Estimating precipitation to determine accumulation is challenging. We present a method that combines melt modelling and snowline tracking to determine winter glacier snow accumulation along snowlines. The method assumes that the net accumulation is zero on the transient snowlines and the maximum winter accumulation at the snowline can be calculated backwards with a temperature-index melt model. To verify the method, the accumulation model is applied for the year 2004 on Storglaciären, Sweden, for which extensive meteorological and mass-balance data are available. The measured mean snowline accumulation is 0.94 ± 0.10mw.e. for 2004. Modelled accumulation, using backward melt modelling, at the same snowlines is 0.82 ± 0.25 m w.e. The accumulation model is also compared with an often used linear regression accumulation model which yields a mean snowline accumulation of 1.02 ± 0.38 m w.e. The reduction in standard error from 0.38 m w.e. to 0.25 m w.e. shows that the backward melt modelling applied at snowlines can provide a better spatial representation of the accumulation pattern than the regression model. Importantly, the applied method requires no field measurements of accumulation during the winter and snowlines can be readily traced in remotely sensed images.

The Ocean and Sea Ice Satellite Application Facility (OSISAF) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) distributes satellite observations operationally. In this paper, we describe the development of a combined optimal interpolation and nudging (COIN) scheme in the Norwegian Meteorological Institute that assimilates OSISAF sea-ice concentration (SIC) into a coupled sea-ice–ocean Regional Ocean Modeling System (ROMS). The scheme modifies the modeled SIC at every time-step, based on the difference between observation and forecast as well as on the ratio of observation error to model error. Snow and sea-ice thickness are diagnostically modified to match the ice concentration field. Hindcast experiments of Arctic sea ice are performed for the whole of 2009. The results are compared with OSISAF and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) SIC, showing a significant improvement in the analyzed sea-ice edge and summer SIC.

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 2.4 m whereas in summer it is 1.0–1.4 m. 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.

The Makunosawa valley, Myoko, Japan, experiences frequent avalanches and is therefore ideally suited to study how meteorological elements influence avalanche activity. Since 2000, five large-scale snow avalanches with running distances >2000 m have been observed and some characteristics of these avalanches have been obtained. However, the characteristics of the snowpack in the starting zones could not be observed because they are too difficult to approach and no snow-pit observations have been carried out. We simulated the variations in the snowpack in the starting zone using the numerical snowpack model SNOWPACK with local meteorological data. The results indicate a layer of faceted crystals with low shear strength followed by rapid loading from snowfall was the cause of three avalanches in February. Conversely, no layer of faceted crystals was shown by the model before a January avalanche and we assume the sliding surface of the avalanche to be precipitation particles. The only wet-snow avalanche is attributed to a decrease in shear strength due to infiltration of meltwater and an increase in liquid water content in the boundary of two layers of different grain sizes.

Temporal and spatial variations of the seasonal snow cover at 40 sites in Nordland county, Norway, since the last decade of the 19th century are examined. Nordland lies across the Arctic Circle. Annual maximum snow depths there have varied, reflecting the interaction of synoptic conditions, temperature and terrain. North/south and coastal/inland differences are evident, but common temporal trends are identified. Maximum snow depths are strongly related to the winter North Atlantic Oscillation index. Early in the 20th century, the index was positive and the associated stormy conditions resulted in a deep, prolonged snow cover. As the index declined in the 1920s, snow depths decreased sharply. Through much of the second half of the 20th century they increased as the index tended to become more positive. The start and duration of the period of continuous snow cover is influenced by the autumn NAO index. A decrease of duration around 1990 was particularly evident at low-lying stations and those in northern Nordland. The NAO has varied considerably over the past 120 years. Because of its influence, forecasting future trends of snow depth and snow-cover duration is not a simple task.

During the 19th Chinese National Antarctic Research Expedition from December 2002 to January 2003, 1085 icebergs were observed along the cruise track within the range 58–68° S in the Southern Ocean using the marine radar on the R/V Xuelong. These icebergs were located mainly in the Ross Sea, Weddell Sea and Prydz Bay with lengths ranging from 68 to 8169 m. Both power-law and Weibull functions are applied to the curve fitting of cumulative probability distribution of iceberg length in each region. The results reveal that the power-law function underestimates the measured data in the middle of the data, but overestimates them for both the smallest and largest iceberg sizes, whereas the Weibull function underestimates the measured data when iceberg length is large enough. To reduce the relative error increasing with iceberg length, the Weibull function is used only in fitting to iceberg lengths less than a threshold value of iceberg size (L t) and the power-law function is used in fitting to iceberg lengths >L t. The improved curve fits show a good correlation over the full range of the data. This clearly reveals that an upper limit of iceberg length exists in the good agreement between the Weibull function and the measured data, which is attributed to different thermodynamic effects on calving processes and subsequent modification of large and small icebergs. In addition, iceberg size in Prydz Bay increases and then decreases when approaching the Amery Ice Shelf as a result of bergy bits and growlers calved from large icebergs in front of the ice shelf.

