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Subglacial lakes have been mapped across Antarctica with two methods, radio‐echo sounding (RES) and ice‐surface deformation. At sites where both are coincident, these methods typically provide conflicting interpretations about the ice‐bed interface. With a single exception, active subglacial lakes identified by surface deformation do not display the expected flat, bright, and specular bed reflection in RES data, characteristic of non‐active lakes. This observational conundrum suggests that our understanding of Antarctic subglacial hydrology, especially beneath important fast‐moving ice streams, remains incomplete. Here, we use an airborne RES campaign that surveyed a well‐characterized group of active subglacial lakes on lower Mercer and Whillans ice streams, West Antarctica, to explore inconsistency between the two observational techniques. We test hypotheses of increased scattering and attenuation due to the presence of an active subglacial lake system that could suppress reflected bed‐echo power for RES observations in these locations, finding that entrained water is most plausible. Plain Language Summary: The bottom of an ice sheet is insulated from cold air temperatures, often warm enough to melt and pond liquid water into lakes. These lakes beneath the ice sheet have been identified by two independent measurements, first with radar methods and second with changes in height of the ice surface (altimetry). Interestingly, the two methods rarely identify the same lakes: radar generally detects lakes in the ice‐sheet interior, whereas altimetry detects active lakes near the ice‐sheet margins that fill and drain within the time series of repeated measurements (∼years). In this study, we investigate a group of active subglacial lakes at which both radar and altimetry data sets are available. We demonstrate that the radar returns from active lake reflections are much dimmer than expected based on non‐active lake signatures and investigate the physical processes controlling those dim reflections. We argue that water moves into the ice when the lake fills or drains and that is the most plausible explanation for the observational discrepancy. Key Points: Active subglacial lakes, identified by surface deformation, do not create the expected bright and specular radar reflectionEntrained water in basal ice suppresses radar power by scattering and attenuation, and it also likely alters the basal ice mechanicsUnderstanding the radar expression of subglacial water on Earth provides context for investigations of subsurface water on planetary bodies [ABSTRACT FROM AUTHOR]

The morphology and motion of auroras have been widely studied due to their indications on magnetospheric processes. Here, we report a new kind of "auroral curls," which have wavelengths in the mesoscale (∼100 km) and propagate azimuthally. Utilizing data from the Chinese Antarctic Zhongshan Station (the all‐sky imager and the high‐frequency radar), the Active Magnetosphere and Planetary Electrodynamics Response Experiment and the Defense Meteorological Satellite Program, we analyze an event occurred on 23 April 2019. We find these curls are fine structures in the poleward boundary of multiple arcs. Corresponding field‐aligned currents manifest as a series of longitudinally arranged pairs, while ionospheric flow velocities nearby oscillate with periods in the Pc 5 band. Observational evidence suggests these curls are connected with ultra‐low frequency (ULF) waves, which opens the possibility of using auroras to globally image ULF waves. Plain Language Summary: Auroras caused by precipitation of magnetospheric particles contain information about physical processes happened in the magnetosphere. In this letter, we report a new kind of auroral dynamic forms observed in Antarctica. These structures present both spatial and temporal periodic characteristics, which have similar scales with those of magnetospheric ultra‐low frequency (ULF) waves. We propose these auroral forms are connected with ULF waves, which provides a potential method to globally image ULF waves by analyzing properties of these auroras. Key Points: Azimuthally propagating "auroral curls" with mesoscale wavelengths were observed in AntarcticaThese curls are fine structures in the poleward boundary of multiple arcs formed by longitudinal‐arranged field‐aligned current pairsIonospheric flow velocities nearby oscillate with periods in the Pc 5 band, indicating connections with ultra‐low frequency waves [ABSTRACT FROM AUTHOR]

Polar mesosphere summer echoes (PMSE) have been observed for more than 30 years with 50 MHz VHF radars at various locations in the Northern Hemisphere. Continuous observation of PMSE is conducted on the northern Norwegian island of Andøya (69.3° N) using the ALWIN radar (1999–2008) and MAARSY (since 2010). The same kind of PMSE measurements began in 2004 in the Southern Hemisphere with the Australian Antarctic Division's VHF radar at Davis Station in Antarctica (68.6° S), which is at an opposite latitude to Andøya. Since the radars at both sites are calibrated, the received echo strength of PMSE from more than 1 decade of mesospheric observations on both hemispheres could be converted to absolute signal power, allowing for direct comparison of the measurements. Comparison of PMSE observations obtained at both radar sites during a period of 23 boreal summers (Andøya) and 15 austral summers (Davis) shows that their PMSE signal strengths are of the same order of magnitude, but significantly fewer PMSE are observed in the Southern Hemisphere than in the Northern Hemisphere. Compared to Andøya, the PMSE season over Davis starts about 7 d later on average and ends 9 d earlier, making it 16 d shorter. PMSE over Davis occur less frequently but with greater variability in seasonal, diurnal, and altitudinal occurrence. For example, PMSE over Davis reach maximum altitudes about 1.5 km higher than those over Andøya. [ABSTRACT FROM AUTHOR]

Winds from two wind-profiling radars, ESRAD (ESrange atmospheric RADar) in Arctic Sweden and MARA (Moveable Atmospheric Radar for Antarctica) on the coast of Antarctica, are compared with collocated (within 100 km) winds measured by the Doppler lidar on board the Aeolus satellite for the time period July 2019–May 2021 (baseline 2B11). Data are considered as a whole and subdivided into summer and winter as well as ascending (afternoon) and descending (morning) passes. Mean differences (bias) and random differences are categorized (standard deviation and scaled median absolute deviation) and the effects of different quality criteria applied to the data are assessed, including the introduction of the "modified Z score" to eliminate gross errors. This last criterion has a substantial effect on the standard deviation, particularly for Mie winds. Significant bias is found in two cases, for Rayleigh winds for the descending satellite passes. at MARA (-1.4 (+ 0.7) m s -1) and for all Mie winds at ESRAD (+ 1.0 (+ 0.3) m s -1). For the Rayleigh winds at MARA, there is no obvious explanation for the bias in the data distribution. The Mie wind error with respect to the wind data measured at ESRAD shows a skewed distribution toward positive values (Aeolus horizontal line-of-sight wind > ESRAD wind). Random differences (scaled median absolute deviation) for all data together are 5.9 and 5.3 m s -1 for Rayleigh winds at MARA and ESRAD, respectively, and 4.9 and 3.9 m s -1 for Mie winds. When the comparison is restricted to Aeolus measurements with a mean location within 25 km from the radars, there is no change to the random differences for Rayleigh winds, but for Mie winds they are reduced to 3.3 and 3.6 m s -1. These represent an upper bound for Aeolus wind random errors since they are due to a combination of spatial differences and random errors in both radar winds and Aeolus winds. The random errors in radar winds are < 2 m s -1 and therefore contribute little, but spatial variability clearly makes a significant contribution for Mie winds, especially at MARA. [ABSTRACT FROM AUTHOR]

Solid precipitation measurements in Antarctica are crucial as snowfall represents the main water input term for the polar cap, and its probable increase in the coming century can mitigate sea-level rise caused by global warming. This paper presents 7 years of Micro Rain Radar (Metek MRR-2) data at the Dumont d'Urville station in coastal Adélie Land, East Antarctica. Statistics are calculated on 3 radar variables (equivalent reflectivity, mean Doppler velocity and signal-to-noise ratio) to outline the main characteristics of the radar dataset. Seasonal and interannual variabilities are also investigated, but no significant temporal trends are detected except for the seasonal mean Doppler velocity which is higher in summer and lower in winter. We then use the snowfall rate (S) data from a colocated snow-gauge to estimate the MRR precipitation profile from the radar equivalent reflectivity (Ze) through a locally derived Ze-S relation. We find the relation Ze = 43.3 S0.88. The processing method used to obtain this relation, data quality and uncertainty considerations are discussed in the manuscript. In order to give an example of application of the dataset, a brief statistical comparison of the MRR precipitation rate along the vertical with model data from the ERA5 reanalysis and the LMDZ climate model is performed, and notably shows that models underestimate heavy precipitation events. [ABSTRACT FROM AUTHOR]

