# Nighttime and Early Morning Atmospheric Waves and Transient Turbulence at Jezero Crater, Mars, Observed by the Perseverance Rover

A. Munguira, R. Hueso, A. Sánchez-Lavega, T. del Rio-Gaztelurrutia, Tanguy Bertrand, G. Martínez

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## To cite this version:

A. Munguira, R. Hueso, A. Sánchez-Lavega, T. del Rio-Gaztelurrutia, Tanguy Bertrand, et al., Nighttime and Early Morning Atmospheric Waves and Transient Turbulence at Jezero Crater, Mars, Observed by the Perseverance Rover. Journal of Geophysical Research. Planets, 2025, 130 (7), pp.1300-1308. 10.1029/2025JE009114. hal-05477992

HAL Id: hal-05477992

https://hal.science/hal-05477992v1

Submitted on 20 Feb 2026

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Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
# JGR Planets

## RESEARCH ARTICLE

10.1029/2025JE009114

### Key Points:

* We study nighttime and early morning transient atmospheric oscillations at Jezero crater from in situ pressure and temperature data

* Nighttime transient oscillations reveal candidates of Kelvin-Helmholtz instability near the surface and solitary waves of depression

* Gravity waves with 10-min periods are common at equinoxes and winter solstice around 20-23 local time, as observed at other landing sites

### Supporting Information:

Supporting Information may be found in the online version of this article.

### Correspondence to:

A. Munguira,
asier.munguira@ehu.eus

### Citation:

Munguira, A., Hueso, R., Sánchez-Lavega, A., del Rio-Gaztelurrutia, T., Bertrand, T., & Martínez, G. M. (2025). Nighttime and early morning atmospheric waves and transient turbulence at Jezero crater, Mars, observed by the Perseverance rover.

Journal of Geophysical Research: Planets, 130, e2025JE009114. https://doi.org/10.1029/2025JE009114

Received 27 MAR 2025

Accepted 13 JUL 2025

### Author Contributions:

**Conceptualization:** A. Munguira,
R. Hueso, A. Sánchez-Lavega, T. del Rio-Gaztelurrutia

**Formal analysis:** A. Munguira, T. del Rio-Gaztelurrutia

**Funding acquisition:** R. Hueso,
A. Sánchez-Lavega, G. M. Martínez

**Investigation:** A. Munguira

**Resources:** T. Bertrand, G. M. Martínez

**Supervision:** R. Hueso, A. Sánchez-Lavega

**Validation:** A. Munguira, T. del Rio-Gaztelurrutia

**Visualization:** A. Munguira

**Writing – original draft:** A. Munguira

© 2025. The Author(s).

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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# Nighttime and Early Morning Atmospheric Waves and Transient Turbulence at Jezero Crater, Mars, Observed by the Perseverance Rover

A. Munguira¹ ID, R. Hueso¹ ID, A. Sánchez-Lavega¹ ID, T. del Rio-Gaztelurrutia¹ ID, T. Bertrand²,³ ID, and G. M. Martínez⁴ ID

¹Física Aplicada, Escuela de Ingeniería de Bilbao, Universidad del País Vasco UPV/EHU, Bilbao, Spain, ²LIRA, Observatoire de Paris, Université PSL, Meudon, France, ³Laboratoire de Planétologie et Géosciences, Nantes Université, Nantes, France, ⁴Centro de Astrobiología (CSIC-INTA), Madrid, Spain

## Abstract
We study atmospheric oscillations in Jezero crater, Mars, that occur at night and dawn over stable conditions of the planetary boundary layer. These atmospheric oscillations are sporadic and can have large amplitudes, resulting in important variations in the dynamic conditions of the atmosphere. We analyze simultaneous measurements of atmospheric pressure and temperature data obtained in situ by the Mars Environmental Dynamics Analyzer (MEDA) instrument onboard the Mars2020/Perseverance rover. The observations span two Martian years of data at the crater floor and in the delta. We separate the wavelike and turbulent components of the oscillations, and use spectral analysis to examine the spectral slopes associated with different types of pressure oscillations. We identify four types of atmospheric transient oscillations: gravity waves (GW), solitary wavelike pulses (SoW), a nighttime pressure dip consistent with a solitary wave of depression, and possible Kelvin-Helmholtz (K-H) waves associated with high local turbulence. We examine diurnal and seasonal trends associated with the frequency of occurrence of these events. All the oscillations are less intense and less frequent around the aphelion season. The diurnal and seasonal trends in GW and SoW are consistent with previous studies at other locations on Mars, which may support a forcing by the large-scale atmospheric circulation. Potential K-H waves were observed during periods of relatively high dust opacity and in complex terrains, suggesting an origin near the surface when compared with similar observations on Earth. These waves had periods of 3.0–11.1 min and induced high-frequency turbulence.

## Plain Language Summary
We characterize near surface atmospheric oscillations in pressure and air temperature during the night and at dawn measured by the meteorological station on the Perseverance rover on Mars. These atmospheric oscillations are sporadic, but they can have large amplitudes that alter the dynamical conditions of the atmosphere. From their observed characteristics, we have identified four types of events: buoyancy waves with a typical period of 10 min, a single wavelike pulse producing a pressure peak during 10 min, a single wavelike oscillation producing a long-lasting pressure drop during 10 min, and events of oscillations with periods between 3 and 11 min superimposed with faster fluctuations. The latter could correspond to Kelvin-Helmholtz instabilities caused by wind shear, which have not been detected on Mars previously. All the oscillations are less intense and less frequent around the Northern Hemisphere summer. We suggest that a particularly intense event with a maximum amplitude of ~3 Pa may have been forced or enhanced by the local topography. The events identified as potential Kelvin-Helmholtz were observed during periods of relatively high dust opacity and in complex terrains and we propose they originated near the surface.

## 1. Introduction

At most locations on Mars, a stably stratified atmospheric layer, often referred to as the stable boundary layer (SBL), develops during the night within the lowest few hundred meters above the surface (Read et al., 2017; Spiga, 2019). In Jezero, the SBL develops 1 hr before sunset and persists at dawn until about an hour and a half after sunrise, when the planetary boundary layer transitions from stable conditions into an unstable layer with convective activity (Munguira et al., 2023, 2024). The nighttime and early morning Martian SBL shows oscillations in pressure and turbulence that are highly variable from sol to sol (Banfield et al., 2020), and models struggle to reproduce these SBL phenomena due to their intermittent and local nature (Read et al., 2017). On Earth, the SBL exhibits different degrees of dynamic stability, quantified by the Richardson number, which constrains the intensity of turbulence and/or wave phenomena that can take place within this layer (Stull, 2017).
Writing – review & editing:

A. Munguira, R. Hueso, A. Sánchez-Lavega, T. del Rio-Gaztelurrutia, T. Bertrand, G. M. Martínez

At the same time, large-amplitude transient waves and turbulence affect the energy redistribution and stability of the SBL (Stull, 1988), and may influence the atmospheric circulation, dust lifting processes, and the persistence of aerosols in the atmosphere. Since Jezero is the location where the Mars Sample Return mission will land to collect the samples acquired by the Perseverance rover for their delivery to Earth, it is important to improve weather predictions at the site (Newman et al., 2021; Pla-García et al., 2020). Our work constrains the effects and occurrence of nighttime transient oscillations at Jezero and provides insight into atmospheric parameters related to their origin mechanisms. Atmospheric oscillations in the SBL occur over a continuum of frequencies, but here, we refer to *waves* to denote oscillations with frequencies *f* < 0.01 Hz, which tend to be regular, and *fluctuations* to denote high-frequency oscillations with *f* > 0.01 Hz, which tend to be more chaotic and irregular suggesting turbulence instead of steady oscillations.

