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The thickness of the Antarctic ice sheet is a crucial parameter for inferring glacier mass and its evolution process. In the literature, the gravity method has been proven to be one of the effective means for estimating ice sheet thickness. And it is a preferred approach when direct measurements are not available. However, few gravity inversion methods are valid in rugged terrain areas with undulating observation surfaces (UOSs). To solve this problem, this paper proposes an improved high-precision 3D density interface inversion method considering terrain and UOSs simultaneously. The proposed method utilizes airborne gravity data at their flight altitudes, instead of the continued data yield from the unstable downward continuation procedure. In addition, based on the undulating right rectangular prism model, the large reliefs of the terrain are included in the iterative inversion. The proposed method is verified on two synthetic examples and is successfully applied to real data in East Antarctica. [ABSTRACT FROM AUTHOR]

Basal melt in the Dome A region will influence the deep-ice-core drilling at Kunlun Station. The melting point (wet bedrock) has a higher reflectivity than the surrounding area, which can be assessed using radar echoes from the bedrock. This paper uses a linear absorption model to determine wet and dry ice–bedrock interfaces around the Kunlun drilling site. In the determination process, an artificial intelligence model was applied to extract the ice–bedrock interface for inferring the ice thickness. Additionally, the various depth-averaged attenuation rates were used to identify the maximal range of basal melting. We mapped the patterns of the wet points on the bottom of the ice sheet and the modeled basal temperature to verify the results of the wet bed conditions. According to these maps of wet bed conditions, the areas with basal melting around the drilling site primarily appear in valley walls with low basal temperatures and are linked with hydraulic potential and bedrock elevation. Identifying the ice–bedrock interface is challenging in the valley bottom area, where the melting points are less than at the valley walls. Additionally, the melting proportions of 11.8% and 3.62% were calculated from two ice-penetrating radar data in this research. The mapped melting points around the site of Kunlun ice core drilling suggest complex ice flow effects and can be used to better interpret archives of old ice for paleoclimate research. [ABSTRACT FROM AUTHOR]

The snow temperature above the ice sheet is one of the basic characteristic parameters of the ice sheet, which plays an important role in the study of the global climate. Because infrared and microwaves with different frequencies have different penetration depths in snow, it is possible to retrieve the snow temperature profiles by combining microwave and infrared brightness temperatures. This paper proposes a conjoint inversion algorithm to retrieve snow temperature profiles by combining multi-frequency microwave brightness temperature (BT) with infrared BT, in which different weight functions of microwave BT at different frequencies are adopted, and the atmosphere influence has also been corrected. The snow temperature profile data are retrieved based on AMSR2 microwave BT data and MODIS infrared BT data in 2017 and 2018, which are evaluated by comparing with the measured snow temperature at Dome-C station. The results confirm that the inverted snow temperature profiles are consistent with the field observation data from the Dome-C station. Multi-frequency microwave brightness temperature can be used to invert the snow temperature profiles; however, the inverted snow surface temperature is more accurate by combining the infrared BT with the microwave BT in the conjoint inversion algorithm. [ABSTRACT FROM AUTHOR]

With global warming, supraglacial lakes play an important role in ice sheet stability and climate change. They are not only the main factors affecting mass balance and sea-level rise but also the key units of surface runoff storage and mass loss. To automatically map the spatiotemporal distribution of supraglacial lakes in Greenland, this paper proposes an attention-based U-Net model with Sentinel-1 SAR imagery. The extraction results show that compared with the traditional network, this method obtains a higher validation coefficient, with an F1 score of 0.971, and it is spatiotemporally transferable, able to realize the extraction of supraglacial lakes in complex areas without ignoring small lakes. In addition, we conducted a case study in the Jakobshavn region and found that the supraglacial lake area peaked in advance between spring and summer due to extreme melting events from 2017 to 2021. Meanwhile, the supraglacial lakes near the 79°N Glacier tended to expand inland during the melting season. [ABSTRACT FROM AUTHOR]

Understanding englacial and subglacial structures is a fundamental method of inferring ice sheets' historical evolution and surface mass balance. The internal layer continuity index and the basal roughness are key parameters and indicators for the speculation of the relationship between the ice sheet's internal structure or bottom and ice flow. Several methods have been proposed in the past two decades to quantitatively calculate the continuity index of ice layer geometry and the roughness of the ice–bedrock interface based on radar echo signals. These methods are mainly based on the average of the absolute value of the vertical gradient of the echo signal amplitude and the standard deviation of the horizontal fluctuation of the bedrock interface. However, these methods are limited by the amount and quality of unprocessed radar datasets and have not been widely used, which also hinders further research, such as the analysis of the englacial reflectivity, the subglacial conditions, and the history of the ice sheets. In this paper, based on geophysical processing methods for radar image denoising and deep learning for ice layer and bedrock interface extraction, we propose a new method for calculating the layer continuity index and basal roughness. Using this method, we demonstrate the ice-penetrating radar data processing and compare the imaging and calculation of the radar profiles from Dome A to Zhongshan Station, East Antarctica. We removed the noise from the processed radar data, extracted ice layer continuity features, and used other techniques to verify the calculation. The potential application of this method in the future is illustrated by several examples. We believe that this method can become an effective approach for future Antarctic geophysical and glaciological research and for obtaining more information about the history and dynamics of ice sheets from their radar-extracted internal structure. [ABSTRACT FROM AUTHOR]

Antarctic basal water storage variation (BWSV) refers to mass changes of basal water beneath the Antarctic ice sheet (AIS). Identifying these variations is critical for understanding Antarctic basal hydrology variations and basal heat conduction, yet they are rarely accessible due to a lack of direct observation. This paper proposes a layered gravity density forward/inversion iteration method to investigate Antarctic BWSV based on multi-source satellite observations and relevant models. During 2003–2009, BWSV increased at an average rate of 43 ± 23 Gt/yr, which accounts for 29% of the previously documented total mass loss rate (−76 ± 20 Gt/yr) of AIS. Major uncertainty arises from satellite gravimetry, satellite altimetry, the glacial isostatic adjustment (GIA) model, and the modelled basal melting rate. We find that increases in basal water mainly occurred in regions with widespread active subglacial lakes, such as the Rockefeller Plateau, Siple Coast, Institute Ice Stream regions, and marginal regions of East Antarctic Ice Sheet (EAIS), which indicates the increased water storage in these active subglacial lakes, despite the frequent water drainage events. The Amundsen Sea coast experienced a significant loss during the same period, which is attributed to the basal meltwater discharging into the Amundsen Sea through basal channels. [ABSTRACT FROM AUTHOR]

Antarctica is covered by a thick ice sheet, and the application of geophysical methods is necessary to image the subglacial structures for studying the hydrologic systems and tectonic deformations in the Antarctic continent. The magnetotelluric (MT) method is one of the best approaches to obtain the subglacial electrical resistivities. However, only a very small volume of data has been collected so far in Antarctica using this method. In this paper, we report on a broadband MT profile collected at 10 sites in the south of the Chinese Zhongshan Station at Prydz Bay, and a 3D resistivity model was constructed by inversion of these data. This 3D model shows two low resistivity zones at a depth shallower than 6 km. They are consistent with the low-velocity zones in the previous shear-wave model and can be interpreted as the result of interconnected fluids associated with a downward migration of subglacial water. In addition, a distinct eastward dipping low resistivity zoneis present in the crust, which extends from the top surface to the lower crust. Since its location coincides with the highly positive magnetization named Amery Lineament, it is proposed that this eastward dipping low resistivity zoneextending in the entire crust probably reveals the geometry structure of the Amery Lineament at depth. Besides, it can be inferred from this new 3D resistivity model that the Amery Lineament is at least a crustal-scale structure, which probably outcrops on the land surface but was covered by the ice sheets in the study area. [ABSTRACT FROM AUTHOR]

