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Manifestations of climate change are often shown as gradual changes in physical or biogeochemical properties1. Components of the climate system, however, can show stepwise shifts from one regime to another, as a nonlinear response of the system to a changing forcing2. Here we show that the Arctic sea ice regime shifted in 2007 from thicker and deformed to thinner and more uniform ice cover. Continuous sea ice monitoring in the Fram Strait over the last three decades revealed the shift. After the shift, the fraction of thick and deformed ice dropped by half and has not recovered to date. The timing of the shift was preceded by a two-step reduction in residence time of sea ice in the Arctic Basin, initiated first in 2005 and followed by 2007. We demonstrate that a simple model describing the stochastic process of dynamic sea ice thickening explains the observed ice thickness changes as a result of the reduced residence time. Our study highlights the long-lasting impact of climate change on the Arctic sea ice through reduced residence time and its connection to the coupled ocean–sea ice processes in the adjacent marginal seas and shelves of the Arctic Ocean.A simple model describes the stochastic process of dynamic sea ice thickening, shows how reduced residence time affects changes in ice thickness and highlights the enduring impact of climate change on the Arctic Ocean. [ABSTRACT FROM AUTHOR]

Despite the exclusion of the Southern Ocean from assessments of progress towards achieving the Convention on Biological Diversity (CBD) Strategic Plan, the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) has taken on the mantle of progressing efforts to achieve it. Within the CBD, Aichi Target 11 represents an agreed commitment to protect 10% of the global coastal and marine environment. Adopting an ethos of presenting the best available scientific evidence to support policy makers, CCAMLR has progressed this by designating two Marine Protected Areas in the Southern Ocean, with three others under consideration. The region of Antarctica known as Dronning Maud Land (DML; 20°W to 40°E) and the Atlantic sector of the Southern Ocean that abuts it conveniently spans one region under consideration for spatial protection. To facilitate both an open and transparent process to provide the vest available scientific evidence for policy makers to formulate management options, we review the body of physical, geochemical and biological knowledge of the marine environment of this region. The level of scientific knowledge throughout the seascape abutting DML is polarized, with a clear lack of data in its eastern part which is presumably related to differing levels of research effort dedicated by national Antarctic programmes in the region. The lack of basic data on fundamental aspects of the physical, geological and biological nature of eastern DML make predictions of future trends difficult to impossible, with implications for the provision of management advice including spatial management. Finally, by highlighting key knowledge gaps across the scientific disciplines our review also serves to provide guidance to future research across this important region. [ABSTRACT FROM AUTHOR]

Information about the state of the Arctic sea ice is becoming increasingly important. This paper describes an approach for automatic retrieval of daily thin sea ice thickness maps around Svalbard. The algorithm uses thermal satellite imagery from MODIS to estimate the surface temperature of the ice and further uses a thermal model of the ice surface to estimate the thickness of the sea ice. The approach is usable for thin sea ice, up to ca. 50 cm thick, during cold weather (freezing) conditions and without cloud cover present. The algorithm is compared with helicopter-borne electromagnetic ice thickness measurements. The comparison yields increasing root-mean-square deviation (RMSD) for thicker ice. The lowest RMSD found is 8.7 cm for ice thickness in the range 10 cm < hi ≤ 20 cm. The highest RMSD found is 25.2 cm for ice thickness in the range 30 cm < hi ≤ 40 cm. The bias shows no such trend, and the overall bias is found to be −5.5 cm. The results show that this is a promising approach, allowing monitoring of thin sea ice thickness at relatively higher spatial resolution. [ABSTRACT FROM AUTHOR]

Fram Strait is the major gateway connecting the Arctic Ocean and North Atlantic Ocean, where nearly 90% of the sea ice export from the Arctic Ocean takes place. The exported sea ice is a large source of freshwater to the Nordic Seas and Subpolar North Atlantic, thereby preconditioning European climate and deep water formation in the North Atlantic Ocean. Here we show that in 2018, the ice export through Fram Strait showed an unprecedented decline since the early 1990s. The 2018 ice export was reduced to less than 40% relative to that between 2000 and 2017. The minimum export is attributed to regional sea ice-ocean processes driven by an anomalous atmospheric circulation over the Atlantic sector of the Arctic. The result indicates that a drastic change of the Arctic sea ice outflow and its environmental consequences happen not only through Arctic-wide ice thinning, but also by regional scale atmospheric anomalies. Fram Strait is the major gateway connecting the Arctic Ocean and North Atlantic Ocean, where nearly 90% of the sea ice export from the Arctic Ocean takes place. Here, the authors show that in 2018, ice export showed an unprecedented decline since at least the 1990s, attributed to ongoing Arctic-wide ice thinning and regional-scale atmospheric anomalies. [ABSTRACT FROM AUTHOR]

