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Jakobshavn Isbrae, West Greenland, which holds a 0.6 m sea level volume equivalent, has been speeding up and retreating since the late 1990s. Interpretation of its retreat has been hindered by difficulties in measuring its ice thickness with airborne radar depth sounders. Here we employ high-resolution, helicopter-borne gravity data from 2012 to reconstruct its bed elevation within 50 km of the ocean margin using a three-dimensional inversion constrained by fjord bathymetry data offshore and a mass conservation algorithm inland. We find the glacier trough to be asymmetric and several 100 m deeper than estimated previously in the lower part. From 1996 to 2016, the grounding line migrated at 0.6 km/yr from 700 m to 1100 m depth. Upstream, the bed drops to 1600 m over 10 km then slowly climbs to 1200 m depth in 40 km. Jakobshavn Isbrae will continue to retreat along a retrograde slope for decades to come.

We document the existence of widespread firn aquifers in an elevation range of ~1200–2000 m, in the high snow-accumulation regions of the Greenland ice sheet. We use NASA Operation IceBridge accumulation radar data from five campaigns (2010–2014) to estimate a firn-aquifer total extent of 21,900 km2. We investigate two locations in Southeast Greenland, where repeated radar profiles allow mapping of aquifer-extent and water table variations. In the upper part of Helheim Glacier the water table rises in spring following above-average summer melt, showing the direct firn-aquifer response to surface meltwater production changes. After spring 2012, a drainage of the firn-aquifer lower margin (5 km) is inferred from both 750 MHz accumulation radar and 195 MHz multicoherent radar depth sounder data. For 2011–2014, we use a ground-penetrating radar profile located at our Ridgeline field site and find a spatially stable aquifer with a water table fluctuating less than 2.5 m vertically. When combining radar data with surface topography, we find that the upper elevation edge of firn aquifers is located directly downstream of locally high surface slopes. Using a steady state 2-D groundwater flow model, water is simulated to flow laterally in an unconfined aquifer, topographically driven by ice sheet surface undulations until the water encounters crevasses. Simulations suggest that local flow cells form within the Helheim aquifer, allowing water to discharge in the firn at the steep-to-flat transitions of surface topography. Supported by visible imagery, we infer that water drains into crevasses, but its volume and rate remain unconstrained.

We assess the impact of known and unknown position errors on two variations of the Minimum Variance Distortionless Response (MVDR) algorithm specifically for measurements using multipass, swarms or constellations that involve non-rigid and varying sensor offsets. We consider this in the context of the radar systems and autonomous aircraft used by Center for the Remote Sensing of Ice Sheets (CReSIS) for conducting measurements of snow and ice in polar regions. We find that unknown position errors affect all algorithms in a uniform way and that the performance impact is not related to known position errors. We also find that MVDR is largely unaffected by known position errors except when the number of elements is small. However, self-nulling can result in substantially worse performance than even the simple nonadaptive periodogram method.

We apply two classification machine learning methods, one versus all logistic regression and a simple neural network, to estimate the model order or number of sources for parametric direction of arrival estimation using a wideband dataset with low snapshots and a range of signal to noise ratios. This particular scenario is of interest because it is common in the radar ice sounding datasets collected by the Center for Remote Sensing of Ice Sheets. We compare results with six standard model order estimation methods that use various functional forms for the cost function. We also compare against a numerically tuned method which is related to the machine learning methods, but the simple optimization method was not as capable as the machine learning methods and the cost function formulation is different. We find that the machine learning based methods outperform all the compared methods for our test cases, suggesting that this is a promising solution to the wideband model order estimation problem.

We present a compact, multi-channel, wideband VHF radar system for fine-resolution measurements of the base and interior of large ice sheets. Data from this radar will be used in the identification of potential drill locations to retrieve ice core samples more than 1 million years old in East Antarctica. The radar is a lightweight instrument equipped with four >1-kW peak power transmit channels, eight independent digital receivers, and an array of high-gain antennas. We developed the system as part of a collaborative effort between the United States of America, Japan and Norway. The instrument was used for surface-based surveys near Dome-Fuji onboard a tracked vehicle during the 2018/2019 Austral Summer, covering 2,000 line-km. This paper presents an overview of the radar system, accompanied by laboratory and field test results that demonstrate the system’s ability to map the internal ice sheet structure and basal conditions with outstanding detail.

Snow in mountainous areas provides freshwater resources for lower basins and coastal areas. Snow layering at mountain summits contains information about local seasonal snow accumulation and climate history. Knowledge of snow depths is required to estimate the snow water equivalent. However, monitoring spatial distribution and temporal changes in snow depth and accumulation over remote mountains and glaciers in wide areas is challenging because of limited accessibility for in-situ measurements. As a part of NASA Operation IceBridge missions, we took airborne radar measurements of snow over Alaskan mountains, icefields and glaciers in late May of 2018, with a compact frequency-modulated continuous wave radar system, operating from 2 GHz to 8 GHz and installed on a Single Otter aircraft. In this paper, we describe the radar instrument, its installation onto the platform, the data collection and processing activities, and report the major results from these surveys. We observed seasonal snow depth between ~0.3 m to ~15 m for elevations above sea level from ~1726 m to ~3624 m. We successfully mapped snow accumulation layers to depths exceeding ~85 m below the surface at high-elevation summits of Mount Wrangell and Bona. The traced snow depth profiles over glaciers and accumulation layers at mountain summits point to the utility of these data to the study of water resource management, hydrology modelling, and regional climate change.

