Average Ice Thickness Research Articles

A method for measuring ice thickness of wind turbine blades based on edge detection

In recent years, with the successive development of mountain wind power resources in the high humidity regions, the problem of ice covering on wind turbine blades has become increasingly prominent. Wind turbine blade icing will affect blade aerodynamic performance and reduce power generation. In this paper, a method for measuring the ice thickness of wind turbine blades based on edge detection was proposed. As the icing images of blades have characteristics like low contrast, unclearness and blurred edges, the images were preprocessed by methods like defogging, gray-scale transformation, histogram correction, Gaussian filtering, and Laplace edge enhancement. Aiming at the characteristics of wind turbine icing images with many noises and many small edges, a multiscale wavelet edge detection algorithm was used to detect the blade icing images. Based on the pixel coordinates of the ice edge and the edge of the blade, through the pre-calibration, a method for calculating the ice thickness of the leading edge of the blade based on the pixel coordinate difference /real length ratio was proposed. Multiple measurement tests were performed in the natural icing environment. The average ice thickness measurement error value of short distance (0.5 m)/long distance (35 m) is 0.31 mm/8.9 mm, and the average ice thickness measurement error rate is 2.62% /6.0%.

The seasonal cycle and break-up of landfast sea ice along the northwest coast of Kotelny Island, East Siberian Sea

AbstractArctic landfast sea ice (LFSI) represents an important quasi-stationary coastal zone. Its evolution is determined by the regional climate and bathymetry. This study investigated the seasonal cycle and interannual variations of LFSI along the northwest coast of Kotelny Island. Initial freezing, rapid ice formation, stable and decay stages were identified in the seasonal cycle based on application of the visual inspection approach (VIA) to MODIS/Envisat imagery and results from a thermodynamic snow/ice model. The modeled annual maximum ice thickness in 1995–2014 was 2.02 ± 0.12 m showing a trend of −0.13 m decade−1. Shortened ice season length (−22 d decade−1) from model results associated with substantial spring (2.3°C decade−1) and fall (1.9°C decade−1) warming. LFSI break-up resulted from combined fracturing and melting, and the local spatiotemporal patterns of break-up were associated with the irregular bathymetry. Melting dominated the LFSI break-up in the nearshore sheltered area, and the ice thickness decreased to an average of 0.50 m before the LFSI disappeared. For the LFSI adjacent to drift ice, fracturing was the dominant process and the average ice thickness was 1.56 m at the occurrence of the fracturing. The LFSI stages detected by VIA were supported by the model results.

High-resolution monitoring of debris-covered glacier mass budget and flow velocity using repeated UAV photogrammetry in Iran

Iran's glaciers are commonly debris-covered. Due to climate changes, the frequency of glacial hazards such as glacial lake outbursts floods is increasing, and consequently, the mass of Iran's glaciers is decreasing. Fieldwork in high-altitude mountains is difficult, thus, the dynamics of debris–covered glaciers and their associated driving factors are poorly studied. In this study, changes in the elevation and the surface flow speed of the largest and most dynamic debris-covered glacier in Iran (Alamkouh glacier) are evaluated during 2018 to 2020 for the first time. For this purpose, images from a high-resolution unmanned aerial vehicle (UAV) are used. Additionally, the spatial distribution of glacier ice thickness is estimated based on the principles of ice-flow and glacier surface velocity data. The distribution of ice thickness is evaluated with in-situ Ground Penetration Radar (GPR) data. The acquired high-resolution images from UAV are processed into a digital elevation model (with a spatial resolution of about 15 cm) and orthoimages (with a spatial resolution of about 8 cm), and glacier ice thickness change and surface flow velocity are derived. In order to estimate glacier surface velocity, a frequency cross-correlation model was applied using the COSI-Corr module. Our results show that the mean glacier ice thinning during the study period 2018–2020 is about −0.23 ± 0.03 m yr−1 and it reaches about −5 ± 0.65 m yr−1 at the terminus and accumulation areas. The observed variations in ice thinning are best explained by the existence of debris cover (and their corresponding insulating effects), the existence of ice cliffs, and their associated supraglacial lakes. We found that ice cliffs and supraglacial lakes show mass losses that can be an order of magnitude higher than average. Moreover, the mean surface velocity of Alamkouh glacier is about 1.1 ± 0.06 m yr−1 from 2018 to 2020 with considerable spatial variation in surface velocities. The maximum surface velocity (about 4.5 ± 0.27 m yr−1) belongs to its upper regions, and lower and marginal areas are nearly stagnant. The slow movement of the glacier, along with a continuous increase in debris and ice thinning, provides a suitable condition for supraglacial pond development, which decreases glacier mass. Total volume of glacier was estimated to be ~102 × 106 m3 in 2020, corresponding to an average ice thickness of ~31.3 ± 7.5 m. Moreover, the average ice thinning rate is 0.66% yr−1 in 2018 to 2020. According to this reduction rate, it is expected that more than 51.7% of the glacier will be lost by the end of the 21st century.