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) 400 m × 60 m 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 snow–ice interface. This leads to a subsequent underestimation of snow depth; if only radar-based information is used, the average airborne snow depth was 0.16 m thinner than that measured in situ at the 2-D survey field. Regional data within 10 km of the 2-D survey field suggested however a smaller deviation between average airborne and in situ snow depth, a 0.06 m 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 (0.15–0.18 m). Our results suggest that seawater flooding of the snow–ice 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. [ABSTRACT FROM AUTHOR]

Airborne electromagnetic induction sensors have demonstrated their extensive capacities to measure sea-ice thickness distributions. However, biases can emerge when comparing these 1-D measurements to a broader 2-D regional scale due to the spatial anisotropy inherent to sea-ice cover. Automated processing of available sea-ice maps could significantly ease the decision on how to set up an optimised flight pattern, which would result in representative ice thickness numbers for the region. In this study, first we investigate the extent to which the sea-ice anisotropy can influence the representativeness of an airborne survey compared to the regional situation. Second, we propose a method to process sea-ice maps prior to flights to help preparing the most representative flight plan possible for the local area. The method is based on automated segmentation of radar satellite images and extensive simulation of flight transects over the image. The spatial analysis of these transects enables for the identification of the most representative survey trajectories for the area. The method was applied for seven different synthetic aperture radar satellite images over Arctic sea ice north of Svalbard. The results indicate that the proposed method improved the representativeness of the airborne survey by identifying the most suitable transect over the ice pack. [ABSTRACT FROM AUTHOR]

The Svalbard archipelago in the Arctic North Atlantic is experiencing rapid changes in the surface climate and sea ice distribution, with impacts for the coupled climate system and the local society. This study utilizes observational data of surface air temperature (SAT) from 1980–2016 across the whole Svalbard archipelago, and sea ice extent (SIE) from operational sea ice charts to conduct a systematic assessment of climatologies, long‐term changes and regional differences. The proximity to the warm water mass of the West Spitsbergen Current drives a markedly warmer climate in the western coastal regions compared to northern and eastern Svalbard. This imprints on the SIE climatology in southern and western Svalbard, where the annual maxima of 50–60% area ice coverage are substantially less than 80–90% in the northern and eastern fjords. Owing to winter‐amplified warming, the local climate is shifting towards more maritime conditions, and SIE reductions of between 5 and 20% per decade in particular regions are found, such that a number of fjords in the west have been virtually ice‐free in recent winters. The strongest decline comes along with SAT forcing and occurs over the most recent 1–2 decades in all regions; while in the 1980s and 1990s, enhanced northerly winds and sea ice drift can explain 30–50% of SIE variability around northern Svalbard, where they had correspondingly lead to a SIE increase. With an ongoing warming it is suggested that both the meteorological and cryospheric conditions in eastern Svalbard will become increasingly similar to what is already observed in the western fjords, namely suppressed typical Arctic climate conditions. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) satellite images are used to monitor Arctic sea ice, with systematic data records dating back to 1991. We propose a semi-supervised classification method that separates open water from sea ice and can utilise ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1 SAR images. The classification combines automatic segmentation with a manual segment selection stage. The segmentation algorithm requires only the backscatter intensities and incidence angle values as input, therefore can be used to establish a consistent decadal sea ice record. In this study we investigate the sea ice conditions in two Svalbard fjords, Kongsfjorden and Rijpfjorden. Both fjords have a seasonal ice cover, though Rijpfjorden has a longer sea ice season. The satellite image dataset has weekly to daily records from 2002 until now, and less frequent records between 1991 and 2002. Time overlap between different sensors is investigated to ensure consistency in the reported sea ice cover. The classification results have been compared to high-resolution SAR data as well as in-situ measurements and sea ice maps from Ny-Ålesund. For both fjords the length of the sea ice season has shortened since 2002 and for Kongsfjorden the maximum sea ice coverage is significantly lower after 2006. [ABSTRACT FROM AUTHOR]

Norske Øer Ice Barrier (NØIB) is a vast region of fast ice off northeast Greenland. To understand its thermodynamics, an ice mass balance buoy (IMB) was deployed in late August 2012. The IMB operated for a full year, providing unique year-round observations of air, snow, ice, and upper ocean. Here, we examine atmospheric conditions and snow and sea ice evolution, derive the ocean heat flux at the deployment site, and investigate the effect of snow on the sea ice mass balance. Although an extremely low surface air temperature of -52°C was recorded at the IMB site, the sum of freezing-degree days (4,848 K·d) is similar to that in the central Arctic. The maximum snow depth 0.73 m (on 29 May 2013, when ice was 2.19 m thick) is thicker than typically observed on level Arctic landfast ice and drift ice, and thick snow appears common in this region. Ocean heat flux was large in autumn and early winter (>7 W m-2), attributed in part to local solar heating of surface waters in summer and advected ocean heat later in the year. The combination of high ocean heat flux and thick snow resulted in a net loss of ice at the ice bottom over the year. A one-dimensional sea ice model suggests that the thick snow cover limits bottom ice growth significantly. The heavy snow load could potentially have contributed 0.29 m snow ice; however, we cannot unambiguously prove this happened. [ABSTRACT FROM AUTHOR]