Previous studies of nighttime oscillations on Mars have focused on the analysis of pressure data. Haberle et al. (2014) and Harri et al. (2014) reported the first detection of GW at the Gale crater from data acquired by the Mars Science Laboratory (MSL). Guzewich et al. (2021) carried out a systematic analysis of pressure oscillations on MSL data showing the greatest occurrence of GW in the late evening at local times between 18 and 24 and during the dusty period (subsolar longitude, $L_s$ 150–360°). Ordoñez-Etxeberria et al. (2018, 2020) reported numerous nighttime pressure drops on MSL data, which were attributed to mechanically forced turbulence near complex terrain. The InSight lander, which took continuous pressure measurements at 10 Hz over a flat terrain, also identified nighttime oscillations associated with GW (Banfield et al., 2020; Hernández-Bernal et al., 2025) as well as solitary wavelike pulses coincident with a dust storm. Temel et al. (2022) used spectral analysis to characterize the changes in the energy distribution produced by these GW at the Insight's landing site, showing that pressure oscillations in the SBL can be especially intense on Mars due to its low atmospheric density. Murdoch et al. (2023) extended the spectral analysis of Insight data over diurnal and seasonal timescales and Chatain et al. (2021) found a period ($L_s$ 210–320°) of intense nighttime turbulence at the same location associated with high wind speeds and dynamic instability.

The Mars Environmental Dynamics Analyzer (MEDA) instrument on the Perseverance rover (Rodríguez-Manfredi et al., 2021) is able to capture the signal of nighttime atmospheric oscillations not only in pressure (Harri et al., 2024; Rodríguez-Manfredi et al., 2023; Sánchez-Lavega et al., 2023), like previous missions, but also in simultaneous near-surface temperature data. The temperature measurements from MEDA span three altitudes above the surface and are very sensitive to atmospheric variations (Munguira et al., 2023) providing information about the local turbulence (Pla-García et al., 2023) and the static stability (Munguira et al., 2024) in the first tens of meters above the surface.

The Perseverance rover landed on Jezero crater on February 2021 in a relatively flat terrain where it performed a crater floor campaign before driving toward the crater rim and ascending over an ancient delta exploring a variety of terrains (Sun et al., 2023; see Figure S1 in Supporting Information S1). Near the delta, MEDA found more intense daytime temperature fluctuations indicative of higher convection and intense GW at night (Munguira et al., 2024). These characteristics were attributed to the more complex topography of the delta. The significant changes in the local terrain witnessed by the Perseverance rover in terms of orography, albedo and thermal inertia of the surface (see e.g. Martínez et al., 2023) make the MEDA data set suitable to assess the influence of the local terrain on the behavior of the SBL. In comparison, the InSight lander's location at Elysium Planitia was fixed and characterized by its flat topography, while the MSL also drove through the complex topography of Gale crater. However, MSL's measurement cadence during nighttime hours is much more limited than MEDA's (Gómez-Elvira et al., 2014), which is very relevant for the detection of transient oscillations.

In this work, we investigate the nature and origin of a diversity of nighttime and dawn oscillations taking place in the SBL at Jezero during two Martian years, from $L_s$ 13° on MY 36 to $L_s$ 13° on MY 38, that is, the first 1,352 sols of the Mars 2020 mission. We have focused on the large-amplitude oscillations since they produce the most significant changes in the dynamic properties of the atmosphere. Section 2 presents the MEDA pressure and temperature data used in this work and the analyses in the time and frequency domains applied to these data. Section 3 focuses on the characterization of the transient oscillations, which are classified according to properties such as wave amplitudes and periods or the high-frequency turbulence during these events. Section 4 investigates the seasonal occurrence of the transient oscillations at Jezero. Section 5 discusses the possible origin of the transient oscillations in terms of the atmospheric stability and surrounding topography. Section 6 summarizes our main findings.
## 2. Data and Analysis Techniques

### 2.1. MEDA Pressure and Temperature

MEDA records pressure and temperature data as well as other meteorological measurements simultaneously at a sampling frequency of 1 or 2 Hz (Rodríguez-Manfredi et al., 2021). The nominal cadence of measurements at the beginning of the mission consisted of blocks of 65 min throughout the sol (1 hr on and 1 hr off), covering around 55% of the total time for each sol (Rodríguez-Manfredi et al., 2023). With this cadence, all sol times can be monitored every two consecutive sols. This nominal cadence has been modified along the mission according to operational constraints as shown in Figure S2 in Supporting Information S1.

Atmospheric oscillations of interest have been identified through a visual inspection of the diurnal pressure cycle. For example, Figure S3 in Supporting Information S1 shows the pressure diurnal cycle on sols 523 and 525 with measurements at the same local times. Distinct oscillations with a peak-to-peak amplitude of about 1.0 Pa are clearly observed in the one-hour block at around 21 hr local true solar time (LTST) on sol 523 but not two sols later at the same time. This event was presented in Munguira et al. (2024), where it was identified as a detection of GW. A visual inspection of the MEDA pressure records for the first 1,352 sols of the mission allows identifying a variety of large-amplitude oscillations with periods of less than 30 min. Examples of these events are presented in Section 3, showing a variety of properties that point toward different physical phenomena. In the interest of characterizing their seasonal occurrence, a more systematic study of pressure oscillations is presented in Section 4. In addition, high-frequency temperature measurements can sometimes provide additional information about these events and therefore, at the times when we detected oscillations in pressure, we examined the behavior of simultaneous air temperature measurements.

Temperatures are recorded with the Air Temperature Sensors (ATS) and the Thermal Infrared Sensor (TIRS); see Rodríguez-Manfredi et al. (2021, 2023) and Sebastián et al. (2025) for details. In this work, we use the ATS5, which is located at an altitude over the terrain of $z = 0.84$ m at the front-right of the rover, and ATS1, located at $z = 1.45$ m, placed on the remote sensing mast and oriented outwards of the rover deck (Munguira et al., 2023). We also use surface and air temperature measurements acquired from TIRS, which is an infrared radiometer sensitive to temperatures at an effective level of $z \sim 40$ m (Martínez et al., 2023; Smith et al., 2023). Temperature oscillations can be recorded simultaneously at these three atmospheric levels with different amplitudes and frequencies. A good correlation between ATS1 and ATS5 at a certain time indicates that air temperatures are sensing the environment with no –or little– influence from the rover (Pla-García et al., 2023).

The noise level of the Pressure Sensor is ~0.01–0.05 Pa (Jaakonaho et al., 2023; Sánchez-Lavega et al., 2023). ATS and TIRS have noise levels of 0.1 and 0.35 K, respectively (Munguira et al., 2023; Sebastián et al., 2020, 2021), and uncertainties in the absolute values of ATS and TIRS of 1 and 3 K, respectively (Rodríguez-Manfredi et al., 2021). We also note that the noise level in TIRS may have increased during the mission to about 0.5 K due to dust deposition (Sebastián et al., 2025).

### 2.2. Wave and Turbulent Components of the Signal

Atmospheric oscillations can be interpreted as a mixture of wave and turbulent components superimposed over a daily cycle associated with global and local circulation. To separate these contributions operating at different timescales, we followed Cheng et al. (2005) and assumed that a given time series, $S$, can be separated in a long-term average, a wavelike component, and a turbulent component denoted by $\bar{S}$, $\tilde{S}$ and $S'$, respectively:

$$S(t) = \bar{S}(t) + \tilde{S}(t) + S'(t) \qquad (1)$$

To find these terms, we used two low-pass filters of different window lengths. Each low-pass filter selects a range of frequencies and uses a Hanning window function to minimize the contribution from oscillations that do not complete an integer number of cycles within the bounding limits of the MEDA measurement blocks, often referred as leakage (Braun, 2001; Kanasewich, 1981). This procedure is similar to that used by Banfield et al. (2020) to analyze meteorological data from the Insight mission, and is applied to MEDA pressure and temperatures from ATS1, ATS5 and TIRS. Figure 1 shows an example of the performance of the two low-pass filters applied to the MEDA pressure block of 65 min starting at 20.6 LTST on sol 523. We used a window of 101 s, or ~2 min ($S_{F2}$), to filter out the turbulent component in the signal while retaining the low frequency
<figure><img src="image_4.png" /><figcaption>**Figure 1.** Illustration of two low pass filters applied to the raw signal. The raw Mars Environmental Dynamics Analyzer pressure data for the event on sol 523 is shown in green (see also Figure S3 in Supporting Information S1). The solid black line and dashed blue lines result from applying to the raw signal low-pass filters of 1.7 and 33.4 min Hanning window functions, respectively.</figcaption></figure>

oscillations, and a window of 2001s, or ~33 min ($S_{F33}$), to filter out all oscillations except the smoothed long-term (or diurnal) tendency of the signal. After applying the two filters, the turbulent component is simply: $S' = S - S_{F2}$, while the wave component is $\tilde{S} = S_{F2} - S_{F33}$. The turbulent component $S'$ contains oscillations in the frequency range of 0.01–0.5 Hz, while the wave component $\tilde{S}$ effectively captures oscillations in the frequency range of 0.0005–0.01 Hz after applying the two filters.