Interannual variability of ice volume in the sea of Okhotsk during the maximum development of ice extent for 2000–2020

Based on the interpretation and analysis of data obtained from passive and active microwave spectroradiometers installed on artificial Earth satellites, the boundaries of the ice extent zones in the Sea of Okhotsk with different age characteristics for the period from 2000 to 2020 have been defined and discretized into monthly components. Weighted average ice thickness in the selected zones has been calculated for three dominant age groups of ice according to World Meteorological Agency Nomenclature without adjustment for ice deformation. Analysis of the estimated characteristics has allowed us to conclude that in the XXI century there was a decrease in the volume of ice in the Sea of Okhotsk by 162 cub.km (or 51.9%). Ice volume decreased at average speed of 7.7 cub.km (or 24.7%) per decade, while ice extent decreased by 11.2% per decade (or 23.6%), and weighted average ice thickness – by 14.1% per decade (or 29.6%). For the 2000 to 2020 research period, changes in the volume of ice have been due to decrease in its thickness by ~ 56% and ice cover by ~ 44%. It has been established that the nature of the development of the ice regime parameters within the boundaries of the regions of the first hierarchical level varies significantly.

Changes in the Thickness of Ice Cover on Water Bodies Subject to Human Pressure (Silesian Upland, Southern Poland)

The paper discusses the reasons behind the variation in the thickness of ice on 39 anthropogenic water bodies located in the Silesian Upland (southern Poland). The studies were conducted over the course of three consecutive winter seasons. The measurements and observations were scheduled every 2 days during the freezing and ablation of the ice, and every 4 days when ice cover was present. Each time the thickness of the ice cover and the snow layer covering it were measured. The results show that the 35 water bodies studied are characterized by a similar—quasi-natural—ice regime, in which ice thickness variation depends mostly on the air temperature and the thickness of the snow layer covering the ice. The ice thickness on those water bodies does not significantly differ from that observed on lakes located in northern Poland, measuring on average from circa 4 to 21 cm, and with maximum thicknesses ranging from circa 14 to 40 cm, depending on the season. Four water bodies are characterized by different ice conditions; in their case the average and maximum ice thickness was significantly lower. In the Niezdara N water body this was caused by the inflow of warmer potamic water (quasi-natural regime), whereas in Pod Borem, Sośnicka, and Somerek it was caused by discharges of warm mine water (anthropogenic regime).

How the growth of ice depends on the fluid dynamics underneath

Convective flows coupled with solidification or melting in water bodies play a major role in shaping geophysical landscapes. Particularly in relation to the global climate warming scenario, it is essential to be able to accurately quantify how water-body environments dynamically interplay with ice formation or melting process. Previous studies have revealed the complex nature of the icing process, but have often ignored one of the most remarkable particularities of water, its density anomaly, and the induced stratification layers interacting and coupling in a complex way in the presence of turbulence. By combining experiments, numerical simulations, and theoretical modeling, we investigate solidification of freshwater, properly considering phase transition, water density anomaly, and real physical properties of ice and water phases, which we show to be essential for correctly predicting the different qualitative and quantitative behaviors. We identify, with increasing thermal driving, four distinct flow-dynamics regimes, where different levels of coupling among ice front and stably and unstably stratified water layers occur. Despite the complex interaction between the ice front and fluid motions, remarkably, the average ice thickness and growth rate can be well captured with the theoretical model. It is revealed that the thermal driving has major effects on the temporal evolution of the global icing process, which can vary from a few days to a few hours in the current parameter regime. Our model can be applied to general situations where the icing dynamics occur under different thermal and geometrical conditions.