The Fram Strait sea ice volume export 1992-2014 is derived by combining sea ice thickness from upward looking sonars (ULS) with satellite observations of sea ice drift and area. Fram Strait is the main gate for sea ice export from the Arctic. The average yearly sea ice export is 2,400 ± 640km³. The mean and modal ULS ice thickness in Fram Strait decreased by 15% and 21% per decade, respectively, during 1990-2014. Combined with sea ice drift and area this leads to a decrease of the Arctic sea ice volume export of 27 ± 2% per decade between 1992 and 2014. Thus, for the given time period, changes in sea ice export do not drive the sea ice volume decrease in the Arctic Basin. However, for individual years like 2007 and 2012 the ice export likely has contributed to the loss of summer sea ice. Combined with PIOMAS model simulation we estimate that 14% of the total Arctic sea ice volume is exported every year through Fram Strait. This fraction of the total sea ice volume exported per year does not show a trend because the Arctic Basin ice volume is decreasing at a similar rate as the Fram Strait ice volume export. Compared to ice velocities from Acoustic Doppler Current Profiler (ADCP) the satellite ice drift shows good correspondence in variability but a negative bias. Ice volume transport estimates presented here thus should be considered a conservative estimate.We show, however, that the transport estimates are not sensitive to the exact flux gate location. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) satellite images are used to monitor Arctic sea ice, with systematic data records dating back to 1991. We propose a semi-supervised classification method that separates open water from sea ice and can utilise ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1 SAR images. The classification combines automatic segmentation with a manual segment selection stage. The segmentation algorithm requires only the backscatter intensities and incidence angle values as input, therefore can be used to establish a consistent decadal sea ice record. In this study we investigate the sea ice conditions in two Svalbard fjords, Kongsfjorden and Rijpfjorden. Both fjords have a seasonal ice cover, though Rijpfjorden has a longer sea ice season. The satellite image dataset has weekly to daily records from 2002 until now, and less frequent records between 1991 and 2002. Time overlap between different sensors is investigated to ensure consistency in the reported sea ice cover. The classification results have been compared to high-resolution SAR data as well as in-situ measurements and sea ice maps from Ny-Ålesund. For both fjords the length of the sea ice season has shortened since 2002 and for Kongsfjorden the maximum sea ice coverage is significantly lower after 2006. [ABSTRACT FROM AUTHOR]

Reflection power derived from the global navigation satellite system (GNSS) observations and its sensitivity to sea-ice concentration are investigated in this article. A corresponding experiment has been conducted during the Fram Strait cruise of the Norwegian research vessel Lance in summer 2016. The dedicated setup with a GNSS Occultation Reflectometry Scatterometry (GORS) receiver and dual-polarization (left- and right-handed) antenna links recorded 1922 h of reflection events during the 20-day cruise of the ship. The antenna setup, mounted 25.0 m above the waterline, serves to acquire sea surface reflections at grazing angles below 30°. Within a 5-min coherent integration period, direct and reflected signal contributions can be separated. Except for the highest sea states, with roll angle changes of 20° peak to peak, the separation allows to retrieve the reflection power and quantifies it in cross-, co-, and cross-to-co-polar ratios. The sea-ice concentration is inverted from power ratios using a non-linear least-squares algorithm. Additional data on sea-ice concentration gathered by a watchman on the ship are used for validation. The inversion results have a 20% resolution in concentration and 3-h resolution in time. The validation shows that the cross- and cross-to-co-polar data are sensitive to the sea-ice concentration. The respective Pearson correlation of 0.75 and 0.67 further suggests studies to foster the application of the GNSS data for sea-ice reflectometry. [ABSTRACT FROM AUTHOR]

