Variations In Ice Thickness Research Articles

Seasonal and Interannual Variations in Sea Ice Thickness in the Weddell Sea, Antarctica (2019–2022) Using ICESat-2

The sea ice extent in the Weddell Sea exhibited a positive trend from the start of satellite observations in 1978 until 2016 but has shown a decreasing trend since then. This study analyzes seasonal and interannual variations in sea ice thickness using ICESat-2 laser altimetry data over the Weddell Sea from 2019 to 2022. Sea ice thickness was calculated from ICESat-2’s ATL10 freeboard product using the Improved Buoyancy Equation. Seasonal variability in ice thickness, characterized by an increase from February to September, is more pronounced in the eastern Weddell sector, while interannual variability is more evident in the western Weddell sector. The results were compared with field data obtained between 2019 and 2022, showing a general agreement in ice thickness distributions around predominantly level ice. A decreasing trend in sea ice thickness was observed when compared to measurements from 2003 to 2017. Notably, the spring of 2021 and summer of 2022 saw significant decreases in Sea Ice Extent (SIE). Although the overall mean sea ice thickness remained unchanged, the northwestern Weddell region experienced a noticeable decrease in ice thickness.

The Characteristics of Different Apparent Optical Property Parameters in Non‐Destructively Estimating Absorptive Substances Within Sea Ice: A Case Study in Liaodong Bay

AbstractAbsorptive substances (AS) embedded in sea ice can alter irradiance transmission, exerting a significant influence on oceanic biogeochemical processes. Their quantification is thus essential, and a regression model based on the normalized difference index of transmittance (T(λ)) has been widely used for retrieving ice algal biomass. However, the potentials of albedo (α(λ)) and the diffuse attenuation coefficient (Kd(λ)) in AS estimation have not been explored. To fill this gap, sea ice optical properties observed in Liaodong Bay in 2009, 2010, 2013, and 2022 were used to investigate the characteristics of α(λ), T(λ), and Kd(λ) in non‐destructively estimating As through sensitivity analyses based on the Hydrolight radiative transfer model. The effects derived from AS vertical distribution, scattering coefficient and ice thickness were studied specifically. Ultimately, a significant relationship between α(λ) and the total absorption coefficient of AS was derived (R2 = 0.79) for Liaodong Bay sea ice. Sensitivity analyses revealed that it could only retrieve AS in the upper 15–20 cm, which was influenced by variations in ice thickness and scattering coefficient. In contrast, T(λ) could retrieve AS throughout the ice column and is less affected by scattering variation; but it is significantly affected by the vertical distribution of AS in the upper layer. Kd(λ) has the best potential in AS estimation, but for sea ice thinner than 30 cm, the effect of variation in ice thickness could not be neglected, similar to T(λ). Knowledge of this is helpful for the future development of AS estimation.

Thermodynamic and Dynamic Variations in Sea Ice Thickness of the Ross Sea, Antarctica, Driven by Atmospheric Circulation

AbstractAtmospheric circulation has significant impacts on sea ice drifting patterns and mass balance, as wind drag induces pressure ridges and leads on the sea ice surface. In this study, the spatiotemporal distributions of these dynamic sea ice deformation features in the Ross Sea are examined using ICESat‐2 (IS2) ATL10 freeboard data (2019–2022). The temporal variation of the modal sea ice thickness (SIT), caused by thermodynamic ice growth and sea ice advection, varies from 0.7–1.0 m in April to 1.0–1.6 m in July–September and decreases thereafter in the northwest (NW) and northeast (NE) sectors. This temporal variation of modal SIT agrees with the air temperature (correlation coefficients >0.5). The southwest (SW) sector shows a consistently low modal SIT (<1.0 m) because of the production of new ice in polynyas and continuous northward sea ice drift. Meanwhile, the southeast (SE) sector shows the thickest ice in Octobers 2019 and 2020 because of the advection of thick ice from the Amundsen Sea, which was reduced in 2021 and 2022. In terms of dynamic sea ice deformation, the SE sector shows the largest deformation because of the wind‐driven convergence of sea ice movement. However, such intense deformation in the SE sector diminished in 2021 and 2022 due to the dominance of strong southerly wind associated with the Amundsen Sea Low (ASL). This study emphasizes the potential of IS2 sea ice products to assess the role of atmospheric driving forces on thermodynamic and dynamic sea ice changes.