Ice loss measurements around the periphery of the Greenland Ice Sheet can provide key information on the response to climate change. Here we use the excellent spatial and temporal coverage provided by the European Space Agency (ESA) CryoSat satellite, together with NASA airborne Operation IceBridge and automatic weather station data, to study the influence of changing conditions on the bias between the height estimated by the satellite radar altimeter and the ice sheet surface. Surface and near-surface conditions on the ice sheet periphery change with season and geographic position in a way that affects the returned altimeter waveform and can therefore affect the estimate of the surface height derived from the waveform. Notwithstanding the possibility of a varying bias between the derived and real surface, for the lower accumulation regions in the western and northern ice sheet periphery (

The mapping of internal annual layers in polar firn with ultra-wideband (UWB) surface-based and airborne radars enables the assessment of past snow accumulation amounts and patterns. We used a UWB microwave radar (snow radar) to image and track internal layers in firn over hundreds of kilometers in West Antarctica (WA). We used dated ice-core records to determine that stratigraphic internal layers (SILs) are mainly formed in spring. The analysis uncertainty is generally small, with the highest values associated with regions and/or years with low accumulation. In survey regions with multiple ice-core records, the choice of ice-core record used for the radar analysis was found to have a very small contribution to the overall analysis uncertainty.

We developed a multichannel wideband synthetic aperture radar (SAR) that operates over a frequency range of 190–450 MHz for measurements over the ice sheets in Antarctica and Greenland. The antenna-array, which consists of eight elements housed in a certified external structure for a BASLER aircraft, was used for measurements during the 2013–2014 Antarctic field season. We performed measurements with this system in conjunction with two ultra-wideband radars operating over a frequency range of 2–8 GHz and 12–18 GHz on Siple Coast ice streams in West Antarctica during December 2013 and January 2014. We sounded ice thicker than 2 km with a signal-to-noise ratio (SNR) of more than 20 dB in an area with two-way ice loss of about 27 dB/km. The same system also simultaneously mapped near-surface internal layers with submeter resolution from the ice-surface to a depth of about 1100 for 1200 m thick ice. In this paper, we provide a detailed overview of the radar instrumentation and signal processing algorithms and present a few sample results. The radar will be operated over a frequency range of 150–550 MHz with a 24-element antenna-array for wide-ranging measurements over the Greenland and Antarctic ice sheets, starting around August 2015.

Keeping a stiff upper layer The interior of the Greenland Ice Sheet is growing thicker, in contrast to the thinning that is occurring at its edges. Why? MacGregor et al. conclude that more snow is accumulating and that the ice in the interior is flowing more slowly than it did thousands of years ago (see the Perspective by Hvidberg). During the last glacial period, higher rates of atmospheric dust deposition produced softer ice, which flowed more readily than cleaner ice. During most of the Holocene, though, atmospheric dust concentrations were lower, and the less-dusty ice that formed was stiffer, meaning it did not flow or thin so rapidly. Thus, the thickening seen today in the central regions of Greenland is partly a response to changes in ice rheology that occurred thousands of years ago. Science , this issue p. 590 ; see also p. 562

Researchers present the first unambiguous discovery of a 31-km-wide impact crater buried beneath the Greenland Ice Sheet., We report the discovery of a large impact crater beneath Hiawatha Glacier in northwest Greenland. From airborne radar surveys, we identify a 31-kilometer-wide, circular bedrock depression beneath up to a kilometer of ice. This depression has an elevated rim that cross-cuts tributary subglacial channels and a subdued central uplift that appears to be actively eroding. From ground investigations of the deglaciated foreland, we identify overprinted structures within Precambrian bedrock along the ice margin that strike tangent to the subglacial rim. Glaciofluvial sediment from the largest river draining the crater contains shocked quartz and other impact-related grains. Geochemical analysis of this sediment indicates that the impactor was a fractionated iron asteroid, which must have been more than a kilometer wide to produce the identified crater. Radiostratigraphy of the ice in the crater shows that the Holocene ice is continuous and conformable, but all deeper and older ice appears to be debris rich or heavily disturbed. The age of this impact crater is presently unknown, but from our geological and geophysical evidence, we conclude that it is unlikely to predate the Pleistocene inception of the Greenland Ice Sheet.

We present improvements to existing implementations of the Viterbi and TRW-S algorithms applied to ice-bottom layer tracking on 2D and 3D radar imagery, respectively. Along with an explanation of our modifications and the reasoning behind them, we present a comparison between our results, the results obtained with the original implementations, and those obtained with other proposed methods of performing ice-bottom layer tracking.

In 2014, as part of the NASA Operation IceBridge project, the Center for Remote Sensing of Ice Sheets operated a multi-beam synthetic aperture radar depth sounder/imager over the Canadian Arctic Archipelago (CAA) to generate digital elevation models (DEMs) of the glacial basal topography. In this work, we briefly describe the processing steps that led to the generation of these DEMs, algorithm improvements over previously published results, and assess the results from two different perspectives. First, we evaluate the self-consistency of the DEMs where flight paths cross over each other and two measurements are made at the same location. Secondly, we compare the quality of the outputs of the ice-bottom tracker before and after applying manual corrections to the tracker results; the tracker is an algorithm that we implemented to automatically track the ice-bottom. Even though the CAA ice-caps are mountainous areas, where the scenes often have ice and no ice regions, which makes the imaging complicated, the statistical results show good tracking performance and a good match between the overlapped DEMs, where the mean error of the crossover DEMs is 37±9 m.