Rapid changes are occurring in the Arctic, including a reduction in sea ice thickness and coverage and a shift towards younger and thinner sea ice. Snow and sea ice models are often used to study these ongoing changes in the Arctic, and are typically forced by atmospheric reanalyses in absence of observations. ERA5 is a new global reanalysis that will replace the widely used ERA-Interim (ERA-I). In this study, we compare the 2 m air temperature (T2M), snowfall (SF) and total precipitation (TP) from ERA-I and ERA5, and evaluate these products using buoy observations from Arctic sea ice for the years 2010 to 2016. We further assess how biases in reanalyses can influence the snow and sea ice evolution in the Arctic, when used to force a thermodynamic sea ice model. We find that ERA5 is generally warmer than ERA-I in winter and spring (0–1.2 ∘ C), but colder than ERA-I in summer and autumn (0–0.6 ∘ C) over Arctic sea ice. Both reanalyses have a warm bias over Arctic sea ice relative to buoy observations. The warm bias is smaller in the warm season, and larger in the cold season, especially when the T2M is below -25 ∘ C in the Atlantic and Pacific sectors. Interestingly, the warm bias for ERA-I and new ERA5 is on average 3.4 and 5.4 ∘ C (daily mean), respectively, when T2M is lower than -25 ∘ C. The TP and SF along the buoy trajectories and over Arctic sea ice are consistently higher in ERA5 than in ERA-I. Over Arctic sea ice, the TP in ERA5 is typically less than 10 mm snow water equivalent (SWE) greater than in ERA-I in any of the seasons, while the SF in ERA5 can be 50 mm SWE higher than in ERA-I in a season. The largest increase in annual TP (40–100 mm) and SF (100–200 mm) in ERA5 occurs in the Atlantic sector. The SF to TP ratio is larger in ERA5 than in ERA-I, on average 0.6 for ERA-I and 0.8 for ERA5 along the buoy trajectories. Thus, the substantial anomalous Arctic rainfall in ERA-I is reduced in ERA5, especially in summer and autumn. Simulations with a 1-D thermodynamic sea ice model demonstrate that the warm bias in ERA5 acts to reduce thermodynamic ice growth. The higher precipitation and snowfall in ERA5 results in a thicker snowpack that allows less heat loss to the atmosphere. Thus, the larger winter warm bias and higher precipitation in ERA5, compared with ERA-I, result in thinner ice thickness at the end of the growth season when using ERA5; however the effect is small during the freezing period. [ABSTRACT FROM AUTHOR]

Precipitable water vapor (PWV) is an important parameter for climate research and a crucial factor to achieve high accuracy in satellite geodesy and satellite altimetry. Currently Global Navigation Satellite System (GNSS) PWV retrieval using static Precise Point Positioning is limited to ground stations. We demonstrated the PWV retrieval using kinematic Precise Point Positioning method with shipborne GNSS observations during a 20‐day experiment in 2016 in Fram Strait, the region of the Arctic Ocean between Greenland and Svalbard. The shipborne GNSS PWV shows an agreement of ~1.1 mm with numerical weather model data and radiosonde observations, and a root‐mean‐square of ~1.7 mm compared to Satellite with ARgos and ALtiKa PWV. An improvement of 10% is demonstrated with the multi‐GNSS compared to the Global Positioning System solution. The PWV retrieval was conducted under different sea state from calm water up to gale. Such shipborne GNSS PWV has the promising potential to improve numerical weather forecasts and satellite altimetry. Plain Language Summary: Atmospheric water vapor retrieval using GNSS kinematic Precise Point Positing technique is demonstrated with shipborne GNSS data collected during a 20‐day cruise in Fram Strait (~80°N), the area in the Arctic Ocean between Greenland and Svalbard. An accuracy of ~1 mm is achieved compared to ERA‐Interim precipitable water vapor (PWV) and radiosonde data, and an agreement of ~2 mm is demonstrated between shipborne GNSS PWV and satellite altimetry PWV observation. The contribution of multi‐GNSS is addressed, and efforts are also made to investigate the PWV spatial resolution in order to include more data for comparison. Static Precise Point Positioning method is widely used at ground‐based GNSS stations in climate research and weather forecasting. However, it is still limited to land. Shipborne GNSS PWV retrieval could fill in the vast ocean with high temporal/spatial resolutions. Shipborne GNSS PWV could cover open sea, coastal, and polar regions (e.g., in this study) where regular meteorological observations are rare. Shipborne GNSS PWV retrieval in real time is feasible and could provide additional information for weather predictions. Moreover, shipborne GNSS PWV retrieval provides a potential method for satellite altimetry calibration, the major technique measuring sea surface height for sea level monitoring. Key Points: Shipborne GNSS PWV retrieval is demonstrated with an accuracy of 1 mm, and an agreement of 1.7 mm with satellite altimetry PWVThe multi‐GNSS solution shows an RMS improvement of ~10% compared to the GPS solution in oceanwide PWV retrieval using kinematic PPP methodShipborne GNSS PWV retrieval could expand GNSS meteorology to ocean and improve NWM, satellite altimetry, and weather forecasting [ABSTRACT FROM AUTHOR]