Arctic lakes thickness measurement in the Lena River delta based on the Sentinel-1 observations

In this paper, we investigate the possibilities of ice thickness remote sensing on freshwater lakes based on Sentinel-1 observations. Fr. was selected as a test site. Kurungnakh Island, located in the Lena River delta, was selected as a test site, where 10 lakes with floating and grounded ice were selected. For the test lakes, the time series of backscatting coefficients measured by Sentinel-1 at horizontal-horizontal polarization (EW mode) and at an angle of 18-20 from September 2015 to June 2017 were analyzed. The average lakes ice thickness was estimated based on the Lebedev’s model and air temperature according to the European Center for Medium-Range Weather Forecasts (ECMWF ERA5). It is shown that, the dependence between backscattering coefficient and ice thickness (120-140 cm) can be described a linear function (with a standard deviation of 13.5-25.3 cm and a determination coefficient of 0.70-0.79). The preliminary studies shows that the Sentinel-1 radar data is promising for remote sensing of ice thickness on freshwater arctic lakes.

Spatiotemporal variation of ice thickness of Lake Qinghai derived from field measurements and model simulation

湖冰厚度是湖泊在封冻期的重要物理参数，明晰其时空变化特征对于认识气候变暖背景下的湖冰响应规律具有重要的理论价值和现实意义.基于ERA5 Climate Reanalysis气温数据集、MODIS MOD09GQ数据产品和2019年湖冰钻孔测厚数据及雷达测厚数据，重建2000-2019年青海湖冰厚时间序列并分析其时空变化特征.结果表明：①2019年3月实测青海湖湖冰厚度平均增长速率为0.30 cm/d，高于2月份（0.12 cm/d）.基于度日法湖冰生长模型模拟的2018年11月-2019年3月青海湖冰厚平均增长速率为0.34 cm/d，与实际观测数据相比，模拟冰厚误差为±2 cm，但在河流入湖口处和湖区南侧误差较大，且冰厚模拟数值在3月中旬前高估而之后有所低估.②青海湖多年平均冰厚介于32~37 cm，其中2008-2016年湖冰厚度年际变化剧烈，呈现先增大再稳定后减小的趋势.冻结初期湖冰厚度增长迅速，12月和1月湖冰增长速率分别为0.45和0.41 cm/d，2月后冰厚增长速率放缓，2月和3月分别为0.29和0.14 cm/d.③2000-2019年冰厚整体呈现北厚南薄、东厚西薄的空间格局，多年冰厚变化幅度湖区西部较东部稳定，湖冰平均厚度与完全封冻时长及封冻期呈正相关.;Ice thickness is an important physical parameter of a lake in the freezing period. It is of great theoretical and practical significance to understand the spatiotemporal characteristics of lake ice, which helps study how lake ice responds to climate under the background of global warming. Based on the ERA5 Climate Reanalysis temperature dataset, MODIS MOD09GQ data product, and ice borehole and radar thickness measurements in 2019, the thickness of lake ice in Lake Qinghai between 2000 and 2019 was reconstructed and the spatial-temporal variation characteristic was analyzed. The results showed that the average growth rate of ice thickness in March (0.30 cm/d) was faster than that in February (0.12 cm/d) based on the field survey data. The average growth rate of ice thickness in Lake Qinghai from November 2018 to March 2019 was 0.34 cm/d simulated by the degree-day model, with the ice thickness error of ±2 cm compared with the actual observation data. However, the error was large at the entrance of the river and the south side of Lake Qinghai. Meanwhile, the simulation of ice thickness was overestimated before the mid-March but underestimated later. The annual average ice thickness of Lake Qinghai was 32-37 cm, in which, it fluctuated dramatically in 2008-2016, showing the tendency of thickening first, then stabilizing and finally thinning. At the beginning of lake freezing, the ice thickness increased rapidly with the growth rate of 0.45 cm/d in December and 0.41 cm/d in January. After February, the rate slowed down, and it was 0.29 cm/d in February and 0.14 cm/d in March. On the whole, the ice thickness of Lake Qinghai showed a spatial pattern of being thicker in the north and east, whereas being thinner in the south and west, years of spatial change were more stable in the west than in the east. The average thickness of lake ice was positively correlated with complete freezing duration and the freeze-up period.