The Finnish Meteorological Institute has installed image-capturing devices on some Baltic Sea coastal radars for operational sea-ice monitoring and ice product validation. These devices produce radar images, which are saved operationally at about every 2 min. These data can efficiently be utilized in automated tracking of ice motion over sequences of radar images. Reliable estimates of point-wise ice drift can be used as virtual drifter buoys to validate fine-scale ice models. For this purpose we have developed an algorithm, which first locates objects that can reliably be recognized from one radar image to another, and then tracks the motion of these objects until they are lost by the algorithm. The recognizable objects in the first image of an image sequence are located by requiring an object to include a textural content, i.e. the object does not solely consist of a uniform area, and detected edge corner points. The corner points are required to exclude straight linear edges. After locating a suitable number of traceable objects, the tracking is performed between each pair of successive images using a two-resolution phase-correlation algorithm. We have tested the tracking algorithm using image sequences of two coastal radars collected during the 2010/11 and 2011/12 winters.

We studied the variability of elemental carbon (EC) over 3 years (2009–11) in the winter snowpack of Storglaciären, Sweden. The goal of this study was to relate the seasonal variation in EC to specific snow accumulation events in order to improve understanding of how different atmospheric circulation patterns control the deposition of EC. Specifically, we related meteorological parameters (e.g. wind direction, precipitation) to snow physical properties, EC content, stable-isotope δ18O ratios and anion concentrations in the snowpack. The distribution of EC in the snowpack varied between years. Low EC contents corresponded to a predominance of weather systems originating in the northwest, i.e. North Atlantic. Analysis of single layers within the snowpacks showed that snow layers enriched in heavy isotopes coincided predominantly with low EC contents but high chloride and sulfate concentration. Based on this isotopic and geochemical evidence, snow deposited during these events had a strong oceanic, i.e. North Atlantic, imprint. In contrast, snow layers with high EC content coincided with snow layers depleted in heavy isotopes but high anion concentrations, indicating a more continental source of air masses and origin of EC from industrial emissions.

A C-band sea-ice radar (SIR) network system was operated to monitor the sea-ice conditions off the Okhotsk Sea coast of northern Hokkaido, Japan, from 1969 to 2004. The system was based on three radar stations, which were capable of continuously monitoring the sea surface as far as 60 km offshore along a 250 km long coastal section. In 2004 the SIR system was closed down and a sea surface monitoring programme was commenced using high-frequency (HF) radar; this system provides information on surface currents in open-water conditions, while areas with ‘no signal’ can be identified as sea ice. The present study compares HF radar data with SIR data to evaluate their feasibility for sea-ice remote sensing. The period of overlapping data was 1.5 months. The results show that HF radar information can be utilized for ice-edge mapping although it cannot fully compensate for the loss of the SIR system. In particular, HF radar does not provide ice concentration, ice roughness and geometrical structures or ice kinematics. The probability of ice-edge detection by HF radar was 0.9 and the correlation of the ice-edge distance between the radars was 0.7.

Large parts of the Arctic are covered by water bodies. Ice covers on lakes and rivers prohibit the exchange of heat and water vapor between the water body and the atmosphere. With melt onset, the ecosystem is subjected to changes, making it important to monitor the ice decay. As ground-based monitoring of these vast uninhabited areas is expensive and thus restricted to a few locations, remote-sensing techniques need to be applied. Here we evaluate the performance of the unsupervised k-means classification for dividing ice and water fractions on lakes and river channels from spaceborne radar data in comparison to threshold-based methods. The analysis is based on six TerraSAR-X and three RADARSAT-2 images, obtained during spring 2011 over the central Lena Delta in northern Siberia. The performance of the k-means classification is found to be similar to a fixed-threshold approach. As the k-means classification does not need prior statistical backscatter analyses to account for the radar configuration and ice conditions, it is easier to use than the threshold method. In addition, we found that the application of a low-pass filter prior to the classification of river channels and a closing filter on the classification results of lakes strongly improves the overall classification results.