Studying precipitation at very high latitudes is difficult because of the harsh environmental conditions that limit the external activity of humans and instruments, especially in the polar winter. The direct monitoring of ice crystal habits and size distribution in Antarctic precipitation is important for the validation of the algorithms used for retrieving precipitation from ground-based and satellite-borne radar instruments and for the improvement of the climatological modelling of polar areas. This paper describes an automated device (ICE-CAMERA) specifically developed for the imaging, measurement, and classification of ice precipitation on the Antarctic high plateau. The instrument gives detailed information on precipitation on an hourly basis. The article provides a description of the device and its image processing software. Starting in 2014, the instrument has operated almost unattended all year round at Concordia station, Antarctica (75 ∘ S, 123 ∘ E, 3220 m altitude). [ABSTRACT FROM AUTHOR]

The Micro Rain Radar PRO (MRR-PRO) is a K-band Doppler weather radar, using frequency-modulated continuous-wave (FMCW) signals, developed by Metek Meteorologische Messtechnik GmbH (Metek) as a successor to the MRR-2. Benefiting from four datasets collected during two field campaigns in Antarctica and Switzerland, we developed a processing library for snowfall measurements named ERUO (Enhancement and Reconstruction of the spectrUm for the MRR-PRO), with a twofold objective. Firstly, the proposed method addresses a series of issues plaguing the radar variables, including interference lines and power drops at the extremes of the Doppler spectrum. Secondly, the algorithm aims to improve the quality of the final variables by lowering the minimum detectable equivalent attenuated reflectivity factor and extending the valid Doppler velocity range through dealiasing. The performance of the algorithm has been tested against the measurements of a co-located W-band Doppler radar. Information from a close-by X-band Doppler dual-polarization radar has been used to exclude unsuitable radar volumes from the comparison. Particular attention has been dedicated to verifying the estimation of the meteorological signal in the spectra covered by interferences. [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]

Riming of ice crystals by supercooled water droplets is an efficient ice growth process, but its basic properties are still poorly known. While it has been shown to contribute significantly to surface precipitation at mid-latitudes, little is known about its occurrence at high latitudes. In Antarctica, two competing effects can influence the occurrence of riming: (i) the scarcity of supercooled liquid water clouds due to the extremely low tropospheric temperatures and (ii) the low aerosol concentration, which may lead to the formation of fewer and larger supercooled drops potentially resulting in an enhanced riming efficiency. In this work, by exploiting the deployment of an unprecedented number of multiwavelength remote sensing systems (including triple-frequency radar measurements) in West Antarctica, during the Atmospheric Radiation Measurements West Antarctic Radiation Experiment (AWARE) field campaign, we evaluate the riming incidence at McMurdo Station and find that riming occurs at much lower temperatures when compared to previous results in the mid-latitudes. This suggests the possible occurrence of a common atmospheric state over Antarctica that includes a rather stable atmosphere inhibiting turbulent mixing, and a high riming efficiency driven by large cloud droplets. We then focus on a peculiar case study featuring a persistent layer with a particularly pronounced riming signature in triple-frequency radar data but only a relatively modest amount of supercooled liquid water. In-depth analysis of the radar observations suggests that such signatures can only be explained by the combined effects of moderately rimed aggregates or similarly shaped florid polycrystals and a narrow particle size distribution (PSD). Simulations of this case study performed with a one-dimensional bin model indicate that similar triple-frequency radar observations can be reproduced when narrow PSDs are simulated. Such narrow PSDs can in turn be explained by two key factors: (i) the presence of a shallow homogeneous droplet or humidified aerosol freezing layer aloft seeding an underlying supercooled liquid layer, and (ii) the absence of turbulent mixing throughout a stable polar atmosphere that sustains narrow PSDs, as hydrometeors grow from the nucleation region aloft to ice particles of several millimeters in size, by vapor deposition and then riming. [ABSTRACT FROM AUTHOR]

The earliest airborne geophysical campaigns over Antarctica and Greenland in the 1960s and 1970s collected ice penetrating radar data on 35 mm optical film. Early subglacial topographic and englacial stratigraphic analyses of these data were foundational to the field of radioglaciology. Recent efforts to digitize and release these data have resulted in geometric and ice-thickness analysis that constrain subsurface change over multiple decades but stop short of radiometric interpretation. The primary challenge for radiometric analysis is the poorly-characterized compression applied to Z-scope records and the sparse sampling of A-scope records. Here, we demonstrate the information richness and radiometric interpretability of Z-scope records. Z-scope pixels have uncalibrated fast-time, slow-time, and intensity scales. We develop approaches for mapping each of these scales to physical units (microseconds, seconds, and signal to noise ratio). We then demonstrate the application of this calibration and analysis approach to a flight in the interior of East Antarctica with subglacial lakes and to a reflight of an East Antarctic ice shelf that was observed by both archival and modern radar. These results demonstrate the potential use of Z-scope signals to extend the baseline of radiometric observations of the subsurface by decades. [ABSTRACT FROM AUTHOR]

Over the past 50 years, the British Antarctic Survey (BAS) has been one of the major acquirers of aerogeophysical data over Antarctica, providing scientists with gravity, magnetic, and radar datasets that have been central to many studies of the past, present, and future evolution of the Antarctic Ice Sheet. Until recently, many of these datasets were not openly available, restricting further usage of the data for different glaciological and geophysical applications. Starting in 2020, scientists and data managers at BAS have worked on standardizing and releasing large swaths of aerogeophysical data acquired during the period 1994–2020, including a total of 64 datasets from 24 different surveys, amounting to ∼ 450 000 line-km (or 5.3 million km 2) of data across West Antarctica, East Antarctica, and the Antarctic Peninsula. Amongst these are the extensive surveys over the fast-changing Pine Island (BBAS 2004–2005) and Thwaites (ITGC 2018–2019 & 2019–2020) glacier catchments, and the first ever surveys of the Wilkes Subglacial Basin (WISE-ISODYN 2005–2006) and Gamburtsev Subglacial Mountains (AGAP 2007–2009). Considerable effort has been made to standardize these datasets to comply with the FAIR (findable, accessible, interoperable and re-usable) data principles, as well as to create the Polar Airborne Geophysics Data Portal (https://www.bas.ac.uk/project/nagdp/ , last access: 18 July 2022), which serves as a user-friendly interface to interact with and download the newly published data. This paper reviews how these datasets were acquired and processed, presents the methods used to standardize them, and introduces the new data portal and interactive tutorials that were created to improve the accessibility of the data. Lastly, we exemplify future potential uses of the aerogeophysical datasets by extracting information on the continuity of englacial layering from the fully published airborne radar data. We believe these newly released data will be a valuable asset to future glaciological and geophysical studies over Antarctica and will significantly extend the life cycle of the data. All datasets included in this data release are now fully accessible at https://data.bas.ac.uk (British Antarctic Survey, 2022). [ABSTRACT FROM AUTHOR]

The retrieval of continuous ice core records of more than 1 Myr is an important challenge in palaeo-climatology. For identifying suitable sites for drilling such ice, knowledge of the subglacial topography and englacial layering is crucial. For this purpose, extensive ground-based ice radar surveys were carried out over Dome Fuji in the East Antarctic plateau during the 2017/18 and 2018/19 austral summers by the Japanese Antarctic Research Expedition, on the basis of ground-based radar surveys conducted over the previous ∼ 30 years. High-gain Yagi antennae were used to improve the antenna beam directivity, thereby significantly decreasing hyperbolic features of unfocused along-track diffraction hyperbolae in the echoes from mountainous ice–bedrock interfaces. We combined the new ice thickness data with the previous ground-based data, recorded since the 1980s, to generate an accurate high-spatial-resolution (up to 0.5 km between survey lines) ice thickness map. This map revealed a complex landscape composed of networks of subglacial valleys and highlands. Based on the new map, we examined the roughness of the ice–bed interface, the bed surface slope, the driving stress of ice and the subglacial hydrological condition. These new products and analyses set substantial constraints on identifying possible locations for new drilling. In addition, our map was compared with a few bed maps compiled by earlier independent efforts based on airborne radar data to examine the difference in features between datasets. Our analysis suggests that widely available bed topography products should be validated with in situ observations where possible. [ABSTRACT FROM AUTHOR]

