Norwegian Young Sea ICE Expedition Research Articles

Exploration of the Types of Rarity in the Arctic Ocean from the Perspective of Multiple Methodologies.

The Arctic Ocean is facing rapid environmental changes with cascading effects on the entire Arctic marine ecosystem. However, we have a limited understanding of the consequences such changes have on bacteria and archaea (prokaryotes) at the base of the marine food web. In this study, we show how the prokaryotic rare biosphere behaves over a range of highly heterogeneous environmental conditions using 16S rRNA gene reads from amplicon and metagenome sequencing data from seawater samples collected during the Norwegian young sea ICE expedition between late winter and early summer. The prokaryotic rare biosphere was analyzed using different approaches: amplicon sequence variants and operational taxonomic units from the 16S rRNA gene amplicons and operational taxonomic units from the 16S rRNA genes of the metagenomes. We found that prokaryotic rare biosphere communities are specific to certain water masses, and that the majority of the rare taxa identified were always rare and disappeared in at least one sample under changing conditions, suggesting their high sensitivity to environmental heterogeneity. In addition, our methodological comparison revealed a good performance of 16S rRNA gene amplicon sequencing in describing rare biosphere patterns, while the metagenome-derived data were better to capture a significant diversity of so-far uncultivated rare taxa. Our analysis on the dynamics of the rare prokaryotic biosphere, by combining different methodological approaches, improves the description of the types of rarity predicted from Community Assembly theory in the Arctic Ocean.

Diversity and Composition of Pelagic Prokaryotic and Protist Communities in a Thin Arctic Sea-Ice Regime.

One of the most prominent manifestations of climate change is the changing Arctic sea-ice regime with a reduction in the summer sea-ice extent and a shift from thicker, perennial multiyear ice towards thinner, first-year ice. These changes in the physical environment are likely to impact microbial communities, a key component of Arctic marine food webs and biogeochemical cycles. During the Norwegian young sea ICE expedition (N-ICE2015) north of Svalbard, seawater samples were collected at the surface (5m), subsurface (20 or 50m), and mesopelagic (250m) depths on 9 March, 27 April, and 16 June 2015. In addition, several physical and biogeochemical data were recorded to contextualize the collected microbial communities. Through the massively parallel sequencing of the small subunit ribosomal RNA amplicon and metagenomic data, this work allows studying the Arctic's microbial community structure during the late winter to early summer transition. Results showed that, at compositional level, Alpha- (30.7%) and Gammaproteobacteria (28.6%) are the most frequent taxa across the prokaryotic N-ICE2015 collection, and also the most phylogenetically diverse. Winter to early summer trends were quite evident since there was a high relative abundance of thaumarchaeotes in the under-ice water column in late winter while this group was nearly absent during early summer. Moreover, the emergence of Flavobacteria and the SAR92 clade in early summer might be associated with the degradation of a spring bloom of Phaeocystis. High relative abundance of hydrocarbonoclastic bacteria, particularly Alcanivorax (54.3%) and Marinobacter (6.3%), was also found. Richness showed different patterns along the depth gradient for prokaryotic (highest at mesopelagic depth) and protistan communities (higher at subsurface depths). The microbial N-ICE2015 collection analyzed in the present study provides comprehensive new knowledge about the pelagic microbiota below drifting Arctic sea-ice. The higher microbial diversity found in late winter/early spring communities reinforces the need to continue with further studies to properly characterize the winter microbial communities under the pack-ice.

Decay phase thermodynamics of ice ridges in the Arctic Ocean

Four ice ridges (R1, R2, R3, and R4) were studied during the spring of 2015 in the Arctic Ocean. During the Norwegian Young Sea Ice expedition (N-ICE2015) from January 11 to June 23, the R/V Lance was moored at four different ice floes (Floe 1, Floe 2, Floe 3, and Floe 4) and drifted along with them. Ice ridge studies were performed on Floe 3 (R1, R2) and Floe 4 (R3, R4). From May 21 to June 23, all ice ridges were drilled several times for structural measurements and cored for physical property measurements. In addition, ridges R1 and R4 were instrumented with Oceanetic thermistor buoys, model 908-20 (OTB 908-20), which remotely logged the vertical temperature profile through the sail and keel of the ridges from April 29 to June 28. After combining these datasets, we obtained thermodynamic properties and evaluated heat budgets of the ridge keels in R1 and R4. Ridge R1 was measured during the transition from the main phase to the decay phase, and ridge R4 was measured during the decay phase. In R1, a 3–4 W/m2 upwards vertical conductive heat flux through the keel was calculated, which caused cooling of the keel and the growth of new ice (i.e., 0.5 m over 22 days from May 5 to May 27, as observed by temperature readings). The total amount of heat extracted from the keel was spent on cooling the keel and growing new ice in fractions of 0.4 and 0.6, respectively. In R4, a downwards vertical conductive heat flux (up to 2 W/m2) transported energy into the keel through the top surface of the keel, while the bottom of the keel melted (i.e., 1.6 m over 12 days from June 12 to June 24) due to the oceanic heat flux.

