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The warming of our planet is changing the Arctic dramatically. The area covered by sea-ice is shrinking and the ice that is left is younger and thinner. We took part in an expedition to the Arctic, to study how these changes affect organisms living in and under the ice. Following this expedition, we found that storms can more easily break the thinner ice. Storms form cracks in the sea ice, allowing sunlight to pass into the water below, which makes algal growth possible. Algae are microscopic “plants” that grow in water or sea ice. Storms also brought thick heavy snow, which pushed the ice surface below the water. This flooded the snow and created slush. We discovered that this slush is another good habitat for algae. If Arctic sea ice continues to thin, and storms become more common, we expect that these algal habitats will become more important in the future.

In this paper, the retrieval of sea-ice surface heights from the interferometric TanDEM-X data is investigated. The data were acquired over fast and drifting ice in Fram Strait located between Greenland and Svalbard. Additional measurements of the sea-ice surface topography were carried out using a stereo camera and a laser altimeter. The comparison of the surface elevation retrieved from TanDEM-X imagery with the results of the stereo camera measurements revealed that sea ice ridges greater than 0.5 m can be estimated with a root mean-square error of 0.3 m or less with the error decreasing as a function of ridge height. Although the helicopter-borne laser data are only available as 1-D profiles with a much higher across-track spatial resolution than the TanDEM-X data, they proved to be useful for the validation. The need for multilook averaging to reduce the phase noise is identified as the main challenge in achieving the spatial resolution necessary for retrieving sea-ice surface topography using synthetic aperture radar interferometry.

We present freeboard measurements from airborne laser scanner (ALS), the Airborne Synthetic Aperture and Interferometric Radar Altimeter System (ASIRAS), and CryoSat-2 SIRAL radar altimeter; ice thickness measurements from both helicopter-borne and ground-based electromagnetic-sounding; and point measurements of ice properties. This case study was carried out in April 2015 during the N-ICE2015 expedition in the area of the Arctic Ocean north of Svalbard. The region is represented by deep snow up to 1.12 m and a widespread presence of negative freeboards. The main scattering surfaces from both CryoSat-2 and ASIRAS are shown to be closer to the snow freeboard obtained by ALS than to the ice freeboard measured in situ. This case study documents the complexity of freeboard retrievals from radar altimetry. We show that even under cold (below −15°C) conditions the radar freeboard can be close to the snow freeboard on a regional scale of tens of kilometers. We derived a modal sea-ice thickness for the study region from CryoSat-2 of 3.9 m compared to measured total thickness 1.7 m, resulting in an overestimation of sea-ice thickness on the order of a factor 2. Our results also highlight the importance of year-to-year regional scale information about the depth and density of the snowpack, as this influences the sea-ice freeboard, the radar penetration, and is a key component of the hydrostatic balance equations used to convert radar freeboard to sea-ice thickness.

© 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 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., 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 2009–2014 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.

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Biogeosciences 122 (2017): 1529–1548, doi: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, 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 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., Norwegian Research Council Grant Number: 244646; Norwegian Ministry of Climate and Environment Grant Number: N-ICE; Norwegian Research Council Grant Number: 221961; Norwegian Ministry of Foreign Affairs Grant Number: ID Arctic; Norwegian Ministry of Foreign Affairs and Ministry of Climate and Environment, Norway; Polish-Norwegian Research Program Grant Number: Pol-Nor/197511/40/2013; Research Council of Norway project STASIS Grant Number: 221961; Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant Canada Foundation for Innovation Investment in Science Fund; Research Council of Norway project Boom or Bust Grant Number: 244646; Centre of Ice, Climate and Ecosystems

Sea-ice concentrations derived from satellite microwave brightness temperatures are less accurate during summer. In the Arctic Ocean the lack of accuracy is primarily caused by melt ponds, but also by changes in the properties of snow and the sea-ice surface itself. We investigate the sensitivity of eight sea-ice concentration retrieval algorithms to melt ponds by comparing sea-ice concentration with the melt-pond fraction. We derive gridded daily sea-ice concentrations from microwave brightness temperatures of summer 2009. We derive the daily fraction of melt ponds, open water between ice floes, and the ice-surface fraction from contemporary Moderate Resolution Spectroradiometer (MODIS) reflectance data. We only use grid cells where the MODIS sea ice concentration, which is the melt-pond fraction plus the ice-surface fraction, exceeds 90 %. For one group of algorithms, e.g., Bristol and Comiso bootstrap frequency mode (Bootstrap_f), sea-ice concentrations are linearly related to the MODIS melt-pond fraction quite clearly after June. For other algorithms, e.g., Near9OGHz and Comiso bootstrap polarization mode (Bootstrap_p), this relationship is weaker and develops later in summer. We attribute the variation of the sensitivity to the melt-pond fraction across the algorithms to a different sensitivity of the brightness temperatures to snow-property variations. We find an underestimation of the sea-ice concentration by between 14 % (Bootstrap_f) and 26 % (Bootstrap_p) for 100 % sea ice with a melt-pond fraction of 40 %. The underestimation reduces to 0 % for a melt pond fraction of 20 %. In presence of real open water between ice floes, the sea-ice concentration is overestimated by between 26 % (Bootstrap_f) and 14 % (Bootstrap_p) at 60 % sea-ice concentration and by 20 % across all algorithms at 80 % sea-ice concentration. None of the algorithms investigated performs best based on our investigation of data from summer 2009. We suggest that those algorithms which are m