The performance of several methods to estimate the number of source signals impinging on a sensor array are compared using a traditional simulator and their performance for synthetic aperture radar tomography is discussed. All methods use a penalty term that increases with model order in order to prevent overestimation. We include both separate estimation of model selection and direction of arrival as well as joint estimation. We formulate a new penalty term, numerically tuned so that it gives optimal performance over our operating conditions, and compare this method as well. Simulation results show that the numerically tuned model selection criteria is optimal and that the typical methods do not do well for low snapshots. We also found that there is little sensitivity to SNR greater than 3 dB when the number of snapshots is high. We discuss some issues to applying the algorithms to data collected by the CReSIS radar depth sounder.

Deep learning methods have surpassed the performance of traditional techniques on a wide range of problems in computer vision, but nearly all of this work has studied consumer photos, where precisely correct output is often not critical. It is less clear how well these techniques may apply on structured prediction problems where fine-grained output with high precision is required, such as in scientific imaging domains. Here we consider the problem of segmenting echogram radar data collected from the polar ice sheets, which is challenging because segmentation boundaries are often very weak and there is a high degree of noise. We propose a multi-task spatiotemporal neural network that combines 3D ConvNets and Recurrent Neural Networks (RNNs) to estimate ice surface boundaries from sequences of tomographic radar images. We show that our model outperforms the state-of-the-art on this problem by (1) avoiding the need for hand-tuned parameters, (2) extracting multiple surfaces (ice-air and ice-bed) simultaneously, (3) requiring less non-visual metadata, and (4) being about 6 times faster., 10 pages, 7 figures, published in WACV 2018

Ice properties inferred from multi-polarization measurements, such as birefringence and crystal orientation fabric (COF), can provide insight into ice strain, viscosity, and ice flow. In 2008, the Center for Remote Sensing of Ice Sheets (CReSIS) used a ground-based VHF (very high frequency) radar to take multi-channel and multi-polarization measurements around the NEEM (North Greenland Eemian Ice Drilling) site. The system operated with 30 MHz bandwidth at a center frequency of 150 MHz. This paper describes the radar system, antenna configurations, data collection, and processing and analysis of this data set. Within the framework derived from uniaxial ice crystal model, we found that ice birefringence dominates the power variation patterns of co-polarization and cross-polarization measurements in the area of 100 km2 around the ice core site. The phase shift between ordinary and extraordinary waves increases nonlinearly with depth. The ice optic axis lies in planes that are close to the vertical plane and perpendicular or parallel to the ice divide depending on depth. The ice optic axis has an average tilt angle of about 11.6° vertically, and its plane may rotate either clockwise or counterclockwise by about 10° across the 100 km2 area, and at a specific location the plane may rotate slightly counterclockwise as depth increases. Comparisons between the radar observations, simulations, and ice core fabric data are in very good agreement. We calculated the effective colatitude at different depths by using azimuth and colatitude measurements of the c axis of ice crystals. We obtained an average effective c axis tilt angle of 9.6° from the vertical axis, very comparable to the average optic axis tilt angle estimated from radar polarization measurements. The comparisons give us confidence in applying this polarimetric radio echo sounding technique to infer profiles of ice fabric in locations where there are no ice core measurements.

Ground-penetrating radar on planes and satellites now makes it practical to collect 3D observations of the subsurface structure of the polar ice sheets, providing crucial data for understanding and tracking global climate change. But converting these noisy readings into useful observations is generally done by hand, which is impractical at a continental scale. In this paper, we propose a computer vision-based technique for extracting 3D ice-bottom surfaces by viewing the task as an inference problem on a probabilistic graphical model. We first generate a seed surface subject to a set of constraints, and then incorporate additional sources of evidence to refine it via discrete energy minimization. We evaluate the performance of the tracking algorithm on 7 topographic sequences (each with over 3000 radar images) collected from the Canadian Arctic Archipelago with respect to human-labeled ground truth., 5 pages, 3 figures, published in ICIP 2017

After 8 years of decay of its ice shelf, Zachariae Isstrom, a major glacier of northeast Greenland that holds a 0.5-meter sea-level rise equivalent, entered a phase of accelerated retreat in fall 2012. The acceleration rate of its ice velocity tripled, melting of its residual ice shelf and thinning of its grounded portion doubled, and calving is now occurring at its grounding line. Warmer air and ocean temperatures have caused the glacier to detach from a stabilizing sill and retreat rapidly along a downward-sloping, marine-based bed. Its equal-ice-volume neighbor, Nioghalvfjerdsfjorden, is also melting rapidly but retreating slowly along an upward-sloping bed. The destabilization of this marine-based sector will increase sea-level rise from the Greenland Ice Sheet for decades to come.