## 2.3. Spectral Analysis

For the spectral analysis, we focus on the pressure signal following previous works with InSight data from Banfield et al. (2020), Temel et al. (2022) and Murdoch et al. (2023). We analyze pressure data blocks of 60 min, which is a typical duration of MEDA's measurement blocks. Before calculating the spectra of the signal, we check that the signal is continuous, that is that the signal has no gaps, and that it has a consistent sampling frequency, $f_s$, during the whole recording time. For time series that meet the continuity conditions, we filter high frequency noise (N) in the raw signal by applying a low-pass Butterworth digital filter with critical frequency of 0.2 Hz, above which the gain of the filter drops. The filter is used to avoid aliasing near the high-frequency spectral limit of the MEDA pressure sensor. We then extract the long-term component of the signal $S_{F33}$, computing the detrended signal $S(t) - \bar{S}_{F33}(t) = \tilde{S}(t) + S'(t)$. Finally, a Fast Fourier Transform is applied to

this detrended signal to convert it from the time domain to the frequency domain and calculate the spectral energy density $E_{SS}(f)$ in the spectral range $0.2 > f > 0.001$ Hz, which is comparable with spectral analyses of InSight's pressure data (Temel et al., 2022). Hereinafter, we will use power spectral density (PSD) to refer to $E_{SS}(f)$. There is an implicit assumption that $E_{SS}(f)$ represents the distribution of the total turbulent kinetic energy (TKE), which is a valid hypothesis for isotropic turbulence (Kaimal & Finnigan, 1994).

We performed the same spectral analysis over temperature data, but it did not provide additional information about the oscillations reported in this work. This was expected because temperature oscillations are driven by multiple sources at local and global scales (Munguira et al., 2023), and therefore, as explained in Stull (1988), in most cases, the temperature spectra cannot be directly associated with eddy motions.

Note that the sampling frequency and measurement height of MEDA are too low and too close to the surface to detect the energy cascade of the inertial subrange (Coimbra et al., 2024; Tillman et al., 1994) and the dissipation regime of the spectra (Maurice et al., 2022). Therefore, the spectral range $0.2 > f > 0.001$ Hz represents the turbulent energy-containing range of the spectrum, which may be susceptible to the effects of atmospheric oscillations from the mean flow, such as those of GW (Kaimal & Finnigan, 1994; Temel et al., 2022). In contrast to the inertial subrange that follows universal scaling laws under ideal conditions (Kolmogorov, 1941), the energy-containing range could change significantly from site to site depending on the atmospheric conditions. The spectra presented in this work enable the characterization of each type of atmospheric oscillation at Jezero.

## 3. Classification of Pressure and Temperature Oscillations

Here, we classify and compare the large-amplitude transient oscillations identified in the MEDA records at nighttime and early morning hours. The spectral analysis of MEDA pressure data in the frequency range from 0.001 Hz (periods of 16.67 min) to 0.2 Hz (periods of 5 s) reveals two distinct spectral regions: The spectral range 0.001–0.005 Hz, which is dominated by large turbulent eddies and the effects of wavelike oscillations, and the range 0.01–0.2 Hz that is dominated by the high-frequency turbulence within the limits of the MEDA sampling frequency. We avoid the intermediate frequencies (0.005–0.01 Hz) to better distinguish between the two spectral regions.

We find four types of transient oscillations based on the decomposition of the signals in wavelike and turbulent components and the PSD of the pressure signals. The four types of transient events are classified as:
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Wave and turbulent components of pressure and temperature measurements and power spectral density (PSD) of the pressure data for the gravity wave on sol 362 ($L_s$ 180.3°, MY 36) starting around 21.6 local true solar time (LTST). (a) Wavelike component of the pressure time series; (b) turbulent component of the pressure time series; (c) wavelike components of the temperature time series at 0.84 m (blue dotted line), 1.45 m (black) and 40 m (orange); (d) high-frequency fluctuations in temperature data (we note that the instrument noise level in TIRS is about 0.5 K as reported in Section 2.1). (e) PSD of the pressure time series with the contributions from the wavelike and turbulent components corresponding to the gravity waves on sol 362 between 21.6 and 22.6 LTST (purple) and to a reference spectra (black) for the pressure signal at the same local time on sol 341 without relevant pressure oscillations. In panel (e), the solid lines at the high frequency portion of the spectra ($f > 0.01$ Hz) represent a smoothed version of the PSD, which helps to identify the slope. The straight lines at $f < 0.005$ Hz represent the spectral slopes (power law fit to the PSD) in this frequency range.</figcaption></figure>

1. GW: Periodic wavelike oscillations in pressure and weak high-frequency turbulence similar to signals identified by Guzewich et al. (2021) and Sánchez-Lavega et al. (2023).

2. Solitary Wavelike pulses (SoW): Oscillations with a single peak in pressure and weak high-frequency turbulence similar to events discussed by Banfield et al. (2020).

3. Pressure dip: Long lasting nighttime pressure drop and weak high-frequency turbulence. This is an unusual event, with only one detection from MEDA and never reported by other missions.

4. Potential Kelvin-Helmholtz (K-H) instability events: Periodic wavelike oscillations with intense high-frequency turbulence. These are unusual events, with a few detections from MEDA and never reported by other missions.

In this section, we show an example of each type of transient oscillation and characterize their properties. Additional examples can be found in Figures S4–S7 in Supporting Information S1.

### 3.1. Gravity Waves

Figures 2a–2d shows the wavelike and turbulent components ($\tilde{S}$ and $S'$ in Section 2.2) for nighttime transient oscillations on sol 362. These signals are morphologically very similar but more intense than events of GW reported on MEDA pressure data by Sánchez-Lavega et al. (2023). Figure 2a shows wavelike oscillations in pressure with maximum peak-to-peak amplitudes of ~1.0 Pa that decay in time over the MEDA session of 100 min. The mean period of these pressure oscillations is 10.6 min, and they are accompanied by oscillations in temperature with similar periodicities but without a clear correlation with the pressure signals (Figure 2c). The periods of the pressure/temperature oscillations are calculated as the average time between successive peaks/minimums in the wavelike component of the signal. Similar pressure waves with amplitudes of ~1.0 Pa and periods of ~10 min are frequently detected by MEDA (see Figure S4 in Supporting Information S1).

Figure 2b shows high-frequency pressure fluctuations that are comparable to the noise level of the sensor, which illustrates that the atmospheric turbulence near the surface is very weak and does not change significantly during the propagation and breaking of these GW. This is a common feature in all the detected GW (see e.g. Figure S4 in Supporting Information S1). The weak turbulence supports the idea that GW form under conditions of dynamic
<figure><img src="image_6.png" /><figcaption>**Figure 3.** Wave and turbulent components of the solitary wavelike pulse on sol 687 (Ls 14.5°, MY 37) starting around 6.5 local true solar time and pressure spectra around the same local time on sols 685, 687 and 690. (a–b) As in Figure 2. (c) Power spectral density of the pressure time series as in Figure 2e corresponding to the solitary wavelike pulse on sols 687 (purple) and 685 (blue) and to a reference spectra (black) for the pressure signal around the same local time on sol 690 without relevant pressure oscillations.</figcaption></figure>

stability, that is, the wind-shear is weak in comparison with the static stability (Stull, 2017). In addition, Figure 2d shows low ATS temperature fluctuations with values below 0.25 K that occasionally increase up to 0.75 K, which is probably related to local changes in winds (Munguira et al., 2023) but not directly related to the waves.