Ice crystals are mechanically and dielectrically anisotropic. They progressively align under cumulative deformation, forming an ice-crystal-orientation fabric that, in turn, impacts ice deformation. However, almost all the observations of ice fabric are from ice core analysis, and its influence on the ice flow is unclear. Here, we present a non-linear inverse approach to process co- and cross-polarized phase-sensitive radar data. We estimate the continuous depth profile of georeferenced ice fabric orientation along with the reflection ratio and horizontal anisotropy of the ice column. Our method approximates the complete second-order orientation tensor and all the ice fabric eigenvalues. As a result, we infer the vertical ice fabric anisotropy, which is an essential factor to better understand ice deformation using anisotropic ice flow models. The approach is validated at two Antarctic ice core sites (EPICA (European Project for Ice Coring in Antarctica) Dome C and EPICA Dronning Maud Land) in contrasting flow regimes. Spatial variability in ice fabric characteristics in the dome-to-flank transition near Dome C is quantified with 20 more sites located along with a 36 km long cross-section. Local horizontal anisotropy increases under the dome summit and decreases away from the dome summit. We suggest that this is a consequence of the non-linear rheology of ice, also known as the Raymond effect. On larger spatial scales, horizontal anisotropy increases with increasing distance from the dome. At most of the sites, the main driver of ice fabric evolution is vertical compression, yet our data show that the horizontal distribution of the ice fabric is consistent with the present horizontal flow. This method uses polarimetric-radar data, which are suitable for profiling radar applications and are able to constrain ice fabric distribution on a spatial scale comparable to ice flow observations and models. [ABSTRACT FROM AUTHOR]

The subglacial bed topography is critical for modelling the evolution of Thwaites Glacier in the Amundsen Sea Embayment (ASE), where rapid ice loss threatens the stability of the West Antarctic Ice Sheet. However, mapping of subglacial topography is subject to uncertainties of up to hundreds of metres, primarily due to large gaps of up to tens of kilometres in airborne ice-penetrating radar flight lines. Deterministic interpolation approaches do not reflect such spatial uncertainty. While traditional geostatistical simulations can model such uncertainty, they become difficult to apply because of the significant non-stationary spatial variation of topography over such large surface area. In this study, we develop a non-stationary multiple-point geostatistical (MPS) approach to interpolate large areas with irregular geophysical data and apply it to model the spatial uncertainty of entire ASE basal topography. We collect 166 high-quality topographic training images (TIs) of resolution 500 m to train the gap-filling of radar data gaps, thereby simulating realistic topography maps. The TIs are extensively sampled from deglaciated regions in the Arctic as well as Antarctica. To address the non-stationarity in topographic modelling, we introduce a Bayesian framework that models the posterior distribution of non-stationary TIs assigned to the local line data. Sampling from this distribution then provides candidate training images for local topographic modelling with uncertainty, constrained to radar flight line data. Compared to traditional MPS approaches that do not consider uncertain TI sampling, our approach results in a significant improvement in the topographic modelling quality and efficiency of the simulation algorithm. Finally, we simulate multiple realizations of high-resolution ASE topographic maps. We use the multiple realizations to investigate the impact of basal topography uncertainty on subglacial hydrological flow patterns. [ABSTRACT FROM AUTHOR]

Random‐noise‐induced biases are inherent issues to the accurate derivation of second‐order statistical parameters (e.g., variances, fluxes, energy densities, and power spectra) from lidar and radar measurements. We demonstrate here for the first time an altitude‐interleaved method for eliminating such biases, following the original proposals by Gardner and Chu (2020, https://doi.org/10.1364/ao.400375) who demonstrated a time‐interleaved method. Interleaving in altitude bins provides two statistically independent samples over the same time period and nearly the same altitude range, thus enabling the replacement of variances that include the noise‐induced biases with covariances that are intrinsically free of such biases. Comparing the interleaved method with previous variance subtraction (VS) and spectral proportion (SP) methods using gravity wave potential energy density calculated from Antarctic lidar data and from a forward model, this study finds the accuracy and precision of each method differing in various conditions, each with its own strengths and weakness. VS performs well in high‐SNR, yet its accuracy fails at lower‐SNR as it often yields negative values. SP is accurate and precise under high‐SNR, remaining accurate in worse conditions than VS would, yet develops a positive bias under low‐SNR. The interleaved method is accurate in all SNRs but requires a large number of samples to drive random‐noise terms in covariances toward zero and to compensate for the reduced precision due to the splitting of return signals. Therefore, selecting the proper bias removal/elimination method for actual signal and sample conditions is crucial in utilizing lidar/radar data, as neglecting this can conceal trends or overstate atmospheric variability. Plain Language Summary: Second‐order statistics like atmospheric wave‐induced variances or fluxes of physical parameters calculated from lidar or radar data would have positive biases if detection‐noise‐induced variances or fluxes were not properly eliminated. If such biases remained, not only would atmospheric variances be overestimated, implying unrealistic wave activity and growth rates, but certain phenomena could be concealed, presenting misleading pictures of the atmospheric observations. While various methods have been developed to account for this, all have limitations to their use. This study summarizes the development, theory, and application procedures for three different methods, namely conventional variance subtraction, the spectral proportion method, and the interleaved method, which can be used to correct such biases. The newest of these methods is adapted from operating on the data time‐wise into an altitude‐wise approach, improving its applicability. The performances of the three methods are compared by calculating the variance‐based gravity wave potential energy density derived from lidar data taken at McMurdo, Antarctica. Their accuracies are assessed by using a forward model. This study aims to guide future research by providing information on how and when to apply each of these methods in order to enhance the outcomes of existing and future lidar/radar systems and datasets. Key Points: We demonstrate for the first time an altitude‐interleaved method for eliminating random‐noise‐induced biases from second‐order statisticsThe interleaved method is compared to the spectral proportion and variance subtraction methods to reveal strengths and limitations of eachLidar data from Antarctica & a forward model are used to assess accuracies and precisions of the three methods under different conditions [ABSTRACT FROM AUTHOR]

The Micro Rain Radar (MRR) PRO is a K-band Doppler weather radar, using frequency modulated continuous wave (FMCW) signals, developed by Metek Meteorologische Messtechnik GmbH (Metek) as successor to the MRR-2. Benefiting from four datasets collected during two field campaigns in Antarctica and Switzerland, we developed a processing library for snowfall measurements, named ERUO (Enhancement and Reconstruction of the spectrUm for the MRR-PRO), with a two-fold objective. Firstly, the proposed method addresses a series of issues plaguing the radar variables, which include interference lines, power drops at the extremes of the Doppler spectrum and abrupt cutoff of the transfer function. Secondly, the algorithm aims to improve the quality of the final variables, by lowering the minimum detectable equivalent attenuated reflectivity factor and extending the valid Doppler velocity range through antialiasing. The performance of the algorithm has been tested against the measurements of a co-locatedW-band Doppler radar. Information from a close-by X-Band Doppler dual-polarization radar has been used to exclude unsuitable radar volumes from the comparison. Particular attention has been dedicated to verify the estimation of the meteorological signal in the spectra covered by interferences. [ABSTRACT FROM AUTHOR]

The subglacial bed topography is critical for modeling the evolution of Thwaites Glacier in the Amundsen Sea Embayment (ASE), where rapid ice loss threatens the stability of the West Antarctic Ice Sheet. However, mapping of subglacial topography is subject to high uncertainty. This is mainly because the bed topography is measured by airborne ice-penetrating radar along flight lines with large gaps up to tens of kilometers. Deterministic interpolation approaches do not reflect such spatial uncertainty. While traditional geostatistical simulation can model such uncertainty, it may be difficult to apply because of the significant non-stationary spatial variation of topography over such large surface area. In this study, we develop a non-stationary multiple-point geostatistical approach to interpolate large areas with irregular geophysical data and apply it to model the spatial uncertainty of entire ASE basal topography. We collect 166 high-resolution topographic training images (TIs) to train the gap-filling of radar data gaps, thereby simulating realistic topography maps. The TIs are extensively sampled from deglaciated regions in the Arctic as well as Antarctica. To address the non-stationarity in topographic modeling, we introduce a Bayesian framework that models the posterior distribution of non-stationary training images to the local modeling domain. Sampling from this distribution then provide candidate training images for local topographic modeling with uncertainty, constrained to radar flight line data. Compared to traditional MPS approaches without considering TI sampling, our approach demonstrates significant improvement in the topographic modeling quality and efficiency of the simulation algorithm. Finally, we simulate multiple realizations of high-resolution ASE topographic maps. We use the multiple realizations to investigate the impact of basal topography uncertainty on subglacial hydrological flow patterns. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar interferometry (InSAR) is an efficient technique for mapping the surface elevation and its temporal change over glaciers and ice sheets. However, due to the penetration of the SAR signal into snow and ice, the apparent elevation in uncorrected InSAR digital elevation models (DEMs) is displaced versus the actual surface. We studied relations between interferometric radar signals and physical snow properties and tested procedures for correcting the elevation bias. The work is based on satellite and in situ data over Union Glacier in the Ellsworth Mountains, West Antarctica, including interferometric data of the TanDEM-X mission, topographic data from optical satellite sensors and field measurements on snow structure, and stratigraphy undertaken in December 2016. The study area comprises ice-free surfaces, bare ice, dry snow and firn with a variety of structural features related to local differences in wind exposure and snow accumulation. Time series of laser measurements of NASA's Ice, Cloud and land Elevation Satellite (ICESat) and ICESat-2 show steady-state surface topography. For area-wide elevation reference we use the Reference Elevation Model of Antarctica (REMA). The different elevation data are vertically co-registered on a blue ice area that is not affected by radar signal penetration. Backscatter simulations with a multilayer radiative transfer model show large variations for scattering of individual snow layers, but the vertical backscatter distribution can be approximated by an exponential function representing uniform absorption and scattering properties. We obtain estimates of the elevation bias by inverting the interferometric volume correlation coefficient (coherence), applying a uniform volume model for describing the vertical loss function. Whereas the mean values of the computed elevation bias and the elevation difference between the TanDEM-X DEMs and the REMA show good agreement, a trend towards overestimation of penetration is evident for heavily wind-exposed areas with low accumulation and towards underestimation for areas with higher accumulation rates. In both cases deviations from the uniform volume structure are the main reason. In the first case the dense sequence of horizontal structures related to internal wind crust, ice layers and density stratification causes increased scattering in near-surface layers. In the second case the small grain size of the top snow layers causes a downward shift in the scattering phase centre. [ABSTRACT FROM AUTHOR]