Ice flow lines are the most dominant feature of ice sheet surfaces. Accurate delineation of basins is a prerequisite for mass balance. We therefore propose a new weight balance-based approach to extract the present most comprehensive ice flow lines and then re-delineate the Antarctic basin on this basis. In our approach, we define three impact factors to represent directional accuracy, smoothness, and physical character. Following this, a weight balance-based method is proposed, in which those factors are integrated via weights, to determine the pointing pixels (points or subpixels of the ice flow line). After that, the ice flow lines are continuously tracked. Finally, Antarctic basins were re-delineated based on it. The results indicate that the derived ice flow lines exhibit a rational ice flow pattern against the DEM and the proposed method remarkably improves the performance of results. Furthermore, compared with the Antarctic IMBIE (Ice sheet Mass Balance Inter-Comparison Exercise) basins, the redivided basins exhibit slight diversity, with differences in area and length of less than 11% and a directional accuracy of less than 1° (covering more than 90% of area). As a result, the redivided basins are beneficial to the investigation of the in-depth mechanism of ice shelf calving and mass balance in the Antarctic. [ABSTRACT FROM AUTHOR]

The sea ice cover in the North evolves at a rapid rate. To adequately monitor this evolution, tools with high temporal and spatial resolution are needed. This paper presents IceMap250, an automatic sea ice extent mapping algorithm using MODIS reflective/emissive bands. Hybrid cloud-masking using both the MOD35 mask and a visibility mask, combined with downscaling of Bands 3-7 to 250 m, are utilized to delineate sea ice extent using a decision tree approach. IceMap250 was tested on scenes from the freeze-up, stable cover, and melt seasons in the Hudson Bay complex, in Northeastern Canada. IceMap250 first product is a daily composite sea ice presence map at 250 m. Validation based on comparisons with photo-interpreted ground-truth show the ability of the algorithm to achieve high classification accuracy, with kappa values systematically over 90%. IceMap250 second product is a weekly clear sky map that provides a synthesis of 7 days of daily composite maps. This map, produced using a majority filter, makes the sea ice presence map even more accurate by filtering out the effects of isolated classification errors. The synthesis maps show spatial consistency through time when compared to passive microwave and national ice services maps. [ABSTRACT FROM AUTHOR]

The airborne ice-penetrating radar (IPR) is an effective method used for ice sheet exploration and is widely applied for detecting the internal structures of ice sheets and for understanding the mechanism of ice flow and the characteristics of the bottom of ice sheets. However, because of the ambient influence and the limitations of the instruments, IPR data are frequently overlaid with noise and interference, which further impedes the extraction of layer features and the interpretation of the physical characteristics of the ice sheet. In this paper, we first applied conventional filtering methods to remove the feature noise and interference in IPR data. Furthermore, machine learning methods were introduced in IPR data processing for noise removal and feature extraction. Inspired by a comparison of the filtering methods and machine learning methods, we propose a fusion method combining both filtering methods and machine-learning-based methods to optimize the feature extraction in IPR data. Field data tests indicated that, under different conditions of IPR data, the application of different methods and strategies can improve the layer feature extraction. [ABSTRACT FROM AUTHOR]

Due to rapid global warming, the relationship between the mass loss of the Antarctic ice sheet and rising sea levels are attracting widespread attention. The Lambert–Amery glacial system is the largest drainage system in East Antarctica, and its mass balance has an important influence on the stability of the Antarctic ice sheet. In this paper, the recent ice flux in the Lambert Glacier of the Lambert–Amery system was systematically analyzed based on recently updated remote sensing data. According to Landsat-8 ice velocity data from 2018 to April 2019 and the updated Bedmachine v2 ice thickness dataset in 2021, the contribution of ice flux approximately 140 km downstream from Dome A in the Lambert Glacier area to downstream from the glacier is 8.5 ± 1.9   Gt · a − 1 , and the ice flux in the middle of the convergence region is 18.9 ± 2.9   Gt · a − 1 . The ice mass input into the Amery ice shelf through the grounding line of the whole glacier is 19.9 ± 1.3   Gt · a − 1 . The ice flux output from the mainstream area of the grounding line is 19.3 ± 1.0   Gt · a − 1 . Using the annual SMB data of the regional atmospheric climate model (RACMO v2.3) as the quality input, the mass balance of the upper, middle, and lower reaches of the Lambert Glacier was analyzed. The results show that recent positive accumulation appears in the middle region of the glacier (about 74–78°S, 67–85°E) and the net accumulation of the whole glacier is 2.4 ± 3.5   Gt · a − 1 . Although the mass balance of the Lambert Glacier continues to show a positive accumulation, and the positive value in the region is decreasing compared with values obtained in early 2000. [ABSTRACT FROM AUTHOR]

The ice shelf is an important component of the Antarctic system, and the interaction between the ice sheet and the ocean often proceeds through mass variations of the ice shelf. The digital elevation model (DEM) of the ice shelf is particularly important for ice shelf elevation change and mass balance estimation. With the development of satellite altimetry technology, it became an important data source for DEM research of Antarctica. The National Aeronautics and Space Administration (NASA) Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) launched in 2018 is a significant improvement in along-track sampling rate and measurement accuracy compared with previous altimetry satellites. This study uses ordinary kriging interpolation to present new DEMs (ICESat-2 DEM hereinafter) for the three ice shelves (Ross, Filchner–Ronne and Amery) in Antarctica with ICESat-2 altimetry data. Two variogram models (linear and spherical) of ordinary kriging interpolation are compared in this paper. The result shows that the spherical model generally shows better performance and lower standard deviation (STD) than the linear models. The precision of the ultimate DEM was evaluated by NASA Operation IceBridge (OIB) data and compared with five previously published Antarctic DEM products (REMA, TanDEM-X PolarDEM, Slater DEM, Helm DEM, and Bamber DEM). The comparison reveals that the mean difference between ICESat-2 DEM of the Ross ice shelf and OIB is −0.016 m with a STD of 0.918 m, and the mean difference between ICESat-2 DEM of the Filchner–Ronne ice shelf and OIB is −0.533 m with a STD of 0.718 m. The three ICESat-2 DEMs show higher spatial resolution and elevation accuracy than five previously published Antarctic DEMs. [ABSTRACT FROM AUTHOR]

Radio-echo sounding (RES) is widely used for polar ice sheet detection due to its wide coverage and high efficiency. The multivariate variational mode decomposition (MVMD) algorithm for the processing of RES data is an improvement to the variational mode decomposition (VMD) algorithm. It processes data encompassing multiple channels. Determining the most effective component combination of the penalty parameter (α) and the number of intrinsic mode functions (IMFs) (K) is fundamental and affects the decomposition results. α and K in traditional MVMD are provided by subjective experience. We integrated the particle swarm optimization (PSO) algorithm to iteratively optimize these parameters—specifically, α and K—with high precision. This was then combined with the four quantitative parameters: energy entropy, signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and root-mean-square error (RMSE). The RES signal decomposition results were judged, and the most effective component combination for noise suppression was selected. We processed the airborne RES data from the East Antarctic ice sheet using the combined PSO–MVMD method. The results confirmed the quality of the proposed method in attenuating the RES signal noise, enhancing the weak signal of the ice base, and improving the SNR. This combined PSO–MVMD method may help to enhance weak signals in deeper parts of ice sheets and may be an effective tool for RES data interpretation. [ABSTRACT FROM AUTHOR]

The knowledge of glacier zones' extent and their temporal variations is fundamental for the retrieval of surface mass balance of glaciers and ice sheets. In this context, a key parameter is the firn line (FL), the lower boundary of the percolation zone, whose location is an indicator of time-integrated mass balance changes. Several approaches have been developed in the last decades to map the FL by means of Synthetic Aperture Radar (SAR) imagery, mainly exploiting backscatter intensities and their seasonal variation. In this paper, an alternative approach is proposed, based on co-polarisation phase differences (CPDs). In particular, CPDs are interpreted as the result of propagation through anisotropic firn layers and are, therefore, proposed as an indicator of the presence of firn. A model is employed to demonstrate the link between CPDs and firn depth, indicating the potential of polarimetric SAR to improve firn characterization beyond spatial extent and FL detection. The proposed approach is demonstrated on L-band airborne data, acquired on 21 May 2015 by the F-SAR sensor of DLR in West Greenland during the ARCTIC15 campaign, and validated with in-situ information available from other studies. [ABSTRACT FROM AUTHOR]

