher spatial resolution. Examination of impacts of model resolution on storm count and comparison of other reanalysis products with the regional model simulations has been conducted in other previous studies [42
Detailed statistical analysis of the storm climatology is summarized in Table 1
, including the maximum and minimum summer storm counts and the climatological mean of the summer storm count throughout the 61 years in both HIRHAM–NAOSIM simulations and the NCEP–NCAR reanalysis. The highest values of the maximum and the climatological mean storm counts occur over the Central Arctic. The maximum storm counts are comparable between the model and the reanalysis data set. However, the minimum storm counts over all subregions during the 61 years period are higher in the model than those in the reanalysis data set, which leads to the higher climatological mean storm count in the model as shown in Table 1
. The higher minimum storm counts may suggest that the high resolution in HIRHAM–NAOSIM may allow better representation of smaller and shallower low-pressure systems when storm activity is weaker. The same feature was found when analyzing Arctic storms using the Arctic system reanalysis (ASR) at relatively high resolutions of 30 km or 15 km, compared to that with ERA-Interim dataset [42
Both summer storm count and intensity demonstrate obvious interannual variability throughout the study period in each of the Arctic subregions in both model simulations and the NCEP–NCAR reanalysis data (Figure 2
and Figure 3
). As expected from the climatological analysis above, the storm count is higher in the model than in the reanalysis data over the study period for all subregions. However, the storm intensities can be close to each other for some subregions, such as the Central Arctic, Beaufort Sea, and East Siberian Sea, between the model and reanalysis. Although there are differences in the magnitude, the variability of the simulated ensemble mean of the storm counts and intensities are well consistent with that derived from the reanalysis.
The simulated year-by-year variability of the storm count is dependent on the region, with the largest variability ranging from 33 to 77 over the Central Arctic and the smallest variability from 2 to 16 over the Chukchi Sea and the Greenland Sea (Figure 2
and Table 1
). The model simulated storm intensities show relatively similar temporal variations to those in the NCEP–NCAR reanalysis. The comparison of storm intensities over the different subregions suggests that larger interannual variability occurs in the areas adjacent to open water or seasonally ice-free seas, such as the Greenland Sea and the Barents–Norwegian Sea, with the intensity ranging from 1 hPa to 40 hPa and 5 hPa to 30 hPa, respectively (Figure 3
). By contrast, the Central Arctic, where almost all sea-ice cover remains during summer, exhibits the smallest magnitude and interannual variability of the storm intensity. In addition, the time series of the storm count and intensity here do not show an identifiable long-term trend. This is different from the annual mean values revealed by previous studies [8
], which could be attributed to seasonality of the long-term changes in storm activity. Regional compensating effects may also mask the overall long-term tends over the entire Arctic as described in [46
When comparing the regional features of the storm count and intensity discussed above, we can also readily find that the Central Arctic generally has a higher storm count but weaker storm intensity, while over the surrounding shelf seas, there are lower numbers of storms but with stronger intensity. This would be due to larger baroclinicity in the shelf seas (e.g., the Norwegian, Barents, Kara, Laptev, and Chukchi seas), resulting from the thermal contrast between open water and sea ice or between the partially sea-ice covered seas and adjacent landmass. A high resolution modeling study on a long-lasting summer storm found that the surface and low troposphere baroclinic instability over the shelf seas is the primary mechanism triggering storm genesis and intensification, though downward intrusion of a synoptic stratospheric polar vortex or dynamically stratospheric potential vorticity anomaly plays a predominantly driving role in storm’s persistence over the sea-ice covered central Arctic Ocean [22
3.2. Intense Storms and Associated Near-Surface Atmospheric Circulation
In addition to the general information about storm activities over the Arctic, intense storms are especially interesting to examine because of their high impacts on other climate and environment components, including dramatic sea-ice changes. We therefore conducted a composite analysis of near-surface atmospheric circulation as represented by SLP and 10 m wind fields, as described in Section 2.2
. Over the North Atlantic Arctic Ocean, when a higher count of the extremely intense storms occurs, the minimum mean low-pressure center appears over the Kara Sea (Figure 4
a). The low pressure extends from the Kara Sea coast area to the Barents Sea, Fram Strait, and the Icelandic Sea. At the same time, a weaker Beaufort high shifts southward to the Alaska coast. This SLP allocation forms a cyclonic circulation over the Atlantic Arctic and, accordingly, favors an intensification of the transpolar drift and Fram Strait export of sea ice [4
Over the North Pacific Arctic Ocean, the composite analysis results show a low-pressure center over the Chukchi Sea in the case of extremely high intense storm count. The low-pressure extends eastward to the Beaufort Sea and the Western Canadian Archipelago, and westward to the East Siberian Sea (Figure 4
b). This SLP pattern alters the climatological wind field steered by the Beaufort high with wind blow from the Beaufort Sea to the Chukchi Sea [48
]. Meanwhile, a high-pressure ridge appears from Scandinavia to the Barents Sea. As a consequence, a well-organized cyclonic circulation occurs over the North Pacific Arctic and wind blows from the Nordic Sea toward the East Siberian coast, against the transpolar drift.