This paper explores the changing infrastructure around weather and sea ice information provisioning for Arctic marine areas. Traditionally, the most important providers of operational information on sea ice and weather conditions are the national sea ice and meteorological services. More recently, the community of Arctic information providers has become more heterogeneous with the establishment of numerous collaborative platforms. Three case studies will enhance our understanding of current developments (BarentsWatch, Polar View and Arctic Web). We analyze their organization and funding structures, the types of services they develop, and their target groups. Based upon these cases, we discuss the information infrastructure's dynamics and underlying drivers of change. Apart from an expected need for customized services due to changing Arctic activity patterns, new initiatives arise due to a combination of (1) progress in information and communication technology, (2) a need to enhance interoperability of data systems, (3) and a desire to improve customized data conveyance from provider to user. The paper concludes with a discussion of the implications of the changing Arctic information infrastructure and defines directions for further research. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

Snow is a crucial component of the Arctic sea ice system. Its thickness and thermal properties control heat conduction and radiative fluxes across the ocean, ice, and atmosphere interfaces. Hence, observations of the evolution of snow depth, density, thermal conductivity, and stratigraphy are crucial for the development of detailed snow numerical models predicting energy transfer through the snow pack. Snow depth is also a major uncertainty in predicting ice thickness using remote sensing algorithms. Here we examine the winter spatial and temporal evolution of snow physical properties on first-year (FYI) and second-year ice (SYI) in the Atlantic sector of the Arctic Ocean, during the Norwegian young sea ICE (N-ICE2015) expedition (January to March 2015). During N-ICE2015, the snow pack consisted of faceted grains (47%), depth hoar (28%), and wind slab (13%), indicating very different snow stratigraphy compared to what was observed in the Pacific sector of the Arctic Ocean during the SHEBA campaign (1997-1998). Average snow bulk density was 345 kg m−3 and it varied with ice type. Snow depth was 41 ± 19 cm in January and 56 ± 17 cm in February, which is significantly greater than earlier suggestions for this region. The snow water equivalent was 14.5 ± 5.3 cm over first-year ice and 19 ± 5.4 cm over second-year ice. [ABSTRACT FROM AUTHOR]

Snow is crucial over sea ice due to its conflicting role in reflecting the incoming solar energy and reducing the heat transfer so that its temporal and spatial variability are important to estimate. During the Norwegian Young Sea ICE (N-ICE2015) campaign, snow physical properties and variability were examined, and results from April until mid-June 2015 are presented here. Overall, the snow thickness was about 20 cm higher than the climatology for second-year ice, with an average of 55 ± 27 cm and 32 ± 20 cm on first-year ice. The average density was 350-400 kg m−3 in spring, with higher values in June due to melting. Due to flooding in March, larger variability in snow water equivalent was observed. However, the snow structure was quite homogeneous in spring due to warmer weather and lower amount of storms passing over the field camp. The snow was mostly consisted of wind slab, faceted, and depth hoar type crystals with occasional fresh snow. These observations highlight the more dynamic character of evolution of snow properties over sea ice compared to previous observations, due to more variable sea ice and weather conditions in this area. The snowpack was isothermal as early as 10 June with the first onset of melt clearly identified in early June. Based on our observations, we estimate than snow could be accurately represented by a three to four layers modeling approach, in order to better consider the high variability of snow thickness and density together with the rapid metamorphose of the snow in springtime. [ABSTRACT FROM AUTHOR]

Knowledge 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. [ABSTRACT FROM AUTHOR]

Research on young thin sea ice is essential to understand the changes in the Arctic. But it is also the most challenging to investigate, both in situ and from satellites. If satellite remote-sensing techniques are developing rapidly, fieldwork remains crucial for the mandatory validation of such data. In April 2016, an Arctic fieldwork campaign was conducted at Kongsfjorden, Svalbard. This campaign provided an opportunity to combine various techniques to record the fjord ice properties ranging from local field sampling to broader ground-based and satellite radar remote sensing of the fjord. Tracking the boat used to access the field sites with hand-held GPS devices offered a good opportunity to map fjord ice and assess the limits of radar identification of small icebergs and thin ice. During 1 week, 17 icebergs and the thin ice edges in two different locations were mapped. The GPS tracks present a good agreement with the Radarsat-2 data analysis for one of the two ice edges. The second ice edge track only partly corresponds to the radar scene. Ice movement, recorded by a ground-based radar, is likely to explain this result. Grounded icebergs could be identified in both Radarsat-2 and ground-based radar. [ABSTRACT FROM AUTHOR]