Climate change is extensively affecting ice sheets resulting in accelerating mass loss in recent decades. Assessment of this reduction and its causes is required to project future ice mass loss. Annual snow accumulation is an important component of the surface mass balance of ice sheets. While in situ snow accumulation measurements are temporally and spatially limited due to their high cost, airborne radar sounders can achieve ice sheet wide coverage by capturing and tracking annual snow layers in the radar images or echograms. In this paper, we use deep learning to uniquely identify the position of each annual snow layer in the Snow Radar echograms taken across different regions over the Greenland ice sheet. We train with more than 15,000 images generated from radar echograms and estimate the thickness of each snow layer within a mean absolute error of 0.54 to 7.28 pixels, depending on dataset. A highly precise snow layer thickness can help improve weather models and, thus, support glaciological studies. Such a well-trained deep learning model can be used with ever-growing datasets to aid in the accurate assessment of snow accumulation on the dynamically changing ice sheets. [ABSTRACT FROM AUTHOR]

Although extensive research of Moderate Resolution Imaging Spectroradiometer (MODIS) albedo data is available on the Greenland Ice Sheet, there is a lack of studies evaluating MODIS albedo products over Antarctica. In this paper, MOD10A1, MYD10A1, and MCD43 (C6) daily albedo products were compared with the in situ albedo data on Livingston Island, South Shetland Islands (SSI), Antarctica, from 2006 to 2015, for both all-sky and clear-sky conditions, and for the entire study period and only the southern summer months. This is the first evaluation in which MYD10A1 and MCD43 are also included, which can be used to improve the accuracy of the snow BRDF/albedo modeling. The best correlation was obtained with MOD10A1 in clear-sky conditions (r = 0.7 and RMSE = 0.042). With MCD43, only data from the backup algorithm could be used, so the correlations obtained were lower (r = 0.6). However, it was found that there was no significant difference between the values obtained for all-sky and for clear-sky data. In addition, the MODIS products were found to describe the in situ data trend, with increasing albedo values in the range between 0.04 decade−1 and 0.16 decade−1. We conclude that MODIS daily albedo products can be applied to study the albedo in the study area. [ABSTRACT FROM AUTHOR]

The India-France SARAL/AltiKa mission is the first Ka-band altimetric mission dedicated primarily to oceanography. The mission objectives were firstly the observation of the oceanic mesoscales but also global and regional sea level monitoring, including the coastal zone, data assimilation, and operational oceanography. SARAL/AltiKa proved also to be a great opportunity for inland waters applications, for observing ice sheet or icebergs, as well as for geodetic investigations. The mission ended its nominal phase after three years in orbit and began a new phase (drifting orbit) in July 2016. The objective of this paper is to highlight some of the most remarkable achievements of the SARAL/AltiKa mission in terms of scientific applications. Compared to the standard Ku-band altimetry measurements, the Ka-band provides substantial improvements in terms of spatial resolution and data accuracy. We show here that this leads to remarkable advances in terms of observation of the mesoscale and coastal ocean, waves, river water levels, ice sheets, icebergs, fine scale bathymetry features as well as for the many related applications. [ABSTRACT FROM AUTHOR]

Cross-correlation of image-pairs derived from both optical and synthetic aperture radar satellite imagery is the most common technique for measuring glacier flow velocity and quantifying the dynamics and discharge of glaciers. While the technique has been shown to be effective on polar ice sheets, the accuracy of satellite-derived velocities in temperate alpine regions is poorly constrained. Flow velocities were measured in situ using an RTK-GPS along four profiles on Taku, Matthes, Vaughan-Lewis, and Llewellyn Glaciers in southeast Alaska from 2016 through 2018. These GNSS-measured velocities were correlated against spatially coincident and contemporaneous satellite-derived velocity datasets, including both versions 1 and 2 of ITS_LIVE and velocities determined by offset tracking of SAR data in the Sentinel Application Platform (SNAP) and GAMMA (RETREAT dataset). Significant gaps in velocity maps derived from optical imagery (Landsat/Sentinel-2) were observed and determined to be due to low coherence rather than cloud contamination. Cross-correlation of SAR data (Sentinel-1) in SNAP and RETREAT achieved better accuracy compared to optical, although a strong dichotomy in performance was observed. SAR-derived velocities in the accumulation zone and transient snowline area showed overall poor correlation to GNSS-measured velocities that were likely due to significant shifts in the backscatter amplitude of the homogenous, snow-covered surface, although both SAR-derived SNAP and RETREAT velocities were anomalously accurate where GNSS velocities were below 0.10 m/day along the glacier margins. SNAP and RETREAT achieved the most accurate results in the study in the ablation zone of the Llewellyn Glacier where stable backscatter targets on the glacier surface (crevasses, supraglacial debris) facilitated high coherence in the cross-correlation procedure. SAR data are likely the most suitable for the derivation of satellite-derived velocities on temperate alpine glaciers, particularly in slow-moving and ablation zones, but should be subject to scrutiny for fast-flowing glaciers and those with an active hydrologic surface system. [ABSTRACT FROM AUTHOR]

Supraglacial meltwater accumulation on ice sheets can be a main driver for accelerated ice discharge, mass loss, and global sea-level-rise. With further increasing surface air temperatures, meltwater-induced hydrofracturing, basal sliding, or surface thinning will cumulate and most likely trigger unprecedented ice mass loss on the Greenland and Antarctic ice sheets. While the Greenland surface hydrological network as well as its impacts on ice dynamics and mass balance has been studied in much detail, Antarctic supraglacial lakes remain understudied with a circum-Antarctic record of their spatio-temporal development entirely lacking. This study provides the first automated supraglacial lake extent mapping method using Sentinel-1 synthetic aperture radar (SAR) imagery over Antarctica and complements the developed optical Sentinel-2 supraglacial lake detection algorithm presented in our companion paper. In detail, we propose the use of a modified U-Net for semantic segmentation of supraglacial lakes in single-polarized Sentinel-1 imagery. The convolutional neural network (CNN) is implemented with residual connections for optimized performance as well as an Atrous Spatial Pyramid Pooling (ASPP) module for multiscale feature extraction. The algorithm is trained on 21,200 Sentinel-1 image patches and evaluated in ten spatially or temporally independent test acquisitions. In addition, George VI Ice Shelf is analyzed for intra-annual lake dynamics throughout austral summer 2019/2020 and a decision-level fused Sentinel-1 and Sentinel-2 maximum lake extent mapping product is presented for January 2020 revealing a more complete supraglacial lake coverage (~770 km2) than the individual single-sensor products. Classification results confirm the reliability of the proposed workflow with an average Kappa coefficient of 0.925 and a F 1 -score of 93.0% for the supraglacial water class across all test regions. Furthermore, the algorithm is applied in an additional test region covering supraglacial lakes on the Greenland ice sheet which further highlights the potential for spatio-temporal transferability. Future work involves the integration of more training data as well as intra-annual analyses of supraglacial lake occurrence across the whole continent and with focus on supraglacial lake development throughout a summer melt season and into Antarctic winter. [ABSTRACT FROM AUTHOR]

David Glacier and Drygalski Ice Tongue are massive glaciers in Victoria Land, Antarctica. The ice from the East Antarctic Ice Sheet is drained through the former, and then discharged into the western Ross Sea through the latter. David Drygalski is the largest outlet glacier in Northern Victoria Land, floating kilometers out to sea. The floating and grounded part of the David Glacier are the main focus of this article. During the XXI Italian Antarctic Expedition (2005–2006), within the framework of the National Antarctic Research Programme (PNRA), two GNSS stations were installed at different points: the first close to the grounding line of David Glacier, and the second approximately 40 km downstream of the first one. Simultaneous data logging was performed by both GNSS stations for 24 days. In the latest data processing, the kinematic PPP technique was adopted to evaluate the dominant diurnal components and the very small semi-diurnal variations in ice motion induced by the ocean tide and the mean ice flow rates of both GNSS stations. Comparison of the GNSS time series with predicted ocean tide calculated from harmonic coefficients of the nearest tide gauge stations, installed at Cape Roberts and Mario Zucchelli Station, highlight different local response of the glacier to ocean tide, with a minor amplitude of vertical motion at a point partially anchored at the bedrock close to the grounding line. During low tide, the velocity of the ice flow reaches its daily maximum, in accordance with the direction of seawater outflow from the fjord into the ocean, while the greatest daily tidal excursion generates an increase in the horizontal ice flow velocity. With the aim to extend the analysis in spatial terms, five COSMO-SkyMED Stripmap scenes were processed. The comparison of the co-registered offset tracking rates, obtained from SAR images, with the GNSS estimation shows good agreement. [ABSTRACT FROM AUTHOR]