Winds measured by lidar from the Aeolus satellite are compared with winds measured by two ground-based radars – MARA in Antarctica (70.77 ∘ S, 11.73 ∘ E) and ESRAD (67.88 ∘ N, 21.10 ∘ E) in Arctic Sweden – for the period 1 July–31 December 2019. Aeolus is a demonstrator mission to test whether winds measured by Doppler lidar from space can have sufficient accuracy to contribute to improved weather forecasting. A comprehensive programme of calibration and validation has been undertaken following the satellite launch in 2018, but, so far, direct comparison with independent measurements from the Arctic or Antarctic regions have not been made. The comparison covers heights from the low troposphere to just above the tropopause. Results for each radar site are presented separately for Rayleigh (clear) winds, Mie (cloudy) winds, sunlit ("summer") and non-sunlit ("winter") seasons, and ascending and descending satellite tracks. Horizontally projected line-of-sight (HLOS) winds from Aeolus, reprocessed using baseline 2B10, for passes within 100 km of the radar sites, are compared with HLOS winds calculated from 1 h averaged radar horizontal wind components. The agreement in most data subsets is very good, with no evidence of significant biases (<1 m s -1). Possible biases are identified for two subsets (about -2 m s -1 for the Rayleigh winds for the descending passes at MARA and about 2 m s -1 for the Mie winds for the ascending passes at ESRAD, both in winter), but these are only marginally significant. A robust significant bias of about 7 m s -1 is found for the Mie winds for the ascending tracks at MARA in summer. There is also some evidence for increased random error (by about 1 m s -1) for the Aeolus Mie winds at MARA in summer compared to winter. This might be related to the presence of sunlight scatter over the whole of Antarctica as Aeolus transits across it during summer. [ABSTRACT FROM AUTHOR]

Airborne observation is an important approach to collect data in the remote, hostile Antarctica and study the relationship between the Antarctica and global climate. During airborne observations, it is necessary to conduct data processing and quality control on site, which can help to timely evaluate the status of airborne instruments, provide scientific clues, and develop ideal schemes for following airborne observations. As one critical component of airborne instruments, airborne ice sounding radar can delineate sub-ice bedrock topography and internal layers, which cannot be realized by other instruments. In this study, we present an on-site data processing algorithm for high-resolution and high signal-to-noise ratio (SNR) ice sounding radar data acquired by the "Snow Eagle 601", the first fixed-wing airplane deployed by China for the Antarctic expeditions. In addition, the algorithm is further optimized in terms of static pre-allocated memory and parallel and block processing of data to enhance processing speed and meet the requirements for quality control and analysis of on-site data. Finally, we test the optimized algorithm with different volume of ice sounding radar data through implementing on different computer configurations, including i7, i5 CPU and 8G, 16G memory with the same disk. The results show that the average processing speed of the optimized algorithm is 5.143 times faster than the non-optimized algorithm on different computer configurations. [ABSTRACT FROM AUTHOR]

Polarimetric radar systems are commonly used to study the microphysics of precipitation. While they offer continuous measurements with a large spatial coverage, retrieving information about the microphysical processes that govern the evolution of snowfall from the polarimetric signal is challenging. The present study develops a new method, called process identification based on vertical gradient signs (PIVSs), to spatially identify the occurrence of the main microphysical processes (aggregation and riming, crystal growth by vapor deposition and sublimation) in snowfall from dual-polarization Doppler radar scans. We first derive an analytical framework to assess in which meteorological conditions the local vertical gradients of radar variables reliably inform about microphysical processes. In such conditions, we then identify regions dominated by (i) vapor deposition, (ii) aggregation and riming and (iii) snowflake sublimation and possibly snowflake breakup, based on the sign of the local vertical gradients of the reflectivity ZH and the differential reflectivity ZDR. The method is then applied to data from two frontal snowfall events, namely one in coastal Adélie Land, Antarctica, and one in the Taebaek Mountains in South Korea. The validity of the method is assessed by comparing its outcome with snowflake observations, using a multi-angle snowflake camera, and with the output of a hydrometeor classification, based on polarimetric radar signal. The application of the method further makes it possible to better characterize and understand how snowfall forms, grows and decays in two different geographical and meteorological contexts. In particular, we are able to automatically derive and discuss the altitude and thickness of the layers where each process prevails for both case studies. We infer some microphysical characteristics in terms of radar variables from statistical analysis of the method output (e.g., ZH and ZDR distribution for each process). We, finally, highlight the potential for extensive application to cold precipitation events in different meteorological contexts. [ABSTRACT FROM AUTHOR]

A phase‐sensitive radar (ApRES) was deployed on Totten Ice Shelf to provide the first in situ basal melt estimate at this dynamic East Antarctic ice shelf. Observations of internal ice dynamics at tidal time scales showed that early arrivals from off‐nadir reflectors obscure the true depth of the ice shelf base. Using the observed tidal deformation, the true base was found to lie at 1,910–1,950‐m depth, at 350–400 m greater range than the first reflection from an ice‐ocean interface. The robustness of the basal melt rate estimate was increased by using multiple basal reflections over the radar footprint, yielding a melt rate of 22 ± 2.1 m a−1. The ApRES estimate is over 40% lower than the three existing satellite estimates covering Totten Ice Shelf. This difference in basal melt is dynamically significant and highlights the need for independent melt rate estimates using complementary instrumentation and techniques that rely on different sets of assumptions. Plain Language Summary: Observations of the rate of melting at the base of ice shelves are needed to model accurately ice sheet evolution. Local measurements are scarce, yet necessary for validation of satellite products and ocean models. We deployed a phase‐sensitive radar in the proximity of grounding zone of Totten Ice Shelf in East Antarctica, to measure basal melt in this dynamic region where uncertainties on melt rate estimates are high. We developed a method that accounts for basal geometry complexities and derived a melt rate estimate of ∼22 m per year, which is lower than previous estimates, but it confirms that the basal melt rate Totten Ice Shelf experiences is unusually high for East Antarctica. Key Points: First in situ radar‐derived basal melt estimate on Totten Ice Shelf yields 22 ± 2.1 m a−1, at least 40% lower than existing satellite estimatesRadar‐derived observation of tidal ice dynamics constrains estimate of ice thickness for a complex baseThe use of multiple basal reflections in melt derivation increases robustness of the estimate when early off‐nadir returns are present [ABSTRACT FROM AUTHOR]