The flow of ice is temperature-dependent, but direct measurements of englacial temperature are sparse. The dielectric attenuation of radio waves through ice is also temperature-dependent, and radar sounding of ice sheets is sensitive to this attenuation. Here we estimate depth-averaged radar-attenuation rates within the Greenland Ice Sheet from airborne radar-sounding data and its associated radiostratigraphy. Using existing empirical relationships between temperature, chemistry, and radar attenuation, we then infer the depth-averaged englacial temperature. The dated radiostratigraphy permits a correction for the confounding effect of spatially varying ice chemistry. Where radar transects intersect boreholes, radar-inferred temperature is consistently higher than that measured directly. We attribute this discrepancy to the poorly recognized frequency dependence of the radar-attenuation rate and correct for this effect empirically, resulting in a robust relationship between radar-inferred and borehole-measured depth-averaged temperature. Radar-inferred englacial temperature is often lower than modern surface temperature and that of a steady state ice-sheet model, particularly in southern Greenland. This pattern suggests that past changes in surface boundary conditions (temperature and accumulation rate) affect the ice sheet's present temperature structure over a much larger area than previously recognized. This radar-inferred temperature structure provides a new constraint for thermomechanical models of the Greenland Ice Sheet.

Satellite radar altimeter (RA) measurements are important for continued monitoring of rapidly changing polar regions. In 2010, the European Space Agency launched CryoSat-2 carrying SIRAL, a Ku-band RA with objectives of determining the thickness and extent of sea ice and the topography of the ice sheets. One difficulty with Ku-band radar surveys over snow and ice is unknown penetration of RA signal into snow cover. Improving our understanding of the interactions of RA signals with snow and ice is needed to produce accurate elevation products. To this end, we developed a low-power, ultrawideband (12–18 GHz) RA for airborne surveys to provide fine resolution measurements capable of detecting both scattering from the surface and layers within sea ice and ice sheets. These measurements provide a means of identifying the dominant scattering location of lower resolution RA measurements comparable to satellite-based instruments. We generated two products: a full-bandwidth waveform (FBW) to identify scattering targets at fine resolution and a reduced-bandwidth waveform (RBW) to represent conventional RA measurements. Retrackers are used to generate height estimates over various surface conditions for comparisons. Over ice sheets, the leading-edge tracker provided consistent ice-surface elevation measurements between the FBW and RBW results; however, there were significant differences between the results from the centroid tracker. Over sea ice, the location of the dominant return between the results from snow-covered sea ice is highly variable. This paper provides an overview of RA surveys in polar regions, a description of the CReSIS system, and a discussion of the results.

We have built and operated an ultra-wideband UHF pulsed-chirp radar for measuring firn stratigraphy from airborne platforms over the ice sheets of Greenland and West Antarctica. Our analysis found a wide range of capabilities, including imaging of post firn–ice transition horizons and sounding of shallow glaciers and ice shelves. Imaging of horizons to depths exceeding 600 m was possible in the colder interior regions of the ice sheet, where scattering from the ice surface and inclusions was minimal. The radar’s high sensitivity and large dynamic range point to loss tangent variations as the dominant mechanism for these englacial reflective horizons. The radar is capable of mapping interfaces with reflection coefficients as low as −80 dB near the firn–ice transition and as low as −64 dB at depths of 600 m. We found that firn horizon reflectivity strongly mirrored density variance, a result of the near-unity interfacial transmission coefficients. Zones with differing compaction mechanisms were also apparent in the data. We were able to sound many ice shelves and areas of shallow ice. We estimated ice attenuation rates for a few locations, and our attenuation estimates for the Ross Ice Shelf, West Antarctica, appear to agree well with earlier reported results.

Accelerated loss of ice from Greenland and Antarctica has been observed in recent decades. Ice thickness is a key factor in making predictions about the future of massive ice reservoirs and can be estimated by calculating the exact location of the ice surface and bottom in radar imagery. Identifying the locations of ice boundaries is typically performed manually which is a very time consuming procedure. Here we propose a novel approach which automatically detects the complex topology of ice surface and bottom boundaries based on charged particle concept. Here we first applied anisotropic diffusion to remove the noise and enhance the image. At the second step, we detected the contours in the image based on Coulomb's electrostatic law and the assumption that each pixel is an electrically charged particle. The final ice surface and bottom are detected based on the projection profile of the contours. The results are evaluated on a large dataset of airborne radar imagery collected during IceBridge mission over Antarctica and show promising results with respect to hand-labeled ground truth.

The basal topography of most of the glaciers that drain the ice caps of the Canadian Arctic Archipelago is largely unknown. To measure the basal topography, NASA Operation IceBridge flew a radar depth sounder in a wide swath mode with three transmit beams to image the glacier beds during three flights over the archipelago in 2014. We describe the measurement setup of the radar system, the algorithms used to process the data to produce a 3D image of the glacier bed, show digital elevation model (DEM) results of the beds, and provide a basic assessment of the tracking algorithm used to extract the DEM.

We have developed an unmanned aerial system consisting of a compact sounding radar operating in the frequency bands of 14 and 35 MHz integrated into a fixed-wing UAV for remote surveys of glaciers and ice-sheets. The system is capable of collecting coherent sounding measurements along multiple parallel tracks. With the use of differential GPS for precise trajectory determination, we demonstrate multipass SAR array processing. The system was recently deployed by CReSIS personnel in the spring of 2016 to survey the Russell glacier in Greenland. This paper reports on the instrumentation including the integration of the radar, antennas, and aircraft; the survey flights in Greenland; and results from measurements collected at 35 MHz.