Estimation of Ice Thickness and the Features of Subglacial Media Detected by Ground Penetrating Radar at the Baishui River Glacier No. 1 in Mt. Yulong, China

Using ground-penetrating radar (GPR), we measured and estimated the ice thickness of the Baishui River Glacier No. 1 of Yulong Snow Mountain. According to the position of the reflected media from the GPR image, combined with the radar waveform amplitude and polarity change information, the ice thickness and the changing medium position at the bottom of this temperate glacier were identified. Water paths were found in the measured ice, including ice caves and crevasses. A debris-rich ice layer was found at the bottom of the glacier, which produces strong abrasion and ploughing action at the bedrock surface. This results in the formation of different detrital layers stagnated at the ice-bedrock interface and numerous crevasses on the bedrock surface. Based on the obtained ice thickness and differential GPS data, combined with Landsat images, the kriging interpolation method was used to obtain grid data. The average ice thickness was 52.48 m and between 4740 and 4890 m above sea level, with a maximum depth of 92.83 m. The bedrock topography map of this area was drawn using digital elevation model from the Shuttle Radar Topography Mission. The central part of the glacier was characterized by small ice basins with distributed ice steps and ice ridges at the upper and lower parts.

Ice thickness distribution and volume estimation of Burqin Glacier No. 18 in the Chinese Altay Mountains

Information on the thickness distribution and volume of glacier ice is highly important for glaciological applications; however, detailed measurements of the ice thickness of many glaciers in the Chinese Altay Mountains remain lacking. Burqin Glacier No. 18 is a northeast-orientated cirque glacier located on the southern side of the Altay Mountains. This study used PulseEKKO® PRO 100A enhancement ground-penetrating radar (GPR) to survey the ice thickness and volume of Burqin Glacier No. 18 in summer 2018. Together with GPR surveying, spatial distributed profiles of the GPR measurements were concurrently surveyed using the real-time kinematic (RTK) global navigation satellite system (GNSS, Unistrong E650). Besides, we used QuickBird, WorldView-2, and Landsat TM to delineate accurate boundary of the glacier for undertaking estimation of glacier ice volume. GPR measurements revealed that the basal topography of profile B1–B2 was flat, the basal topography of profile C1–C2 presented a V-type form, and the basal topography of profile D1–D2 had a typical U-type topographic feature because the bedrock near the central elevation of the glacier was relatively flat. The longitudinal profile A1–A2 showed a ladder-like distribution. Glacier ice was thin at the terminus and its thickness increased gradually from the elevation of approximately 2620 m a.s.l. along the main axis of the glacier tongue with an average value of 80 (±1) m. The average ice thickness of the glacier was determined as 27 (±2) m and its total ice volume was estimated at 0.031 (±0.002) km3. Interpretation of remote sensing images indicated that during 1989–2016, the glacier area reduced from 1.30 to 1.17 km2 (reduction of 0.37%/a) and the glacier terminus retreated at the rate of 8.48 m/a. The mean ice thickness of Burqin Glacier No. 18 was less than that of the majority of other observed glaciers in China, especially those in the Qilian Mountains and Central Chinese Tianshan Mountains; this is probably attributable to differences in glacier type and climatic setting.

Comparison of direct measurements of sea ice thickness and snow height, CryoSat-2 observations and PIOMAS numerical estimates

The paper presents the results of comparison of contact measurements of ice thicknesses and snow heights performed at the points of the hydrological stations of the “Transarktika-2019” expedition in April 2019 north of Franz-Josef Land archipelago, with altimetry observations of the Cryosat-2 satellite and numerical estimates of the PIOMAS (Pan-Arctic numerical Ice and Ocean Modeling system and data Assimilation). A significantly better correspondence is predictably shown between the variability of the ice thickness directly measured and observed using the CryoSat-2 satellite than that for the numerical PIOMAS system estimates. A trial correction of the algorithm for calculating the ice thickness by replacing the climatic values of the ice density, snow density and height with data from direct measurements also predictably improves the quality of calculating the ice thickness from satellite observations. The mean / route mean square differences obtained for ice thicknesses (+44/+96 cm for uncorrected and +30/+95 cm for corrected CryoSat-2 satellite, –14/+81 cm for PIOMAS system) and snow height (–4/+12 cm for CryoSat-2 satellite, –15/+12 cm for PIOMAS system) show the scale of uncertainty in estimating sea ice thickness and snow height for areas dominated by medium and thick first-year ice. An anomaly of the ice thicknesses observed during the expedition is given in comparison with the background characteristics based on historical ice charting data for 1970s — 1990s, earlier High-Arctic aircraft “Sever” expeditions during 1950s — 1970s and the stated remote observations and numerical estimates for 2000s — 2019. Comparison shows that the AARI expedition was actually carried out in one of the most favorable years for ice research in the last decade for this region — the average ice thickness in April 2019 was 15 — 28 cm higher than that for the interval 2011 — 2019 with a slightly lower (1 — 2 cm) height of the snow cover. In the earlier period of the 1970 — 1990s this area was characterized by significantly thicker old ice with characteristic thicknesses ~ 60 cm more than in April 2019.