This paper presents an ice classification algorithm based on combined active and passive microwave radiometer data in Lützow-Holm Bay (LHB), East Antarctica. The ice classification algorithm is developed based on the threshold values of an advanced scatterometer (ASCAT) and advanced microwave scanning radiometer 2 (here, AMSR2). These values are calculated via the features of various ice types, including open ice, first-year (FY) ice, multi-year (MY) ice, MY ice including icebergs (MY IB), ice shelves, coastal ice sheets, and inland ice sheets. To verify the validity of the ice classification algorithm, the algorithm results are compared with visual observation data and satellite imagery. Except for the flaw polynya and area with surface melting, the FY ice, MY ice, and the ice shelf areas estimated here using the proposed ice classification algorithm match those discernible from the verification data. Inter-annual changes in the areal extents of FY ice, MY ice, and the ice shelves are investigated here using the proposed ice classification algorithm. Investigation of MY ice and ice shelf areas revealed that the breakup of MY ice induced a breakup of an ice shelf. A comparison of the FY ice and MY ice areas showed the replacement of these ice types. The proposed ice classification algorithm can detect ice breakup events as quantitative changes in the distribution and ice type. In future work, we plan to classify sea ice in other sea ice areas, applying the proposed algorithm throughout the Antarctic region. [ABSTRACT FROM AUTHOR]

The Antarctic ice sheet and the continent both play critical roles in global sea level rise and climate change but they remain poorly understood because data collection is greatly limited by the remote location and hostile conditions there. Airborne platforms have been extensively used in Antarctica due to their capabilities and flexibility and have contributed a great deal of knowledge to both the ice sheet and the continent. The Snow Eagle 601 fixed-wing airborne platform has been deployed by China for Antarctic expeditions since 2015. Scientific instruments on the airplane include an ice-penetrating radar, a gravimeter, a magnetometer, a laser altimeter, a camera and a Global Navigation Satellite System (GNSS). In the past five austral seasons, the airborne platform has been used to survey Princess Elizabeth Land, the largest data gap in Antarctica, as well as other critical areas. This paper reviews the scientific operations of Snow Eagle 601 including airborne and ground-based scientific instrumentation, aviation logistics, field data acquisition and processing and data quality control. We summarize the progress of airborne surveys to date, focusing on scientific motivations, data coverage and national and international collaborations. Finally, we discuss potential regions for applications of the airborne platform in Antarctica and developments of the airborne scientific system for future work. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) Tomography is a technique to provide direct three-dimensional (3D) imaging of the illuminated targets by processing SAR data acquired from different trajectories. In a large part of the literature, 3D imaging is achieved by assuming mono-dimensional (1D) approaches derived from SAR Interferometry, where a vector of pixels from multiple SAR images is transformed into a new vector of pixels representing the vertical profile of scene reflectivity at a given range, azimuth location. However, mono-dimensional approaches are only suited for data acquired from very closely-spaced trajectories, resulting in coarse vertical resolution. In the case of continuous media, such as forests, snow, ice sheets and glaciers, achieving fine vertical resolution is only possible in the presence of largely-spaced trajectories, which involves significant complications concerning the formation of 3D images. The situation gets even more complicated in the presence of irregular trajectories with variable headings, for which the one theoretically exact approach consists of going back to raw SAR data to resolve the targets by 3D back-projection, resulting in a computational burden beyond the capabilities of standard computers. The first aim of this paper is to provide an exhaustive discussion of the conditions under which high-quality tomographic processing can be carried out by assuming a 1D, 2D, or 3D approach to image formation. The case of 3D processing is then further analyzed, and a new processing method is proposed to produce high-quality imaging while largely reducing the computational burden, and without having to process the original raw data. Furthermore, the new method is shown to be easily parallelized and implemented using GPU processing. The analysis is supported by results from numerical simulations as well as from real airborne data from the ESA campaign AlpTomoSAR. [ABSTRACT FROM AUTHOR]

The internal layers of ice sheets from ice-penetrating radar (IPR) investigation preserve critical information about the ice-flow field and englacial conditions. This paper presents a new detailed analysis of spatial distribution characteristics of internal layers and subglacial topography of the East Antarctic ice sheet (EAIS) from Zhongshan Station to Dome A. The radar data of 1244 km along a traverse between Zhongshan Station and Dome A of EAIS were collected during the 29th Chinese National Antarctic Research Expedition (CHINARE 29, 2012/2013). In this study, the Internal Layering Continuity Index (ILCI) and basal roughness were taken as indicators to provide an opportunity to evaluate the past internal environment and dynamics of the ice sheet. Except for the upstream of Lambert Glacier, the fold patterns of internal layers are basically similar to that of the bed topography. The relatively flat basal topography and the decrease of ILCI with increasing depth provide evidence for identifying previous rapid ice flow areas that are unavailable to satellites, especially in the upstream of Lambert Glacier. Continuous internal layers of Dome A, recording the spatial change of past ice accumulation and ice-flow history over 160 ka, almost extend to the bed, with high ILCI and high basal roughness of the corresponding bed topography. There are three kinds of basal roughness patterns along the traverse, that is, "low ξt low η", "low ξt high η", and "high ξt high η", where ξt represents the amplitude of the undulations, and quantifies the vertical variation of the bedrock, and η measures the frequency variation of fluctuations and the horizontal irregularity of the profile. The characteristics of internal layers and basal topography of the traverse between Zhongshan Station and Dome A provide new information for understanding the ancient ice-flow activity and the historical evolution of EAIS. [ABSTRACT FROM AUTHOR]

Accurate monitoring of surface temperature and melting on the Greenland Ice Sheet (GrIS) is important for tracking the ice sheet's mass balance as well as global and Arctic climate change. Using a moderate-resolution-imaging-spectroradiometer (MODIS)-derived land-surface-temperature (LST) data product with a resolution of 1 km from 2000 to 2020, the temporal and spatial variations of annual and seasonal 'clear-sky' surface temperature were evaluated. We also monitored summer surface melting and studied the relationship between the mass balance of the ice sheet and changes in surface temperature and melting. The results show that the mean annual LST during the study period is −24.86 ± 5.46 °C, with the highest of −22.48 ± 5.61 °C in 2010 and the lowest temperature of −26.49 ± 5.30 °C in 2015. With the change of season, the spatial variation of the ice-sheet surface temperature changes greatly. 2012 and 2019 experienced the warmest summers (−5.92 ± 4.01 °C and −6.51 ± 3.93 °C), with extreme cumulative melting detected on the ice-sheet surface (89.9% and 89.7%, respectively), and 2002 also experienced a greater extent of melting. But short period of melt in 2002 and 2019 (30.6% and 31.4%, respectively), accounted for a larger proportion, with neither the duration nor intensity of the melt reaching that of 2012. There is a strong correlation between the GrIS surface temperature and its mass balance. By fitting the relationship between surface temperature and mass balance, it was found that 93.83% (6.17%) of the ice-sheet response to surface-temperature change was via surface-mass balance (discharge and basal-mass balance). [ABSTRACT FROM AUTHOR]

The Gamburtsev Subglacial Mountains (GSMs) in the interior East Antarctic Craton are entirely buried under the massive East Antarctic ice sheet, with a ~50–60 km thick crust and ~200 km thick lithosphere, but little is known of the crustal structure and uplift mechanism. Here, we use airborne gravity and aeromagnetic anomalies for characteristic analysis and inverse calculations. The gravity and magnetic images show three distinct geophysical domains. Based on the gravity anomalies, a dense lower crustal root is modelled to underlie the GSMs, which may have formed by underplating during the continental collision of Antarctica and India. The high frequency linear magnetic characteristics parallel to the suture zone suggest that the upper crustal architecture is dominated by thrusts, consisting of a large transpressional fault system with a trailing contractional imbricate fan. A 2D model along the seismic profile is created to investigate the crustal architecture of the GSMs with the aid of depth to magnetic source estimates. Combined with the calculated crustal geometry and physical properties and the geological background of East Antarctica, a new evolutionary model is proposed, suggesting that the GSMs are underlain by part of a Pan-African age advancing accretionary orogen superimposed on Precambrian basement. [ABSTRACT FROM AUTHOR]

