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In polar regions, blowing snow (BLSN) can play a substantial role in regional thermodynamics and radiation properties. The extent of the impact depends upon the depth of the BLSN layer, a property that is difficult to measure and not well understood. The West Antarctic Radiation Experiment (AWARE) Field Campaign saw the deployment of a large suite of observational instruments to McMurdo Station, Antarctica, allowing for in‐depth investigation of BLSN. During the year of the campaign, BLSN occurred ∼7.4% of the time. In this study, additional remote sensing observations are used to supplement an existing ceilometer‐based BLSN characterization algorithm creating a multi‐instrument (MI) depth estimation algorithm to yield layer depths with more certainty. Backscatter coefficient and linear depolarization ratios from the micropulse and high spectral resolution lidar (HSRL) are incorporated along with color ratio derived from HSRL backscatter and Ka‐band radar reflectivity observations. This provided estimates of BLSN depth that were less impacted by noise/artifacts in any one set of observations. When applied to the data from AWARE, the MI algorithm yielded an average depth of 168.2 m with ∼60% of plumes less than 200 m in depth. Events occurring with precipitation saw the most value in the additional instruments, with the suite of observations allowing for more separation of BLSN particles from fallstreaks. Plain Language Summary: This study used multiple lidar and radar instruments to identify the height of blowing snow (BLSN) layers at McMurdo Station in Antarctica. This information can be used to evaluate and improve BLSN models which have had minimal verification above ground. Results of this study compare well to prior studies, however, the suite of instruments demonstrate that agreement is partially due to compensating errors within single instrument (ceilometer) studies. Key Points: Inclusion of additional lidars and radar improve estimates of blowing snow layer heightsCeilometer only algorithms are prone to offsetting height errors due to extinction and fallstreaksFuture in situ observations are paramount to improving and validating this experimental algorithm [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]

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]

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]

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]

Ground-based snowfall observations over Antarctica are rare due to the harsh environment and high logistical, equipment maintenance, and operational costs. Satellite measurements are crucial to provide continent-wide precipitation estimates, and this highlights the importance of validating the satellite estimates with measurements collected by ground-based Antarctic stations. The NASA CloudSat satellite, launched in 2006, is equipped with a 94 GHz (W-band) Cloud Profiling Radar (CPR) that provides measurements of reflectivity profiles of clouds and precipitation, whereas the incoming ESA/JAXA EarthCARE mission will add Doppler capability to a 94 GHz radar. This study explores how the synergy between two instruments available at most Antarctic stations, i.e., Micro Rain Radar (24 GHz, K-band) and laser disdrometer, can be used to validate satellite-borne W-band radar measurements, including Doppler estimates. A new validation methodology (K2W) was proposed to combine these instruments for simulating the 94 GHz reflectivity and Doppler measurements from Micro Rain Radar spectra. Assessment of the proposed K2W conversion methodology showed that the CloudSat Z e profiles can be simulated by the method with 0.2 dB mean difference at the lowest satellite radar range bin when time lag within ±12.5 min and the distance within 25 km around the CloudSat overpass were considered. With the K2W method, the 94 GHz Doppler velocity below 1 km altitude that would be observed by EarthCARE was obtained, and the standard deviation of the simulated Doppler velocity was found to be smaller than about 0.2 m s−1. The simulated 94 GHz Doppler radar profile information, which is less affected by attenuation compared to ground-based 94 GHz radar, will significantly improve the quantification of precipitation over Antarctica. This methodology will be applied to further assess the EarthCARE CPR Doppler velocity measurement accuracy as well as the Level 2 standard products for precipitation in Antarctica and at many other ground observation sites. • Synergy between 24 GHz Micro Rain Radar and disdrometer is used by K2W methodology • 94 GHz Doppler Spectra below 1 km were obtained in Antarctica • CloudSat radar reflectivity was evaluated within 0.2 dB by K2W • EarthCARE radar Doppler velocities are expected to be evaluated within 0.2 m s−1 • The wide applicability of K2W hugely raises opportunities for EarthCARE validation [ABSTRACT FROM AUTHOR]

To understand the dynamics of ice shelves, a knowledge of their internal and basal structure is very important. As the capacity to perform local surveys is limited, remote sensing provides an opportunity to obtain the relevant information. We must prove, however, that the relevant information can be obtained from remote sensing of the surface. That is the aim of this study. The Jelbart Ice Shelf, Antarctica, exhibits a variety of surface structures appearing as stripe-like features in radar imagery. We performed an airborne geophysical survey across these features and compared the results to TerraSAR-X imagery. We find that the stripe-like structures indicate surface troughs coinciding with the location of basal channels and crevasse-like features, revealed by radio-echo sounding. HH and VV polarizations do not show different magnitude. In surface troughs, the local accumulation rate is larger than at the flat surface. Viscoelastic modelling is used to gain an understanding of the surface undulations and their origin. The surface displacement, computed with a Maxwell model, matches the observed surface reasonably well. Our simulations show that the surface troughs develop over decadal to centennial timescales. [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]

Radar altimeters are important tools to monitor the volume of the ice sheets. The penetration of radar waves in the snowpack is a major source of uncertainty to retrieve surface elevation. To correct this effect, a better understanding of the sensitivity of the radar waveforms to snow properties is needed. Here, we present an extension of the Snow Model Radiative Transfer (SMRT) to compute radar waveforms and conduct a series of simulations on the Antarctic ice sheet. SMRT is driven by snow and surface roughness properties measured over a large latitudinal range during two field campaigns on the Antarctic Plateau. These measurements show that the snowpack is rougher, denser, less stratified, warmer, and has smaller snow grains near the coast than on the central Plateau. These simulations are compared to satellite observations in the Ka, Ku, and S bands. SMRT reproduces the observed waveforms well. For all sites and all sensors, the main contribution comes from the surface echo. The echo from snow grains (volume scattering) represents up to 40% of the amplitude of the total waveform power in the Ka band, and less at the lower frequencies. The highest amplitude is observed on the central Plateau due to the combination of higher reflection from the surface, higher scattering by snow grains in the Ka and Ku bands, and higher inter-layer reflections in the S band. In the Ka band, the wave penetrates in the snowpack less deeply on the central Plateau than near the coast because of the strong scattering caused by the larger snow grains. The opposite is observed in the S band, the wave penetrates deeper on the central Plateau because of the lower absorption due to the lower snow temperatures. The elevation bias caused by wave penetration into the snowpack show a constant bias of 10 cm for all sites in the Ka band, and a bias of 11 cm, and 21 cm in the Ku band for sites close to the coast and the central Plateau, respectively. Now that SMRT is performing waveform simulations, further work will address how the snowpack properties affect the parameters retrieved by more advanced retracking algorithms such as ICE-2 for different snow cover surfaces. • The snow radiative transfer model (SMRT) is extended for altimetry applications. • Waveform simulations are in good agreement with satellite observations in Antarctica. • The surface echo is the most important contribution in the Ka, Ku and S bands. • Smoother surfaces at the southern sites lead to higher waveform amplitudes. • In the Ka (resp. S) band, grain size (temperature) regulates the wave penetration depth. [ABSTRACT FROM AUTHOR]