We present an overview of a set of radar instruments developed at the University of Kansas for multi-spectral measurements of ice and snow properties. The systems operate at different frequency bands ranging from 14 MHz to 38 GHz, onboard manned and unmanned aircraft. The data collected with these systems are used to estimate parameters such as ice thickness, ice surface and bedrock topography, snow cover thickness on sea ice, and annual snow accumulation. We give a summary of recent field programs (including operations out of Punta Arenas, Chile) and discuss current collaborations with Chilean institutions.

Radar research has been synonymous with the University of Kansas (KU) for over half a century. As part of this special session organized to highlight significant radar programs in academia, this paper surveys recent and ongoing work at KU. This work encompasses a wide breadth of sensing applications including the remote sensing of ice sheets, autonomous navigation methods for unmanned aerial vehicles (UAVs), novel laser radar capabilities, detection of highenergy cosmic rays using bistatic radar, different forms of waveform diversity such as MIMO radar and pulse agility, and various radar-embedded communication methods. The results of these efforts impact our understanding of the changing nature of the environment, address the proliferation of unmanned systems in the US airspace, realize new sensing modalities enabled by the joint consideration of electromagnetics and signal processing, and greater facilitate radar operation in an increasingly congested and contested spectrum.

We present a compilation of radio-echo sounding (RES) measurements of five radar systems (AWI, BAS, CReSIS, INGV and UTIG) around the EPICA Dome C (EDC) drill site, East Antarctica. The aim of our study is to investigate the differences of the various systems in their resolution of internal reflection horizons (IRHs) and bed topography, penetration depth and capacity of imaging the basal layer. We address the questions of the compatibility of existing radar data for common interpretation and the suitability of the individual systems for reconnaissance surveys. We find that the most distinct IRHs and IRH patterns can be identified and transferred between most data sets. Considerable differences between the RES systems exist in range resolution and depiction of the bottom-most region. Considering both aspects, which we judge as crucial factors in the search for old ice, the CReSIS and the UTIG systems are the most suitable ones. In addition to the RES data set comparison we calculate a synthetic radar trace from EDC density and conductivity profiles. We identify 10 common IRHs in the measured RES data and the synthetic trace. We then conduct a sensitivity study for which we remove certain peaks from the input conductivity profile. As a result the respective reflections disappear from the modeled radar trace. In this way, we establish a depth conversion of the measured travel times of the IRHs. Furthermore, we use these sensitivity studies to investigate the cause of observed reflections. The identified IRHs are assigned ages from the EDC's timescale. Due to the isochronous character of these conductivity-caused IRHs, they are a means to extend the Dome C age structure by tracing the IRHs along the RES profiles.

When basal meltwater refreezes, the resulting warm ice can influence the flow dynamics of the ice sheet above. An analysis of airborne gravity and radar data identifies extensive basal-ice units across the northern Greenland ice sheet that coincide with areas of deformed ice and fast ice flow.

This paper presents a radar sensor package specifically developed for wide-coverage sounding and imaging of polar ice sheets from a variety of aircraft. Our instruments address the need for a reliable remote sensing solution well-suited for extensive surveys at low and high altitudes and capable of making measurements with fine spatial and temporal resolution. The sensor package that we are presenting consists of four primary instruments and ancillary systems with all the associated antennas integrated into the aircraft to maintain aerodynamic performance. The instruments operate simultaneously over different frequency bands within the 160 MHz-18 GHz range. The sensor package has allowed us to sound the most challenging areas of the polar ice sheets, ice sheet margins, and outlet glaciers; to map near-surface internal layers with fine resolution; and to detect the snow-air and snow-ice interfaces of snow cover over sea ice to generate estimates of snow thickness. In this paper, we provide a succinct description of each radar and associated antenna structures and present sample results to document their performance. We also give a brief overview of our field measurement programs and demonstrate the unique capability of the sensor package to perform multifrequency coincidental measurements from a single airborne platform. Finally, we illustrate the relevance of using multispectral radar data as a tool to characterize the entire ice column and to reveal important subglacial features.

The evaluation of ice sheet models is one of the pressing problems in the study of ice sheet dynamics. Here we examine the question of how much isochronous information is contained within the publicly available Center for Remote Sensing of Ice Sheets (CReSIS) Greenland airborne radio echo soundings data set. We identify regions containing isochronous reflectors using automatic radio echo sounding processing (ARESP) algorithms. We find that isochronous reflectors are present within 36% of the CReSIS radio echo sounding englacial data by location and 41% by total number of data. Between 1000 and 3000 m in depth, isochronous reflectors are present along more than 50% of the data set flight path. Lower volumes of cold glacial period ice also correspond with more isochronous reflectors. We find good agreement between ARESP and continuity index results, providing confidence in these findings. Ice structure data sets, based on data identified here, will be of use in evaluating ice sheet simulations and the assessment of past rates of snow accumulation.