Method for Producing Columnar Ice in Laboratory and Its Application

This study presents the design of a small open-circuit wind tunnel for laboratory use and a method for preparing columnar ice. The ice formation process was analyzed in terms of temperature and ice thickness variations under varying environmental temperatures and wind speeds. Observations revealed that as wind speed increased, the grain size of the columnar ice decreased. Key findings include the following: (1) the selection and validation of two cubic arcs for the wind tunnel contraction section, achieving an acceleration ratio of 6.7–6.8 and stable wind speeds of 1–10 m/s; (2) real-time temperature monitoring indicated rapid cooling before freezing and slower cooling post-freezing, with lower ambient temperatures and higher wind speeds accelerating the icing process; (3) the −1/2 power of grain size was found to be positively correlated with wind speed; and (4) the method’s feasibility for studying mechanical properties of polar columnar ice was confirmed. This technique offers a controlled approach for producing columnar ice in the laboratory, facilitating comprehensive research on ice properties and providing a foundation for future studies on the mechanical behavior of ice under windy polar conditions.

Influence of the Atlantic and Pacific Multidecadal Variability on Arctic Sea Ice in Pacemaker Simulations during 1920–2013

Abstract The Atlantic multidecadal variability (AMV) and Pacific multidecadal variability (PMV) can influence Arctic sea ice and modulate its trend, but to what extent the AMV and PMV can affect Arctic sea ice and which processes are dominant are not well understood. Here, we analyze the Community Earth System Model, version 1, idealized and time-varying pacemaker ensemble simulations to investigate these issues. These experiments show that the sea ice concentration varies mainly over the marginal Arctic Ocean, while the sea ice thickness variations occur over the entire Arctic Ocean. The internal components of AMV and PMV can enhance or weaken the decadal sea ice loss rates over the marginal Arctic Ocean by more than 50%. The AMV- or PMV-induced anomalous atmospheric energy transport and downward longwave radiation related to low clouds (thermodynamical processes) and sea ice motion (dynamical processes) contribute to the Arctic surface air temperature and sea ice concentration and thickness changes. Anomalous oceanic heat flux is mainly a response to rather than a cause of sea ice variations. The dynamic processes contribute to the winter Arctic sea ice variations as much as the thermodynamic processes, but they contribute less (more) to the summer Arctic sea ice variability than the thermodynamic processes over the marginal Arctic Ocean (parts of the central Arctic Ocean). Sea ice loss enhances air–sea heat fluxes, which cause oceanic heat convergence and warm near-surface air and the lower troposphere, which in turn melt more sea ice.

Motion of Submerged Body in a Frozen Channel with Compressed Porous Ice

The problem of submerged body motion in a frozen channel is considered. The fluid in the channel is assumed to be inviscid and incompressible. Fluid flow is the potential. The ice cover has non-uniform compression along the principal coordinates. The damping of hydroelastic waves generated by the motion of submerged body is modeled by taking into account porosity of ice. The submerged body is modeled as a dipole, the potential of which is determined using mirror images from the channel walls. The main problem of the submerged body motion at constant speed along the central line of the channel is considered. Two subproblems are addressed: comparison of damping effects of the porosity and viscosity of ice and investigation of effects of symmetrically variable ice thickness relative to the central line of the channel. It was found that the most important compressive stress is the stress in the direction of the motion of the submerged body. The speed of the body, which was subcritical for uncompressed ice, may become critical or supercritical. Compressive stresses perpendicular to the direction of motion do not qualitatively change the character of the ice response. These stresses, in combination with compressive stresses along the direction of motion, strengthen the effect of the latter, making the transition from subcritical to supercritical regime faster.

Inferring glacier mass balance from Sentinel-1 derived ice thickness changes using geoinformatics: A case study of Gangotri glacier, Uttarakhand, India