Albedo is a fundamental parameter in earth sciences, and many analyses utilize the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo (MCD43) algorithms. While derivative albedo products have been evaluated over Greenland, we present a novel, direct comparison with nadir surface reflectance collected from an unmanned aerial system (UAS). The UAS was flown from Summit, Greenland, on 210 km transects coincident with the MODIS sensor overpass on board the Aqua and Terra satellites on 5 and 6 August 2010. Clear-sky acquisitions were available from the overpasses within 2 h of the UAS flights. The UAS was equipped with upward- and downward-looking spectrometers (300-920 nm) with a spectral resolution of 10 nm, allowing for direct integration into the MODIS bands 1, 3, and 4. The data provide a unique opportunity to directly compare UAS nadir reflectance with the MODIS nadir BRDF-adjusted surface reflectance (NBAR) products. The data show UAS measurements are slightly higher than the MODIS NBARs for all bands but agree within their stated uncertainties. Differences in variability are observed as expected due to different footprints of the platforms. The UAS data demonstrate potentially large sub-pixel variability of MODIS reflectance products and the potential to explore this variability using the UAS as a platform. It is also found that, even at the low elevations flown typically by a UAS, reflectance measurements may be influenced by haze if present at and/or below the flight altitude of the UAS. This impact could explain some differences between data from the two platforms and should be considered in any use of airborne platforms. [ABSTRACT FROM AUTHOR]

In this paper we investigate the potential of melt pond fraction retrieval from X-band polarimetric synthetic aperture radar (SAR) on drifting first-year sea ice. Melt pond fractions retrieved from a helicopter-borne camera system were compared to polarimetric features extracted from four dual-polarimetric X-band SAR scenes, revealing significant relationships. The correlations were strongly dependent on wind speed and SAR incidence angle. Copolarisation ratio was found to be the most promising SAR feature for melt pond fraction estimation at intermediate wind speeds (6:2ms-1), with a Spearman's correlation coefficient of 0:46. At low wind speeds (0:6ms-1), this relation disappeared due to low backscatter from the melt ponds, and backscatter VV-polarisation intensity had the strongest relationship to melt pond fraction with a correlation coefficient of -0:53. To further investigate these relations, regression fits were made both for the intermediate (Rfit2 D 0:21) and low (Rfit2 D 0:26) wind case, and the fits were tested on the satellite scenes in the study. The regression fits gave good estimates of mean melt pond fraction for the full satellite scenes, with less than 4% from a similar statistics derived from analysis of low-altitude imagery captured during helicopter ice-survey flights in the study area. A smoothing window of 51×51 pixels gave the best reproduction of the width of the melt pond fraction distribution. A considerable part of the backscatter signal was below the noise floor at SAR incidence angles above ~40°, restricting the information gain from polarimetric features above this threshold. Compared to previous studies in C-band, limitations concerning wind speed and noise floor set stricter constraints on melt pond fraction retrieval in X-band. Despite this, our findings suggest new possibilities in melt pond fraction estimation from X-band SAR, opening for expanded monitoring of melt ponds during melt season in the future. [ABSTRACT FROM AUTHOR]

Horizontal and vertical variability of first-year drift-ice bacterial communities was investigated along a North-South transect in the Fram Strait during the winter/spring transition. Two different developmental stages were captured along the transect based on the prevailing environmental conditions and the differences in bacterial community composition. The differences in the bacterial communities were likely driven by the changes in sea-ice algal biomass (2.6-5.6 fold differences in chl-a concentrations). Copiotrophic genera common in late spring/summer sea ice, such as Polaribacter, Octadecabacter and Glaciecola, dominated the bacterial communities, supporting the conclusion that the increase in the sea-ice algal biomass was possibly reflected in the sea-ice bacterial communities. Of the dominating bacterial genera, Polaribacter seemed to benefit the most from the increase in algal biomass, since they covered approximately 39% of the total community at the southernmost stations with higher (>6 µg l-1) chl-a concentrations and only 9% at the northernmost station with lower chl-a concentrations (<6 µg l-1). The sea-ice bacterial communities also varied between the ice horizons at all three stations and thus we recommend that for future studies multiple ice horizons be sampled to cover the variability in sea-ice bacterial communities in spring. [ABSTRACT FROM AUTHOR]

In this study, we investigate the influence of Arctic sea ice surface roughness on full polarimetric C-band SAR features in the late summer season. Surface roughness measured from a helicopter-borne laser altimeter is compared to 14 individual SAR features holding a documented theoretical or empirical relation to surface roughness. Three C-band Radarsat-2 SAR scenes, covering a study area with both first-year ice and old ice surfaces with a variety of roughnesses are included in the study. Nine of the individual investigated SAR features were, in at least one of the scenes, correlated to laser altimeter measured root-mean-square height with a Spearman’s correlation coefficient better than $\pm 0.6$. The strength of the correlation varied from scene to scene, and the between-scene variation was explained by differences in incidence angle, changes in the meteorological conditions, and changes in the microscale surface roughness of both the sea ice and the melt pond surfaces. We highlight that knowledge of temperature and weather history could improve the quality of surface roughness interpretation in SAR scenes in the late summer. The findings are important for improved interpretation of satellite SAR sea ice imagery, relevant to, e.g., shipping and detection of sea ice changes in the context of climate research and monitoring. [ABSTRACT FROM PUBLISHER]