Two atmospheric VHF radars: ESRAD (Esrange MST radar) located near Kiruna in the Swedish Arctic and MARA (Moveable Atmospheric Radar for Antarctica) at the Indian research station Maitri in Antarctica perform wind measurements in the troposphere and lower stratosphere on a regular basis. We compared horizontal winds at altitudes between about 0.5 and 14 km derived from the radar data using the full correlation analysis (FCA) technique with radiosonde observations and models. The comparison with 28 radiosondes launched from January 2017 to August 2019 showed that ESRAD underestimates the zonal and meridional winds by about 8 % and 25 %, respectively. This is likely caused by the receiver group arrangement used for the FCA together with a high level of non-white noise. A similar result was found when comparing with the regional numerical weather prediction model HARMONIE-AROME (Bengtsson et al., 2017) for the period September 2018–May 2019. The MARA winds were compared with winds from radiosondes for the period February–October 2014 (291 occasions). In contrast to ESRAD, there is no indication that MARA underestimates the winds compared to the sondes. The mean difference between the radar and radiosonde winds is close to zero for both zonal and meridional components. The comparison of MARA with the ECMWF ERA5 reanalysis for January–December 2019 reveals good agreement with the mean difference between 0.1 and - 0.5 m/s depending on the component and season. The random errors in the wind components (standard deviations over all estimates in 1 h averages) are typically 2–3 m/s for both radars. Standard deviation of the differences between radars and sondes are 3–5 m/s. [ABSTRACT FROM AUTHOR]

The area near Dome C, East Antarctica, is thought to be one of the most promising targets for recovering a continuous ice-core record spanning more than a million years. The European Beyond EPICA consortium has selected Little Dome C (LDC), an area ∼ 35 km southeast of Concordia Station, to attempt to recover such a record. Here, we present the results of the final ice-penetrating radar survey used to refine the exact drill site. These data were acquired during the 2019–2020 austral summer using a new, multi-channel high-resolution very high frequency (VHF) radar operating in the frequency range of 170–230 MHz. This new instrument is able to detect reflectors in the near-basal region, where previous surveys were largely unable to detect horizons. The radar stratigraphy is used to transfer the timescale of the EPICA Dome C ice core (EDC) to the area of Little Dome C, using radar isochrones dating back past 600 ka. We use these data to derive the expected depth–age relationship through the ice column at the now-chosen drill site, termed BELDC (Beyond EPICA LDC). These new data indicate that the ice at BELDC is considerably older than that at EDC at the same depth and that there is about 375 m of ice older than 600 kyr at BELDC. Stratigraphy is well preserved to 2565 m, ∼ 93 % of the ice thickness, below which there is a basal unit with unknown properties. An ice-flow model tuned to the isochrones suggests ages likely reach 1.5 Myr near 2500 m, ∼ 65 m above the basal unit and ∼ 265 m above the bed, with sufficient resolution (19 ± 2 kyr m -1) to resolve 41 kyr glacial cycles. [ABSTRACT FROM AUTHOR]

We propose a lightweight radar that autonomously measures snow depth over sea ice from an unmanned aerial vehicle (UAV). Development of this snow radar and its integration with an octocopter UAV is presented. Field trials of the UAV-mounted snow radar, conducted in Antarctica during the summer season of 2017/2018, are also described. The radar allows measurements of snow depths on sea ice between 10 and 100 cm. Additional reflections due to internal layers within the snow are evident at a few measurement points. The snow radar is evaluated for various flight parameters: stationary; flying at speeds between 1 and 3 m/s, and at heights from 5 to 15 m. Evaluation of snow-depth results indicates that a depth accuracy of ±3.2 cm is achieved with stationary measurements, and of ±9.1 cm with measurements at the various flight speeds. [ABSTRACT FROM AUTHOR]

Polarimetric radar systems are commonly used to study the microphysics of precipitation. While they offer continuous measurements with a large spatial coverage, retrieving information about the microphysical processes that govern the evolution of snowfall from the polarimetric signal is challenging. The present study develops a new method, called Process Identification based on Vertical gradient Signs (PIVS), to spatially identify the occurrence of the main microphysical processes (aggregation and riming, crystal growth by vapor deposition, and sublimation) in snowfall from dual-polarization Doppler radar scans. We first derive an analytical framework to assess in which meteorological conditions the local vertical gradients of radar variables reliably inform about microphysical processes. In such conditions, we then identify regions dominated by (i) vapor deposition, (ii) aggregation and riming and (iii) snowflake sublimation and possibly snowflake breakup based on the sign of the local vertical gradients of the reflectivity ZH and the differential reflectivity ZDR. The method is then applied to data from two frontal snowfall events: one in coastal Adélie Land, Antarctica and one in the Taebaeck mountains in South Korea. The validity of the method is assessed by comparing its outcome with snowflake observations using a Multi-Angle Snowflake Camera and with the output of a hydrometeor classification based on polarimetric radar signal. The application of the method further makes it possible to better characterize and understand how snowfall forms, grows and decays in two different geographical and meteorological contexts. For the Antarctic case study, we show that crystal growth by vapor deposition dominates above 2500 m a.g.l., aggregation and riming prevail between 1500 and 2500 m a.g.l. and snowflake sublimation by low-level katabatic winds occurs below 1500 m a.g.l.. For the event in South Korea, aggregation and riming dominate between 4000 and 4800 m a.g.l., with local sublimation below and vapor deposition above. We infer some microphysical characteristics in terms of radar variables from statistical analysis of the method output (e.g. ZH and ZDR distribution for each process). We finally highlight the potential for extensive application to cold precipitation events in different meteorological contexts. [ABSTRACT FROM AUTHOR]

The surface mass balance (SMB) of West Antarctica is an important glaciological input to understanding polar climate and sea-level rise but with historically poor in situ data coverage. Previous studies demonstrate the utility of frequency-modulated continuous-wave radar to image subsurface layering in ice sheets, providing an additional source of data with which to estimate SMB. Traditional methods, however, require time-intensive manual oversight. Here, we present a probabilistic, fully automated approach to estimate annual SMB and uncertainties from radar echograms using successive peak-finding and weighted neighborhood search algorithms with the Monte Carlo simulations based on annual-layer likelihood scores. We apply this method to ground-based and airborne radar in a 175-km transect of the West Antarctic interior and compare the results to traditional manual methods and independent estimates from firn cores. The method demonstrates an automated estimation of SMB across a range of accumulation rates (100–450-mm water equivalent per year) and layer gradients up to 2 m/km. Based on likelihood-weighted F-scores, automated layer picks have a success rate between 64% and 84.6% compared with manually picked layers for three validation sites dispersed across the region. Comparisons between the automated SMB estimates and independent firn cores show a bias of 24 ± 70-mm water equivalent per year (12% ± 35% water equivalent of the in situ mean accumulation rate) although individual core site biases differ. This new approach permits the fully automated extraction of annual SMB rates and should be broadly and readily applicable to previously collected and ongoing radar data sets across polar regions. [ABSTRACT FROM AUTHOR]

We have examined a general expression giving the specular reflection coefficient for a radar wave approaching a reflecting interface with normal incidence. The reflecting interface separates two homogeneous isotropic media, the properties of which are fully described by three scalar quantities: dielectric permittivity, magnetic permeability, and electrical conductivity. The derived relationship indicates that electrical conductivity should not be neglected a priori in glaciological investigations of subglacial materials and in ground-penetrating radar (GPR) studies of saturated sediments and bedrock, even at the high end of typical linear radar frequencies used in such investigations (e.g., 100–400 MHz). Our own experience in resistivity surveying in Antarctica, combined with a literature review, suggests that a wide range of geologic materials can have electrical conductivity that is high enough to significantly impact the value of radar reflectivity. Furthermore, we have given two examples of prior studies in which inclusion of electrical conductivity in calculation of the radar bed reflectivity may provide an explanation for results that may be considered surprising if the impact of electrical conductivity on radar reflection is neglected. The commonly made assumption that only dielectric permittivity of the two media needs to be considered in interpretation of radar reflectivity can lead to erroneous conclusions. [ABSTRACT FROM AUTHOR]

Using frequency-modulated continuous wave radar data from the 32nd Chinese Antarctic Research Expedition in 2015/16, subsurface profiles were obtained along an East Antarctic inland traverse from Zhongshan station to Dome A, and four distinct regions were selected to analyze the spatiotemporal variability in historical surface mass balance (SMB). Based on depth, density, and age data from ice cores along the traverse, the radar data were calibrated to yield average SMB data. The zone 49–195 km from the coast has the highest SMB (235 kg m−2 a−1). The 780–892 km zone was most affected by the Medieval Warm Period and the Little Ice Age, and the SMB during ad 1454–1836 (71 kg m−2 a−1) was only one-quarter of that in the 20th century. The SMB in the 1080–1157 km zone fluctuates the most, possibly due to erosion or irregular deposition of snow by katabatic winds in low SMB areas with surface elevation fluctuations. Dome A (1157–1236 km) has the lowest SMB (29 kg m−2 a−1) and did not decrease during Little Ice Age. Understanding the spatiotemporal variability of SMB in a larger space can help us understand the complex climate history of Antarctica. [ABSTRACT FROM AUTHOR]