All glaciers respond to climatic changes by fluctuating their mass. Investigations of glacier dynamics are necessary for glacier monitoring. Himalayan glaciers make ongoing glacier observations challenging due to their location in a severe topographic environment and inhospitable terrain. Glacier area contraction or extension, together with a corresponding snout shift, can be linked to oscillations in glacier mass. Sentinel-1 dual-polarized datasets were used in this investigation to retrieve glacier surface velocity. Estimates of ice thickness were enhanced by segmenting the glacier into 100-m height intervals. Also, ice thickness variations between 2017 and 2022 have been used to compute glacier mass balance, and the results for several glacier zones have been briefly analyzed. The study revealed that the maximum surface velocity above Gangotri Glacier was approximately 0.33 m/day, with an estimated average of 0.09 m/day. Surface velocities of the central trunk have been seen to range from 0.12 m/day to 0.23 m/day. Additionally, between 2017 and 2022, the surface velocity was spotted between 0.19 m/day to 0.35 m/day. For the glacier, an average ice thickness of 189 ± 17.01 m was calculated. In the central parts, where the drag was least noticeable, thicknesses up to 587 ± 52.83 m were estimated. In the lower accumulation zone and middle reaches, the thickness was found to be decreasing between 2017 and 2022, which can be attributed to increased melting and glacier slowdown. Due to the increased glacier movement throughout time, the lower accumulation reaches over the main glacier body, and its tributaries have experienced mass balancing rates ranging from −1.3 m.w.e./year to −0.5 m.w.e./year (thickness change between −3 m/year and −0.6 m/year). With the help of previous research and existing data, the results were compared and validated. The suggested algorithm and findings can serve as inputs for satellite-based ice thickness measurements and as fundamental research for the forthcoming NISAR mission (expected by mid-2024) which will carry L- and S-band antennas.

Modeling Climate Characteristics of Qinghai Lake Ice in 1979–2017 by a Quasi-Steady Model

Lakes on the Qinghai Tibet Plateau (QTP) are widely distributed spatially, and they are mostly seasonally frozen. Due to global warming, the thickness and phenology of the lake ice has been changing, which profoundly affects the regional climate evolution. There are a few studies about lake ice in alpine regions, but the understanding of climatological characteristics of lake ice on the QTP is still limited. Based on a field experiment in the winter of 2022, the thermal conductivity of Qinghai Lake ice was determined as 1.64 W·m−1·°C−1. Airborne radar ice thickness data, meteorological observations, and remote sensing images were used to evaluate a quasi-steady ice model (Leppäranta model) performance of the lake. This is an analytic model of lake ice thickness and phenology. The long-term (1979–2017) ice history of the lake was simulated. The results showed that the modeled mean ice thickness was 0.35 m with a trend of −0.002 m·a−1, and the average freeze-up start (FUS) and break-up end (BUE) were 30 December and 5 April, respectively, which are close to the field and satellite observations. The simulated trend of the maximum ice thickness from 1979 to 2017 (0.004 m·a−1) was slightly higher than the observed result (0.003 m·a−1). The simulated trend was 0.20 d·a−1 for the FUS, −0.34 d·a−1 for the BUE, and −0.54 d·a−1 for the ice duration (ID). Correlation and detrending analysis were adopted for the contribution of meteorological factors. In the winters of 1979–2017, downward longwave radiation and air temperature were the two main factors that had the best correlation with lake ice thickness. In a detrending analysis, air temperature, downward longwave radiation, and solar radiation contributed the most to the average thickness variability, with contributions of 42%, 49%, and −48%, respectively, and to the maximum thickness variability, with contributions of 41%, 45%, and −48%, respectively. If the six meteorological factors (air temperature, downward longwave radiation, solar radiation, wind speed, pressure, and specific humidity) are detrending, ice thickness variability will increase 83% on average and 87% at maximum. Specific humidity, wind, and air pressure had a poor correlation with ice thickness. The findings in this study give insights into the long-term evolutionary trajectory of Qinghai Lake ice cover and serve as a point of reference for investigating other lakes in the QTP during cold seasons.

The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms

Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future.

Synthetic aperture radar backscatter is influenced by bubbles at the ice/water interface of an Antarctic lake

Synthetic aperture radar is an invaluable tool for monitoring lake ice. This study utilizes synthetic aperture radar to analyze the 2019-2023 backscatter time series of perennially ice-covered Lake Untersee in East Antarctica. We observed stark seasonal backscatter variations, averaging –9.6 dB from December to March and –3.7 dB from May to November. These fluctuations correspond to the abundance of sub-centimeter bubbles at the ice/water interface. Notably, the backscatter increase in April-May aligns closely with variations in ice thickness across the lake. Our findings suggest that ice cover thickness influences the timing and duration of ice accretion at the bottom, the accumulation of dissolved gases and bubbles, and the resultant changes in surface roughness at the ice/water interface. These factors collectively impact the backscatter response. This study enhances our understanding of the interactions between subsurface processes and synthetic aperture radar backscatter, shedding light on the seasonal dynamics of perennially ice-covered lakes.