Sea-ice hazard causes serious harm to aquaculture, marine navigation, offshore oil production and other activities in the Bohai Sea, China. To study the spatial distribution characteristics of sea-ice-hazard risk in Bohai is therefore desirable. The thickness and area of sea ice in the Bohai Sea during the winters (December–March) of 1987–2011 were estimated using data from the NOAA (US National Oceanic and Atmospheric Administration) satellite. The sea-ice thickness was converted into a sea-ice-hazard index after defining this index, and the different sea-ice-hazard risk grades were classified. The occurrence probability of sea-ice hazard was also calculated using fuzzy risk theory, and the spatial distribution characteristics of sea-ice-hazard risk in the Bohai Sea were studied. The results show that the sea-ice-hazard risk for offshore aquaculture decreased as the offshore distance increased. All the oilfields in Liaodong Bay are influenced by sea-ice hazard, two of the fields in Bohai Bay are slightly affected and the remaining fields are not influenced. The risk for marine navigation is related to the location of the port and the distance from the port. The risk in the port area is the highest; it is reduced by more than 30% at distances 10 km away from the port.

Triglav glacier is situated on the northeast side of the highest Slovenian mountain peak, Triglav; it is a glacier remnant of the Little Ice Age. Next to Triglav glacier is the Kredarica mountain hut with a meteorological station. At 2514 ma.s.l., it is the highSest meteorological station in Slovenia, and has been in continuous operation since 1954. In this paper, the acquisition of three-dimensional data from archived, non-metric, panoramic, Horizont images is presented. The annual variations of Triglav glacier’s area are given for the period 1976–2010, together with monthly snow variations for the years 1977 and 1998. Additionally, theoretical and empirical volumes and an empirical thickness reduction are computed. The changes to Triglav glacier are compared with the summarized meteorological data from the Kredarica meteorological station. In 1976 Triglav glacier covered an area of 15 ha; by 1992 this had shrunk to 4.3 ha, and it reached its minimum of 0.6 ha in 2003, as measured from Horizont images. Since then the glacier has been mainly conserved by the snow cover from previous winters.

We have studied the accuracy of ice thickness (hi) retrieval based on night-time MODIS (Moderate Resolution Imaging Spectroradiometer) ice surface temperature (Ts) images and HIRLAM (High Resolution Limited Area Model) weather forcing data from the Arctic. The study area is the Kara Sea and eastern part of the Barents Sea, and the study period spans November-April 2008–11 with 199 hi charts. For cloud masking of the MODIS data we had to use manual methods in order to improve detection of thin clouds and ice fog. The accuracy analysis of the retrieved hi was conducted with different methods, taking into account the inaccuracy of the HIRLAM weather forcing data. Maximum reliable hi under different air-temperature and wind-speed ranges was 35–50 cm under typical weather conditions (air temperature <–20cC, wind speed <5ms–1) present in the MODIS data. The accuracy is best for the 15–30 cm thickness range, ∼38%. The largest hi uncertainty comes from air temperature data. Our ice-thickness limits are more conservative than those in previous studies where numerical weather prediction model data were not used in the hi retrieval. Our study gives new detailed insight into the capability of Ts-based hi retrieval in the Arctic marginal seas during freeze-up and wintertime, and should also benefit work where MODIS hi charts are used.

To investigate the spatio-temporal characteristics of sea-ice resource, we used sea-ice volume to measure the amount of sea-ice resource in the Bohai Sea, China. The sea-ice area was extracted from Advanced Very High Resolution Radiometer (AVHRR) remote-sensing images using the zonal threshold method. The sea-ice thickness was estimated using a sea-ice model based on shortwave radiation theory and field measurements. The spatio-temporal characteristics of sea-ice volume were then analysed using GIS technology. The results indicate that the Bohai Sea experienced two sea-ice volume peaks in winter 2009/10. The largest sea-ice volume was in Liaodong Bay (∼80.26% of the entire sea-ice volume of the Bohai Sea). Bohai Bay had the second largest ice volume, and Laizhou Bay the smallest. The relationship between sea-ice volume and distance from shore is essentially exponential. The proportion of total sea-ice volume that is 0–10 km from shore is ∼42.43%, whereas the proportion that is 100–110 km from shore is only 0.002%.

Snow and ice thickness in the coastal Kara Sea, Russian Arctic, were investigated by applying the thermodynamic sea-ice model HIGHTSI. The external forcing was based on two numerical weather prediction (NWP) models: the High Resolution Limited Area Model (HIRLAM) and the European Centre for Medium-Range Weather Forecasts (ECMWF) model. A number of model experiments were carried out applying different snow parameterization schemes. The modelled ice thickness was compared with in situ measurements and the modelled snow thickness was compared with the NASA Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) snow thickness. The HIRLAM and ECMWF model results agreed with each other on air temperature and wind. The NWP model precipitation forecasts caught up the synoptic-scale snowfall events, but the magnitude was liable to errors. The ice growth was modelled reasonably well applying HIGHTSI either with a simple parameterization for snow thickness or with the HIRLAM or ECMWF model precipitation as input. For the latter, however, an adjustment of snow accumulation in early winter was necessary to avoid excessive accumulation and consequent underestimation of ice thickness. Applying effective snow heat conductivity improved the modelled ice thickness. The HIGHTSI-modelled snow thickness had a seasonal evolution similar to that of the AMSR-E snow thickness. New field data are urgently needed to validate NWP and ice models and remote-sensing products for snow and sea ice in the Kara Sea.