Dynamics of glacier surface velocity and ice thickness for maritime glaciers in the southeastern Tibetan Plateau

Influenced by climate warming, glacial hazards become increasingly frequent after glacier mass loss in the southeastern Tibetan Plateau. Investigations of mountain glacier surface velocities and volume are of great significance. However, no information is given regarding the specific changes in ice flow to climate warming, the spatiotemporal variations of glacier surface velocity and ice thickness are still unclear. In this study, offset tracking was used to measure glacier surface velocity in the southeastern Tibetan Plateau using Landsat TM/ETM+/OLI imagery from 1990 to 2018. And then spatially-distributed glacier ice thickness was estimated from mass-balance distribution data, glacier surface velocities and the principles of ice-flow. Results show that all maritime glaciers velocity in study area experienced a clear regional slowdown from 1991 to 2018, with robust overall trends of −5.26 m a−1 dec−1 (-19.8% dec−1) and 7.16 m a−1 dec−1 (25.2% dec−1) at elevations below and above 4 600 m a.s.l., respectively. Total volume for glaciers with an area of 954.34 km2 was found to be ~ 86.64 ± 11.09 km3 in 2013, corresponding to an average ice thickness of ~ 91 ± 12 m. The average ice thickness thinned by 0.62% a−1 during 2000–2013, and an accelerated melting can be expected in the long term and then glacier volume decreases more rapidly than in the last decades.

Evaluation of ice volume in the Okhotsk Sea by the ice age characteristics for the period of 2001–2019

Age of ice in the Okhotsk Sea in 2001–2019 is determined by analysis of satellite data from passive and active microwave spectroradiometers. The areas with certain age composition are contoured with monthly discreteness. Mean thickness of ice in these areas is calculated by weighted averaging of thickness for three main forms, neglecting the ice deformation. The ice volume is calculated by these areas, taking into account the ice concentration. The total mean winter ice volume in the Okhotsk Sea decreased in two decades with the rate of 32.2 km3/decade, on average, while the ice cover decreased by 3.2 %/decade and the average ice thickness decreased by 3.4 cm/decade. Total loss of the ice volume in the Okhotsk Sea in 2001–2019 is estimated as 34.5 %. The ice volume decreasing was caused by both ice thickness lowering (60 %) and ice cover reduction (40 %).

Decadal Variations of Sea Ice Thickness in the Amundsen‐Bellingshausen and Weddell Seas Retrieved From ICESat and IceBridge Laser Altimetry, 2003–2017

AbstractThe changing distributions of sea ice thickness in different regions around Antarctica are important metrics of climate variability, but estimates have large uncertainties. Here, we analyze laser altimetry data from ICESat and IceBridge to generate a record of total freeboard and sea ice thickness in the Amundsen‐Bellingshausen and Weddell seas during austral springs from 2003 to 2017. We improve the buoyancy approach (BOC) to estimate sea ice thickness from total freeboard without altimetry‐coincident measurements of snow depth. The sea ice thickness estimated by the improved BOC agrees well with field measurements and is slightly larger than those derived by previous approaches of zero ice freeboard and empirical relationship. The average sea ice thickness had large interannual variations with no significant trend in both seas from 2003 to 2017. Although sea ice thickness usually did not covary with sea ice extent in these regions, sea ice thickness showed a similar rapid decline with ice extents in the Weddell Sea during 2014–2017. The nearly continuous long‐term record of sea ice thickness is of great significance for the sea ice and global climatic model communities, especially given the future extension of the record using measurements from ICESat‐2 launched in late 2018.