High spatial and temporal resolution products of near-surface air temperature (T2m) over the Greenland Ice Sheet (GrIS) are required as baseline information in a variety of research disciplines. Due to the sparse network of in situ data on the GrIS, remote sensing data and machine learning methods provide great advantages, due to their capacity and accessibility. The Land Surface Temperature (LST) at 780 m resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) and T2m observation from 25 Automatic Weather Stations (AWSs) are used to establish a relationship over the GrIS by comparing multiple machine learning approaches. Four machine learning methods—neural network (NN), gaussian process regression (GPR), support vector machine (SVM), and random forest (RF)—are used to reconstruct the T2m at daily and monthly scales. We develop a reliable T2m reconstruction model based on key meteorological parameters, such as albedo, wind speed, and specific humidity. The reconstructions daily and monthly products are generated on a 780 m × 780 m spatial grid spanning from 2007 to 2019. When compared with in situ observations, the NN method presents the highest accuracy, with R of 0.96, RMSE of 2.67 °C, and BIAS of −0.36 °C. Similar to the regional climate model (RACMO2.3p2), the reconstructed T2m can better reflect the spatial pattern in term of latitude, longitude, and altitude effects. [ABSTRACT FROM AUTHOR]

Salt marshes are vulnerable to sea-level rise, sediment deficits, and storm impacts. To remain vertically resilient, salt marshes must accrete sediment at rates greater or equal to sea-level rise. Ice-rafted debris (IRD), sediment that has been moved and deposited from ice sheets, is one of many processes that contribute to salt marsh sediment accretion in northern latitudes. On 4 January 2018, a winter storm caused major ice mobilization in the Plum Island Estuary (PIE), Massachusetts, USA, which led to large deposits of ice-rafted sediment. We aimed to quantify the volume and mass of deposited sediment, and evaluate the significance of IRD to sediment supply in Plum Island using pixel-based land-cover classification of aerial imagery collected by an Unmanned Aircraft System (UAS) and a Digital Elevation Model. Field measurements of patch thickness, and the area of IRD determined from the classification were used to estimate annual sediment accretion from IRD. Results show that IRD deposits are localized in three areas, and estimates show that IRD contributes an annual sediment accretion rate of 0.57 ± 0.14 mm/y to the study site. New England salt marsh accretion rates typically vary between 2–10 mm/y, and the average PIE sediment accretion rate is 2.5–2.7 mm/y. Therefore, this event contributed on average 20% of the annual volume of material accreted by salt marshes, although locally the deposit thickness was 8–14 times the annual accretion rate. We show that pixel-based classification can be a useful tool for identifying sediment deposits from remote sensing. Additionally, we suggest that IRD has the potential to bring a significant supply of sediment to salt marshes in northern latitudes and contribute to sediment accretion. As remotely sensed aerial imagery from UASs becomes more readily available, this method can be used to efficiently identify and quantify deposited sediment. [ABSTRACT FROM AUTHOR]

Meteorological variables (e.g., air temperature (T2), radiation flux, and precipitation) determine the evolution of glacier mass and characteristics. Observations of these variables are not available with adequate spatial coverage and spatiotemporal resolution over the Tibetan Plateau. Albedo is the key factor of net radiation and is determined by the land cover and snow-related variables. This study focuses on evaluating the performance of the albedo parameterization scheme in WRF coupled with Noah-MP in terms of glacio-meteorological variables, by conducting experiments applying the standard surface albedo scheme with the default vegetation and corrected to ice cover and the modified glacial albedo scheme to the Parlung No. 4 Glacier in the 2016 ablation season. In situ glacio-meteorological element observations and MODIS-retrieved albedo are selected to assess the performance of the model. The key results are as follows. First, compared to the air temperature bias of 1.56 °C in WRF applying the standard surface albedo scheme and the default vegetation cover, realistic land-use categories considerably reduce the model warm bias on the glacier. The model using realistic land-use categories yields similar T2 diurnal patterns to the observations, with a mean bias of only −0.5 °C, no matter which glacial albedo scheme is implemented. Second, the default glacial albedo scheme gives a rather high albedo value of 0.68, causing an apparent underestimation of the net shortwave radiation and net radiation; the modified glacial albedo scheme gives a mean albedo value of 0.35, close to the in situ observations, helping to relieve underestimations of net shortwave radiation and net radiation. Compared with the MODIS albedo of the glacier, WRF applying the default glacial albedo scheme apparently overestimates the albedo with a mean error of 0.18, while WRF applying the modified glacial albedo scheme slightly underestimates the albedo with a mean error of only −0.08. Third, the mean net radiation flux (142 W m−2) and high ground heat flux (182 W m−2) values that were estimated by WRF applying the corrected land cover and the modified glacial albedo scheme result in the heating of the glacier surface and subsurface, causing ice melt and the liquid water content to increase more quickly and preferentially, equating to an estimated ice thickness decrease of 1 m by mid-June in the ablation region. Our study confirms the ability of the WRF model to reproduce glacio-meteorological variables as long as a reasonable glacial albedo scheme and the corrected land cover is applied and provides a theoretical reference for researchers that are committed to further improvement of the glacial albedo scheme. [ABSTRACT FROM AUTHOR]

The aim of this article is to characterize the penetration bias of the ENVIronmental SATellite (ENVISAT) radar altimeter over the Antarctic ice sheet through comparison with the more accurate measurements of the Ice, Cloud and land Elevation Satellite (ICESat) altimeter at crossover points. We studied the difference between ENVISAT and ICESat fluctuations over six years. We observed the same patterns between the leading edge width and the elevation difference. Both parameters are linked, and the major bias is due to the lengthening of the leading edge width due to the radar penetration. We show that the elevation difference between both altimeters and the leading edge width are linearly well-linked with a 0.8 Pearson correlation coefficient, whereas the slope effect over the coasts is difficult to analyze. When we analyze each crossover point temporal evolution locally, the linear correlation between the leading edge width and the elevation difference is between -0.6 and -1. Fitting a linear model between them, we find a reliability index greater than 0.7 for the Antarctic Plateau and Dronning Maud Land, which confirms that the penetration effect has a linear influence on the retrieved height. Moreover, we present results from SARAL/AltiKa (launched in February 2013) that confirm SARAL/AltiKa accuracy and the promising information it will provide. [ABSTRACT FROM AUTHOR]

The velocity of ice flow in the Antarctic is a crucial factor to determine ice discharge and thus future sea level rise. Feature tracking has been widely used in optical and radar imagery with fine resolution to retrieve flow parameters, although the primitive result may be contaminated by noise. In this paper, we present a series of modified post-processing steps, such as SNR thresholding by residual, complex Butterworth filters, and triple standard deviation truncation, to improve the performance of primitive results, and apply it to MODIS-based Mosaic of Antarctica (MOA) datasets. The final velocity field result displays the general flow pattern of the peripheral Antarctic. Seventy-eight out of 97 streamlines starting from seed points are smooth and continuous. The RMSE with 178 manually selected tie points is within 60 m·a−1. The systematic comparison with Making Earth System Data Records for Use in Research Environments (MEaSUREs) datasets in seven drainages shows that the results regarding high magnitude and large-scale ice shelf are highly reliable; absolute mean and median difference are less than 18 m·a−1, while the result of localized drainage suffered from too much tracking error. The relative differences from manually selected and random points are controlled within 8% when speed is beyond 500 m·a−1, but bias and uncertainty are pronounced when speed is lower than that. The result through our accuracy control strategy highlights that coarse remote-sensed images such as Moderate Resolution Imaging Spectrophotometer (MODIS) can still offer the capability for comprehensive and long-term continental ice sheet surface velocity mapping. [ABSTRACT FROM AUTHOR]

Ice velocity is one of the products associated with the Ice Sheets Essential Climate Variable. This paper describes the intercomparison and validation of ice-velocity measurements carried out by several international research groups within the European Space Agency Greenland Ice Sheet Climate Change Initiative project, based on space-borne Synthetic Aperture Radar (SAR) data. The goal of this activity was to survey the best SAR-based measurement and error characterization approaches currently in practice. To this end, four experiments were carried out, related to different processing techniques and scenarios, namely differential SAR interferometry, multi aperture SAR interferometry and offset-tracking of incoherent as well as of partially-coherent data. For each task, participants were provided with common datasets covering areas located on the Greenland ice-sheet margin and asked to provide mean velocity maps, quality characterization and a description of processing algorithms and parameters. The results were then intercompared and validated against GPS data, revealing in several cases significant differences in terms of coverage and accuracy. The algorithmic steps and parameters influencing the coverage, accuracy and spatial resolution of the measurements are discussed in detail for each technique, as well as the consistency between quality parameters and validation results. This allows several recommendations to be formulated, in particular concerning procedures which can reduce the impact of analyst decisions, and which are often found to be the cause of sub-optimal algorithm performance. [ABSTRACT FROM AUTHOR]

