206 research outputs found
Snow contribution to first-year and second-year Arctic sea ice mass balance north of Svalbard
The salinity and water oxygen isotope composition (ÎŽ18O) of 29 first-year (FYI) and second-year (SYI) Arctic sea ice cores (total length 32.0 m) from the drifting ice pack north of Svalbard were examined to quantify the contribution of snow to sea ice mass. Five cores (total length 6.4 m) were analyzed for their structural composition, showing variable contribution of 10â30% by granular ice. In these cores, snow had been entrained in 6â28% of the total ice thickness. We found evidence of snow contribution in about three quarters of the sea ice cores, when surface granular layers had very low ÎŽ18O values. Snow contributed 7.5â9.7% to sea ice mass balance on average (including also cores with no snow) based on ÎŽ18O mass balance calculations. In SYI cores, snow fraction by mass (12.7â16.3%) was much higher than in FYI cores (3.3â4.4%), while the bulk salinity of FYI (4.9) was distinctively higher than for SYI (2.7). We conclude that oxygen isotopes and salinity profiles can give information on the age of the ice and enables distinction between FYI and SYI (or older) ice in the area north of Svalbard
Internal conversion coefficients for superheavy elements
The internal conversion coefficients (ICC) were calculated for all atomic
subshells of the elements with 104<=Z<=126, the E1...E4, M1...M4
multipolarities and the transition energies between 10 and 1000 keV. The atomic
screening was treated in the relativistic Hartree-Fock-Slater model. The Tables
comprising almost 90000 subshell and total ICC were recently deposited at LANL
preprint server.Comment: 6 pages including 3 figures, needs files myown.sty and epsfig.sty
(both included
Implications of surface flooding on airborne estimates of snow depth on sea ice
Snow depth observations from airborne snow radars, such as the
NASA's Operation IceBridge (OIB) mission, have recently been used in
altimeter-derived sea ice thickness estimates, as well as for model
parameterization. A number of validation studies comparing airborne and
in situ snow depth measurements have been conducted in the western Arctic
Ocean, demonstrating the utility of the airborne data. However, there have
been no validation studies in the Atlantic sector of the Arctic. Recent
observations in this region suggest a significant and predominant shift
towards a snow-ice regime caused by deep snow on thin sea ice. During the Norwegian
young sea Ice, Climate and Ecosystems (ICE) expedition (N-ICE2015) in the area north of Svalbard, a
validation study was conducted on 19 March 2015. This study collected
ground truth data during an OIB overflight. Snow and ice thickness
measurements were obtained across a two-dimensional (2-D) 400âmâĂâ60âm grid.
Additional snow and ice thickness measurements collected in situ from
adjacent ice floes helped to place the measurements obtained at the gridded
survey field site into a more regional context. Widespread negative
freeboards and flooding of the snowpack were observed during the N-ICE2015
expedition due to the general situation of thick snow on relatively thin
sea ice. These conditions caused brine wicking into and saturation of the
basal snow layers. This causes the airborne radar signal to undergo more
diffuse scattering, resulting in the location of the radar main scattering
horizon being detected well above the snowâice interface. This leads to a
subsequent underestimation of snow depth; if only radar-based information is
used, the average airborne snow depth was 0.16âm thinner than that measured
in situ at the 2-D survey field. Regional data within 10âkm of the 2-D
survey field suggested however a smaller deviation between average airborne
and in situ snow depth, a 0.06âm underestimate in snow depth by the airborne
radar, which is close to the resolution limit of the OIB snow radar system.
Our results also show a broad snow depth distribution, indicating a large
spatial variability in snow across the region. Differences between the
airborne snow radar and in situ measurements fell within the standard
deviation of the in situ data (0.15â0.18âm). Our results suggest that seawater flooding of the snowâice interface leads to underestimations of snow
depth or overestimations of sea ice freeboard measured from radar
altimetry, in turn impacting the accuracy of sea ice thickness estimates.</p
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 dataset from a 9km2 area of first 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 seaso
On the reliability of the theoretical internal conversion coefficients
Possible sources of uncertainties in the calculations of the internal
conversion coefficients are studied. The uncertainties induced by them are
estimated.Comment: 16 pages (including 3 figures inserted by 'epsfig' macro
The seeding of ice algal blooms in Arctic pack ice: The multiyear ice seed repository hypothesis
Source at http://dx.doi.org/10.1002/2016JG003668 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,
fi
rst 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 toward 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 dominant ice diatom
Nitzschia frigida
. The
proposed seeding mechanism may be compromised due to the disappearance of older ice in the anticipated
regime shift toward a seasonally ice-free Arctic Ocean
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Sea-ice-free Arctic during the Last Interglacial supports fast future loss
The Last Interglacial (LIG), a warmer period 130-116 ka before present, is a potential analog for future climate change. Stronger LIG summertime insolation at high northern latitudes drove Arctic land summer temperatures 4-5 °C higher than the preindustrial era. Climate model simulations have previously failed to capture these elevated temperatures, possibly because they were unable to correctly capture LIG sea-ice changes. Here, we show the latest version of the fully-coupled UK Hadley Center climate model (HadGEM3) simulates a more accurate Arctic LIG climate, including elevated temperatures. Improved model physics, including a sophisticated sea-ice melt-pond scheme, result in a complete simulated loss of Arctic sea ice in summer during the LIG, which has yet to be simulated in past generations of models. This ice-free Arctic yields a compelling solution to the longstanding puzzle of what drove LIG Arctic warmth and supports a fast retreat of future Arctic summer sea ice
Leads in Arctic pack ice enable early phytoplankton blooms below snow-covered sea ice
© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 7 (2017): 40850, doi:10.1038/srep40850.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 16â±â6âgâC mâ2. 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.This study was supported by the Centre for Ice, Climate and Ecosystems (ICE) at the Norwegian Polar Institute, the Ministry of Climate and Environment, Norway, the Research Council of Norway (projects Boom or Bust no. 244646, STASIS no. 221961, CORESAT no. 222681, CIRFA no. 237906 and AMOS CeO no. 223254), and the Ministry of Foreign Affairs, Norway (project ID Arctic), the ICE-ARC program of the European Union 7th Framework Program (grant number 603887), the Polish-Norwegian Research Program operated by the National Centre for Research and Development under the Norwegian Financial Mechanism 2009â2014 in the frame of Project Contract Pol-Nor/197511/40/2013, CDOM-HEAT, and the Ocean Acidification Flagship program within the FRAM- High North Research Centre for Climate and the Environment, Norway
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