Polona Itkin

Leads in Arctic pack ice enable early phytoplankton blooms below snow-covered sea ice

The Arctic icescape is rapidly transforming from a thicker multiyear ice cover to a thinner and largely seasonal first-year ice cover with significant consequences for Arctic primary production. One critical challenge is to understand how productivity will change within the next decades. Recent studies have reported extensive phytoplankton blooms beneath ponded sea ice during summer, indicating that satellite-based Arctic annual primary production estimates may be significantly underestimated. Here we present a unique time-series of a phytoplankton spring bloom observed beneath snow-covered Arctic pack ice. The bloom, dominated by the haptophyte algae Phaeocystis pouchetii, caused near depletion of the surface nitrate inventory and a decline in dissolved inorganic carbon by 16 ± 6 g C m−2. Ocean circulation characteristics in the area indicated that the bloom developed in situ despite the snow-covered sea ice. Leads in the dynamic ice cover provided added sunlight necessary to initiate and sustain the bloom. Phytoplankton blooms beneath snow-covered ice might become more common and widespread in the future Arctic Ocean with frequent lead formation due to thinner and more dynamic sea ice despite projected increases in high-Arctic snowfall. This could alter productivity, marine food webs and carbon sequestration in the Arctic Ocean.

Thin ice and storms: Sea ice deformation from buoy arrays deployed during N-ICE2015

Arctic sea ice has displayed significant thinning as well as an increase in drift speed in recent years. Taken together this suggests an associated rise in sea ice deformation rate. A winter and spring expedition to the sea ice covered region north of Svalbard–the Norwegian young sea ICE2015 expedition (N-ICE2015)—gave an opportunity to deploy extensive buoy arrays and to monitor the deformation of the first-year and second-year ice now common in the majority of the Arctic Basin. During the 5 month long expedition, the ice cover underwent several strong deformation events, including a powerful storm in early February that damaged the ice cover irreversibly. The values of total deformation measured during N-ICE2015 exceed previously measured values in the Arctic Basin at similar scales: At 100 km scale, N-ICE2015 values averaged above 0.1 d−1, compared to rates of 0.08 d−1 or less for previous buoy arrays. The exponent of the power law between the deformation length scale and total deformation developed over the season from 0.37 to 0.54 with an abrupt increase immediately after the early February storm, indicating a weakened ice cover with more free drift of the sea ice floes. Our results point to a general increase in deformation associated with the younger and thinner Arctic sea ice and to a potentially destructive role of winter storms.

Observations of flooding and snow-ice formation in a thinner Arctic sea-ice regime during the N-ICE2015 campaign: Influence of basal ice melt and storms

Seven ice mass balance instruments deployed near 83°N on different first-year and second-year ice floes, representing variable snow and ice conditions, documented the evolution of snow and ice conditions in the Arctic Ocean north of Svalbard in January–March 2015. Frequent profiles of temperature and thermal diffusivity proxy were recorded to distinguish changes in snow depth and ice thickness with 2 cm vertical resolution. Four instruments documented flooding and snow-ice formation. Flooding was clearly detectable in the simultaneous changes in thermal diffusivity proxy, increased temperature, and heat propagation through the underlying ice. Slush then progressively transformed into snow-ice. Flooding resulted from two different processes: (i) after storm-induced breakup of snow-loaded floes and (ii) after loss of buoyancy due to basal ice melt. In the case of breakup, when the ice was cold and not permeable, rapid flooding, probably due to lateral intrusion of seawater, led to slush and snow-ice layers at the ocean freezing temperature (−1.88°C). After the storm, the instruments documented basal sea-ice melt over warm Atlantic waters and ocean-to-ice heat flux peaked at up to 400 W m−2. The warm ice was then permeable and flooding was more gradual probably involving vertical intrusion of brines and led to colder slush and snow-ice (−3°C). The N-ICE2015 campaign provided the first documentation of significant flooding and snow-ice formation in the Arctic ice pack as the slush partially refroze. Snow-ice formation may become a more frequently observed process in a thinner ice Arctic.