The roles of river discharge and sea ice melting in formation of freshened surface layers in the Kara, Laptev, and East Siberian seas

Wide areas of the Siberian Arctic shelf are covered by freshened surface water layers, which are among the largest in the World Ocean. River discharge is the main freshwater source for formation of these layers; therefore, they are commonly referred to as river plumes (the Ob-Yenisei plume in the Kara Sea and the Lena plume in the Laptev and East Siberian seas). The contribution of sea ice meltwater (SIM) to the Ob-Yenisei and Lena plumes is pointed out to be small, albeit its actual volume remains unknown. In this study, we use a novel dataset of satellite-derived sea ice thickness in the Arctic Ocean during the melt period to quantify the annual volume of SIM, which was received by the Ob-Yenisei and Lena plumes during 2012–2020. We reveal that SIM is a significant source for the Lena plume providing, on average, 20% of total annual freshwater content. Moreover, the share of SIM in the Lena plume shows large inter-annual (14%–29%) variability, i.e., during certain years, SIM provides almost one-third of freshwater volume of the Lena plume. This variability is governed by inter-annual variability of ice thickness, as well as seasonal variability of sea ice melting conditions. Conversely, the contribution of SIM to the Ob-Yenisei plume is relatively low (8% on average), and its total annual share varies from 6% to 11% during the study period. This difference is mainly caused by significantly smaller area of the Ob-Yenisei plume as compared with the Lena plume. The forecasted earlier onset of ice melting in the Arctic Ocean in future decades due to climate change could decrease the contribution of SIM to the Ob-Yenisei plume, whereas its influence on the Lena plume remains unclear.

ПАРАМЕТРИЗАЦИЯ ТЕПЛО- И ВЛАГООБМЕНА В РЕГИОНАЛЬНОЙ ТЕРМОДИНАМИЧЕСКОЙ МОДЕЛИ МОРСКОГО ЛЬДА

The prevailing types of the atmospheric stratification over the snow-ice cover at the top of Taganrog Bay for eleven winter seasons of 2007/2008-2017/2018 have been determined using the numerical experiments on reproducing the seasonal variations in the sea ice thickness. Series of calculations both with the constant transfer coefficients and with the coefficients obtained taking into account the surface stratification of the atmosphere have been carried out. The model results of both series have been compared with each other and with in situ measurements.

Assessment of atmospheric circulation impacts on the Caspian Sea level and ice regime

The research aimed to assess the influence of atmospheric processes in the Northern Hemi-sphere’s Atlantic-European Sector on the Caspian Sea level based on the data for the days with Wangenheim-Girs atmospheric general circulation forms. The inputs covered the time period from 1900 to 2022. The information on the sea level, precipitation and ice events were harvested from 22 observation points in Kazakhstan and Russia. The statistical and comparative analysis as well as the climate change assessment within the framework of the study pointed to a stable correlation between the sea level and atmospheric circulation; re-vealed certain patterns reflected in precipitation distribution and frequency of moisture defi-cient and excessive years. The research also identified that the climatic changes have al-tered the sea’s ice regime, with the maximum ice thickness decreasing by 13-28 cm depend-ing on a specific water area. In addition to ice thickness variation, the recent decades show an increased frequency of moderate and mild winters, and the shift of the main glaciation dates, i.e. a stable ice cover forming later, the date of fixed maximum ice thickness observed in mid-February, the date of complete ice clearing observed in early-mid March, and the freezing period being shorter.

Ice geometry and thermal regime of Lyngmarksbræen Ice Cap, West Greenland

Abstract Observations remain sparse for peripheral glaciers and ice caps in Greenland. Here, we present the results of a multi-frequency radar survey of Lyngmarksbræen Ice Cap in West Greenland conducted in April 2017. Radar measurements show thick ice of up to ~120 m in subglacial valleys associated with the largest outlet glaciers, while relatively thin ice cover the upper plateau ice divides, suggesting future vulnerability to ice cap fragmentation. At the time of the radar survey, Lyngmarksbræen Ice Cap had a total volume of 0.82 ± 0.1 km3. Measurements show a 1.5–2 m thick end-of-winter snowpack, and that firn is largely absent, signifying a prolonged period of negative mass balance for most of the ice cap. The thermal regime of Lyngmarksbræen Ice Cap is investigated through analysis of scattering observed along radar profiles. Results show that the ice cap is largely below the pressure melting point, but that temperate ice exists both in deep basal pockets and in shallow zones that some places extend from ~15 m depth and to the ice base. The distribution of shallow temperate ice appears unrelated to variations in ice thickness; instead we find a strong correlation to the presence of nearby surface crevasses.