The PSD is a measure of “how much of the variance of the time series is associated with a particular frequency” (Stull, 1988), and the pressure spectra allow us to quantify the relative contributions of the low and high frequency oscillations to the TKE budget. Figure 2e shows the PSD of the pressure signal on sols 362 and 341 (reference time series without GW) between 21.6 and 22.6 LTST with the contributions from the wavelike and turbulent components (see Section 2.3). The propagation of the GW produced a steep slope of *n* = −5.9 in the low frequency range of 0.001–0.005 Hz (16.67–3.33 min). This range of the spectra is typically representative of the energy contained in the large turbulent eddies, and in the absence of GW, it showed a slope of *n* = −2.7 at a similar local time and season at Jezero. Temel et al. (2022) and Murdoch et al. (2023) also reported steep slopes of *n* ≲ −3 at low frequencies in the evening spectra possibly associated with GW at Elysium Planitia. Interestingly, we find steeper slopes compared with those on Elysium Planitia and the Earth (Weinstock, 1978). This could imply that the atmospheric waves at Jezero have relatively large amplitudes or that the high-frequency turbulence at this location is more inhibited due to stronger thermal inversions or weaker wind shears (see Section 5.1).

## 3.2. Solitary Wavelike Pulses

We refer to solitary wavelike pulses (SoW) to denote oscillations characterized by a single pressure peak. These pulses might correspond to solitary waves, which are nonlinear buoyancy waves that propagate along the nocturnal inversion through a waveguide (Christie, 1989). A thorough definition of solitary waves from Earth observations, often occurring at dawn, can be found in Christie et al. (1978). Figure 3a shows a SoW with a peak-to-peak amplitude of ~3.0 Pa, three times higher than the amplitudes of any GW observed by MEDA. Figure 3b shows very small pressure fluctuations with no changes associated with the propagation of the SoW, as in the case of GW. The low fluctuations are also evidenced in the pressure spectra (Figure 3c), with the low-frequency range showing slopes of *n* = −6.0 and *n* = −6.1 on sols 687 and 685, respectively, similar to the slope of the GW on sol 362. The similar low turbulent regime observed for the GW suggests that this SoW event and another event shown in Figure S5 in Supporting Information S1 also formed under dynamic stability. We compare the SoW observed by MEDA with those observed by Insight (Banfield et al., 2020) in Section 5.4.

Temperature oscillations at different heights are not correlated with each other during this event (Figure S5 in Supporting Information S1), which makes it difficult to assess the effect, or lack of effect, of the SoW on
<figure><img src="image_7.png" /><figcaption>**Figure 4.** Wave and turbulent components of the pressure dip on sol 1,140 ($L_s$ 248.7°, MY 37) starting around 22.2 local true solar time and the corresponding pressure spectra. (a–b) As in Figure 2. (c) Power spectral density of the pressure time series as in Figure 2e corresponding to the pressure dip (purple) and to a reference spectra (black) for the pressure signal at the same local time on sol 1,142 without relevant pressure oscillations.</figcaption></figure>

temperatures. This is common during most of the detections of SoW because they are typically found after sunrise, when temperature records are affected by the rapid heating of the rover (Munguira et al., 2023). Studies on Earth have shown that temperature oscillations produced by solitary waves decay with altitude and are not typically detected close to the surface (Knupp, 2006; Rottman and Einaudi, 1993).

### 3.3. Pressure Dip

A single wavelike cycle of oscillation with peak-to-peak amplitude of 1.3 Pa and a period of about 10–15 min was observed by MEDA on sol 1,140 (Figure 4a), causing a significant pressure dip that differs from the SoW event described above. The large duration of the dip is not consistent with nighttime mechanically forced vortices reported, for example, in Ordóñez-Etxeberria et al. (2018, 2020). At the borders of the pressure dip, we identify “shoulders” consisting of small pressure peaks above the mean pressure of the time series. This is consistent with solitary waves of depression observed on Earth (see Figure 18 in Rottman and Einaudi, 1993 and Figure 6 in Christie et al., 1978). Figure 4b shows weak turbulence that slightly increases coinciding with the pressure dip, which also contrasts with the very stable conditions found in connection with GW and SoW. The turbulence induced by the pressure dip translates in a less steep slope of –5.2 in the low-frequency range of the spectrum as compared with GW and SoW, although the pressure dip clearly affects this range of the spectrum when compared with the reference data set two sols later (Figure 4c). In Section 5.4, we discuss the possible origin mechanism of this event. A single wavelike oscillation cannot be identified in temperatures measured during this event (Figure S6 in Supporting Information S1), but temperature oscillations and turbulent fluctuations are roughly correlated at 0.84, 1.45 and 40 m with high-frequency temperature fluctuations slightly higher before and during the event.

We note that we have only found one such event with an amplitude above 1 Pa. This is consistent with the much lower frequency of occurrence observed by Christie et al. (1978) for solitary waves of depression as compared with solitary waves of elevation. Another candidate was found on sol 586 at around 20 LTST with a similar duration and a pressure drop of 3 Pa, but it was detected in a shorter measurement block of 15 min, which did not allow a clear characterization.

### 3.4. Potential Kelvin-Helmholtz Instability Events

Certain transient oscillations in pressure have significant amplitudes in both wavelike and turbulent components. One example of those events occurred on sol 1,109 around 3.5 LTST. The wavelike oscillations in pressure had dominant periodicities of 3.0 min and peak-to-peak amplitudes of 1.5 Pa (Figure 5a). To analyze this event in terms of its wavelike and turbulent components and correctly identify its periodicities, we used a small window
<figure><img src="image_8.png" /><figcaption>**Figure 5.** Wave and turbulent components of the pressure and temperature oscillations on sol 1,109 ($L_s$ 228.6°, MY 37) starting around 3.5 local true solar time and the corresponding pressure spectra. (a–d) As in Figure 2. (e) power spectral density (PSD) of the pressure time series as in Figure 2e corresponding to the pressure oscillations on sol 1,109 (purple) and to a reference spectra (black) for the pressure signal at the same local time on sol 1,111 without relevant pressure oscillations. The magenta line in the high-frequency end of the spectrum represents the power law fit to the PSD in the frequency range $0.2<f<0.01$ Hz.</figcaption></figure>

length filter of 0.5 min instead of ~2 min (see Section 2.2). Despite using a smaller window length, high-frequency pressure fluctuations during this event (Figure 5b) are clearly higher than in previous cases, suggesting higher turbulence in the atmosphere during this nighttime event.

Interestingly, the amplitudes of temperature oscillations obtained by TIRS at ~40 m have values of up to 3.0 K (Figure 5c), which are strongly anticorrelated with the pressure waves. On Earth, strong temperature oscillations at tens of meters that decay at lower altitudes are consistent with the effects of Kelvin-Helmholtz (K-H) instabilities that originate tens of meters above the surface (Blumen et al., 2001). In addition, TIRS detects the signal 7 s before ATS on average, which further supports that the atmospheric oscillations originated above the rover's height, closer to 40 m than to 1.45 m. Figure 5d shows isolated bursts of thermal turbulence with values up to 3.0 K that also resemble observations of K-H instabilities on Earth reported by Cheng et al. (2005). A discussion on the origin of K-H wave candidates and associated thresholds is included in Section 5.3.

The PSD of pressure also presents singular characteristics (Figure 5e). The spectra show a flat distribution at low frequencies that transitions to a spectral slope of $n = -2.4$ at higher frequencies. This behavior contrasts with the typical spectral slope of $n \sim -1$ found during nighttime (e.g., see Figure 2e, Figures 3c and 4c). In addition, nearby sols (e.g., sol 1,111 in Figure 5e) show slopes of $n = -1.5$, suggesting relatively high turbulence around sol 1,109, even if intense waves only formed on sol 1,109. Similarly, the lower panel of Figure 5 in Murdoch et al. (2023) reports nighttime slopes down to $n = -1.5$ during the turbulent “Season 5” found at InSight (Chatain et al., 2021). The high turbulence present in the atmosphere during the event on sol 1,109 probably requires dynamic instability (see Figure 10 in Murdoch et al., 2023), which would support the formation of K-H waves. Unfortunately, the absence of wind data after sol 313 does not allow confirming dynamic instability conditions during this event (Section 5.1), nor that the event indeed corresponds to a K-H instability. Since K-H instability candidates have not been reported in previous studies, we suggest that looking for nighttime slopes of $n < -2.0$ at high-frequencies on Mars surface pressure data might reveal more of these events.