Application of an ice-ocean coupled model to Bohai Sea ice simulation

The HAMSOM (Hamburg Shelf Ocean Model), a high-resolution regional ice-ocean coupled model, was applied to investigate the seasonal evolution of Bohai Sea ice for winter 2015/2016. HAMSOM was initialized with monthly climatological temperature and salinity data from WOA13 and driven by hourly meteorological data obtained from the NCEP above the sea surface and tides at the open boundary. The ice model used here is a modified Hibler-type dynamic-thermodynamic sea ice model based upon viscous-plastic rheology. The ice extent, concentration, area, thickness, length of ice season as well as the distance between the top of Liaodong Bay (North China) and the outer ice edge line were simulated and compared with the observed data. Three types of modeling experiments were carried out to investigate the effects of wind, tide, and both wind and tide on Bohai Sea ice. The results show that wind, as both a dynamic and a thermodynamic factor, has a significant impact on the ice thickness, ice area, and ice-freezing and ice breakup dates as well as the ice velocity, while tides are a dynamic factor that influences only the ice velocity. During the severe ice period, the wind speed intensity increased by 25%, the average ice thickness thickened by approximately 4.0 cm in Liaodong Bay, approximately 2.1 cm in Bohai Bay and approximately 2.5 cm in Laizhou Bay, and the total ice coverage area and total ice actual area increased by about 2×104 km2 and 1.4×104 km2, respectively. While the tidal amplitude intensity increased by 25%, the average ice velocity increased by approximately 0.1 m/s.

Volume Changes of Elbrus Glaciers From 1997 to 2017

This study describes the analysis of changes in area and volume of the Mt. Elbrus glacier system, Central Caucasus from 1997 to 2017. It is based on helicopter-borne ice thickness measurements, comparison of high-resolution imagery and two digital elevation models (DEMs) with 10 meter resolution. More than 250 km of ground-penetrating radar (GPR) profiles of ice thickness with reliable reflections were obtained. The total volume of Mt. Elbrus glaciers was 5.03±0.85 km3 of ice in 2017. Our results show that 68% of the total ice volume is concentrated below 4000 m a.s.l. where the average ice thickness was 44.6±7.3 m, 18% of the volume lies within 4000-4500 m a.s.l. (thickness of 41.2±7.3 m), and just 14% lies above 4500 m a.s.l. (thickness of 29.7±6.65 m). The glacier-covered area of Mt. Elbrus decreased from 125.76±0.65 km2 in 1997 to 112.20±0.58 km2 in 2017, a reduction of 10.8%. Over the same period the volume decreased by 22.8%. The mass balance of the Elbrus glaciers decreased by -0.55±0.04 m w.e. a-1 from 1997 to 2017. Mass balance on west-oriented glaciers is less negative than on east-and south-oriented glaciers where mass balance is most negative. The mass balance of the east-oriented Djikiugankez glacier decreased at the fastest average rate (-0.97±0.07 m w.e. a-1). This glacier contains 28% of the total Elbrus glacier system ice volume, most of which is concentrated below 4000 m a.s.l. Only one small glacier on the western slope demonstrated mass gain. Our results match well with the long term direct mass balance measurements on the Garabashi glacier on Elbrus which lost 12.58 m w.e. and 12.92±0.95 m w.e. between 1997 and 2017 estimated by glaciological and geodetic method, respectively. The rate of Elbrus glacier mass loss tripled in 1997-2017 compared with the 1957-1997 period.

Calibrated Ice Thickness Estimate for All Glaciers in Austria

Knowledge on ice thickness distribution and total ice volume is a prerequisite for computing future glacier change for both glaciological and hydrological applications. Various ice thickness estimation methods have been developed but regional differences in fundamental model parameters are substantial. Parameters calibrated with measured data at specific points in time and space can vary when glacier geometry and dynamics change. This study contributes to a better understanding of accuracies and limitations of modelled ice thicknesses by taking advantage of a comprehensive data set of in-situ ice thickness measurements from 58 glaciers in the Austrian Alps and observed glacier geometries of three Austrian glacier inventories between 1969 and 2006. The field data are used to calibrate an established ice thickness model to calculate an improved ice thickness data set for the Austrian Alps. A cross-validation between modelled and measured point ice thickness indicates a model uncertainty of 25-31% of the measured point ice thickness. The comparison of the modelled and measured average glacier ice thickness revealed an underestimation of 5% with a mean standard deviation of 15% for the glaciers with calibration data. The apparent mass balance gradient, the primary model parameter accounting for the effects of surface mass balance distribution as well as ice flux, substantially decreases over time and has to be adjusted for each temporal increment to correctly reproduce observed ice thickness. This reflects the general stagnation of glaciers in Austria. We applied optimized apparent mass balance gradients to all glaciers of the latest Austrian glacier inventory and found a volume of 15.9 km³ for the year 2006. The ten largest glaciers account for 25% of area and 35% of total ice volume. An estimate based on mass balance measurements from nine glaciers indicates an additional volume loss of 3.5 ± 0.4 km³ (i.e. 22 ± 2.5%) until 2016. Relative changes in area and volume were largest at glaciers smaller than 1 km², and relative volume changes appear to be higher than relative area changes for all considered time periods.