To assure the impacts of the intense storms on the near-surface atmospheric circulation revealed above, we also did the same composite analysis for the days when storms occur, but the intense storm count is less than
over the Atlantic and Pacific Arctic Ocean, respectively. The results indicate that there is no obviously identifiable SLP or circulation system over the Arctic Ocean (Figure 4
c,d). Differences of composite results between the higher and lower intense storm counts reinforce the results shown in Figure 4
3.3. Changes in Sea Ice in Association with Intense Storm Activity
In correspondence to the near-surface atmospheric circulation as an integrative consequence of the intense storm activity (Figure 4
), we examined the associated changes in the sea ice and ocean fields to understand possible impacts of intense storms. In this analysis, we employed the same composite analysis approach.
In the Atlantic Arctic Ocean, the difference of the composite sea-ice concentration (SIC) between the extremely high and low intense storm count shows negative values over the broad area from the Barents and Kara seas to the Greenland Sea, except for a few small spots on the downstream side of Svalbard and Novaja Zemlja (Figure 5
a; see also wind pattern in Figure 4
a). The largest and statistically significant SIC decrease occurs in the Northwestern Barents Sea, Southeastern Kara Sea, and Northern Greenland Sea. Sea-ice thickness (SIT) demonstrates the same decreasing pattern, but the largest decrease appears in the Northern Greenland Sea (Figure 5
c). Corresponding to the decrease area of SIC and SIT, sea surface temperature (SST) exhibits an increase when more numerous intense storms occur (Figure 5
e). Similarly, in the Pacific Arctic, SIC and SIT decrease in the East Siberian Sea, Chukchi Sea, and the Beaufort Sea, associated with more numerous intense storms, but increase in the Canada Basin and the Canadian Archipelago (Figure 5
b,d). Major SST increase occurs along the Eastern Beaufort Sea shelf (Figure 5
To understand the changes in sea ice and SST identified above, we conducted the composite analysis for sea-ice motion and sea-ice energy budgets. Figure 6
shows the composite sea ice drift vectors and speed when the anomalously high and low intense storm count occurs, and their difference for the Atlantic and Pacific Arctic Ocean regions. In the Atlantic Arctic Ocean, there are obviously large sea-ice outflows from the Arctic Ocean, in particular from the Kara and Laptev Seas to the East Greenland Sea (Figure 6
a), corresponding to the surface wind patterns associated with the high intense storm count as shown in Figure 4
a. The comparable magnitude of the sea-ice velocity only occurs in the East Greenland Sea when there is a low number of the intense storms. The enhanced sea-ice export via Fram Strait associated with the more numerous intense storms dynamically contributes to the sea-ice loss in this area as shown in Figure 5
a,c. On the other hand, the thinned ice would become vulnerable to wind forcing and further increase its velocity.