Other candidates for K-H waves are scarce and the largest amplitude events were found on sols 315 and 1,124 (Figure S7 in Supporting Information S1), with nighttime high-frequency slopes of $n = -2.1$ and $n = -2.0$ respectively. While all GW reported in this work have periods of ~10 min, the periods of potential K-H waves span from 3.0 min on sol 1,109 to 11.1 min on sol 315.
<figure><img src="image_9.png" /><figcaption>**Figure 6.** Occurrence of nighttime pressure oscillations at different local times during two Martian years. Standard deviation of pressure oscillations in 30-min windows (crosses) as a function of Sol and $L_s$ averaged over the local time intervals (a) 3–6 local true solar time (LTST), (b) 6–8 LTST and (c) 20–23 LTST. We note that the limits of the y-axis are different in panel (b). Thick colored lines show two-sol running averages. The dashed horizontal line is a reference value of $\sigma_p = 0.05$ Pa that represents the approximate noise level of the pressure sensor. Brown vertical lines on the upper part of the panels represent equinoxes and solstices. The seasons are denoted in panel (a) with respect to the Northern Hemisphere. The large-amplitude oscillations presented in Section 3 and in the Supporting Information S1 are indicated in the figure. Other labels provide additional information about other periods of large $\sigma_p$ (see main text). The temporal distribution of the Mars Environmental Dynamics Analyzer (MEDA) measurement blocks used for this figure are shown in Figure S8 in Supporting Information S1. MEDA blocks between $L_s$ 285–360° on MY 37 were typically shorter than 15 min, resulting in gaps in that period of MY 37.</figcaption></figure>

4. Seasonal Trends in the Occurrence of Pressure Oscillations

In order to find seasonal trends in the occurrence of pressure oscillations, we have calculated the standard deviations of the pressure oscillations, $\sigma_p$, after subtracting a second-order polynomial fit to the signal in 30-min windows for the entire MEDA pressure data set over two Martian years. This results in a systematic analysis of a selection of the MEDA data shown in Figure S8 in Supporting Information S1. This systematic analysis is not limited to the large amplitude oscillations already discussed in Section 3. Interestingly, transient oscillations that occurred around the same local times tend to share other characteristics too, such as their wavelike or turbulent behaviors, at any season of the Martian year. Thus, we have averaged $\sigma_p$ in three intervals of the Martian sol: 20–23 LTST (evening), 3–6 LTST (night), 6–8 LTST (post-sunrise or dawn). Figure 6 presents the results from this analysis, including some artifacts that are discussed in the text. The night hours are dominated by high-frequency turbulence, the post-sunrise hours are dominated by SoW, and the evening hours mostly present wavelike oscillations with weak nocturnal turbulence, especially GW. However, we note that low-amplitude oscillations are difficult to classify, and that some nocturnal turbulence is also present during the evening hours and wavelike oscillations with weak nocturnal turbulence during the night hours.

Figure 6 shows a significant sol-to-sol variability in the formation of waves and nocturnal turbulence, which illustrates the transient nature of these pressure oscillations. However, some seasonal patterns can be identified in
the figure at all times of the sol between nighttime and post-sunrise hours. Atmospheric oscillations are weakest during the aphelion seasons ($L_s$ 45–135°) covered in this study, without any large-amplitude events at the crater floor (MY 36) and at the crater rim (MY 37). In addition, the propagation of dust storms at Jezero, which peaked at $L_s$ 153, 225 and 315° on MY 36 and $L_s$ 210° on MY 37 (Lemmon et al., 2022; Sánchez-Lavega et al., 2023, 2025), seems to increase the transient oscillations at all times of the sol.

Figure 6a suggests that the nocturnal turbulence was more intense during the dusty period of MY36 as well as at the beginning of spring and autumn of MY 37. In addition, the three large-amplitude K-H candidates labeled in Figure 6a occurred at moderately dusty conditions ($\tau \sim 1$), which further supports an increase in nocturnal turbulence associated with the atmospheric dust content. For example, the passage of a regional dust storm over Jezero on sol 315 influenced the thermal gradient and local circulation (Lemmon et al., 2022) and possibly resulted in the observed increase in turbulence. However, the cadence of MEDA records during the dusty period of MY 37 (Figure S2 in Supporting Information S1) does not allow to confirm a seasonal trend on nocturnal turbulence associated with the dust load. In addition, the nocturnal turbulence in Figure 6a shows inter-annual variations during non-dusty periods of the Martian year that may reflect the influence of the local terrain on the atmospheric dynamics, for example around $L_s$ 360° on MY 36 and MY 37 as the rover changed its elevation significantly as it climbed over the delta (see Section 5.2 and Section 5.3).

Figure 6b shows that large-amplitude oscillations between 6 and 8 LTST concentrate at equinoxes, as it was found at the InSight location (Hernández-Bernal et al., 2025). Near autumnal equinoxes, the daily pressure cycle changes very fast at 6–8 LTST (Figure S9 in Supporting Information S1), and the standard 30-min polynomial fit departs from the pressure signal contributing to the peaks in Figure 6b. Fast oscillations of the pressure cycle at dawn have been observed by several previous missions and have been interpreted as caused by the divergence and convergence of winds in the Martian tropical troposphere induced by the combined effect of the diurnal and semidiurnal tides (Yang et al., 2023). Thus, it is the long-term trend of the diurnal pressure cycle in Jezero, rather than wavelike atmospheric oscillations such as SoW, that produces the large $\sigma_p$ at autumnal equinoxes. In contrast, SoW peak at spring equinoxes and show large inter-annual variability from $L_s$ 360° on MY 36 to the same $L_s$ on MY 37. The SoW with the largest amplitudes are examined in Section 5.4.

Figure 6c shows frequent wavelike oscillations and a few cases of nocturnal turbulence between 20 and 23 LTST. These events follow a clear seasonal trend with minimums around the aphelion and maximums at equinoxes and winter solstices. Inter-annual variations are small except at the spring equinoxes, when the amplitudes of the wavelike oscillations decayed by half at $L_s$ 360° on MY 37 with respect to the previous year, like in the 6–8 LTST timeframe (Figure 6b). We also note that large $\sigma_p$ around sol 580 coincide with shorter MEDA blocks that make it difficult to analyze the oscillations, and large $\sigma_p$ between sols 600 and 700 include SoW and GW with lower amplitudes than those presented in Section 3.1 and Figure S4 in Supporting Information S1 for sols 362, 523, and 1,166.

# 5. Discussion

## 5.1. Atmospheric Stability

The occurrence of nighttime transient oscillations is heavily determined by the dynamic stability, that is, the relative contribution of the buoyancy force and the wind shear to the turbulence generation (Stull, 1988, 2017). The gradient Richardson number is typically used to assess the dynamic stability (Sánchez-Lavega, 2011):

$$Ri = \frac{\frac{g}{T_s}(\Gamma_d - \Gamma)}{\left(\frac{\Delta u}{\Delta z}\right)^2} \quad (2)$$

where $g = 3.71 \text{ m s}^{-2}$ is the acceleration due to gravity on the surface of Mars, $T_s$ is the surface temperature, $\Gamma = -\Delta T / \Delta z$ is the lapse rate between two atmospheric levels, $u$ is the total horizontal wind speed, $\Delta u / \Delta z$ represents the wind shear between two layers, and $\Gamma_d = g / C_p = 5.1 \cdot 10^{-3} \text{ K m}^{-1}$ is the adiabatic lapse rate at typical nighttime air temperatures in Jezero crater (Munguira et al., 2024). In this calculation, the specific heat at constant pressure of carbon dioxide $C_p$ has been calculated at $T = 190 \text{ K}$, considering the dependence of the specific heat on temperatures like in Woolley (1954).
<figure><img src="image_10.png" /></figure>

**Figure 7.** Locations along the rover traverse where intense pressure oscillations were detected. The rover drive since landing is indicated by the white line. Colored circles indicate the locations at which the most intense transient oscillations of each type discussed in Section 3 were detected: blue for gravity waves on sol 362 and 523, green for the SoW on sol 687, yellow for the pressure dip on sol 1,140, purple for the K-H wave candidate on sol 1,109 and violet for the K-H wave candidate on sol 1,124. Colored arrows indicate the mean wind direction around the time of the transient oscillations, estimated from the relative correlation of the measurements from the five Air Temperature Sensors following Munguira et al. (2024). The white circles indicate the start of the climb on sols 708 ($L_s$ 25°, MY 37) and 1,284 ($L_s$ 337°, MY 37), and the gray circle indicates the rover's location on sol 1,352. The background map was generated with the software Multi-Mission Geographical Information System (https://nasa-ammos.github.io/MMGIS/).

