The Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) onboard Mars Express, which operates between 0.1 and 5.5 MHz, suffered from a complete blackout for 10 days in September 2017 when observing on the nightside (a rare occurrence). Moreover, the Shallow Radar (SHARAD) onboard the Mars Reconnaissance Orbiter, which operates at 20 MHz, also suffered a blackout for three days when operating on both dayside and nightside. We propose that these blackouts are caused by solar energetic particles of few tens of keV and above associated with an extreme space weather event between 10 and 22 September 2017, as recorded by the Mars Atmosphere and Volatile EvolutioN (MAVEN) mission. Numerical simulations of energetic electron precipitation predict that a lower O 2 + nighttime ionospheric layer of magnitude~10 10 m −3 peaking at~90-km altitude is produced. Consequently, such a layer would absorb radar signals at high frequencies and explain the blackouts. The peak absorption level is found to be at 70-km altitude. Plain Language Summary Several instrument operations, as well as communication systems with rovers at the surface, depend on radio signals that propagate throughout the atmosphere of Mars. This is the case also for two radars that are currently working in Mars' orbit, sounding the ionosphere, surface, and subsurface of the planet. In mid-September 2017, a powerful solar storm hit Mars, producing a large amount of energetic particle precipitation over a 10-day period. We have found that high-energy electrons ionized the atmosphere of Mars, creating a dense layer of ions and electrons at~90 km on the Martian nightside. This layer attenuated radar signals continuously for 10 days, stopping the radars to receive any signal from the planetary surface. In this work, we assess the properties of this layer in order to understand the implications of this kind of phenomenon for radar performance and communications.

An optical communications system employing intradyne reception and offline digital signal processing is tested over a 10.45 km link through the atmosphere. 40 GBaud transmission using binary phase-shift keying in the C-band is demonstrated and compared with laboratory measurements. Simultaneous photodetector measurements show that the turbulence in the atmospheric channel is representative for relevant and worst-case conditions in the geostationary satellite uplink scenario.

Phase unwrapping, also known as ambiguity resolu-1 tion, is an underdetermined problem in which assumptions must 2 be made to obtain a result in SAR interferometry (InSAR) time 3 series analysis. This problem is particularly acute for distributed 4 scatterer InSAR, in which noise levels can be so large that 5 they are comparable in magnitude to the signal of investigation. 6 In addition, deformation rates can be highly nonlinear and orders 7 of magnitude larger than neighboring point scatterers, which 8 may be part of a more stable object. The combination of these 9 factors has often proven too challenging for the conventional 10 InSAR processing methods to successfully monitor these regions. 11 We present a methodology which allows for additional environ-12 mental information to be integrated into the phase unwrapping 13 procedure, thereby alleviating the problems described above. 14 We show how problematic epochs that cause errors in the tempo-15 ral phase unwrapping process can be anticipated by the machine 16 learning algorithms which can create categorical predictions 17 about the relative ambiguity level based on the readily available 18 meteorological data. These predictions significantly assist in the 19 interpretation of large changes in the wrapped interferometric 20 phase and enable the monitoring of environments not previously 21 possible using standard minimum gradient phase unwrapping 22 techniques. 23

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