In the Pacific Arctic Ocean, when more numerous intense storms occur, a cyclonic sea-ice circulation appears in the Chukchi and East Siberian Seas, while the conventional Beaufort gyre shifts southeastward (Figure 6
b). This is well consistent with the alteration of SLP and surface wind fields associated with the anomalously high number of intense storms as shown in Figure 4
b. In the opposite case with the low number of intense storms, the Beaufort gyre expands to the north and northwest, forming an anticyclonic circulation in a large area of the Western Arctic. Compared to the latter, the former sea-ice circulation pattern reduces sea-ice transport from the thick ice area north of the Canadian Archipelago to the Beaufort–Chukchi Seas (Figure 6
b), which contributes to the decrease in SIC and SIT in the latter areas (Figure 5
b,d). However, there is an increase in sea-ice transport to the East Siberian Sea. The sea-ice circulation associated with the low number of intense storms (Figure 6
d) obviously accounts for the SIT increase in the Canada Basin and the Canadian Archipelago (Figure 5
d) due to the convergence effect of sea ice.
The composite analysis was continually extended to the net sea-ice heat fluxes, calculated as the difference between the net atmospheric surface heat fluxes and the oceanic heat flux of a model grid cell. The difference represents the net contribution from all radiative, sensible, and latent heat fluxes from the atmosphere and the turbulent heat flux from the ocean, indicating the total thermodynamic contribution to sea-ice changes (melt and growth). In this paper, we used the sign convention that negative (positive) net heat fluxes point downward (upward), which we can interpret as snow/ice melt (sea-ice growth).
When the high count of intense storms occurs over the Atlantic Arctic Ocean, a slightly negative value of the net sea-ice heat flux occurs in the Northern Barents Sea and the Kara Sea, and a large negative value appears along the sea-ice marginal zone in the East Greenland Sea (Figure 7
a). There are also small positive net sea-ice heat fluxes in the interior area of the study domain. This shows great difference from the case of the low count of intense storms, which exhibits an obviously larger negative value for the entire domain of the Atlantic Arctic Ocean (Figure 7
c). The larger negative values, i.e., increased downward net sea-ice heat fluxes, indicate more sea-ice melt when less numerous intense storms occur. The same as these in the Atlantic Arctic Ocean, there are small (large) negative net sea-ice heat fluxes when more (less) numerous intense storms occur (Figure 7
b,d). The decrease in the negative net sea-ice heat fluxes is further confirmed for both regions by the positive differences of the net sea-ice heat fluxes between the high and low counts of intense storms (Figure 7
According to the dynamic and thermodynamic analysis above, the large decrease in SIC and SIT in the Barents–Kara–Laptev Seas of the Atlantic Arctic and the Chukchi–Beaufort seas of the Pacific Arctic can obviously be attributed to the enhanced sea ice export from these areas, considering the decreased downward net sea ice heat flux and sea-ice melt, in the case of a high number of intense storms. However, the decreased SIC and SIT in the East Greenland Sea and the East Siberian Sea could not straightforwardly be explained because of the sea-ice import in these downstream areas of the changed sea ice transport and the decreased downward net heat fluxes and sea-ice melt. The decrease in SIC and SIT in these areas may be ascribed to prior conditions before intense storms occur, which the composite analysis here may not be able to reveal. For example, these areas are under influences of storm tracks, and many storms travel through these areas before they reach the criterion of intense storms used for the composite analysis. This transient effect needs to be examined to understand storm impacts on sea ice during their different development phases and would be a follow-up study.
The dynamic and thermodynamic analysis results here augment existing case studies or statistical analysis about sea-ice changes associated with storms [24
]. Nevertheless, we have only analyzed overall changes in dynamics and thermodynamics here. Better understanding of storm impacts on underlying sea ice and ocean as well as associated interactions between them need further detailed energy budget analyses, in particular associated with finer scale processes. For example, reduced downward shortwave radiation due to increased cloudiness and increased upward turbulent fluxes due to break-up of temperature inversions and destabilization of the boundary layer may contribute to the decreased downward net sea-ice surface heat fluxes (including radiative fluxes and turbulent fluxes) and reduced sea-ice melt rates when numerous intense storms occur, as shown in Figure 7
. Storm-induced cloudiness seasonally changes partitioning of downward shortwave and longwave radiation fluxes, altering surface energy budgets. Intense storm may also break up pack ice and subsequently increase open water to enhance air–sea heat exchange and albedo feedback, which may further influence sea-ice energy budgets and sea-ice melt and growth.