Blowing snow is a common weather phenomenon in Antarctica and plays an important role in the water vapor cycle and ice sheet mass balance. Although it has a significant impact on the climate of Antarctica, people do not know much about this process. Fog events are difficult to distinguish from blowing snow events using existing detection algorithms by a ceilometer. In this study, based on ceilometer, the meteorological parameters observed by surface meteorology systems are further combined to detect blowing snow and fog using the AdaBoost algorithm. The weather phenomena recorded by human observers are 'true'. The dataset is collected from 1 January 2016 to 31 December 2016 at the AWARE site. Among them, three-quarters of the data are used as the training set and the rest of the data as the testing set. The classification accuracy of the proposed algorithm for the testing set is about 94%. Compared with the Loeb method, the proposed algorithm can detect 89.12% of blowing snow events and 76.10% of fog events, while the Loeb method can only identify 64.29% of blowing snow events and 31.87% of fog events. [ABSTRACT FROM AUTHOR]

Arctic warming is leading to substantial changes to permafrost including rapid degradation of ice and ice-rich coasts and riverbanks. In this study, we present and evaluate a high spatiotemporal resolution three-year time series of X-Band microwave satellite data from the TerraSAR-X (TSX) satellite to quantify cliff-top erosion (CTE) of an ice-rich permafrost riverbank in the central Lena Delta. We apply a threshold on TSX backscatter images and automatically extract cliff-top lines to derive intra- and inter-annual CTE. In order to examine the drivers of erosion we statistically compare CTE with climatic baseline data using linear mixed models and analysis of variance (ANOVA). Our evaluation of TSX-derived CTE against annual optical-derived CTE and seasonal in situ measurements showed good agreement between all three datasets. We observed continuous erosion from June to September in 2014 and 2015 with no significant seasonality across the thawing season. We found the highest net annual cliff-top erosion of 6.9 m in 2014, in accordance with above-average mean temperatures and thawing degree days as well as low precipitation. We found high net annual erosion and erosion variability in 2015 associated with moderate mean temperatures but above average precipitation. According to linear mixed models, climate parameters alone could not explain intra-seasonal erosional patterns and additional factors such as ground ice content likely drive the observed erosion. Finally, mean backscatter intensity on the cliff surface decreased from 􀀀5.29 to 􀀀6.69 dB from 2013 to 2015, respectively, likely resulting from changes in surface geometry and properties that could be connected to partial slope stabilization. Overall, we conclude that X-Band backscatter time series can successfully be used to complement optical remote sensing and in situ monitoring of rapid tundra permafrost erosion at riverbanks and coasts by reliably providing information about intra-seasonal dynamics. [ABSTRACT FROM AUTHOR]

Englacial layering reflects ice dynamics within the ice bodies, which improves understanding of ice flow variation, past accumulation rates and vertical flows transferring between the surface and the underlying bedrock. The internal layers can be observed by using Radar Echo Sounding (RES), such as the Multi-channel Coherent Radar Depth Sounder (MCoRDS) used in NASA's Operation IceBridge (OIB) mission. Since the 1960s, the accumulation of the RES data has prompted the development of automated methods to extract the englacial layers. In this study, we propose a new automated method that combines peak detection methods, namely the CWT-based peak detection or the Automatic Phase Picker (APP), with a Hough Transform (HT) to trace boundaries of englacial layers. For CWT-based peak detection, we test it using two different wavelets. The proposed method is tested with twelve MCoRDS radio echograms, which are acquired south of the Northern Greenland Eemian (NEEM) ice drilling site, where the folding of ice layers was observed. The method is evaluated in comparison to the isochrones that were extracted in an independent study. In comparison, the proposed new automated method can restore more than 70% of the englacial layers. This new automated layer-tracing method is publicly available on github. [ABSTRACT FROM AUTHOR]

In this study, the ice velocity changes from 2004 to 2015 of the Polar Record Glacier (PRG) in East Antarctica were investigated based on a feature-tracking method using Landsat-7 enhanced thematic mapper plus (ETM+) and Landsat-8 operational land imager (OLI) images. The flow field of the PRG curves make it difficult to generate ice velocities in some areas using the traditional normalized cross-correlation (NCC)-based feature-tracking method. Therefore, a rotation-invariant parameter from scale-invariant feature transform (SIFT) is introduced to build a novel rotation-invariant feature-tracking approach. The validation was performed based on multi-source images and the making earth system data records for use in research environments (MEaSUREs) interferometric synthetic aperture radar (InSAR)-based Antarctica ice velocity map data set. The results indicate that the proposed method is able to measure the ice velocity in more areas and performs as well as the traditional NCC-based feature-tracking method. The sequential ice velocities obtained present the variations in the PRG during this period. Although the maximum ice velocity of the frontal margin of the PRG and the frontal iceberg reached about 900 m/a and 1000 m/a, respectively, the trend from 2004 to 2015 showed no significant change. Under the interaction of the Polar Times Glacier and the Polarforschung Glacier, both the direction and the displacement of the PRG were influenced. This impact also led to higher velocities in the western areas of the PRG than in the eastern areas. In addition, elevation changes and frontal iceberg calving also impacted the ice velocity of the PRG. [ABSTRACT FROM AUTHOR]

The Arctic sea ice cover has decreased strongly in extent, thickness, volume and age in recent decades. The melt season presents a significant challenge for sea ice forecasting due to uncertainty associated with the role of surface melt ponds in ice decay at regional scales. This study quantifies the relationships of spring melt pond fraction (fp) with both winter sea ice roughness and thickness, for landfast first-year sea ice (FYI) and multiyear sea ice (MYI). In 2015, airborne measurements of winter sea ice thickness and roughness, as well as high-resolution optical data of melt pond covered sea ice, were collected along two ~5.2 km long profiles over FYI- and MYI-dominated regions in the Canadian Arctic. Statistics of winter sea ice thickness and roughness were compared to spring fp using three data aggregation approaches, termed object and hybrid-object (based on image segments), and regularly spaced grid-cells. The hybrid-based aggregation approach showed strongest associations because it considers the morphology of the ice as well as footprints of the sensors used to measure winter sea ice thickness and roughness. Using the hybrid-based data aggregation approach it was found that winter sea ice thickness and roughness are related to spring fp. A stronger negative correlation was observed between FYI thickness and fp (Spearman rs = -0.85) compared to FYI roughness and fp (rs = -0.52). The association between MYI thickness and fp was also negative (rs = -0.56), whereas there was no association between MYI roughness and fp. 47% of spring fp variation for FYI and MYI can be explained by mean thickness. Thin sea ice is characterized by low surface roughness allowing for widespread ponding in the spring (high fp) whereas thick sea ice has undergone dynamic thickening and roughening with topographic features constraining melt water into deeper channels (low fp). This work provides an important contribution towards the parameterizations of fp in seasonal and long-term prediction models by quantifying linkages between winter sea ice thickness and roughness, and spring fp. [ABSTRACT FROM AUTHOR]

Sea ice monitoring and classification is one of the main applications of Synthetic Aperture Radar (SAR) remote sensing. C-band SAR imagery is regarded as an optimal choice for sea ice applications; however, other SAR frequencies has not been extensively assessed. In this study, we evaluate the potential of fully polarimetric L-band SAR imagery for monitoring and classifying sea ice during dry winter conditions compared to fully polarimetric C-band SAR. Twelve polarimetric SAR parameters are derived using sets of C- and L-band SAR imagery and the capabilities of the derived parameters for the discrimination between First Year Ice (FYI) and Old Ice (OI), which is considered to be a mixture of Second Year Ice (SYI) and Multiyear Ice (MYI), are investigated. Feature vectors of effective C- and L-band polarimetric parameters are extracted and used for sea ice classification. Results indicate that C-band SAR provides high classification accuracy (98.99%) of FYI and OI in comparison to the obtained accuracy using L-band SAR (82.17% and 81.85%), as expected. However, L-band SAR was found to classify only the MYI floes as OI, while merging both FYI and SYI into one separate class. This comes in contrary to C-band SAR, which classifies as OI both MYI and SYI. This indicates a new potential for discriminating SYI from MYI by combining C- and L-band SAR in dry ice winter conditions. [ABSTRACT FROM AUTHOR]