$Ri < 0$ corresponds to statically unstable layers with $\Gamma_d < \Gamma$. During the nighttime, the numerator is usually positive; therefore, the buoyancy force contributes to reduce the TKE near the surface in both Earth and Mars (Read et al., 2017; Stull, 2017). At $Ri > 1$, it is often assumed that there is no turbulence, and wavelike oscillations take place instead. In addition, when $1 < Ri > 0.25$, shear-generated turbulence is still relatively weak and waves constitute the main atmospheric oscillations. For statically stable air, a thin layer of the atmosphere is dynamically unstable if $0 < Ri < 0.25$, which leads to shear generated turbulence, as shown for Mars with Insight data in Chatain et al. (2021) and Murdoch et al. (2023), and as it also seems to be the case in the periods of intense nocturnal turbulence found by MEDA (Figure 6a). Unfortunately, MEDA wind measurements are not currently available after sol 313 (Viudez-Moreiras et al., 2022), preventing a direct calculation of $Ri$ from MEDA measurements. Ongoing recalibration activities may allow the retrieval of wind measurements by exploiting the redundancy in the components of the MEDA wind sensor (Rodríguez-Manfredi et al., 2021).

## 5.2. Surrounding Topography

Several mechanisms can produce nighttime transient oscillations and turbulence (Holton & Hakim, 2013). The surrounding topography is an important feature of the environment that might affect the local meteorology, as shown by Munguira et al. (2024) for Jezero. Figure 7 shows the rover's drive since the beginning of the mission up to sol 1,352 and the locations near the delta where the most intense nighttime oscillations were observed. For additional context, Figure S1 in Supporting Information S1 shows the elevation of the terrain in the same region. The influence of the surrounding complex topography on the oscillations is not obvious, and a careful assessment is required in each case.

## 5.3. Constraints on the Characteristics of Kelvin-Helmholtz Instability Candidates

In Section 3.4, we argue that nighttime oscillations on sols 315, 1,109 and 1,124 (Figure 5 and Figure S7 in Supporting Information S1) might be indicative of K-H waves originating near the surface. Kelvin-Helmholtz
instabilities develop when there is a large enough wind shear at the interface between two laminar flows under positive static stability, verifying condition $0 < Ri < 0.25$ (Stull, 2017). The restrictive conditions and the limited range of Ri that can give rise to K-H instabilities may explain that these are relatively uncommon in the atmosphere. A K-H instability produces roll vortices (billows or K-H waves) that induce mixing of momentum, heat and mass between the two layers. These vortices do not propagate vertically (Drazin, 2015), which implies that if the K-H waves are observed in situ, they must form at low altitudes “close” to the meteorological station.

Blumen et al. (2001) studied a K-H billow event on Earth's SBL and found maximum wave amplitudes at 56 m above the surface, with decreasing temperature fluctuations at lower altitudes, in agreement with our results for Mars (Figure 5c). In the same work, the Richardson number during the event was $Ri = 0.18$ and the dominating wave period was 60 s. For the same terrestrial event, Newsom and Banta (2003) studied the vertical profiles of wind shear and $Ri$ before, during and after the event, and showed that the K-H instability was produced by a slowing of the winds below a Low Level Jet (LLJ), which increased the shear. This might also be the case for Jezero, for which models in Newman et al. (2021) predict the lowest near-surface wind speeds around $L_s = 270°$, and Pla-García et al. (2023) found an LLJ producing nighttime shear-driven turbulence that propagated down to the surface on some sols. In contrast, Chatain et al. (2021) reported that the most intense nocturnal turbulence at Elysium Planitia was related to a period of higher wind speeds at the surface produced by an LLJ, which also coincided with a dustier local environment (Stott et al., 2025). Whether nocturnal turbulence at InSight's location produced K-H instability candidates is still to be determined.

The most intense candidates for K-H waves were found at Jezero's delta front on MY 37 on sol 1,109 ($L_s = 228.6°$). The absence of large-amplitude oscillations in the same season on MY36, and the topographic contrast between the crater floor and the crater rim suggest that the local topography might play a non-negligible role in triggering the K-H instability. This is because the friction with complex terrains may cause near-surface winds to slow down and favor stronger wind shears. In the delta region, MEDA detects potential K-H instabilities with the near-surface flow blowing across two different terrains (see the wind directions corresponding to sol 1,109 and 1,124 in Figure 7). In addition, the atmospheric dust opacity (Bell et al., 2022; Lemmon et al., 2022) was relatively high ($\tau \sim 1$) during the three intense events reported in Figure 5 and Figure S7 in Supporting Information S1 and may also play a role in enhancing the nocturnal turbulence as discussed in Section 4. The dust might reduce the static stability of the atmosphere (Read et al., 2017) and affect the local circulation, leading to low Richardson numbers.

We can estimate the minimum wind shear that should be implied in the observed K-H candidate event on sol 1,124 from Equation 2, with $\Gamma$ calculated from the temperature difference between the surface and the air at $\sim 40$ m from TIRS ($\Delta T = -4.3$ K; $-\Gamma = 0.1075$ K m$^{-1}$). We use the event on sol 1,124, since surface temperature measurements on sols 315 and 1,109 lead to negative values of $-\Gamma$, which is interpreted as a very local result due to the anomalies in the surface temperature over terrains of heterogeneous thermal inertia (see discussions regarding the local absence of nighttime thermal inversion over certain locations in Rodríguez-Manfredi et al., 2023; Savijärvi et al., 2023). We find that the lower limit for the wind shear is $\Delta u \approx 4$ m s$^{-1}$ for $Ri = 0.25$, and since the wind must be zero very close to the surface due to friction, the wind speed at 40 m should be at least $u_{40m} \approx 4$ m s$^{-1}$ to trigger the K-H instability. A lower Richardson number of $Ri = 0.10$ would translate in wind speed thresholds of $u_{40m} \approx 6$ m s$^{-1}$. These wind speeds are comparable to predictions from numerical models applied to Jezero (Newman et al., 2021). Nevertheless, K-H candidates are scarce, and this suggests that higher wind shears could be needed to trigger the K-H instability. For example, Jackson et al. (2025) derived daytime wind profiles at Jezero at heights over the terrain of up to 24 m using the attitude data of the Ingenuity Helicopter on Mars 2020 and found high wind speeds of 25 m s$^{-1}$. Unusually high wind speeds may also occur during nighttime and trigger the K-H instabilities.