The East Antarctic Ice Sheet (EAIS) is the largest source of potential sea-level rise, containing approximately 52 m of sea-level equivalent. To constrain estimates of sea-level rise into the future requires knowledge of ice-sheet properties and geometry and ice-penetrating radar offers a means to estimate these properties (e.g. ice thickness, englacial temperatures). One of the regions that have been extensively surveyed using ice-penetrating radar from the Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project in East Antarctica is Law Dome, a small independent ice cap situated to the west of Totten Ice Shelf. The ice cap is slow-moving, has a low melt-rate at the surface and moderate wind speeds, making it a useful study site for estimating the radar attenuation. A new method is proposed for the estimation of attenuation rate from radar data which is mathematically modelled as a constrained regularised l2 minimisation problem. In the proposed method, only radar data is required and the englacial reflectors are automatically detected from the radar data itself. To validate our methodology, attenuation differences at flight crossover points are calculated and statistical analyses performed to assess the accuracy of the results. For spatial analyses, the errors are of the order 22.6 %, 15.2 %, and 32.8 % for mean absolute error, median absolute error, and root mean square error respectively. Also, for the depth analyses, up to the depth of 800 m, the errors are under 29.9 %, 24.2 %, and 38.8 % for mean absolute error, median absolute error, and root mean square error respectively. A final product of 3D attenuation rates and uncertainty estimates is provided. The generated dataset is publicly available at https://doi.org/10.25959/5e6851e266f4a (Abdul Salam, 2020). [ABSTRACT FROM AUTHOR]

Two atmospheric VHF radars: ESRAD located near Kiruna in the Swedish Artic and MARA at Indian research station Maitri in Antarctica perform wind measurements in the troposphere and lower stratosphere on a regular basis. We compared horizontal winds at altitudes between about 0.5 km and 14 km derived from the radar data using the full correlation analysis technique with radiosonde observations and models. The comparison with 28 radiosondes launched from January 2017 to August 2019 showed that ESRAD underestimates the zonal and meridional winds by about 8 % and 25 %, respectively. The mean differences between the radar and radiosonde winds are -1.4 m/s and 0.4 m/s. A similar result was found when comparing with the regional NWP model HARMONIE-AROME for the period September 2018-May 2019. The ESRAD random error was estimated to be 2.8 m/s (2.4 m/s) for the zonal (meridional) component. The comparison of MARA with the ECMWF ERA5 reanalysis for January-December 2019 reveals good agreement between them with the mean difference between 0.1 m/s and -0.5 m/s depending on the component and season. The MARA random errors are 2.6 m/s and 2.3 m/s for the zonal and meridional winds, respectively. [ABSTRACT FROM AUTHOR]

In order to measure the variance of wind velocity, which is contributed from turbulence, via radar observations, it is necessary to remove the unwanted contribution from strong horizontal velocity components through the finite beamwidth of the radar. This effect is referred to as beam broadening. Although the amount of beam broadening has thus far been calculated based on the approximating assumption that the pattern of the beam is rotationally symmetric and has very low sidelobes, we need to take a more theoretical approach to radar—one that does not have a simple beam pattern like the Antarctic Program of the Antarctic Syowa Station (PANSY) radar (69S, 39E). In this article, we clarify the theoretical relationship in a very simple form between the turbulence spectrum, which is directly associated with the variance of turbulence, two-way beam patterns, and the observed spectrum, using autocorrelation functions (ACFs). The theory is thoroughly universal and applicable to any type of atmospheric radar, such that we can quantitatively analyze radar observation systems. Furthermore, we propose a “debroadening” algorithm based directly on this theory and from calculations of the general maximum likelihood (ML). We performed numerical simulations that validate our theory and the algorithm. [ABSTRACT FROM AUTHOR]

Radar surveys across ice sheets typically measure numerous englacial layers that can often be regarded as isochrones. Such layers are valuable for extrapolating age–depth relationships away from ice-core locations, reconstructing palaeoaccumulation variability, and investigating past ice-sheet dynamics. However, the use of englacial layers in Antarctica has been hampered by underdeveloped techniques for characterising layer continuity and geometry over large distances, with techniques developed independently and little opportunity for inter-comparison of results. In this paper, we present a methodology to assess the performance of automated layer-tracking and layer-dip-estimation algorithms through their ability to propagate a correct age–depth model. We use this to assess isochrone-tracking techniques applied to two test case datasets, selected from CreSIS MCoRDS data over Antarctica from a range of environments including low-dip, continuous layers and layers with terminations. We find that dip-estimation techniques are generally successful in tracking englacial dip but break down in the upper and lower regions of the ice sheet. The results of testing two previously published layer-tracking algorithms show that further development is required to attain a good constraint of age–depth relationships away from dated ice cores. We recommend that auto-tracking techniques focus on improved linking of picked stratigraphy across signal disruptions to enable accurate determination of the Antarctic-wide age–depth structure. [ABSTRACT FROM AUTHOR]

The mesosphere is one of the most difficult parts of the atmosphere to sample; it is too high for balloon measurements and too low for in situ satellites. Consequently, there is a reliance on remote sensing (either from the ground or from space) to diagnose this region. Ground-based radars have been used since the second half of the 20th century to probe the dynamics of the mesosphere; medium-frequency (MF) radars provide estimates of the horizontal wind fields and are still used to analyse tidal structures and planetary waves that modulate the meridional and zonal winds. The variance of the winds has traditionally been linked qualitatively to the occurrence of gravity waves. In this paper, the method of wind retrieval (full correlation analysis) employed by MF radars is considered with reference to two systems in Antarctica at different latitude (Halley at 76 ∘ S and Rothera at 67 ∘ S). It is shown that the width of the velocity distribution and occurrence of "outliers" is related to the measured levels of anisotropy in the received signal pattern. The magnitude of the error distribution, as represented by the wind variance, varies with both insolation levels and geomagnetic activity. Thus, it is demonstrated that for these two radars the influence of gravity waves may not be the primary mechanism that controls the overall variance. [ABSTRACT FROM AUTHOR]

Englacial layers in Antarctica and Greenland are indicators of the dynamic, rheological and subglacial configuration of the ice sheets. Airborne radar sounder data is the primary remote sensing solution for directly observing englacial layers and structures at the glacier-catchment to ice-sheet scale. However, when traditional along-track synthetic aperture radar (SAR) processing is applied, steep layers can disappear, limiting the detectability and interpretability of englacial layer geometry. This study provides a reconstruction algorithm to address the problem of destructive phase interference during the radargram formation. We develop and apply a novel SAR processor optimized for layer detection that enhances the Signal-to-Noise ratio (SNR) of specular reflectors. The algorithm also enables the automatic estimation of layer slope. We demonstrate the algorithm using data acquired at the Institute Ice Stream, West Antarctica. [ABSTRACT FROM AUTHOR]

Airborne radar sounding can measure conditions within and beneath polar ice sheets. In Antarctica, most digital radar-sounding data have been collected in the last 2 decades, limiting our ability to understand processes that govern longer-term ice-sheet behavior. Here, we demonstrate how analog radar data collected over 40 y ago in Antarctica can be combined with modern records to quantify multidecadal changes. Specifically, we digitize over 400,000 line kilometers of exploratory Antarctic radar data originally recorded on 35-mm optical film between 1971 and 1979. We leverage the increased geometric and radiometric resolution of our digitization process to show how these data can be used to identify and investigate hydrologic, geologic, and topographic features beneath and within the ice sheet. To highlight their scientific potential, we compare the digitized data with contemporary radar measurements to reveal that the remnant eastern ice shelf of Thwaites Glacier in West Antarctica had thinned between 10 and 33% between 1978 and 2009. We also release the collection of scanned radargrams in their entirety in a persistent public archive along with updated geolocation data for a subset of the data that reduces themean positioning error from 5 to 2.5 km. Together, these data represent a unique and renewed extensive, multidecadal historical baseline, critical for observing and modeling ice-sheet change on societally relevant timescales. [ABSTRACT FROM AUTHOR]