The assessment of water body dynamics is not only in itself a topic of strong demand, but the presence of water bodies is important information when it comes to the derivation of products such as land surface temperature, leaf area index, or snow/ice cover mapping from satellite data. For the TIMELINE project, which aims to derive such products for a long time series of Advanced Very High Resolution Radiometer (AVHRR) data for Europe, precise water masks are therefore not only an important stand-alone product themselves, they are also an essential interstage information layer, which has to be produced automatically after preprocessing of the raw satellite data. The respective orbit segments from AVHRR are usually more than 2000 km wide and several thousand km long, thus leading to fundamentally different observation geometries, including varying sea surface temperatures, wave patterns, and sediment and algae loads. The water detection algorithm has to be able to manage these conditions based on a limited amount of spectral channels and bandwidths. After reviewing and testing already available methods for water body detection, we concluded that they cannot fully overcome the existing challenges and limitations. Therefore an extended approach was implemented, which takes into account the variations of the reflectance properties of water surfaces on a local to regional scale; the dynamic local threshold determination will train itself automatically by extracting a coarse-scale classification threshold, which is refined successively while analyzing subsets of the orbit segment. The threshold is then interpolated by fitting a minimum curvature surface before additional steps also relying on the brightness temperature are included to reduce possible misclassifications. The classification results have been validated using Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data and proven an overall accuracy of 93.4%, with the majority of errors being connected to flawed geolocation accuracy of the AVHRR data. The presented approach enables the derivation of long-term water body time series from AVHRR data and is the basis for applied geoscientific studies on large-scale water body dynamics. [ABSTRACT FROM AUTHOR]

Growing interest in supraglacial channels, coupled with the increasing availability of high-resolution remotely sensed imagery of glacier surfaces, motivates the development and testing of new approaches to delineating surface meltwater channels. We utilized a high-resolution (2 m) digital elevation model of parts of the western margin of the Greenland Ice Sheet (GrIS) and retention of visually identified sinks (i.e., moulins) to investigate the ability of a standard D8 flow routing algorithm to delineate supraglacial channels. We compared these delineated channels to manually digitized channels and to channels extracted from multispectral imagery. We delineated GrIS supraglacial channel networks in six high-elevation (above 1000 m) and one low-elevation (below 1000 m) catchments during and shortly after peak melt (July and August 2012), and investigated the effect of contributing area threshold on flow routing performance. We found that, although flow routing is sensitive to data quality and moulin identification, it can identify 75% to 99% of channels observed with multispectral analysis, as well as low-order, high-density channels (up to 15.7 km/km2 with a 0.01 km2 contributing area threshold) in greater detail than multispectral methods. Additionally, we found that flow routing can delineate supraglacial channel networks on rough ice surfaces with widespread crevassing. Our results suggest that supraglacial channel density is sufficiently high during peak melt that low contributing area thresholds can be employed with little risk of overestimating the channel network extent. [ABSTRACT FROM AUTHOR]

In 2018, the National Aeronautics and Space Administration (NASA) is scheduled to launch the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2), with a new six-beam, green-wavelength, photon-counting lidar system, Advanced Topographic Laser Altimeter System (ATLAS). The primary objectives of the ICESat-2 mission are to measure ice-sheet elevations, sea-ice thickness, and global biomass. However, if bathymetry can be reliably retrieved from ATLAS data, this could assist in addressing a key data need in many coastal and inland water body areas, including areas that are poorly-mapped and/or difficult to access. Additionally, ATLAS-derived bathymetry could be used to constrain bathymetry derived from complementary data, such as passive, multispectral imagery and synthetic aperture radar (SAR). As an important first step in evaluating the ability to map bathymetry from ATLAS, this study involves a detailed assessment of bathymetry from the Multiple Altimeter Beam Experimental Lidar (MABEL), NASA's airborne ICESat-2 simulator, flown on the Earth Resources 2 (ER-2) high-altitude aircraft. An interactive, web interface, MABEL Viewer, was developed and used to identify bottom returns in Keweenaw Bay, Lake Superior. After applying corrections for refraction and channel-specific elevation biases, MABEL bathymetry was compared against National Oceanic and Atmospheric Administration (NOAA) data acquired two years earlier. The results indicate that MABEL reliably detected bathymetry in depths of up to 8 m, with a root mean square (RMS) difference of 0.7 m, with respect to the reference data. Additionally, a version of the lidar equation was developed for predicting bottom-return signal levels in MABEL and tested using the Keweenaw Bay data. Future work will entail extending these results to ATLAS, as the technical specifications of the sensor become available. [ABSTRACT FROM AUTHOR]

The presence of sea-ice leads represents a key feature of the Arctic sea ice cover. Leads promote the flux of sensible and latent heat from the ocean to the cold winter atmosphere and are thereby crucial for air-sea-ice-ocean interactions. We here apply a binary segmentation procedure to identify leads from MODIS thermal infrared imagery on a daily time scale. The method separates identified leads into two uncertainty categories, with the high uncertainty being attributed to artifacts that arise from warm signatures of unrecognized clouds. Based on the obtained lead detections, we compute quasi-daily pan-Arctic lead maps for the months of January to April, 2003-2015. Our results highlight the marginal ice zone in the Fram Strait and Barents Sea as the primary region for lead activity. The spatial distribution of the average pan-Arctic lead frequencies reveals, moreover, distinct patterns of predominant fracture zones in the Beaufort Sea and along the shelf-breaks, mainly in the Siberian sector of the Arctic Ocean as well as the well-known polynya and fast-ice locations. Additionally, a substantial inter-annual variability of lead occurrences in the Arctic is indicated. [ABSTRACT FROM AUTHOR]

The winter regime of river-ice covers in high northern latitude regions is often a determining factor in the management of water resources, conservation of aquatic ecosystems and preservation of traditional and cultural lifestyles of local peoples. As ground-based monitoring of river-ice regimes in high northern latitudes is expensive and restricted to a few locations due to limited accessibility to most places along rivers from shorelines, remote sensing techniques are a suitable approach for monitoring. This study developed a RADARSAT-2 based method to monitor the spatio-temporal variation of ice covers, as well as ice types during the freeze-up period, along the main channel of the Slave River Delta in the Northwest Territories of Canada. The spatio-temporal variation of ice covers along the river was analyzed using the backscatter-based coefficient of variation (CV) in the 2013-2014 and 2014-2015 winters. As a consequence of weather and flow conditions, the ice cover in the 2013-2014 winter had the higher variation than the 2014-2015 winter, particularly in the potential areas of flooded/cracked ice covers. The river sections near active channels (e.g., Middle Channel and Nagle Channel), Big Eddy, and Great Slave Lake also yielded higher intra-annual variation of ice cover characteristics during the winters. With the inclusion of backscatter and texture analysis from RADARSAT-2 data, four water and ice cover classes consisting of open water, thermal ice, juxtaposed ice, and consolidated ice, were discriminated in the images acquired between November and March in both the studied winters. In addition to river geomorphology and climatic conditions such as river width, sinuosity or air temperature, the fluctuation of water flows during the winter has a significant impact on the variation of ice cover as well as the formation of different ice types in the Slave River. The RADARSAT-2 based monitoring algorithm can also be applied to other river systems in high latitude ecosystems to annually monitor their river-ice variation and formation during the freeze-up and ice cover progression period. [ABSTRACT FROM AUTHOR]

The Sentinel satellite constellation series, developed by the European Space Agency, represents the dedicated space component of the European Copernicus program, committed to long-term operational services in a wide range of application domains. Here, we address the potential of the Sentinel-1 mission for mapping and monitoring the surface velocity of glaciers and ice sheets. We present an ice velocity map of Greenland, derived from synthetic aperture radar (SAR) data acquired in winter 2015 by Sentinel-1A, the first satellite of the Copernicus program in orbit. The map is assembled from about 900 SAR scenes acquired in Interferometric Wide swath (IW) mode, applying the offset tracking technique. We discuss special features of IW mode data, describe the procedures for producing ice velocity maps, and assess the uncertainty of the ice motion product. We compare the Sentinel-1 ice motion product with velocity maps derived from high resolution SAR data of the TerraSAR-X mission and from PALSAR data. Beyond supporting operational services, the Sentinel-1 mission offers enhanced capabilities for comprehensive and long-term observation of key climate variables, such as the motion of ice masses. [ABSTRACT FROM AUTHOR]