Morphosedimentary response of a fluvio-estuarine beach to interannual variability in landfast ice dynamics

Landfast ice plays a significant role in the morphodynamics of cold coasts and accelerating anthropogenic pressures on coastal sedimentary environments are increasing the complexity of its distribution and behavior. However, understanding its interannual variability and geomorphic role along the wide range of inhabited and uninhabited coastal environments remains a challenge. In fact, the difficulty in obtaining periodic high-resolution field data on its physical properties and their temporal evolution is often a major limitation in developing knowledge on landfast ice processes. Here, we present an approach for improving the monitoring of landfast ice dynamics and its geomorphic impact on sedimentary systems by combining (1) topographic datasets from UAS surveys, (2) hydrometeorological conditions during the freezing season, and (3) observations from time-lapse video. This study was conducted over two contrasting freezing seasons at the urban beach of Tibbits Cove in the fluvial estuary of the St. Lawrence River in a context of a low energy wave environment. Results demonstrate the great ability of the approach for (1) measuring interannual variations in ice thickness, surface ruggedness and volume with high accuracy and (2) constraining geomorphic changes due to ice action. These results also reveal the existence of a strong relationship between the severity of the freezing season and the response of landfast ice to hydrometeorological events in a fetch-limited environment. Consequently, a distinct geomorphic response of the beach was also observed following the opposite winter conditions of 2021 and 2022, where ice processes exported almost three times more sediment during a cold winter than during a mild winter. The overall trend in sediment budgets remained negative following two winters, suggesting an important role for landfast ice in the long-term evolution of the beach. Observations also suggest the prevalence of wave-independent sediment entrainment processes such as basal adfreezing in fetch-limited environments. Other ice-related processes, including ice wallowing and gouging, show a negligible influence on the sediment budget of the system and appear to be less powerful than those described in open coastal environments. Ultimately, expanding the use of this approach could greatly enhance our knowledge of the behavior, processes and products of coastal ice in a constantly changing climate, while informing decision-makers of its important influence on the evolution of geosystems in cold regions.

The modulation effect of ice thickness variations on convection in icy ocean worlds

ABSTRACT It has been long puzzling whether the ice thickness variations observed on Enceladus can be sustained solely by a polar-amplified bottom heating. The key to this question is to understand how the upward heat transport by convective plumes would be interfered by the temperature and salinity variations beneath the ice due to the ice thickness variations, which, however, has yet to be explored. Here, we find that the horizontal temperature variation induced by the ice topography can easily be orders of magnitude greater than the vertical temperature variation induced by bottom heating using scaling analysis. Due to the dominance of horizontal temperature gradient, convective plumes are completely shut off by a stratified layer under the thin ice formed out of baroclinic adjustment, largely slowing down the vertical tracer transport. The stratified layer will also deflect almost all of the core-generated heating towards the regions with thicker ice shell, destroying the ice thickness gradient. These results allow us to put an upper bound on the core-generated heating on Enceladus, which is crucial for the estimate of habitability. Scaling laws for the bottom heat flux to penetrate the stratification are derived and examined. This scaling can be used to constrain the maximum ice thickness variations induced by heterogeneous bottom heating on icy satellites in general, which can be used to differentiate icy satellites that generate the majority of heat in the ice shell from those that generate the majority of heat in the silicate core.

Morphology Dynamics of Ice Cover in a River Bend Revealed by the UAV-GPR and Sentinel-2

After the formation of the bend ice cover, the ice thickness of the bend is not uniformly distributed, and an open-water area is usually formed downstream of the bend. The spatial and temporal variation of the ice thickness in seven cross sections was determined via Unmanned Aerial Vehicle Ground Penetrating Radar (UAV-GPR) technology and traditional borehole measurements. The plane morphology change of the open water was observed by Sentinel-2. The results show that the average dielectric permittivity of GPR was 3.231, 3.249, and 3.317 on three surveys (5 January 2022, 16 February 2022, and 25 February 2022) of the Yellow River ice growing period, respectively. The average ice thickness of the three surveys was 0.402 m, 0.509 m, and 0.633 m, respectively. The ice thickness of the concave bank was larger than that of the convex bank. The plane morphology of the open water first shrinks rapidly longitudinally and then shrinks slowly transversely. The vertical boundary of the open water was composed of two arcs, in which the slope of Arc I (close to the water surface) was steeper than that of Arc II, and the hazardous distance of the open-water boundary was 10.3 m. The increased flow mostly affected the slope change of Arc I. Finally, we discuss the variation of hummocky ice and flat ice in GPR images and the physical factors affecting GPR detection accuracy, as well as the ice-thickness variation of concave and convex banks in relation to channel curvature.