The Program of the Antarctic Syowa Mesosphere–Stratosphere–Troposphere/Incoherent Scatter (PANSY) radar is a large atmospheric radar located at the Antarctic Syowa Station (69.01°S, 39.59°E). The PANSY radar performed the first incoherent scatter (IS) measurements in the Antarctic region in 2015. Several specific observations were undertaken in 2017 including a 24-h observation of the ionosphere using a peripheral antenna array to suppress interference from the field-aligned irregularities (FAIs). This paper presents the preliminary results derived from the IS measurements using the PANSY radar and the adaptive signal processing techniques to suppress FAIs. The norm-constrained and directionally constrained minimization of power (NC-DCMP) algorithm was applied to the 24-h ionosphere observations by the PANSY radar with a weighting applied to the directional constraint based on the gain differences of the subarrays. When compared with the conventional nonadaptive approach, the number of usable power profiles was increased by about 24% by the gain-weighted NC-DCMP algorithm, suggesting its effectiveness for FAI clutter suppression in ionosphere observations. Furthermore, detection of FAIs using the dedicated antenna array was found valuable in assessing the reliability of estimations of electron density based on VHF-band IS radar data. [ABSTRACT FROM AUTHOR]

We derive the surface and basal radar reflectance and backscatter coefficients of the southern McMurdo Ice Shelf (SMIS) and part of the nearby Ross Ice Shelf (RIS), Antarctica, from radar statistical reconnaissance using a 60-MHZ airborne survey. The surface coefficients are further inverted in terms of snow density and roughness, providing a spatial distribution of the processes contributing to the surface boundary conditions. We disentangle the basal coefficients from surface transmission losses, and we provide the basal coherent content, an indicator of the boundary geometric disorder that is also self-corrected from englacial attenuation. The basal radar properties exhibit sharp gradients along specific iso-depths, suggesting an abrupt modification of the ice composition and geometric structure. We interpret this behavior as locations where the pressure-melting point is reached, outlining fields of freezing and melting ice. Basal steps are observed at both SMIS and RIS, suggesting a common geometric expression of widespread basal processes. This technique offers a simultaneous view of both the surface and basal boundary conditions to help investigate the ice-shelf stability, while its application to airborne data significantly improves coverage of the difficult-to-observe ice–ocean boundary. It also provides constraints on thermohaline circulation in ice shelves cavities, which are analogs for ice-covered ocean worlds. [ABSTRACT FROM AUTHOR]

The mesosphere is one of the most difficult parts of the atmosphere to sample; too high for balloon measurements and too low for in-situ satellites. Consequently there is a reliance on remote sensing (either from the ground or from space) to diagnose this region. Ground based radars have been used since the second half of the 20th century to probe the dynamics of the mesosphere; Medium Frequency (MF) radars provide estimates of the horizontal wind fields and are still used to analyse tidal structures and planetary waves that modulate the meridional and zonal winds. The variance of the winds has traditionally been linked qualitatively to the occurrence of gravity waves. In this paper the method of wind retrieval (full correlation analysis) employed by MF radars is considered with reference to two systems in Antarctica at different latitude (Halley at 76° S and Rothera at 67° S). It is shown that the width of the velocity distribution and occurrence of 'outliers' is related to the measured levels of anisotropy in the received signal pattern. The magnitude of the error distribution, as represented by the wind variance, varies with both insolation levels and geomagnetic activity. Thus it is demonstrated that for these two radars the influence of gravity waves may not be the primary mechanism that controls the overall variance. [ABSTRACT FROM AUTHOR]

During the past decades, radar sounder (RS) instruments have been effectively used to detect subglacial lakes (SLs). SLs appear as flat, smooth, and bright reflectors in RS radargrams. The visual interpretation has been the main approach to SL detection in radargrams. However, this approach is subjective and inappropriate for processing large amounts of radargrams. While the analysis of RS data for understanding the subglacial hydrology has recently received increased attention, the literature on the development of automatic methods specifically designed for SL detection is still limited. In order to fill this gap, in this paper, we propose a novel automatic technique for SL detection. The technique is made up of two steps: 1) feature extraction and 2) automatic detection. In the first step, we define and extract three families of features for discriminating between the lake and nonlake radar reflections. The features model locally the basal topography, the shape of the basal reflected waveforms, and the statistical properties of the basal signal. In the second step, we provide the features as input to a support vector machine classifier to perform the automatic SL detection. The proposed technique has been applied to radargrams acquired over two large regions in East Antarctica and Siple Coast. The obtained results, which are validated both quantitatively and qualitatively, confirm the robustness of the features and their capabilities to effectively characterize SLs. Moreover, they prove the potentiality of the method to process large amounts of radargrams and update the current SL inventory. [ABSTRACT FROM AUTHOR]

The Antarctic continent is a vast desert and is the coldest and the most unknown area on Earth. It contains the Antarctic ice sheet, the largest continental water reservoir on Earth that could be affected by the current global warming, leading to sea level rise. The only significant supply of ice is through precipitation, which can be observed from the surface and from space. Remote-sensing observations of the coastal regions and the inner continent using CloudSat radar give an estimated rate of snowfall but with uncertainties twice as large as each single measured value, whereas climate models give a range from half to twice the space–time-averaged observations. The aim of this study is the evaluation of the vertical precipitation rate profiles of CloudSat radar by comparison with two surface-based micro-rain radars (MRRs), located at the coastal French Dumont d'Urville station and at the Belgian Princess Elisabeth station located in the Dronning Maud Land escarpment zone. This in turn leads to a better understanding and reassessment of CloudSat uncertainties. We compared a total of four precipitation events, two per station, when CloudSat overpassed within 10 km of the station and we compared these two different datasets at each vertical level. The correlation between both datasets is near-perfect, even though climatic and geographic conditions are different for the two stations. Using different CloudSat and MRR vertical levels, we obtain 10 km space-scale and short-timescale (a few seconds) CloudSat uncertainties from -13 % up to +22 %. This confirms the robustness of the CloudSat retrievals of snowfall over Antarctica above the blind zone and justifies further analyses of this dataset. [ABSTRACT FROM AUTHOR]

CloudSat spaceborne radar snowfall retrievals using two different methodologies – the 2C-SNOW-PROFILE (2C-SNOW) CloudSat product and the combined Kulie and Bennartz (2009) technique with the Hiley et al. (2011) reflectivity (Z) to snowfall rate (S) conversion (KBH) - are compared over Antarctica and surrounding Southern Ocean environments. KBH algorithm sensitivity tests are performed to demonstrate how retrievals are affected by algorithm assumptions (e.g., vertical reflectivity continuity test, the choice of near surface bin used to make surface snowfall rate retrievals, and temperature filters). These algorithm components are found to be detrimental to snowfall detection over this region by significantly reducing the snowfall population compared to 2C-SNOW, especially over ocean regions prone to ERA-interim indicated convective snow. After accounting for key algorithm differences, 2C-SNOW mean annual snowfall rates are systematically higher than KBH due to the Z -S relationship adopted. Spatial annual mean snowfall accumulation differences between the two datasets are minimized over interior Antarctica, but large differences are observed over the ocean. 2C-SNOW Z -S relationships for all snowfall events (Z = 10.9 S 1.3 ), over ocean and sea ice (Z = 8.2 S 1.3 ), escarpments and Antarctic coastal areas - below 2000 m a.s.l. (Z = 6.7 S 1.4 ), and Antarctic plateau - above 2000 m a.s.l. (Z = 5.5 S 1.6 ) are also derived. A multi-year 2C-SNOW mean annual snowfall analysis is also provided, and comparisons with ERA-Interim snowfall datasets show similar spatial patterns, but magnitude differences over oceans are observed. A monthly 2C-SNOW and acoustic depth gauge analysis is provided to demonstrate qualitative trends in snowfall accumulation between the respective datasets. [ABSTRACT FROM AUTHOR]

Snowfall rate (SR) estimates over Antarctica are sparse and characterised by large uncertainties. Yet, observations by precipitation radar offer the potential to get better insight in Antarctic SR. Relations between radar reflectivity (Ze) and snowfall rate (Ze-SR relations) are however not available over Antarctica. Here, we analyse observations from the first Micro Rain Radar (MRR) in Antarctica together with an optical disdrometer (Precipitation Imaging Package; PIP), deployed at the Princess Elisabeth station. The relation Ze = A*SR B was derived using PIP observations and its uncertainty was quantified using a bootstrapping approach, randomly sampling within the range of uncertainty. This uncertainty was used to assess the uncertainty in snowfall rates derived by the MRR. We find a value of A = 18 [11–43] and B = 1.10 [0.97–1.17]. The uncertainty on snowfall rates of the MRR based on the Ze-SR relation are limited to 40%, due to the propagation of uncertainty in both Ze as well as SR, resulting in some compensation. The prefactor (A) of the Ze-SR relation is sensitive to the median diameter of the snow particles. Larger particles, typically found closer to the coast, lead to an increase of the value of the prefactor (A = 44). Smaller particles, typical of more inland locations, obtain lower values for the prefactor (A = 7). The exponent (B) of the Ze-SR relation is insensitive to the median diameter of the snow particles. In contrast with previous studies for various locations, shape uncertainty is not the main source of uncertainty of the Ze-SR relation. Parameter uncertainty is found to be the most dominant term, mainly driven by the uncertainty in mass-size relation of different snow particles. Uncertainties on the snow particle size distribution are negligible in this study as they are directly measured. Future research aiming at reducing the uncertainty of Ze-SR relations should therefore focus on obtaining reliable estimates of the mass-size relations of snow particles. [ABSTRACT FROM AUTHOR]

The article compares the link obtained between the Dome C and Vostok ice cores in East Antarctica using radar reflections only with that obtained with the help of volcanic tie-points in the two ice cores. The deepest volcanic tie-point reaches 1804 metres and 1992 metres depth at Dome C and Vostok, respectively.

