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Measurements of ground and near surface atmospheric temperatures at Jezero obtained during 700 sols by the Mars Environmental Dynamics Analyzer (MEDA) characterize the thermal behavior of the near surface Martian atmosphere during a full Martian Year. The seasonal evolution of MEDA measurements is compared with predictions from the Mars Climate Database and the solar irradiance at the surface. Thermal tides observed in the daily cycle of temperatures follow a seasonal cycle with additional variations greater than 2 K on time‐scales of tens of sols. We also observe sol‐to‐sol variations of about 1 K in mean daily air temperatures in autumn and winter with periodicities of 4–7 sols that might be related to baroclinic disturbances that are frequent in those seasons at high latitudes. We examine the evolution of the vertical thermal gradient and temperature fluctuations without finding a seasonal response to irradiance and dust load. We find that the convective boundary layer becomes isothermal and collapses 1 hr before sunset except during northern hemisphere winter, when the collapse occurs closer to sunset, implying a longer duration of the daytime convective instability. Around this period, the rover was located in the delta front in a location of complex topography where we observed stronger thermal gradients and intense daytime air temperature fluctuations. We also find in this place a nighttime event of gravity waves on near‐surface air temperatures, with amplitudes of 2 K and periods of 10 min. These waves possibly propagate downward through a near isothermal stable layer. Plain Language Summary: The Perseverance rover on Mars is carrying a meteorological station that among other measurements obtains air temperatures at three heights near the surface as well as ground temperatures. We analyze seasonal and local changes in temperatures measured over one Martian year (687 Earth days) in which Perseverance moved several kilometers across Jezero crater, comparing in situ observations with the output from a Global Climate Model of the atmosphere of Mars. Our results show that the diurnal cycle of temperatures is modulated by the solar irradiance on the surface, the amount of dust in the atmosphere, local dynamics and large‐scale weather systems. The temperature difference between the ground and the atmosphere greatly determines the meteorology in the lower atmosphere. Neither this temperature difference, nor temperature fluctuations, which during daytime are a proxy of atmospheric convection driven by the heating of the surface, show seasonal variations in line with the seasonal solar irradiance or dust load. Instead, the rover path toward a more complex topography led to the highest surface‐to‐air temperature difference during the northern hemisphere winter, despite the solar irradiance being minimum at that time. Close to this complex topography, the meteorological station recorded oscillations in near‐surface temperature related to gravity waves. Key Points: Seasonal variations in irradiance at Mars' surface drive observed daily mean near‐surface air temperatures with some differences from modelsThermal tides and long‐period traveling waves present a clear seasonal cycle with autumn and winter seasons more prone to variabilityAir temperatures underwent non‐seasonal changes near Jezero's delta, with strong daytime convection and nighttime gravity waves [ABSTRACT FROM AUTHOR]

We study the diurnal cycle of rapid thermal fluctuations observed by the Mars Environmental Dynamics Analyzer, onboard the Perseverance rover at Jezero Crater, as a function of local time and season. In this context, rapid refers to periods between 15 min and half a second. Some insight is also provided into wind fluctuations that are the base for most of the existing theories on turbulent flows. The results expand the observations from previous Mars missions, namely Viking, Mars Pathfinder, and Phoenix, and they add to our knowledge of near‐surface fluctuations on Mars. (a) Probability distribution functions of the fluctuations are determined and found to have exponential tails. This means that models that represent the interaction within the environment and with the surface as a stochastic forcing need to account for the sudden events responsible for the exponential tails. (b) Power density spectra are calculated and show several dynamical regimes with different slopes associated to forcing, an intermediate regime, and a higher frequency regime. All change with time of the day. The results imply that the fastest regime is not a universal scenario for the temperature fluctuations near the surface. (c) The scale dependence of the fluctuations confirms the existence of intermittent outbursts associated to the slower fluctuations, possibly associated to the larger scale structures, and explains why the spectral density slopes do not follow Kolmogorov's law. Understanding the role of larger scale structures would help refine scaling theories of the near‐surface Martian atmosphere and its interactions with the surface. Plain Language Summary: The Martian atmosphere is mostly driven by solar radiative forcing that also controls how it interacts with the surface. Atmospheric phenomena respond within seconds to years, but models can only resolve limited ranges of these time scales. This work explores how temperature fluctuates at time scales faster than what models typically resolve, and how this variability affects phenomena at the time scales that they resolve. The statistical properties of rapid environmental changes, or fluctuations, caused by solar forcing help us understand how the lowest atmosphere and surface evolve and interact. Theories that have been tested on Earth predicting how energy transfers or dissipates between the fast and slow dynamical regimes are explored here searching for rules that relate both regimes on another world. This work finds that fluctuations of air temperature and horizontal winds near the Martian surface do not follow probability distributions typical of normal random processes. The energy transfer rate is not consistent at scales faster than 10 s with a unique, or universal, rule relating fast to slow fluctuations. Finally, it suggests that this lack of universality is caused by intermittent disruptions through sudden large coherent structures, like convective vortices and waves, that influence how temperature dissipates. Key Points: Probability Distribution functions for temperature fluctuations at Jezero Crater on the time scale of seconds have exponential tailsPower density spectra of temperature fluctuations find at least two dynamical regimes that evolve differently with time of the daySudden outbursts, likely associated to coherent structures, disrupt intermittently the rate of temperature dissipation to the smaller scales [ABSTRACT FROM AUTHOR]