In this paper, a molecular-dynamics sea-ice model is used to study contact and force networks in fragmented sea ice, composed of separate floes with power-law size distribution. The momentum equations for individual floes, taking into account floe/floe collisions (with Hertzian contact mechanics), are formulated in a way suitable for a computationally efficient numerical algorithm, allowing simulation of systems of thousands of floes. The simulations are performed for a number of scenarios: pure convergence without wind, through a jamming phase transition; constant wind at a constant ice concentration; and an idealized marginal ice zone. An analysis of the statistical properties of the contact and force networks reveals a highly localized, intermittent character of internal stress in the ice, as well as the role of the size-dependent response of floes to the forcing in formation of spatial patterns of internal stress at lower ice concentrations. The results provide a valuable starting point for formulating improved rheology models for fragmented sea ice.

Solar radiation penetrating the ice is one of the most important factors that determine the functioning of lake ecosystem in late winter. Parameterization of the attenuation of solar radiation in the snow-ice sheet is an essential tool in the study of the light regime of ice-covered lakes. The optical properties of the snow-ice sheet in Vendyurskoe lake, northwestern Russia, are investigated on the basis of long-term field observations (1995–2012). The four-layer approach (snow, white ice, slush and congelation ice) is used to study the attenuation of the downwelling planar irradiance in the snow-ice sheet. The bulk attenuation coefficients for four layers (18.8 m–1 for snow, 6 m−1 for white ice, 3.5 m−1 for slush and 2.1 m−1 for congelation ice) are calculated by the quasi-Newton method. A comparison of observed and calculated values of the irradiance beneath the ice shows that the determined coefficients adequately describe the attenuation of the downwelling irradiance by snow-ice cover.

We identified ikaite crystals (CaCO3·6H2O) and examined their shape and size distribution in first-year Arctic pack ice, overlying snow and slush layers during the spring melt onset north of Svalbard. Additional measurements of total alkalinity (TA) were made for melted snow and sea-ice samples. Ikaite crystals were mainly found in the bottom of the snowpack, in slush and the surface layers of the sea ice where the temperature was generally lower and salinity higher than in the ice below. Image analysis showed that ikaite crystals were characterized by a roughly elliptical shape and a maximum caliper diameter of 201.0±115.9 μm (n = 918). Since the ice-melting season had already started, ikaite crystals may already have begun to dissolve, which might explain the lack of a relationship between ikaite crystal size and sea-ice parameters (temperature, salinity, and thickness of snow and ice). Comparisons of salinity and TA profiles for melted ice samples suggest that the precipitation/dissolution of ikaite crystals occurred at the top of the sea ice and the bottom of the snowpack during ice formation/melting processes.

Surface elevation data for sea ice in the northwesternty - Weddell Sea, Antarctica, collected by a helicopter-borne laser altimeter during the Winter Weddell Outflow Study 2006, were used to estimate the form drag on pressure ridges and its contribution to the total wind drag, and the air-ice drag coefficient at a reference height of 10 m under neutral stability conditions (C dn(10)). This was achieved by partitioning the total wind drag into two components: form drag on pressure ridges and skin drag over rough sea-ice surfaces. The results reveal that for the compacted ice field, the contribution of form drag on pressure ridges to the total wind drag increases with increasing ridging intensity Ri (where Ri is the ratio of mean ridge height to spacing), while the contribution decreases with increasing roughness length. There is also an increasing trend in the air-ice drag coefficient C dn(10) as ridging intensity R i increases. However, as roughness length increases, C dn(10) increases at lower ridging intensities (Ri < 0.023) but decreases at lower ridging intensities (0.023 < Ri < 0.05). These opposing trends are mainly caused by the dominance of the form drag on pressure ridges and skin drag over rough ice surfaces. Generally, the form drag becomes dominant only when the ridging intensity is sufficiently large, while the skin drag is the dominant component at relatively larger ridging intensities. These results imply that a large value of C dn(10) is caused not only by the form drag on pressure ridges, but also by the skin drag over rough ice surfaces. Additionally, the estimated drag coefficients are consistent with reported measurements in the northwestern Weddell Sea, further demonstrating the feasibility of the drag partition model.