Dynamic ice-sheet models are used to assess the contribution of mass loss from the Greenland ice sheet to sea-level rise. Mass transfer from ice sheet to ocean is in a large part through outlet glaciers. Bed topography plays an important role in ice dynamics, since the acceleration from the slow-moving inland ice to an ice stream is in many cases caused by the existence of a subglacial trough or trough system. Problems are that most subglacial troughs are features of a scale not resolved in most ice-sheet models and that radar measurements of subglacial topography do not always reach the bottoms of narrow troughs. The trough-system algorithm introduced here employs mathematical morphology and algebraic topology to correctly represent subscale features in a topographic generalization, so the effects of troughs on ice flow are retained in ice-dynamic models. The algorithm is applied to derive a spatial elevation model of Greenland subglacial topography, integrating recently collected radar measurements (CReSIS data) of the Jakobshavn Isbræ, Helheim, Kangerdlussuaq and Petermann glacier regions. The resultant JakHelKanPet digital elevation model has been applied in dynamic ice-sheet modeling and sea-level-rise assessment.

This paper presents the bed topography of Jakobshavn Isbræ, Greenland, and Byrd Glacier, Antarctica, derived from sounding these glaciers with high-sensitivity radars. To understand the processes causing the speed-up and retreat of outlet glaciers, and to enable the development of next-generation ice-sheet models, we need information on bed topography and basal conditions. To this end, we performed measurements with the progressively improved Multichannel Coherent Radar Depth Sounder/Imager (MCoRDS/I). We processed the data from each antenna-array element using synthetic aperture radar algorithms to improve radar sensitivity and reduce along-track surface clutter. We then applied array and image-processing algorithms to extract the weak bed echoes buried in off-vertical scatter (cross-track surface clutter). At Jakobshavn Isbræ, we observed 2.7 km thick ice ~30 km upstream of the calving front and ~850 m thick ice at the calving front. We also observed echoes from multiple interfaces near the bed. We applied the MUSIC algorithm to the data to derive the direction of arrival of the signals. This analysis revealed that clutter is dominated by the ice surface at Jakobshavn Isbræ. At Byrd Glacier, we found ~3.62 km thick ice, as well as a subglacial trench ~3.05 km below sea level. We used ice thickness information derived from radar data in conjunction with surface elevation data to generate bed maps for these two critical glaciers. The performance of current radars must be improved further by ~15 dB to fully sound the deepest part of Byrd Glacier. Unmanned aerial systems equipped with radars that can be flown over lines spaced as close as 5 m apart in the cross-track direction to synthesize a two-dimensional aperture would be ideal for collecting fine-resolution data over glaciers like Jakobshavn near their grounding lines.

The accelerating loss of mass from the Greenland ice sheet is a major contribution to current sea level rise. Increased melt water runoff is responsible for half of Greenlands mass loss increase. Surface melt has been increasing in extent and intensity, setting a record for surface area melt and runoff in 2012. The mechanisms and timescales involved in allowing surface melt water to reach the ocean where it can contribute to sea level rise are poorly understood. The potential capacity to store this water in liquid or frozen form in the firn (multi-year snow layer) is significant, and could delay its sea-level contribution. Here we describe direct observation of water within a perennial firn aquifer persisting throughout the winter in the southern ice sheet,where snow accumulation and melt rates are high. This represents a previously unknown storagemode for water within the ice sheet. Ice cores, groundairborne radar and a regional climatemodel are used to estimate aquifer area (70 plue or minus 10 x 10(exp 3) square kilometers ) and water table depth (5-50 m). The perennial firn aquifer represents a new glacier facies to be considered 29 in future ice sheet mass 30 and energy budget calculations.

Accurate measurements of fast flowing outlet glaciers in Greenland and Antarctica are of vital importance to improve ice-sheet models that predict the ice-sheets' contribution to sea-level rise over the next century. Radars with high sensitivity and advanced processing capabilities are required to sound ice in fast-flowing glaciers. We developed the multichannel coherent radar depth sounder/imager (MCoRDS/I) for ice thickness measurements and 3-D imaging of bedrock over important areas of Greenland and Antarctica. Radio frequency interference (RFI) degrades the sensitivity of the MCoRDS/I system, thus affecting the quality of the data collected. Data from the 2010 Greenland field season exhibited a degraded signal-to-noise ratio (SNR), requiring extensive RFI analysis, investigation, and mitigation for the MCoRDS/I system. Measurements were taken in an electromagnetic interference (EMI) chamber on individual sections of the MCoRDS/I system to isolate the sources of RFI. Then, RFI mitigation techniques were implemented for the offending sections and EMI chamber measurements verified the integrity of the solution prior to the 2011 Greenland deployment. Recorded data from the 2011 Greenland field season also verified that the RFI mitigation resulted in more than 20 dB improvement in the SNR compared to the 2010 Greenland data. The reduction of EMI emissions has also been beneficial to data collection in subsequent deployments.

