Abstract: 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.

Abstract: The high frequency radars in the Super Dual Auroral Radar Network (SuperDARN) estimate the elevation angles of returned backscatter using interferometric techniques. These elevation angles allow the ground range to the scattering point to be estimated, which is crucial for the accurate geolocation of ionospheric measurements. For elevation angles to be accurately estimated, it is important to calibrate the interferometer measurements by determining the difference in the signal time delays caused by the difference in the electrical path lengths from the main array and the interferometer array to the point at which the signals are correlated. This time delay is known as tdiff. Several methods have been proposed to estimate tdiff using historical observations; these methods are summarised in this paper. Comparisons of the tdiff estimates from the different calibration methods are presented and sources of uncertainty discussed. The effect of errors in the estimated tdiff value on the accuracy of geolocation is evaluated and discussed. The paper concludes with a series of recommendations for both scientific SuperDARN data users and SuperDARN radar operators.

Abstract: The atmospheric cosmic-ray environment is composed of secondary particles produced when primary cosmic rays interact with the nucleus of atmospheric atoms. Modeling of atmospheric radiations is essential for investigating their impacts on human activities such as radiation risks in aviation or scientific fields such as cosmogenic dating. The nuclear transport codes are a common and accurate way to model the cosmic ray interaction in the atmosphere with minimal approximations. However, tracking all produced secondary particles in each event in the whole depth of the atmosphere and sampling many events to obtain the statistically meaningful results would be a computational challenge and disadvantageous from the point of view of time consumption. This paper presents a computational platform names ATMOS CORE based on pre-calculated databases coupled to physical models and computational methods. The fields of application concern the atmospheric cosmic-rays characterization as well as their effects on electronics systems, on the ambient dose for aircrews or the cosmogenic nuclide production for dating activities. Some comparisons between simulations and measurements are also presented and discussed.