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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]

Glaciers in polar regions are sensitive to climate and ocean changes and can thin rapidly as a consequence of global warming. Digital Elevation Models (DEMs) from remote sensing observations have been widely used to detect changes in polar glaciers. DEMs from Terrestrial Radar Interferometer (TRI) have recently been used for high frequency glacier change and glacier-ocean interaction studies. However, it is unclear whether TRI DEM over a large study area can be combined directly with remote sensing observations to investigate glacier changes as well as the accuracy of TRI DEM at far range. In this study, we deployed a TRI close to Helheim Glacier, East Greenland and generated DEMs using TRI and satellite laser altimetry. We analyzed the accuracy of the TRI DEM using theoretical calculations, comparisons based on repeat observations, and comparisons with a high accurate ArcticDEM. The validation results suggest that for stable ground surfaces, the uncertainty (standard deviation) is <5 m at range < 9.8 km. Averaging across time (e.g. one hour) decreases the uncertainty almost linearly with range, over 0.5 m to 1.2 m when the range increases from 7.0 km to 10.0 km. Increasing the correlation coefficient threshold for phase unwrapping does not significantly reduce uncertainty. TRI DEMs are influenced by systematic error at far range primarily due to coarse azimuth resolution and phase unwrapping difficulties in discontinuous interferograms. As the absolute accuracy of TRI DEMs is not uniformly distributed in the range direction (farther points have worse uncertainty), our findings indicate that TRI DEMs within range of 10 km can reach <5 m uncertainty, which can be compared with DEMs obtained from remote sensing satellites to detect glacier thinning. • A method to generate TRI DEM referring to WGS-84 ellipsoid is presented. • Averaging across time decreases the DEM uncertainty almost linearly with range. • Increasing correlation coefficient threshold does not significantly improve TRI DEM. • Large uncertainty at far range is caused by coarser azimuth resolution and discontinuous interferogram. • TRI DEMs with range < 10 km have <5 m uncertainty and can match satellite observations. [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]