A Distributed Snow‐Evolution Model for Sea‐Ice Applications (SnowModel)

AbstractSnow‐depth distributions on sea ice have substantial impacts on winter ice growth and summer ice melt. There are two types of wind‐related snow distributions in this environment: snowdrifts that form around ice pressure ridges; and snow dunes and other snow bedforms that form on relatively level, undeformed ice. A snow‐evolution modeling system (SnowModel) was tested against winter snow observations collected during the Norwegian young sea ICE expedition (N‐ICE2015) north of Svalbard, with an emphasis on reproducing these two types of snow distributions. The SnowModel simulation spanned 1 year, summer 2014 through summer 2015, over a 1.5 km by 1.5 km domain, using a 1 m horizontal grid increment and 3 h time step. Existing SnowModel components, created originally for terrestrial applications, performed energy balance, snow property, snowdrift, and data assimilation calculations in response to prescribed meteorological forcings. A new SnowModel component, SnowDunes, was created to simulate snow‐bedform distributions on level, undeformed ice. Model results reproduced observed snowdrift profiles around pressure ridges and snow‐depth distributions over level, undeformed ice, resulting in physically realistic snow heterogeneity and property information. We conclude that the SnowModel toolkit contains the components required to simulate most processes driving the seasonal distribution of snow on sea ice. SnowModel can evolve snow on sea ice over local to pan‐Arctic areas, using grid increments ranging from 1 m to tens of km, and time increments of subhourly to daily.

Spatiotemporal Variability of Barium in Arctic Sea‐Ice and Seawater

AbstractFreshwater export from the Arctic is critical in determining the density of water at sites of North Atlantic deep water formation, which in turn influences the global flux of oceanic heat and nutrients. We need geochemical tracers and high‐resolution observations to refine our freshwater budgets and constrain models for future change. The use of seawater barium concentrations in the Arctic Ocean as a freshwater tracer relies on the conservative behavior of barium in seawater; while this has been shown to be an unreliable assumption in Arctic summers, there are a lack of studies observing seasonal progressions. Here, we present barium concentrations from seawater and sea‐ice collected during the Norwegian Young Sea ICE expedition from boreal winter into summer. We use other tracers (salinity, oxygen isotopes, and alkalinity) to reconstruct freshwater inputs and calculate a barium “deficit” that can be attributed to nonconservative processes. We locate a deficit in winter when biological production is low, which we attribute to uptake by barite formation associated with old organic matter or by internal sea‐ice processes. We also find a significant barium deficit during the early spring bloom, consistent with uptake into organic‐matter associated microenvironments. However, in summer, there no strong barium deficit near the surface, despite high biological production and organic carbon standing stocks, perhaps reflecting phytoplankton assemblage changes, and/or rapid internal cycling. Our findings challenge the assumptions surrounding the use of barium as an Arctic freshwater tracer, and highlight the need to improve our understanding of barium in sea‐ice environments.

Can we extend local sea-ice measurements to satellite scale? An example from the N-ICE2015 expedition

ABSTRACTKnowledge of Arctic sea-ice conditions is of great interest for Arctic residents, as well as for commercial usage, and to study the effects of climate change. Information gained from analysis of satellite data contributes to this understanding. In the course of using in situ data in combination with remotely sensed data, the question of how representative local scale measurements are of a wider region may arise. We compare in situ total sea-ice thickness measurements from the Norwegian young sea ICE expedition in the area north of Svalbard with airborne-derived total sea-ice thickness from electromagnetic soundings. A segmented and classified synthetic aperture radar (SAR) quad-pol ALOS-2 Palsar-2 satellite scene was grouped into three simplified ice classes. The area fractions of the three classes are: 11.2% ‘thin’, 74.4% ‘level’, and 14.4% ‘deformed’. The area fractions of the simplified classes from ground- and helicopter-based measurements are comparable with those achieved from the SAR data. Thus, this study shows that there is potential for a stepwise upscaling from in situ, to airborne, to satellite data, which allow us to assess whether in situ data collected are representative of a wider region as observed by satellites.