The National Aeronautics and Space Administration (NASA) initiated a program called Operation IceBridge for monitoring critical parts of Greenland and Antarctica with airborne LIDARs until ICESat-II is launched in 2016. We have been operating radar instrumentation on the NASA DC-8 and P-3 aircraft used for LIDAR measurements over Antarctica and Greenland, respectively. The radar package on both aircraft includes a radar depth sounder/imager operating at the center frequency of 195 MHz. During high-altitude missions flown to perform surface-elevation measurements, we also collected radar depth sounder data. We obtained good ice thickness information and mapped internal layers for both thicker and thinner ice. We successfully sounded 3.2-km-thick low-loss ice with a smooth surface and also sounded about 1-km or less thick shallow ice with a moderately rough surface. The successful sounding required processing of data with an algorithm to obtain 56-dB or lower range sidelobes and array processing with a minimum variance distortionless response algorithm to reduce cross-track surface clutter. In this paper, we provide a brief description of the radar system, discuss range-sidelobe reduction and array processing algorithms, and provide sample results to demonstrate the successful sounding of the ice bottom interface from high altitudes over the Antarctic and Greenland ice sheets.

Radio-echo sounding surveys over the Greenland ice sheet show clear, extensive internal layering, and comparisons with age–depth scales from deep ice cores allow for dating of the layering along the ice divide. We present one of the first attempts to extend the dated layers beyond the ice core drill sites by locating the depth of the Bølling–Allerød transition in >400 flight-lines using an automated fitting method. Results show that the transition is located in the upper one-third of the ice column in the central part of North Greenland, while the transition lowers towards the margin. This pattern mirrors the present surface accumulation, and also indicates that a substantial amount of pre-Holocene ice must be present in central North Greenland.

Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100 mW signal is swept from 2 to 8 GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 cm range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10 cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar.

Detailed maps of bed elevation and ice thickness are essential for understanding and projecting the evolution of the ice sheets. Such maps are traditionally obtained using airborne radar-sounding profiler data interpolated onto regular grids using geostatistical tools such as kriging. Here we compare three mapping techniques applied to a dense radar survey of Russell Glacier, West Greenland, by NASA Operation IceBridge: (1) radar tomography (RT) processing of the radar data to map the bed elevation, (2) interpolation of radar-derived thickness by ordinary kriging (KR) and (3) reconstruction of ice thickness based on the principles of mass conservation (MC) combining radar-sounding profiler and ice motion data. RT eliminates ambiguities caused by off-nadir reflections, but is spatially limited. KR yields a standard error in bed elevation of 35 m, but large errors (>300 m a−1) in flux divergence when combined with ice motion data. MC yields a comparable performance in bed elevation mapping, and errors smaller than 1 m a−1 in flux divergence. When the number of radar-sounding tracks is reduced, the performance of KR decreases more rapidly than for MC. Our study site shows that MC is capable of maintaining precision levels of 60 m at 400 m posting with flight tracks separated by 5 km.

Antenna arrays with low sidelobes in the cross-track direction are needed for sounding and imaging ice-sheets margins including outlet glaciers. Weak radar signals from the ice-bed interface are often masked by off-vertical surface clutter from extremely rough crevassed surfaces in ice-sheet margins. Synthetic aperture radar (SAR) processing can be used to synthesize a large array for reducing clutter in the along-track direction. Low-side-lobe transmit- and receive-antenna patterns must be generated from a limited size array in the cross-track direction. Airborne antenna pattern measurements are critical to verifying pattern characteristics in the presence of a non-ideal ground plane and neighboring aircraft structures, as well as in-flight operational dynamics. In this paper, we describe a set of airborne measurements performed to determine and optimize antenna patterns for the very high frequency (VHF) array used to sound and image polar ice sheets. We measured antenna patterns by flying over a relatively smooth ice surface at an altitude of about 2700 m. The pattern data were obtained by processing the surface echoes with aircraft rolled from left to right over more than five cycles. We also simulated antenna patterns using a three-dimensional computer model of the entire airborne platform and compared with experimental results. The discrepancies between the measured and simulated results are less than 2.7 dB for 85% of the data samples. The measured pattern data will be used to optimize our array processing algorithms.

The basal thermal state of an ice sheet (frozen or thawed) is an important control upon its evolution, dynamics and response to external forcings. However, this state can only be observed directly within sparse boreholes or inferred conclusively from the presence of subglacial lakes. Here we synthesize spatially extensive inferences of the basal thermal state of the Greenland Ice Sheet to better constrain this state. Existing inferences include outputs from the eight thermomechanical ice-flow models included in the SeaRISE effort. New remote-sensing inferences of the basal thermal state are derived from Holocene radiostratigraphy, modern surface velocity and MODIS imagery. Both thermomechanical modeling and remote inferences generally agree that the Northeast Greenland Ice Stream and large portions of the southwestern ice-drainage systems are thawed at the bed, whereas the bed beneath the central ice divides, particularly their west-facing slopes, is frozen. Elsewhere, there is poor agreement regarding the basal thermal state. Both models and remote inferences rarely represent the borehole-observed basal thermal state accurately near NorthGRIP and DYE-3. This synthesis identifies a large portion of the Greenland Ice Sheet (about one third by area) where additional observations would most improve knowledge of its overall basal thermal state.

In this paper, we present the development of a multi-channel VHF/UHF ultra-wideband airborne radar sounder and imager for measurements of polar ice sheets. The radar was developed at the Center for Remote Sensing of Ice Sheets (CReSIS) for operation onboard the German Alfred Wegener Institute (AWI) Basler BT-67 aircraft. The system operates from 150 to 600 MHz corresponding to a vertical resolution of 33 cm in free space. The radar is equipped with three 4-m long 8-element antenna subarrays installed under the fuselage and both wings to support 8 transmit and 24 receive channels. The radar waveform from each transmit channel can be configured individually to enable real-time transmit beamforming for wide-swath ice bed imaging of up to 10 km wide. The radar system was deployed to Greenland in the spring of 2016 as a part of the joint AWI/CReSIS test campaign to conduct measurements over glaciers. Sample radar data from this field campaign are presented to illustrate the capability of the radar.