In the case of K-H waves, disturbances of the form $e^{ikx}$ become unstable and grow if the wavenumber $k$ obeys (Sánchez-Lavega, 2011):

$$k > g \frac{\rho_1^2 - \rho_2^2}{\rho_1 \rho_2 (u_1 - u_2)^2} \quad (3)$$
where $\rho_1$ and $u_1$ are the density and wind speeds of the underlaying fluid layer, and $\rho_2$ and $u_2$ are the density and wind speeds of the overlaying fluid layer. The wavelength $\lambda$ is related to the wavenumber $k$ as $k = 2\pi/\lambda$, and the wavelength is also $\lambda = \tau\nu$, where $\tau$ is the period of the waves and $\nu$ the phase velocity. Rearranging Equation 3, we can constrain the $\lambda$ and $\nu$ associated with the candidates for K-H waves on sol 1,124 using our previous estimates of $\Delta u = u_1 - u_2$.

$$ \lambda = \tau\nu < \frac{2\pi \frac{\rho_2}{\rho_1} (\Delta u)^2}{g(1 - \left(\frac{\rho_2}{\rho_1}\right)^2)} \quad (4) $$

From the ideal gas equation, the density of an air layer is $\rho = P/R_g^*T$, where $P$ is the air pressure, $T$ is the air temperature, and $R_g^* = 190 \text{ J Kg}^{-1}\text{K}^{-1}$ is the ideal gas constant for Mars. For sol 1,124, we calculate $\rho_1$ from surface values of pressure and temperatures, and $\rho_2$ from TIRS air temperature at 40 m and the pressure at 40 m, $P_2$, calculated assuming hydrostatic equilibrium. We get $\rho_2/\rho_1 = 0.974$. Therefore, with the previously estimated lower limit of $\Delta u \approx 4 \text{ m s}^{-1}$ at $Ri = 0.25$, we constrain the wavelength of the K-H waves to $\lambda < 510 \text{ m}$ and the phase velocity to $\nu < 1 \text{ m s}^{-1}$ for the wave period of $\tau = 9.7 \text{ min}$ observed on sol 1,124. A lower Richardson number of $Ri = 0.10$ would result in $\lambda < 1150 \text{ m}$ and $\nu < 2 \text{ m s}^{-1}$. If we assume the same atmospheric conditions of pressure and temperature for the event of sol 1,109 (but with wave periods of $\tau = 3.0 \text{ min}$), we obtain phase velocities of $\nu < 6 \text{ m s}^{-1}$. These estimates of wavelength and phase velocities for K-H wave candidates are comparable to their Earth counterparts with dominant wavelengths of 300 m and phase velocities of 5 m s$^{-1}$ (Blumen et al., 2001).

Finally, the high degree of local turbulence and mixing produced by K-H waves tend to restore the equilibrium between layers unless the source of the instability is maintained (Stull, 1988). Therefore, it is interesting to note the long duration of the K-H instability candidates found on Mars, with up to 6 hr on sol 1,124, compared to similar events on Earth (30 min for Blumen et al., 2001) that would require continuous triggering of the K-H instability. This is even more surprising for the lower Reynolds numbers on Mars than on Earth for the same wind speeds (Read et al., 2017), which may support that turbulent flows and K-H instability close to the surface are less frequent on Mars, and that their development might require very specific forcing over a favorable terrain.

## 5.4. Possible Influence of the Topography on Solitary Wavelike Pulses and on the Pressure Dip

It is relatively frequent in the MEDA data to find similar atmospheric oscillations at the same local time during consecutive sols over tens of sols (see Figure 6). The best example is the sequence of solitary wavelike pulses that were observed at around 6.5–8.0 LTST between sols 660 and 695 intermittently (some sols showed a GW or a flat pressure signal instead). MEDA's even-odd hour cadence (Section 2.1) did not enable an ideal sol-to-sol track of the SoW. However, for the subset of sols 675–690 in Figure 8, it is clear that pressure peaks of up to 3.0 Pa around 7.0 LTST are followed by damped oscillations. This sequence of SoW is comparable to previous observations at the InSight location in terms of their amplitudes and duration (Figure 4b in Banfield et al., 2020). However, there are large differences between the environmental conditions related to the SoW observed by MEDA and the those detected by Banfield et al. (2020). Bores and solitary waves arise in regions where wind convergence occurs under stably stratified conditions forcing air upwards (Christie et al., 1978; Karyampudi et al., 1995; Knupp, 2006). In the flat terrain at the location of InSight, Banfield et al. (2020) suggested that the SoW was associated with a dust storm and its influence on the local dynamics, with the pressure peak of the SoW showing a gradual evolution and delay sol-to-sol during ~20 sols. MEDA observed a SoW triggered during the decay of the regional dust storm (Lemmon et al., 2022) on sol 319, but the SoW did not have a sol-to-sol repeatability. In contrast, the atmospheric opacity at Jezero between sols 675 and 690 was relatively low and did not show rapid changes, with all values of opacity between 0.49 and 0.60 (Bell et al., 2022, Lemmon et al., 2022, Figure 4 in Munguira et al., 2024). Moreover, the wave did not show any consistent delay or sol-to-sol evolution.

We assess whether the SoW between sols 675–690 ($L_s \sim 12^\circ$ on MY37) might have been produced or enhanced by convergence of air at surrounding topographic obstacles. The rover drove at a rate of ~50 m/sol to the north during these sols with no significant changes in its location relative to topography. By sol 696, the rover drove toward a new location to the north and stopped recording the SoW. The location where these SoW were detected was labeled Three Forks by the M2020 mission team and it was a location the rover traversed several times. Perseverance had
<figure><img src="image_11.png" /><figcaption>**Figure 8.** Wave component of the pressure oscillations ($\tilde{P}$) between 6.6 and 8.0 local true solar time on sols 675 through 690. Purple colors are used for odd number sols and blueish colors are used for even number sols. In y-axis the time series, $\tilde{P}$, are shifted by the sol number for clarity, but the amplitudes of the waves are unchanged. The time series centered on the horizontal line at 68 Pa is equivalent to Figure 3a. Horizontal lines are separated by 1 Pa and the maximum amplitude of these oscillations was found on sol 677 with a value of 3.5 Pa peak-to-peak.</figcaption></figure>

parked in *Three Forks* on sols 414, 432 and 433 ($L_s \sim 220^{\circ}$), with no signatures of SoW, which supports the seasonal trend in SoW discussed in Section 4. Derived wind directions on sols 675–690 from ATS data indicate that the air was blowing from the South on average at the time of the oscillations shown in Figure 8. In the surrounding area (Figure 7), the isolated flat-topped hill named *Kodiak*, with an elevation of about 80 m, is situated 800 m to the South of *Three Forks* and might interfere with the wind forcing a hydraulic jump. Figure 9 illustrates the topography profile across the line separating *Three Forks* and *Kodiak* in the derived wind direction. Assuming that the maximum vertical amplitude of the SoW is $a = 80$ m (*Kodiak*'s height), and that the undisturbed fluid layer is at $h \ge 2a$, we derive the speed of propagation of the SoW, $\nu$, as presented in Christie et al. (1978):

$$ \nu = [gh(1 + \alpha)]^{1/2} \qquad (5) $$

where $\alpha = a/h$ is the relative amplitude of the oscillation. Since the SBL is expected to be shallow after sunrise, we assume a thin fluid layer ($h = 2a$). We get minimum speeds of propagation of $\nu \sim 30$ m s$^{-1}$ for SoW in a thin fluid layer with $h = 160$ m. The estimated speed of propagation is comparable to the values observed by Christie et al. (1978) on Earth: $\nu \sim 4 - 18$ m s$^{-1}$ for SoW of elevation and $\nu \sim 14 - 50$ m s$^{-1}$ for SoW of depression. In addition, we estimate the effective wavelength as the full width at half maximum of the SoW profile using the Boussinesq approximation:

$$ \lambda = \frac{4 \ln(1 + \sqrt{2})}{(3\alpha)^{1/2}} h \qquad (6) $$

It is reasonable to invoke the Boussinesq approximation given the small density changes of the air in the first 160 m of the Mars atmosphere. This leads to a wavelength of $\lambda \approx 460$ m, which is notably similar to *Kodiak*'s horizontal width of at least 350 m (Figure 9). However, modeling efforts would be needed to ascertain whether the observed intense SoW might originate or reinforce at *Kodiak*.