Vertical thermodynamic structure of the troposphere during the Norwegian young sea ICE expedition (N‐ICE2015)

AbstractThe Norwegian young sea ICE (N‐ICE2015) expedition was designed to investigate the atmosphere‐snow‐ice‐ocean interactions in the young and thin sea ice regime north of Svalbard. Radiosondes were launched twice daily during the expedition from January to June 2015. Here we use these upper air measurements to study the multiple cyclonic events observed during N‐ICE2015 with respect to changes in the vertical thermodynamic structure, moisture content, and boundary layer characteristics. We provide statistics of temperature inversion characteristics, static stability, and boundary layer extent. During winter, when radiative cooling is most effective, we find the strongest impact of synoptic cyclones. Changes to thermodynamic characteristics of the boundary layer are associated with transitions between the radiatively “clear” and “opaque” atmospheric states. In spring, radiative fluxes warm the surface leading to lifted temperature inversions and a statically unstable boundary layer. Further, we compare the N‐ICE2015 static stability distributions to corresponding profiles from ERA‐Interim reanalysis, from the closest land station in the Arctic North Atlantic sector, Ny‐Ålesund, and to soundings from the SHEBA expedition (1997/1998). We find similar stability characteristics for N‐ICE2015 and SHEBA throughout the troposphere, despite differences in location, sea ice thickness, and snow cover. For Ny‐Ålesund, we observe similar characteristics above 1000 m, while the topography and ice‐free fjord surrounding Ny‐Ålesund generate great differences below. The long‐term radiosonde record (1993–2014) from Ny‐Ålesund indicates that during the N‐ICE2015 spring period, temperatures were close to the climatological mean, while the lowest 3000 m were 1–3°C warmer than the climatology during winter.

Meteorological conditions in a thinner Arctic sea ice regime from winter to summer during the Norwegian Young Sea Ice expedition (N‐ICE2015)

AbstractAtmospheric measurements were made over Arctic sea ice north of Svalbard from winter to early summer (January–June) 2015 during the Norwegian Young Sea Ice (N‐ICE2015) expedition. These measurements, which are available publicly, represent a comprehensive meteorological data set covering the seasonal transition in the Arctic Basin over the new, thinner sea ice regime. Winter was characterized by a succession of storms that produced short‐lived (less than 48 h) temperature increases of 20 to 30 K at the surface. These storms were driven by the hemispheric scale circulation pattern with a large meridional component of the polar jet stream steering North Atlantic storms into the high Arctic. Nonstorm periods during winter were characterized by strong surface temperature inversions due to strong radiative cooling (“radiatively clear state”). The strength and depth of these inversions were similar to those during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. In contrast, atmospheric profiles during the “opaquely cloudy state” were different to those from SHEBA due to differences in the synoptic conditions and location within the ice pack. Storm events observed during spring/summer were the result of synoptic systems located in the Barents Sea and the Arctic Basin rather than passing directly over N‐ICE2015. These synoptic systems were driven by a large‐scale circulation pattern typical of recent years, with an Arctic Dipole pattern developing during June. Surface temperatures became near‐constant 0°C on 1 June marking the beginning of summer. Atmospheric profiles during the spring and early summer show persistent lifted temperature and moisture inversions that are indicative of clouds and cloud processes.

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.

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.

Windows in Arctic sea ice: Light transmission and ice algae in a refrozen lead

AbstractThe Arctic Ocean is rapidly changing from thicker multiyear to thinner first‐year ice cover, with significant consequences for radiative transfer through the ice pack and light availability for algal growth. A thinner, more dynamic ice cover will possibly result in more frequent leads, covered by newly formed ice with little snow cover. We studied a refrozen lead (≤0.27 m ice) in drifting pack ice north of Svalbard (80.5–81.8°N) in May–June 2015 during the Norwegian young sea ICE expedition (N‐ICE2015). We measured downwelling incident and ice‐transmitted spectral irradiance, and colored dissolved organic matter (CDOM), particle absorption, ultraviolet (UV)‐protecting mycosporine‐like amino acids (MAAs), and chlorophyll a (Chl a) in melted sea ice samples. We found occasionally very high MAA concentrations (up to 39 mg m−3, mean 4.5 ± 7.8 mg m−3) and MAA to Chl a ratios (up to 6.3, mean 1.2 ± 1.3). Disagreement in modeled and observed transmittance in the UV range let us conclude that MAA signatures in CDOM absorption spectra may be artifacts due to osmotic shock during ice melting. Although observed PAR (photosynthetically active radiation) transmittance through the thin ice was significantly higher than that of the adjacent thicker ice with deep snow cover, ice algal standing stocks were low (≤2.31 mg Chl a m−2) and similar to the adjacent ice. Ice algal accumulation in the lead was possibly delayed by the low inoculum and the time needed for photoacclimation to the high‐light environment. However, leads are important for phytoplankton growth by acting like windows into the water column.