Snow accumulation is the primary mass input to the Antarctic ice sheets. Its long-term spatio-temporal variability is however not well known, and the uncertainty in snow accumulation rates results in mass budget estimation errors. In this frame, while the Western part of Antarctica is now increasingly monitored, the Eastern part suffers a lack of in situ data. We therefore concentrate our study on this region, and use GNSS Interferometric Reflectrometry (GNSS-IR) to determine the long-term variations of the snow accumulation/ablation.
GNSS-IR is a well-established technique that uses signal-to-noise ratio (SNR) measurements to sense the antenna near field environment. Reflected signals, usually considered as a detriment in positioning methods, are here exploited and turned into a source of information on the reflecting surface. The frequency of the SNR interference sinusoidal pattern depends indeed on the vertical distance between the phase centre of the GNSS receiver antenna and the reflecting surface, and on the signal wavelength.
GNSS-IR (i.e. GPS and GLONASS) applied to antennas in Antarctica allows to retrieve snow height variations and to study snow precipitation/ablation in a meteorological sense. We used the homemade software ROB-IONO and Atomium to access the snow height variations at several GNSS stations in East Antarctica. The first antenna considered has been deployed in the snow by the Royal Observatory of Belgium on the Derwael Ice Rise, in the coastal Dronning Maud land. This station provided continuous data from late 2012 to early 2016. At the beginning, the marker of the antenna was buried 1.85 m in the firn. Every year a stick of roughly 1.6 meters was manually added to avoid the complete sink of the antenna in the snow. This effect is mainly due to the vertical movements (1.3 my-1) of the antenna towards the geocenter, caused by ice convective movements. Taking the antenna subsidence into account, we highlighted an annual variation of snow accumulation in April-May (~30-50 cm) and ablation during spring/summer period.
We also apply the method to GNSS stations from the IGS and POLENET networks, covering both the East and West Antarctic areas. From this study, first results on an Antarctica map of snow accumulation/ablation seasonal variations will be presented.

The primary goal of Global Navigation Satellite Systems (GNSS) is still the provision of the bases for positioning and navigation. However, in the course of the last two or three decades an overwhelming number of different applications far from navigation were discovered, developed and implemented. This paper discusses the use of reflected as well as of refracted GNSS signals for the determination of snow depth, surface inclination and snow water equivalent.
After a short introduction of ground based reflectometry, the application to the determination of terrain inclination on an airport will be reported. The multipath theory can conveniently help to formulate the basis of determination of snow depth by reflectometry. The environment around the antenna is of utmost importance since any reflected signal with enough strength will possibly jeopardize the GNSS direct signal. Especially in mountainous areas the reflectors (e.g. flanks of a Peak) lead to difficult interpretations of the measurements. In contrast to the reflectometry, we use refracted GNSS signals for determining the snow water equivalent above a buried antenna. The method works very well and allows determining the SWE at few mm precision. The tests, comparison and validation of the GNSS derived SWE were carried out at the test and observation site of the Swiss Snow and Avalanche Research Center in Davos. Results agree with a median relative bias below 10%. The GNSS solutions were compared to the manual reference (snow profiles), a snow pillow and a snow scale.
The systematic GNSS campaign measured data over three annual cycles, thus making possible a very comprehensive validation. The sensitivity of the SWE quantification is assessed for different GPS ambiguity resolution techniques, as the results strongly depend on the GPS processing.