We present sea-ice surface roughness estimates, i.e. the standard deviation of relative surface elevation, in the Arctic regions of Fram Strait and the Nansen Basin north of Svalbard acquired by an airborne laser scanner and a single-beam laser altimeter in 2010. We compare the scanner to the altimeter and compare the differences between the two survey regions. We estimate and correct sensor roll from the scanner data using the hyperbolic response of the scanner over a flat surface. Measurement surveys had to be longer than 5 km north of Svalbard and longer than 15 km in Fram Strait before the statistical distribution in surface roughness from the scanner and altimeter became similar. The shape of the surface roughness probability distributions agrees with those of airborne electromagnetic induction measurements of ice thickness. The ice in Fram Strait had a greater mean surface roughness, 0.16 m vs 0.09 m, and a wider distribution in roughness values than the ice in the Nansen Basin. An increase in surface roughness with increasing ice thickness was observed over fast ice found in Fram Strait near the coast of Greenland but not for the drift ice. [ABSTRACT FROM AUTHOR]

Snow ice and superimposed ice formation on landfast sea ice in a Svalbard fjord, Kongsfjorden, was investigated with a high-resolution thermodynamic snow and sea-ice model, applying meteorological weather station data as external forcing. The model shows that sea-ice formation occurs both at the ice bottom and at the snow/ice interface. Modelling results indicated that the total snow ice and superimposed ice, which formed at the snow/ice interface, was about 14 cm during the simulation period, accounting for about 15% of the total ice mass and 35% of the total ice growth. Introducing a time-dependent snow density improved the modelled results, and a time-dependent oceanic heat flux parameterization yielded reasonable ice growth at the ice bottom. Model results suggest that weather conditions, in particular air temperature and precipitation, as well as snow thermal properties and surface albedo are the most critical factors for the development of snow ice and superimposed ice in Kongsfjorden. While both warming air and higher precipitation led to increased snow ice and superimposed ice forming in Kongsfjorden in the model runs, the processes were more sensitive to precipitation than to air temperature. [ABSTRACT FROM AUTHOR]

Variability of sea-ice and snow conditions on the scale of a few hundred meters is examined using in situ measurements collected in first-year pack ice in the European Arctic north of Svalbard. Snow thickness and surface elevation measurements were performed in the standard manner using a snow stick and a rotating laser. Altogether, 4109m of measurement lines were surveyed. The snow loading was large, and in many locations the ice freeboard was negative (38.8% of snowline measurements), although the modal ice and snow thickness was 1.8m. The mean of all the snow thickness measurements was 36 cm, with a standard deviation of 26 cm. The mean freeboard was only 3 cm, with a standard deviation of 23 cm. There were noticeable differences in snow thickness among the measurement sites. Over the undeformed ice areas, the mean snow thickness and freeboard were 23 and 2.4 cm, respectively. Over the ridged ice areas, the mean freeboard was only -0.3 cm due to snow accumulation on the sails of ridges (average thickness 54 cm). These findings imply that retrieval algorithms for converting freeboard to ice thickness should take account of spatial variability of snow cover. [ABSTRACT FROM AUTHOR]

The large-scale thickness distribution of sea ice was measured during several campaigns in the European Arctic north of Svalbard from 2007 using an airborne electromagnetic induction device. In August 2010 and April-May 2011, this was complemented by extensive on-ice work including measurements of snow thickness and freeboard. Ice thicknesses show a clear difference between the seasons, with thicker ice during spring than in summer. In spring 2011, negative freeboard and flooding were observed as a result of the extensive snow cover. We find that the characteristics of the first-year sea ice allow combining observations from different years. The ice thickness in the marginal ice zone increases with increasing latitude and increasing distance to the ice edge; however, in the inner ice pack from ~100 km from the ice edge the thickness remains almost constant. Modal ice thickness in spring reaches 2.4m whereas in summer it is 1.0-1.4m. Our study provides new insight into ice thickness distributions of a typical ice cover consisting of mainly first- and second-year ice, which may become the dominant ice type in the Arctic in the future. [ABSTRACT FROM AUTHOR]