There is currently a gap in satellite observations of the moisture structure during heavy precipitation conditions, since infrared and microwave sounders cannot sense water‐vapour structure near the surface in the presence of intense precipitation. Conversely, Global Navigation Satellite System (GNSS) radio occultations (RO) can profile the moisture structure with high precision and vertical resolution, but cannot indicate the presence of precipitation directly. Polarimetric RO (PRO) measurements have been proposed as a method to characterize heavy rain in GNSS RO, by measuring the polarimetric differential phase delay induced by large size hydrometeors. Previous studies have shown that the PRO polarimetric phase shift is sensitive to the path‐integrated rain rate under intense precipitation scenarios, but there is no current method to invert PRO measurements into quantitative estimates of the path‐averaged rain rate. In this manuscript, a probabilistic inversion approach to the GNSS PRO observables is proposed, where the GPM precipitation products are used for the construction of an a priori look‐up table (LUT) database. The performance of the LUTs is assessed for use in the inversion of satellite‐based GNSS PRO observations, based on synthetically generated PRO data of actual events, which correspond to co‐locations between GNSS RO profiles and the TRMM observations. The synthetic data include end‐to‐end propagation effects of the polarimetric observables and a simple separation algorithm to isolate the hydrometeor component of the observation. The assessment results in agreement better than ±1 mm/hr between the reference LUT and the actual rain statistics of the synthetic data, proving the suitability of the GPM‐based probabilistic inversion tool. These findings indicate that the GNSS PRO products are capable of extending the current GNSS RO ones by associating indications of rain‐rate probabilities at different altitudes, at ∼250 m vertical resolution and under intense precipitation scenarios with the standard vertical thermodynamic profiles. A probabilistic inversion technique has been developed for GNSS polarimetric radio occultation (GNSS‐PRO) observables. The retrieval is based on information obtained from the Global Precipitation Measurement (GPM) mission, organized as a look‐up table (LUT) database. Confronting the LUTs and the phase shift suffered by the GNSS‐PRO signals results in a series of probabilities of rain rates at different altitudes. These vertical profiles of rain probability complement the standard GNSS‐RO thermodynamic profiles, providing a unique insight within intense precipitation scenarios. [ABSTRACT FROM AUTHOR]

This study describes the first experimental observations showing that hydrometeors induce polarimetric signatures in Global Navigation Satellite System (GNSS) signals. This evidence is relevant to the PAZ Low Earth Orbiter, which will test the concept and applications of polarimetric GNSS Radio Occultation (RO) (i.e. ROs obtained with a two-polarization antenna). A ground field campaign was carried out in preparation for PAZ to verify the theoretical sensitivity studies about this concept (Cardellach et al., 2015). The main aim of the campaign is to identify and understand the factors that might affect the polarimetric GNSS observables. Studied for the first time, GNSS signals measured with two polarimetric antennas (H, horizontal and V, vertical) are shown to discriminate heavy rain events, by comparing the measured phase difference between the H and V phase delays (ΔΦ) in different weather scenarios. The measured phase difference indicates higher dispersion under rain conditions. When individual events are examined, significant increases of ΔΦ occur when the radio signals cross rain cells. Moreover, the amplitude of such signal is much higher than the theoretical prediction for precipitation; thus other sources of polarimetric signatures have been explored and identified. Modelling of other hydrometeors like melting particles and ice crystals have been proposed to explain the obtained measurements, with good agreement in more than 90 % of the cases. [ABSTRACT FROM AUTHOR]