Landfast ice affects the stability of the Arctic halocline: Evidence from a numerical model

Landfast ice covers large surface areas of the winter Siberian Seas. The immobile landfast ice cover inhibits divergent and convergent motion, hence dynamical sea ice growth and redistribution, decouples winter river plumes in coastal seas from the atmosphere, and positions polynyas at the landfast ice edge offshore. In spite of the potentially large effects, state-of-the-art numerical models usually do not represent landfast ice in its correct extent. A simple parametrization of landfast ice based on bathymetry and internal sea ice strength is introduced and its effects on the simulated Arctic Ocean are demonstrated. The simulations suggest that the Siberian landfast ice impacts the Arctic halocline stability through enhanced brine production in polynyas located closer to the shelf break and by redirecting river water to the Canadian Basin. These processes strengthen the halocline in the Canadian Basin, but erode its stability in the Makarov and Eurasian Basins.

Small‐scale sea ice deformation during N‐ICE2015: From compact pack ice to marginal ice zone

We studied small scale (50 m to 5 km) sea ice deformation from ship radar images recorded during the N-ICE2015 campaign. The campaign consisted of 4 consecutive drifting ice stations (Floes 1 to 4) north of Svalbard, with a total duration of nearly 5 months. Deformation was calculated using 5 different time intervals from 10 min to 24 h, and the deformation rate was found to depend strongly on the time scale. Floes 1 to 3 had a mean deformation rate within the range of 0.06 to 0.07 h– 1 with the interval of 10 min, and 0.03 to 0.04 h– 1 with the interval of 1 h. Floe 4 represented marginal ice zone (MIZ) with very high deformation rate, 0.14/0.08 h– 1 with the interval of 10 min/1 h. Deep in the ice pack, high deformation rates occurred only with high wind and drift speed, while in MIZ they were found also during calm conditions. The deformation rates were found to follow power law scaling with respect to length and time scale even on this small scales and in small domain (15 km × 15 km). The length scale dependence of deformation rate depends on the time scale: the power law scaling exponent β of the whole study period decreases from 0.82 to 0.52 with the time interval increasing from 10 min to 24 h. Ship radar images reveal the importance of the deformation history of the ice pack, since the deformation events were initialized along the lines of previous damages.

The seeding of ice algal blooms in Arctic pack ice : the multiyear ice seed repository hypothesis

During the Norwegian young sea ICE expedition (N-ICE2015) from January to June 2015 the pack ice in the Arctic Ocean north of Svalbard was studied during four drifts between 83° and 80° N. This pack ice consisted of a mix of second-year, first-year and young ice. The physical properties and ice algal community composition was investigated in the three different ice types during the winter-spring-summer transition. Our results indicate that algae remaining in sea ice that survived the summer melt season are subsequently trapped in the upper layers of the ice column during winter and may function as an algal seed repository. Once the connectivity in the entire ice column is established, as a result of temperature-driven increase in ice porosity during spring, algae in the upper parts of the ice are able to migrate towards the bottom and initiate the ice-algal spring bloom. Furthermore, this algal repository might seed the bloom in younger ice formed in adjacent leads. This mechanism was studied in detail for the often dominating ice diatom Nitzschia frigida.The proposed seeding mechanism may be compromised due to the disappearance of older ice in the anticipated regime shift towards a seasonally ice-free Arctic Ocean.

Is weaker Arctic sea ice changing the Atlantic water circulation

With a numerical model we test the sensitivity of the Arctic Ocean circulation at mid-depth (212-1200 m) to the change in the sea ice rheology parameter P* that controls the sea ice compressive strength. We show that the reduction of the sea ice strength via P* within commonly used envelope reduces the sea ice extent and consequently enhances the ocean surface heat loss in the marginal ice zone. This leads to cooling of the Atlantic water inflow into the Arctic Ocean. As a result Eurasian Basin and Amerasian Basin temperatures are in average cooled by 0.1 °C and 0.05 °C, respectively. An increased sea ice drift speed in the central Arctic leads to an enhanced circulation of the anticyclonic Beaufort Gyre of the Amerasian Basin, which in turn weakens the cyclonic Atlantic water circulation below and enhances the recirculation of the Atlantic water in the Eurasian Basin. Consequently the balance of the volume fluxes through the Arctic gateways changes. Fram Strait net outflow increases by 0.46 Sv, Barents Sea Opening net inflow increases by 0.19 Sv and Davis Strait net outflow decreases by 0.28 Sv. This can spread the effects of the sea ice strength change beyond the limits of the Arctic Ocean and into the deep water convection zones in the North Atlantic. These substantial effects should be considered also in the model optimization efforts where P* is commonly used as one of the tuning parameters to achieve better sea ice simulations, whereas the effects on the ocean circulation are rarely taken into account.