Rijpfjorden (80° N, 22° E) is a high-Arctic fjord on Nordaustlandet in the Svalbard archipelago. To monitor the thermodynamic change of sea ice in spring, an ice mass-balance buoy (IMB) was deployed for 2.5 months (10 April-26 June 2011), with accompanying in situ measurements, sea-ice sampling on three occasions and ice-core analysis. Uncertainties and sources of error in in situ measurements and IMB data are discussed. The in situ measurements, ice-core analysis and IMB data together depict the development of snow and ice in spring. Snow and ice thickness exhibited large spatial and temporal variability. After relatively stable conditions with only little change in ice thickness and accumulation of snow, a layer of superimposed ice ~0.06m thick formed at the snow–ice interface due to refreezing of snow meltwater in late spring. Ice thickness (except for growth of superimposed ice) did not change significantly based on in situ observations. In contrast, the under-ice sonar data from the IMB show reflections from a layer deeper than the underside of the ice during the melting phase. This can be explained as a reflection of the sonar pulses from an interface between a freshwater layer under the ice and more saline water below, or as a false-bottom formation. [ABSTRACT FROM AUTHOR]

Initial results from a field experiment on fast ice in Kongsfjorden, Svalbard, in March 2002 are presented. We measured surface reflectance and under-ice irradiance using an advanced, portable spectroradiometer sensitive in the visible and near-infrared parts of the electromagnetic spectrum, i.e. 350-1100 nm. Under-ice irradiance (UV-A, UV-B and photosynthetically active radiation [PAR]) was measured down to depths of 7.5 111 by vertical profiling using a six-channel radiometer. We also present model results of wavelength-dependent transmittance of radiation through a combined snow and sea ice layer for various thicknesses of snow. Model results show that the snow and sea ice is more transparent for solar radiation in the PAR region (400–700 nm) than at shorter and longer wavelengths. This is confirmed by the field measurements. Even very thin snow layers on top of the sea ice efficiently prevent solar radiation from penetrating the snow sea ice system. For example, a 5 cm thick snow layer reduces under-ice irradiance in the PAR region with a lector of about 10. Measurements of under-ice UV irradiance show that both UV-A and UV-B irradiance is reduced with a lector of more than 10 at depths of 7.5 m below the ice compared to at the ice sea water interlace. [ABSTRACT FROM AUTHOR]

This article details the results of an investigation into the application of geostatistical data analysis to two environmental radiometric time series. The data series employed consist of 99Tc values for seaweed (Fucus vesiculosus) and seawater samples taken as part of a marine monitoring program conducted on the coast of northern Norway by the Norwegian Radiation Protection Authority. Geostatistical methods were selected in order to provide information on values of the variables at unsampled times and to investigate the temporal correlation exhibited by the data sets. This information is of use in the optimisation of future sampling schemes and for providing information on the temporal behaviour of the variables in question that may not be obtained during a cursory analysis. The results indicate a high degree of temporal correlation within the data sets, the correlation for the seawater and seaweed data being modelled with an exponential and linear function, respectively. The semi-variogram for the seawater data indicates a temporal range of correlation of approximately 395 days with no apparent random component to the overall variance structure and was described best by an exponential function. The temporal structure of the seaweed data was best modelled by a linear function with a small nugget component. Evidence of drift was present in both semi-variograms. Interpolation of the data sets using the fitted models and a simple kriging procedure were compared, using a cross-validation procedure, with simple linear interpolation. Results of this exercise indicate that, for the seawater data, the kriging procedure outperformed the simple interpolation with respect to error distribution and correlation of estimates with actual values. Using the unbounded linear model with the seaweed data produced estimates that were only marginally better than those produced by the simple interpolation. [ABSTRACT FROM AUTHOR]

A ground truth study was performed on first year fast ice in Kongsfjorden, Svalbard, during spring 1997 and 1998. The survey included sea ice thickness monitoring as well as observation of surface albedo, attenuation of optical radiation in the ice, physical properties and texture of snow and sea ice. The average total sea ice thickness in May was about 0.9 m, including a 0.2 m thick snow layer on top. Within a few weeks in both years, the snow melted almost completely, whereas the ice thickness decreased by not more than 0.05 m. During spring, the lower part of the snow refroze into a solid layer. The sea ice became more porous. Temperatures in the sea ice increased and the measurable salinity of the sea ice decreased with time. Due to snow cover thinning and snow grain growth, maximum surface albedo decreased from 0.96 to 0.74. Texture analysis on cores showed columnar ice with large crystals (max. crystal lenght > 0.1 m) below a 0.11 m thick mixed surface layer of granular ice with smaller crystals. In both years, we observed sea ice algae at the bottom part of the ice. This layer has a significant effect on the radiation transmissivity. [ABSTRACT FROM AUTHOR]

We describe an improved nondestructive technique for density measurement based on gamma-ray absorption that permits construction of high-resolution density profiles of marine sediment cores. The system is capable of resolving vertical density variations with a spatial resolution of 4 mm and absolute accuracy of ± 1%. Comparison with conventional density determination on samples confirms the absolute accuracy. In addition to standard vertical profiling, a core rotation option is included to measure density as a function of rotation angle. This allows the quantification of the variability of density within a layer and detection of inhomogenities like icerafted debris or biogenic structures. [ABSTRACT FROM AUTHOR]