We present a compilation of radio-echo sounding (RES) measurements of five radar systems (AWI, BAS, CReSIS, INGV and UTIG) around the EPICA Dome C (EDC) drill site, East Antarctica. The aim of our study is to investigate the differences of the various systems in their resolution of internal reflection horizons (IRHs) and bedrock topography, penetration depth, and quality of imaging the basal layer. We address the questions of the compatibility of existing radar data for common interpretation, and the suitability of the individual systems for Oldest Ice reconnaissance surveys. We find that the most distinct IRHs and IRH patterns can be identified and transferred between most data sets. Considerable differences between the RES systems exist in range resolution and depiction of the basal layer. Considering both aspects, which we judge as crucial factors in the search for old ice, the CReSIS and the UTIG systems are the most valuable ones. In addition to the RES data set comparison we calculate a synthetic radar trace from EDC density and conductivity profiles. We identify ten common IRHs in the measured RES data and the synthetic trace. The reflection-causing conductivity sections are determined by sensitivity studies with the synthetic trace. In this way, we accomplish an accurate two-way travel time to depth conversion for the reflectors, without having to use a precise velocity-depth function that would accumulate depth uncertainties with increasing depth. The identified IRHs are assigned with the AICC2012 time scale age. Due to the isochronous character of these conductivity-caused IRHs, they are a means to extend the Dome C age structure by tracing the IRHs along the RES profiles.

The Center for Remote Sensing of Ice Sheets (CReSIS) at the University of Kansas has collected approximately 1000 terabytes (TB) of radar depth sounding data over the Arctic and Antarctic ice sheets since 1993 in an effort to map the thickness of the ice sheets and ultimately understand the impacts of climate change and sea level rise. In addition to data collection, the storage, management, and public distribution of the dataset are also primary roles of the CReSIS. The Open Polar Server (OPS) project developed a free and open source infrastructure to store, manage, analyze, and distribute the data collected by CReSIS in an effort to replace its current data storage and distribution approach. The OPS infrastructure includes a spatial database management system (DBMS), map and web server, JavaScript geoportal, and MATLAB application programming interface (API) for the inclusion of data created by the cryosphere community. Open source software including GeoServer, PostgreSQL, PostGIS, OpenLayers, ExtJS, GeoEXT and others are used to build a system that modernizes the CReSIS data distribution for the entire cryosphere community and creates a flexible platform for future development. Usability analysis demonstrates the OPS infrastructure provides an improved end user experience. In addition, interpolating glacier topography is provided as an application example of the system.

Radar-inference of the bulk properties of glacier beds, most notably identifying basal melting, is, in general, derived from the basal reflection coefficient. On the scale of an ice-sheet, unambiguous determination of basal reflection is primarily limited by uncertainty in the englacial attenuation of the radio wave, which is an exponential function of temperature. Most existing radar algorithms assume stationarity in the attenuation rate, which is not feasible at an ice-sheet wide scale. Here we introduce a new framework for deriving englaical attenuation and basal reflection, and, to demonstrate its efficacy, we apply it to the Greenland Ice-Sheet. A central feature is the use of a prior Arrhenius temperature model to estimate the spatial variation in englaical attenuation as a first guess input for the radar algorithm. We demonstrate regions of solution convergence for two input temperature fields, and for independently analysed field campaigns. The coverage achieved is a trade-off with uncertainty and we propose that the algorithm can be "tuned" for discrimination of basal melt (attenuation loss uncertainty ∼ 5 dB). This is supported by our physically realistic (∼ 20 dB) range for the basal reflection coefficient. Finally, we show that the attenuation solution can be used to predict the temperature bias of thermomechanical ice-sheet models.

Radar inference of the bulk properties of glacier beds, most notably identifying basal melting, is, in general, derived from the basal reflection coefficient. On the scale of an ice sheet, unambiguous determination of basal reflection is primarily limited by uncertainty in the englacial attenuation of the radio wave, which is an Arrhenius function of temperature. Existing bed-returned power algorithms for deriving attenuation assume that the attenuation rate is regionally constant, which is not feasible at an ice-sheet-wide scale. Here we introduce a new semi-empirical framework for deriving englacial attenuation, and, to demonstrate its efficacy, we apply it to the Greenland Ice Sheet. A central feature is the use of a prior Arrhenius temperature model to estimate the spatial variation in englacial attenuation as a first guess input for the radar algorithm. We demonstrate regions of solution convergence for two input temperature fields and for independently analysed field campaigns. The coverage achieved is a trade-off with uncertainty and we propose that the algorithm can be "tuned" for discrimination of basal melt (attenuation loss uncertainty ∼ 5 dB). This is supported by our physically realistic ( ∼ 20 dB) range for the basal reflection coefficient. Finally, we show that the attenuation solution can be used to predict the temperature bias of thermomechanical ice sheet models and is in agreement with known model temperature biases at the Dye 3 ice core.