Thin Sea Ice, Thick Snow, and Widespread Negative Freeboard Observed During N‐ICE2015 North of Svalbard

In recent years, sea-ice conditions in the Arctic Ocean changed substantially toward a younger and thinner sea-ice cover. To capture the scope of these changes and identify the differences between individual regions, in situ observations from expeditions are a valuable data source. We present a continuous time series of in situ measurements from the N-ICE2015 expedition from January to June 2015 in the Arctic Basin north of Svalbard, comprising snow buoy and ice mass balance buoy data and local and regional data gained from electromagnetic induction (EM) surveys and snow probe measurements from four distinct drifts. The observed mean snow depth of 0.53 m for April to early June is 73% above the average value of 0.30 m from historical and recent observations in this region, covering the years 1955–2017. The modal total ice and snow thicknesses, of 1.6 and 1.7 m measured with ground-based EM and airborne EM measurements in April, May, and June 2015, respectively, lie below the values ranging from 1.8 to 2.7 m, reported in historical observations from the same region and time of year. The thick snow cover slows thermodynamic growth of the underlying sea ice. In combination with a thin sea-ice cover this leads to an imbalance between snow and ice thickness, which causes widespread negative freeboard with subsequent flooding and a potential for snow-ice formation. With certainty, 29% of randomly located drill holes on level ice had negative freeboard.

Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: Empirical and model results

Large changes in the sea ice regime of the Arctic Ocean have occurred over the last decades justifying the development of models to forecast sea ice physics and biogeochemistry. The main goal of this study is to evaluate the performance of the Los Alamos Sea Ice Model (CICE) to simulate physical and biogeochemical properties at time scales of a few weeks and to use the model to analyze ice algal bloom dynamics in different types of ice. Ocean and atmospheric forcing data and observations of the evolution of the sea ice properties collected from 18 April to 4 June 2015, during the Norwegian young sea ICE expedition, were used to test the CICE model. Our results show the following: (i) model performance is reasonable for sea ice thickness and bulk salinity; good for vertically resolved temperature, vertically averaged Chl a concentrations, and standing stocks; and poor for vertically resolved Chl a concentrations. (ii) Improving current knowledge about nutrient exchanges, ice algal recruitment, and motion is critical to improve sea ice biogeochemical modeling. (iii) Ice algae may bloom despite some degree of basal melting. (iv) Ice algal motility driven by gradients in limiting factors is a plausible mechanism to explain their vertical distribution. (v) Different ice algal bloom and net primary production (NPP) patterns were identified in the ice types studied, suggesting that ice algal maximal growth rates will increase, while sea ice vertically integrated NPP and biomass will decrease as a result of the predictable increase in the area covered by refrozen leads in the Arctic Ocean.

Contribution of deformation to sea-ice mass balance: a case study from an N-ICE2015 storm

The fastest and most efficient process of gaining sea ice volume is through the mechanical redistribution of mass as a consequence of deformation events. During the ice growth season divergent motion produces leads where new ice grows thermodynamically, while convergent motion fractures the ice and either piles the resultant ice blocks into ridges or rafts one floe under the other. Here we present an exceptionally detailed airborne data set from a 9 km2 area of first year and second year ice in the Transpolar Drift north of Svalbard that allowed us to estimate the redistribution of mass from an observed deformation event. To achieve this level of detail we analyzed changes in sea ice freeboard acquired from two airborne laser scanner surveys just before and right after a deformation event brought on by a passing low-pressure system. A linear regression model based on divergence during this storm can explain 64% of freeboard variability. Over the survey region we estimated that about 1.3% of level sea ice volume was pressed together into deformed ice and the new ice formed in leads in a week after the deformation event would increase the sea ice volume by 0.5%. As the region is impacted by about 15 storms each winter, a simple linear extrapolation would result in about 7% volume increase and 20% deformed ice fraction at the end of the season.