Assessment of glacier stored water in Karakoram Himalaya using satellite remote sensing and field investigation

Karakoram Himalaya (KH) has continental climatic conditions and possesses largest concentration of glaciers outside the polar regions. The melt water from these glaciers is a major contributor to the Indus river. In this study, various methods have been used to estimate the ice volume in the Karakoram Range of glaciers such as Co-registration of Optically Sensed Images and Correlation (COSI-Corr) method and Area-Volume relations. Landsat 8 satellite data has been used to generate the ice displacement, velocity and thickness map. Our study for 558 Karakoram glaciers revealed that the average ice thickness in Karakoram is 90 m. Ground Penetrating Radar (GPR) survey has been conducted in one of the KH glacier i.e. Saser La glacier and the collected GPR data is used for the validation of satellite derived thickness map. GPR measured glacier thickness values are found comparable with satellite estimated values with RMSE of 4.3 m. The total ice volume of the Karakoram glaciers is estimated to be 1607±19 km3(1473±17 Gt), which is equivalent to 1473±17 km3 of water equivalent. Present study also covers the analysis of glacier surface displacement, velocity and ice thickness values with reference to glacier mean slope.

Spatial heterogeneity in the structure of fast ice level in the area of the research station “Ice base Cape of Baranov”

Two ice coring transects in the Shokalsky Strait were made in order to analyze a spatialheterogeneity in the structure of fast ice in the area of the research station “Ice base Cape of Baranov”. The first transect was 16 km long made off the shore of Bolshevik Island in a western direction across the Shokalsky Strait. The second transect was made along the eastern shore of the Shokalsky Strait. Structural analysis of the recovered sea ice cores shows that fast ice in the Shokalsky Strait features a complicated multilayer structure formed of congelation ice, congelation-frazil ice, frazil slush, and infiltration formations. Various conditions of ice formation form the ices of various genetic types. In terms of ice thickness, a sequence of layer occurrence and type, all level fast ice of the Shokalsky Strait in the area of the station can be divided into three main groups. The group I, being the most common one, is the ice group formed directly in the strait, approximately outside the 100 m isobath. Its structure comprises three to four layers. The average ice thickness measured in the end of May was 132 cm. A distinctive feature of the ice belonging to (or associated with) this group is the presence of a distinct lamination in the texture pattern for almost all recovered ice cores. The ice of this group also has an increased salinity compared to the ice of other groups, especially in the upper layers.The ice of the group II prevails, mainly in closed bays or gulfs. This group ice forms in dynamically stable conditions. Formation of fast ice in these regions of the study area began some earlier than in other locations, and the thickness of this ice reached 160 cm or more.The ice of the group III is transitional from the group II to the group I. Its distinctive feature is the presence of a thick layer of rafting ice. The main place of its formation is the boundary of separation of fast ice with drifting ice or open water.In the Shokalsky Strait, in the bays and in the coastal regions, there was observed the spatial ordering of the columnar ice crystals. This feature was especially pronounced in level fast ice from the open part of the strait.

Interannual sea ice thickness variability in the Bay of Bothnia

Abstract. While variations of Baltic Sea ice extent and thickness have been extensively studied, there is little information about drift ice thickness, distribution, and its variability. In our study, we quantify the interannual variability of sea ice thickness in the Bay of Bothnia during the years 2003–2016. We use various different data sets: official ice charts, drilling data from the regular monitoring stations in the coastal fast ice zone, and helicopter and shipborne electromagnetic soundings. We analyze the different data sets and compare them to each other to characterize the interannual variability, to discuss the ratio of level and deformed ice, and to derive ice thickness distributions in the drift ice zone. In the fast ice zone the average ice thickness is 0.58±0.13 m. Deformed ice increases the variability of ice conditions in the drift ice zone, where the average ice thickness is 0.92±0.33 m. On average, the fraction of deformed ice is 50 % to 70 % of the total volume. In heavily ridged ice regions near the coast, mean ice thickness is approximately half a meter thicker than that of pure thermodynamically grown fast ice. Drift ice exhibits larger interannual variability than fast ice.