Mapping snow depth on Canadian sub-arctic lakes using ground-penetrating radar

Abstract. Ice thickness across lake ice is mainly influenced by the presence of snow and its distribution, which affects the rate of lake ice growth. The distribution of snow depth over lake ice varies due to wind redistribution and snowpack metamorphism, affecting the variability of lake ice thickness. Accurate and consistent snow depth data on lake ice are sparse and challenging to obtain. However, high spatial resolution lake snow depth observations are necessary for the next generation of thermodynamic lake ice models to improve the understanding of how the varying distribution of snow depth influences lake ice formation and growth. This study was conducted using ground-penetrating radar (GPR) acquisitions with ∼9 cm sampling resolution along transects totalling ∼44 km to map snow depth over four Canadian sub-arctic freshwater lakes. The lake snow depth derived from GPR two-way travel time (TWT) resulted in an average relative error of under 10 % when compared to 2430 in situ snow depth observations for the early and late winter season. The snow depth derived from GPR TWTs for the early winter season was estimated with a root mean square error (RMSE) of 1.6 cm and a mean bias error of 0.01 cm, while the accuracy for the late winter season on a deeper snowpack was estimated with a RMSE of 2.9 cm and a mean bias error of 0.4 cm. The GPR-derived snow depths were interpolated to create 1 m spatial resolution snow depth maps. The findings showed improved lake snow depth retrieval accuracy and introduced a fast and efficient method to obtain high spatial resolution snow depth information. The results suggest that GPR acquisitions can be used to derive lake snow depth, providing a viable alternative to manual snow depth monitoring methods. The findings can lead to an improved understanding of snow and lake ice interactions, which is essential for northern communities' safety and wellbeing and the scientific modelling community.

Finetuning ground penetrating radar velocity analysis from hyperbola fitting using migration

AbstractThe widely used tool, ground penetrating radar (GPR), has proven to be an excellent research method for glaciological studies. The total ice thickness and englacial structures can be studied, and the method can give information on the temperature regime within the ice. Good velocity profiles are needed to convert measured two‐way travel time to depth information. In addition, a good velocity analysis can be used to improve data processing. A number of methods can be used to find the GPR wave velocity, which are briefly described. This study used hyperbola fitting to estimate the velocity in a glaciological study. In addition, Kirchhoff's migration was used to fine‐tune this velocity estimate. Within the Longyearbreen glacier, situated next to Longyearbyen on Spitsbergen, Svalbard archipelago, objects in the ice act as scattering points that create hyperbolas. Using the hyperbola‐fitting method, a GPR wave velocity equal to 0.170 ± 0.005 m/ns was estimated. By doing Kirchhoff's migration and studying the collapse of hyperbolas with variations of the migration velocity, a more accurate velocity estimate can be achieved; 0.172 ± 0.002 m/ns. A more accurate velocity estimate like this opens possibilities for better characterization of the ice body and ice thickness variations, as well as the variation of these as a function of time. In March 2022, the maximum ice thickness in the investigated area was calculated to be 88 ± 1 m.

Ice Mass Balance in Liaodong Bay: Modeling and Observations

During the winters of 2009/2010 and 2020/2021, observations were carried out at an eastern port of Liaodong Bay to examine the variations in sea ice thickness and atmospheric conditions. The daily ice thickness (DIT) and the cumulative ice thickness (CIT) are the two main observation items related to the thickness of sea ice. For DIT, the sea ice thickness gradually decreases as the temperature increases, and the freezing rate a is 1.48 cm/(°C·d)1/2. For CIT, when the temperature is −12 °C, the maximum growth rate of ice thickness decreases from 3.5 cm/d to 1.5 cm/d as the ice thickness increases from 0 to 20 cm. The residual method was applied to calculate the oceanic heat flux, which is an important parameter of ice modeling, and both the analytic model (Stefan’s law) and numerical model (high-resolution thermodynamic snow-and-ice model) were utilized in this work. It was found that the accuracy of the simulation results was high when the growth coefficient of the analytic mode was 2.3 cm/(°C·d)1/2. With an oceanic heat flux of 2 W·m−2, the maximum error of the numerical model approached 60% in 2010 and 3.7% in 2021. However, using the oceanic heat flux calculated in this work, the maximum error can be significantly reduced to 4.2% in the winter of 2009/2010 and 1.5% in 2020/2021. Additionally, the oceanic heat flux in Liaodong Bay showed a decreasing trend with the increase in ice thickness and air temperature.