Ice shelves fringe much of the Antarctic continent, and, despite being up to 2 km thick, are vulnerable to climate change. Owing to their role in helping to control the ice sheet contribution to sea level change there is great interest in measuring the rate at which they are melting into the ocean. This study describes the development and deployment of an icepenetrating phase-sensitive FMCW radar, sufficiently robust and with sufficiently low-power consumption to be run through the Antarctic winter as a standalone instrument, yet with the stability and mm-precision needed to detect the very slow changes in ice shelf thickness in this exceptionally demanding environment. A number of elegant processing techniques are described to achieve reliable, high-precision performance and results presented on field data obtained from the Larsen-C ice shelf, Antarctica. [ABSTRACT FROM AUTHOR]

A Rayleigh-Raman lidar system was installed in January 2011 at Syowa Station, Antarctica (69.0° S, 39.6° E). Polar mesospheric clouds (PMCs) were detected by lidar at around 22:30UTC (LT -3 h) on 4 February 2011, which was the first day of observation. This was the first detection of PMCs over Syowa Station by lidar. On the same day, a Super Dual Auroral Radar Network (SuperDARN) HF radar with oblique-incidence beams detected polar mesospheric summer echoes (PMSE) between 21:30 and 23:00 UTC. This event is regarded as the last PMC activity around Syowa Station during the austral summer season (2010-2011), since no other PMC signals were detected by lidar in February 2011. This is consistent with results of PMC and mesopause temperature observations by satellite-born instruments of AIM (Aeronomy of Ice in the Mesosphere)/CIPS (Cloud Imaging and Particle Size) and AURA/MLS (Microwave Limb Sounder) and horizontal wind measurements taken by a separate MF radar. Doppler velocity of PMSE observed by the HF radar showed motion toward Syowa Station (westward). This westward motion is consistent with the wind velocities obtained by the MF radar. However, the PMSE region showed horizontal motion from a north-to-south direction during the PMC event. This event indicates that the apparent horizontal motion of the PMSE region can deviate from neutral wind directions and observed Doppler velocities. [ABSTRACT FROM AUTHOR]

In this study, ion drift velocities measured by Digisonde instruments over Zhongshan Station (ZHS, geog. 69.38°S, 76.38°E), Antarctica, are compared with measurements from Super Dual Auroral Radar Network (SuperDARN) HF radars. For SuperDARN Syowa East (SYE) and Kerguelen (KER) radars that intersect with ZHS, a data set comprised of adjacent range gates from nearest radar beams is used. Digisonde ion drift measurements were projected onto the direction of co-located and concurrent line-of-sight SuperDARN velocities. A comparison of the velocities shows a clear correlation (R = 0.92) between the two data sets. Projected Digisonde velocity was found to be, on average, larger than the line-of-sight SuperDARN radar velocities by a factor of 1.7. Time dependence distributions of Digisonde-SuperDARN SYE radars showed that the larger velocity discrepancies are more located at the dawnside convection cell. Considering the known features of the high-latitude convection patterns at cusp latitude, the statistical results imply the velocity discrepancies are related to the differences in the temporal and spatial evolution of plasma structures. [ABSTRACT FROM AUTHOR]

Snow plays a crucial role in the hydrological cycle and energy budget of the Earth, and remote sensing instruments with the necessary spatial coverage, resolution, and temporal sampling are essential for snowfall monitoring. Among such instruments, ground-radars have scanning capability and a resolution that make it possible to obtain a 3D structure of precipitating systems or vertical profiles when used in profiling mode. Radars from space have a lower spatial resolution, but they provide a global view. However, radar-based quantitative estimates of solid precipitation are still a challenge due to the variability of the microphysical, geometrical, and electrical features of snow particles. Estimations of snowfall rate are usually accomplished using empirical, long-term relationships between the equivalent radar reflectivity factor (Ze) and the liquid-equivalent snowfall rate (SR). Nevertheless, very few relationships take advantage of the direct estimation of the microphysical characteristics of snowflakes. In this work, we used a K-band vertically pointing radar collocated with a laser disdrometer to develop Ze-SR relationships as a function of snow classification. The two instruments were located at the Italian Antarctic Station Mario Zucchelli. The K-band radar probes the low-level atmospheric layers, recording power spectra at 32 vertical range gates. It was set at a high vertical resolution (35 m), with the first trusted range gate at a height of only 100 m. The disdrometer was able to provide information on the particle size distribution just below the trusted radar gate. Snow particles were classified into six categories (aggregate, dendrite aggregate, plate aggregate, pristine, dendrite pristine, plate pristine). The method was applied to the snowfall events of the Antarctic summer seasons of 2018–2019 and 2019–2020, with a total of 23,566 min of precipitation, 15.3% of which was recognized as showing aggregate features, 33.3% dendrite aggregate, 7.3% plates aggregate, 12.5% pristine, 24% dendrite pristine, and 7.6% plate pristine. Applying the appropriate Ze-SR relationship in each snow category, we calculated a total of 87 mm water equivalent, differing from the total found by applying a unique Ze-SR. Our estimates were also benchmarked against a colocated Alter-shielded weighing gauge, resulting in a difference of 3% in the analyzed periods. [ABSTRACT FROM AUTHOR]

SUMMARY Based on the Ice, Cloud and Land Elevation Satellite (ICESat) laser altimetry data, the hydrostatic equilibrium (HE) condition for the subglacial Lake Vostok, East Antarctica, is evaluated. A digital elevation model (DEM) of the ice surface is derived by a regional crossover adjustment. The analysis of the DEM and its comparison with GPS derived ice-surface elevations and an ice-surface DEM based on radar altimetry data reveal an overall accuracy of better than ± 0.7 m for the lake area. The DEM is combined with an ice-thickness model and a regional geoid model to determine the deviation of the local ice-surface height from HE. For large parts of the lake, the ice sheet fulfils the HE. Our results reveal a strong positive deviation of about 10 m along the lake shoreline. In addition, positive deviations are found in the northern part of the lake which coincide with ice rumples detected by radio-echo sounding. In the southern part of the lake, we find a linear negative deviation ( −4.0 m) which coincides with the convoy route from Vostok station to Mirny base. In addition to the DEM, relative biases for the ICESat laser operational periods are determined in the regional crossover adjustment. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we investigate the impact of the error due to the penetration of the altimetric wave within the snowpack. The phenomenon has two different impacts. The first one, due to temporal change in snow characteristics, affects the ice sheet volume trend as derived from altimetric series. The second one, because of both the anisotropy of the ice sheet surface properties and of the linear antenna polarization, introduces a difference in measurements at crossover points. These two phenomena are the cause of what are probably the most critical limitations to the interpretation of long-term altimetric series in term of mass balance and to the comparison between or data fusion of different missions. Moreover, they will lead to the largest error when comparing data from EnviSat with data from CryoSat, because of the different orbits, or with data from AltiKa, because of the different radar frequencies. We show that waveform distortions due to snow characteristics fluctuation are complex. In the central part of the East Antarctica, the height and the leading edge width fluctuations vary together while elsewhere, height fluctuations may occur with no variations in the waveform shape, mostly during winter. As a consequence, these induced errors cannot be corrected with solely the help of the backscatter: waveform shape parameters are also needed. They are however not enough to fully correct these two errors. We propose an empirical correction for these effects. We show that crossover differences may be significantly reduced to up 22cm. In terms of volume change, the estimation may vary up to 4cm/yr at cross-overs depending on the correction used and is reduced in average to 2.3cm/yr with our correction. The difference between the height trends estimated with both corrections is weak in average but may locally reach 5cm/yr with a clear geographical pattern. [Copyright &y& Elsevier]