We use 124 scenes of TerraSAR-X data that were acquired in 2009 and 2010 to analyse the spatial and temporal variability in surface kinematics of the debris-covered Inylchek Glacier, located in the Tien Shan mountain range in Central Asia. By applying the feature tracking method to the intensity information of the radar data and combining the results from the ascending and descending orbits, we derive the surface velocity field of the glaciated area. Analysing the seasonal variations over the upper part of the Southern Inylchek branch, we find a temperature-related increase in velocity from 25 cm/d up to 50 cm/d between spring and summer, with the peak occurring in June. Another prominent velocity peak is observable one month later in the lower part of the Southern Inylchek branch. This area shows generally little motion, with values of approximately 5-10 cm/d over the year, but yields surface kinematics of up to 25 cm/d during the peak period. Comparisons of the dates of annual glacial lake outburst floods (GLOFs) of the proglacial Lake Merzbacher suggest that this lower part is directly influenced by the drainage, leading to the observed mini-surge, which has over twice the normal displacement rate. With regard to the GLOF and the related response of Inylchek Glacier, we conclude that X-band radar systems such as TerraSAR-X have a high potential for detecting and characterising small-scale glacial surface kinematic variations and should be considered for future inter-annual glacial monitoring tasks. [ABSTRACT FROM AUTHOR]

Altimetry is probably one of the most powerful tools for ice sheet observation. Our vision of the Antarctic ice sheet has been deeply transformed since the launch of the ERS1 satellite in 1991. With the launch of ERS2 and Envisat, the series of altimetric observations now provides 19 years of continuous and homogeneous observations that allow monitoring of the shape and volume of ice sheets. The topography deduced from altimetry is one of the relevant parameters revealing the processes acting on ice sheet. Moreover, altimeter also provides other parameters such as backscatter and waveform shape that give information on the surface roughness or snow pack characteristics. [ABSTRACT FROM AUTHOR]

Crevasses are formed by glacier movement and the stresses within glacier ice. Knowledge of the crevasses' distribution is critical for understanding the glacier and ice shelf stability. In this study, we propose an automated crevasse extraction framework based on Sentinel-1 SAR imagery and an improved U-Net network. The spatial distribution of crevasses on Antarctic ice shelves in 2020 was mapped with a spatial resolution of ~40 m, and the characteristics of crevasses on the Nickerson Ice Shelf, Jelbart Ice Shelf, Amery Ice Shelf, Thwaites Glacier, and Shackleton Ice Shelf were analyzed. The results indicated the extraction accuracy of our method was 84.2% and the F1 score was 72.5%. Compared with previous published studies, the identification of the crevasse areas had good visual consistency. However, in some scenes, the recall rate was relatively lower due to the quality of the SAR image, terrain surrounding the crevasses, and observation geometry. The crevasses on different ice shelves had different characteristics in terms of length, density, type, and spatial pattern, implying the different stress structures of ice shelves. The Thwaites Glacier and the Nickerson Ice Shelf in the West Antarctica Ice Sheet (WAIS) had shorter ice crevasses, whereas the lengths of ice crevasses on the Jelbart Ice Shelf and the Amery Ice Shelf in the East Antarctica Ice Sheet (EAIS) were relatively long. Nevertheless, there are more closely spaced crevasses on the ice shelf in WAIS compared to that in the EAIS. For the distribution of crevasse types, the Nickerson Ice Shelf and the Shackleton Ice Shelf had various forms of crevasses. There were mainly transverse crevasses developed on the Jelbart Ice Shelf and the Amery Ice Shelf. This study provides a helpful reference and guidance for automated crevasse extraction. The method proposed by this study manifests great application potential and the efficacy of producing a time-series crevasse data set with higher spatial resolution and larger coverage. In the future, more Sentinel-1 SAR imagery will be applied and the effect of temporal and spatial variations in crevasses on the stability of ice shelves will be investigated, which will contribute to project the ice shelf stability and explore the sea level rise implications of recent and future cryosphere changes. [ABSTRACT FROM AUTHOR]

Ice surface albedo is a primary modulator of melt and runoff, yet our understanding of how reflectance varies over time across the Greenland Ice Sheet remains poor. This is due to a disconnect between point or transect scale albedo sampling and the coarser spatial, spectral and/or temporal resolutions of available satellite products. Here, we present time-series of bare-ice surface reflectance data that span a range of length scales, from the 500 m for Moderate Resolution Imaging Spectrometer's MOD10A1 product, to 10 m for Sentinel-2 imagery, 0.1 m spot measurements from ground-based field spectrometry, and 2.5 cm from uncrewed aerial drone imagery. Our results reveal broad similarities in seasonal patterns in bare-ice reflectance, but further analysis identifies short-term dynamics in reflectance distribution that are unique to each dataset. Using these distributions, we demonstrate that areal mean reflectance is the primary control on local ablation rates, and that the spatial distribution of specific ice types and impurities is secondary. Given the rapid changes in mean reflectance observed in the datasets presented, we propose that albedo parameterizations can be improved by (i) quantitative assessment of the representativeness of time-averaged reflectance data products, and, (ii) using temporally-resolved functions to describe the variability in impurity distribution at daily time-scales. We conclude that the regional melt model performance may not be optimally improved by increased spatial resolution and the incorporation of sub-pixel heterogeneity, but instead, should focus on the temporal dynamics of bare-ice albedo. [ABSTRACT FROM AUTHOR]

In this study, we present a new level-2 processing chain dedicated to the CryoSat-2 Synthetic Aperture Radar Interferometric (SARIn) measurements acquired over ice sheets. Compared to the ESA ground segment processor, it includes revised methods to detect waveform leading edges and perform retracking at the Point of Closest Approach (POCA). CryoSat-2 SARIn mode surface height measurements retrieved from the newly developed processing chain are compared to ICESat-2 surface height measurements extracted from the ATL06 product. About 250,000 space–time nearly coincident observations are identified and examined over the Antarctic ice sheet, and over a one-year period. On average, the median elevation bias between both missions is about −18 cm, with CryoSat-2 underestimating the surface topography compared to ICESat-2. The Median Absolute Deviation (MAD) between CryoSat-2 and ICESat-2 elevation estimates is 46.5 cm. These performances were compared to those obtained with CryoSat-2 SARIn mode elevations from the ESA PDGS level-2 products (ICE Baseline-D processor). The MAD between CryoSat-2 and ICESat-2 elevation estimates is significantly reduced with the new processing developed, by about 42%. The improvement is more substantial over areas closer to the coast, where the topography is more complex and surface slope increases. In terms of perspectives, the impacts of surface roughness and volume scattering on the SARIn mode waveforms have to be further investigated. This is crucial to understand geographical variations of the elevation bias between CryoSat-2 and ICESat-2 and continue enhancing the SARIn mode level-2 processing. [ABSTRACT FROM AUTHOR]

Antarctic geothermal heat flux is a basic input variable for ice sheet dynamics simulation. It greatly affects the temperature and mechanical properties at the bottom of the ice sheet, influencing sliding, melting, and internal deformation. Due to the fact that the Antarctica is covered by a thick ice sheet, direct measurements of heat flux are very limited. This study was carried out to estimate the regional heat flux in the Antarctic continent through geophysical inversion. Princess Elizabeth Land, East Antarctica is one of the areas in which we have a weak understanding of geothermal heat flux. Through the latest airborne geomagnetic data, we inverted the Curie depth, obtaining the heat flux of bedrock based on the one-dimensional steady-state heat conduction equation. The results indicated that the Curie depth of the Princess Elizabeth Land is shallower than previously estimated, and the heat flux is consequently higher. Thus, the contribution of subglacial heat flux to the melting at the bottom of the ice sheet is likely greater than previously expected in this region. It further provides research clues for the formation of the developed subglacial water system in Princess Elizabeth Land. [ABSTRACT FROM AUTHOR]