Other sources of wind convergence that could produce the SoW are the sunrise and sunset transitions between the stable and convective periods (Munguira et al., 2023). After sunrise, downslope winds change direction turning into upslope winds at Jezero crater (Newman et al., 2022; Pla-García et al., 2023; Rodríguez-Manfredi et al., 2023) producing a convergence of the flow (see for instance Figure 3d in Rodríguez-Manfredi et al., 2023).
<figure><img src="image_12.png" /><figcaption>**Figure 9.** Elevation profiles of the surrounding topography on sols 675–690 (SoW) and sol 1,140 (pressure dip). The red lines in panels (a) and (b) indicate the horizontal distance in which we derived the topography profiles. The red lines are drawn to coincide with the wind direction shown in Figure 7. (c) Elevation profiles (w.r.t. Areoid of Mars) as a function of the horizontal distance. The white circles in panels (a, b, c) indicate the position of the rover along the horizontal line given by red lines in panels (a) and (b). At the time of the oscillations, winds can be thought as blowing from right to left in panel (c), as indicated by the arrows with the colors as in Figure 7. *Three Forks* region and *Kodiak* hill are indicated in panels (a).</figcaption></figure>

This is consistent with the reanalysis in Hernández-Bernal et al. (2025) of the SoW studied by Banfield et al. (2020), which shows another SoW after sunset on the same sols. Lastly, it is possible that the intense SoW on sols 675–690 is a combination of the two mechanisms, that is, driven by the transition after sunrise (that may present seasonal effects) and enhanced due to topographical features. This would explain that the wave amplitude of this event is twice that of the second most intense SoW found on MEDA data (Figure 6b).

The pressure dip observed on sol 1,140 has characteristics similar to the solitary waves of depression found on Earth (Section 3.3). A mechanically forced vortex is another plausible phenomenon that could cause the observed pressure dip. However, our analysis of ATS data suggests that the wind direction remained very stable during the event on sol 1,140, and the same was found for the other candidate on sol 586. Rottman and Einaudi (1993) modeled solitary waves of depression and showed that they require the layer above their waveguide to be strongly stratified. This is consistent with the MEDA detection of these waves at 22 LTST, and not after sunrise as in the case of SoW, since the static stability decreases rapidly after sunrise (Munguira et al., 2023). Given that we find similar turbulent regimes for the pressure dip and the SoW detected by MEDA in terms of spectral slopes, we assessed whether the pressure dip might have formed due to a topographic “obstacle” Figures 9b and 9c show the elevation profile in the direction of the wind during the event on sol 1,140, with a depression of the terrain that corresponds to a valley network (Figure 7). We speculate that a valley circulation of cold air might produce a hydraulic jump on the transverse flow consistent with the observed oscillation. Terrestrial studies have observed solitary waves of depression always developing in specific wind directions, which would be consistent with a topographic origin (Christie et al., 1978).

## 6. Conclusions

We have identified several transient oscillations in the SBL of Jezero at nighttime and early morning hours using MEDA pressure and temperature data (Section 3). Shear-driven nocturnal turbulence in Jezero occurred at all times of the night but peaked between 3 and 6 LTST. Kelvin-Helmholtz wave candidates have been identified on Mars for the first time, associated with the most intense nocturnal turbulence observed at Jezero. The Kelvin-
Helmholtz wave candidates with the largest amplitudes developed in Jezero's delta on sols 1,109 and 1,124 and during the regional dust storm on sol 315. We suggest that the complex local topography of the delta and a dusty atmosphere may play a role in the development of K-H instabilities by leading to dynamic instability with Richardson number values between 0 and 0.25 (Section 5.3). For the observed K-H wave candidates, we estimate periodicities, wavelengths, and phase speeds of the order of their counterparts on Earth (Blumen et al., 2001), despite the vast differences between the atmospheres of Earth and Mars in terms of atmospheric density and Reynolds number.

Gravity waves are most intense during the evening hours (20–23 LTST) at the equinoxes and winter solstices and solitary wavelike pulses are mainly observed after sunrise (6–8 LT) at the spring equinoxes. These diurnal and seasonal occurrences of waves are in agreement with findings at other locations on Mars (Guzewich et al., 2021; Hernández-Bernal et al., 2025), which may suggest that GW and SoW are forced by the large-scale atmospheric circulation. However, we suggest that the SoW observed between sols 675–690 with peak-to-peak wave amplitude of ~3.0 Pa might be enhanced by the influence of local topography (Section 5.4). A nighttime pressure dip of –1.3 Pa and duration of 10–15 min recorded at 22.4 LTST on sol 1,140 is consistent with solitary waves of depression observed on Earth.

We propose that spectral slopes satisfying $n \le -2.0$ in the range 0.01–0.2 Hz of the pressure records during the night might reveal K-H wave candidates at other locations on Mars (Section 3.4). We also note that the slope of $n = -2.4$ observed on sol 1,109 is close to $-7/3 = -2.33$, which is the slope predicted for the inertial subrange in the pressure spectra according to Kolmogorov's universal law (Kolmogorov, 1941). Although the inertial subrange is not resolved with the sampling frequency of MEDA (Coimbra et al., 2024), assuming that the inertial subrange on Mars would have a similar slope as on Earth, we find some situations in which the *energy cascade* that is typical of the inertial subrange starts at the dominant frequencies of the potential K-H waves (Figure 5e). Therefore, the atmospheric oscillations interpreted as K-H waves might help constrain suitable environmental conditions to investigate the universal behavior of turbulence in the Mars atmosphere.

The mutual feedback between waves/turbulence and atmospheric stability, and the transient nature of the atmospheric oscillations poses difficulties for the parameterization of stable conditions in atmospheric models (Read et al., 2017). Our work supports the observations on Earth that suggest that some degree of turbulent mixing may still persist even when $R_i > 1$ (Read et al., 2017). For example, we have shown in Section 3 and Section 4 that local turbulence is not completely absent when waves propagate in the atmosphere. We have also shown that some nighttime transient oscillations might be produced or strengthened by the local circulation, which is modulated, at least in part, by the local topography. On Mars, mesoscale models have spatial resolutions of a few kilometers (Newman et al., 2021), whereas LES have maximum resolutions of 10 m and generally assume a flat topography (Spiga et al., 2016). GW and SoW with periods of ~10 min can possibly be simulated with current models. In addition, recent LES have already included idealized mountains or craters that are promising for the simulation of K-H waves. Therefore, our observations call for more LES and mesoscale modeling of atmospheric waves in Jezero crater to fully understand the near surface dynamics at play. In addition, since atmospheric models would struggle to reproduce local circulations in complex topography sites, in situ observations with a good data cadence during nighttime remain essential to investigate the nighttime transient waves and turbulence.

## Data Availability Statement

The MEDA data used in this study are available via the NASA Planetary Data System (PDS) (Rodríguez-Manfredi & de la Torre Juárez, 2021). Atmospheric opacities at Jezero are calculated from publicly available data from the ZCAM instrument via the PDS (Bell & Maki, 2021). The Multi-Mission Geographical Information System (MMGIS) software used to generate the maps in the Jezero region is available at https://nasa-ammos.github.io/MMGIS/. Online interactive access to maps produced by this software is available at https://science.nasa.gov/mission/mars-2020-perseverance/location-map/.

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## Acknowledgments

The authors are very grateful to the entire Mars 2020 science operations team as well as to the MEDA PI J.A. Rodríguez-Manfredi and former Deputy PI Manuel de la Torre Juárez for the funding acquisition and team leadership. The authors would also like to thank Audrey Chatain and an anonymous reviewer for their comments, which helped us to improve the quality of the manuscript. We also acknowledge enriching feedback from Alex Stott and Eduardo Sebastián regarding atmospheric turbulence and the TIRS instrument, respectively. AM is supported by the Grant PRE2020-092562 funded by MCIN/AEI/ 10.13039/501100011033 and by “ESF Investing in your future.” AM, RH, ASL and TdR are supported by Grant PID2023-149055NB-C31 funded by MICIU/AEI/ 10.13039/501100011033 and FEDER, UE, and by Grupos de Investigación del Gobierno Vasco IT1742-22. This work has been funded by the Spanish Ministry of Economy and Competitiveness, through the projects ESP2014-54256-C4-1-R and AYA2015-65041-P; Ministry of Science, Innovation and Universities, projects ESP2016-79612-C3-1-R, ESP2016-80320-C2-1-R, RTI2018-098728-B-C31, RTI2018-099825-B-C31, MDM-2017-0737 and PID2021-126719OB-C41; Instituto Nacional de Técnica Aeroespacial; Ministry of Science and Innovation's Centre for the Development of Industrial Technology.
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