After developing a wind speed retrieval algorithm from TechDemoSat-1 (TDS-1) space-borne GNSS Reflectometry (GNSS-R), the reliability of the GNSS-R ocean surface winds is characterized. This cross-validation is carried out in comparison to well-established Advanced SCATterometer (ASCAT) as a well-established ocean wind scatterometer. European Reanalysis Interim (ERA-Interim) wind fields of European Centre for Medium-range Weather Forecasts (ECMWF) are used as reference. The evaluation demostrates in an RMSE and bias of 2.77 and -0.33 m/s for TDS-1, while the RMSE and bias derived by ASCAT winds are as large as 2.33 and 0.25 m/s, respectively. The rain-affected observation of ASCAT and TDS-1 are collected for a performance evaluation during precipitation being collocated with rain microwave-IR estimates of the Tropical Rainfall Measuring Mission (TRMM). Despite the degradation in performance of ASCAT resulting in RMSE and bias of 3.16 and 1.03 m/s during rain events, TDS-1 wind speeds show a higher level of reliability with an RMSE and bias of 2.94 and -0.21 m/s, respectively. This fact demonstrates the promising capability of GNSS-R technique for wind retrievals during rainfalls.
Furthermore, a machine learning technique is implemented for wind speed inversion as a geophysical model function for the purpose of improving the wind speed quality. More specifically, a feedforward neural network is trained for the TDS-1 wind speed inversion. The fitted network results in a significant improvement of 17% in the wind speed RMSE compared to the least-squares-based approach. It also demonstrates an ability to model a variety of effects degrading the retrieval accuracy such as the different transmitted level of the effective isotropic radiated power of GPS satellites.
In the end, this study presents the first evidence that the bistatic radar cross section derived from TDS-1 measurements is decreased during rain events at winds lower than almost 6 m/s. This is characterized as the effect of altered roughness by the raindrops impinging on the ocean surface. The reduction is approximately 0.7 dB at the wind speed of 3 m/s due to a precipitation of 0-2 mm/h. The simulations based on the recently published scattering theory provide a plausible explanation for this phenomenon which potentially enables the GNSS-R technique to detect precipitation over oceans at low winds.

Spire Global, Inc. operates the world’s largest and rapidly growing constellation of CubeSats performing GNSS-based science and Earth observation. Currently, the Spire constellation consists of more than 70 3U CubeSats, with more than 25 satellites capable of performing a variety of GNSS science, including radio occultation, ionosphere measurements, and precise orbit determination. Beginning in 2018, Spire began an effort to design and build the first of many GNSS bistatic radar (or GNSS-R) missions for Earth observations for a variety of applications, including soil moisture measurement, wetlands and flood inundation mapping, sea surface roughness and winds, and sea ice characterization. Following an agile model of rapid, iterative satellite development that has been refined over many years to produce radio occultation payloads optimized for operation on ultra-small 3U CubeSats, we adopted a very aggressive schedule to adapt the current Spire 3U bus and STRATOS GNSS science receiver to perform GNSS-R measurements, with an expected launch in mid-2019. We will discuss the goals of the 2019 Spire GNSS-R missions, the design and operational modes of the first batch of Spire GNSS-R satellites, and plans for an iterative design effort for the next batch of Spire GNSS-R satellites.

Prior to the launch of the dedicated GNSS-R missions to perform scatterometry, Spire has also adapted it's currently orbiting GNSS radio occultation payload to perform grazing angle, phase-delay altimetry, a technqiue that may estimate surface heights to cm-level precision. Recently, with the launch of dedicated GNSS-R missions such as TechDemoSat-1 (TDS-1) and the eight-satellite CYGNSS constellation, phase observations of grazing angle reflections has again garnered interest and shown that the technique can perform cm-level precision altimetry over sea ice, lakes, and ice sheet surfaces. But these measurements have been limited to a few collections using the raw intermediate frequency (IF) modes on these satellites and have not been able to produce reliable statistics of the measurements, e.g., the likelihood of coherent reflections and their spatial and temporal distributions across various Earth surface types. To address this issue and to pursue an operational system for collection of grazing angle GNSS reflections, Spire recently reprogrammed its STRATOS GNSS science receiver to perform this measurement on currently orbiting RO satellites. To accomplish this, the open loop tracking used in RO collection was modified to perform open loop prediction and tracking of grazing angle reflections between 5-30 deg. This software mode was subsequently uploaded to one orbiting satellite and a tested successfully on the first attempt, acquiring 50 Hz in-phase and quadrature samples of GNSS reflections from sea ice and ocean surfaces. Initial results confirm coherency of reflections over sea ice surfaces and some open ocean surfaces. Further analysis will compute ocean and sea ice height profiles from these measurements. A production period has now begun on multiple satellites that will result in large quantities of diverse measurements from space in a relatively short time. We will present further results of this new and potentially revolutionary technique to use existing orbiting RO satellites to perform GNSS phase delay altimetry.