Main

Middle atmosphere ice clouds are observed year-round1,2 and in 30–50% of the solar and stellar occultation measurements of the Martian middle atmosphere3,4,5,6,7,8 (here defined as ~30–60 km above the surface or at pressures between ~100 and 1 Pa). Above 65 km, cloud layers are probably CO2 ice7,8,9,10. However, between 30 and 60 km, water ice clouds are also observed5,8,11,12,13. General circulation models struggle to replicate the observed vertical distribution of water ice clouds and typically confine cloud layers to pressures higher than approximately 100 Pa (heights below ~25 km)14,15,16. Inaccurate representations of clouds directly and indirectly impact the simulated climate. Optically thin clouds, particularly at high altitudes where the density scaled opacity is greatest17, can be a significant source of temperature variability that impacts the diurnal and semidiurnal thermal waves18,19,20,21 and the large-scale meridional overturning circulation14,17. To accurately simulate the processes that control the nucleation, growth and evolution of middle atmosphere clouds is, therefore, fundamental to capturing the true complexity of the Martian climate cycle16.

The prevailing view of ice cloud formation on Mars is that surface mineral dust mixes aloft and serves as heterogeneous ice nuclei when the air is supersaturated with respect to water ice22. Although supersaturation is observed23 and modelled17 at high altitudes, the models predict limited nuclei above the planetary boundary layer. Few cloud particles nucleate in these models, and those that do nucleate grow quickly to large sizes and gravitationally sediment to lower altitudes. Some recent models include parameterizations to enhance the vertical mixing of mineral dust; these include topographic upslope flows24,25 and enhanced convective updrafts in ‘rocket dust storms’26. These parameterizations enhance ice nuclei concentrations in bursts that should decay over several sols (Martian days) and therefore cannot easily explain the persistence of high cloud features.

On Earth, optically thin noctilucent clouds nucleate on meteoric smoke particles27,28. If a sufficient mass of interplanetary dust particles (IDPs) ablates in the Martian atmosphere, cloud formation by the same mechanism is likely. The MAVEN IUVS (Imaging Ultraviolet Spectrograph) instrument identified a persistent meteoroid ablation layer near ~80–90 km (ref. 29). Chemical ablation models predict that ~5–10% of the total intercepted meteoric mass will ablate and recondense30. However, as recondensed particles are small, their numbers are large even when the ablation rate is low. Meteoric smoke particles, therefore, represent an abundant and likely source of ice nuclei for cloud nucleation at high altitudes and in lower regions where the atmospheric load of surface mineral dust is depleted.

In this study, we investigated the impact on water ice cloud formation of including a new ablated IDP fluence of 0.4 ton per Mars sol distributed evenly across our model top30. Observations with the MAVEN IUVS instrument29 found an IDP fluence of 2–3–ton sol−1. As discussed in the Supplementary Information, our model top is near 60 km, which is about 25 km below the observed ablation level. To account for coagulation and chemical processes that occur above our model top, we distributed the total ablated mass into the predicted 50 km size distribution for meteoric smoke or ‘dirty ice’ particles as illustrated by Plane et al.30. We compare the results with simulations that include no meteoric smoke.

We simulated clouds using a size-resolving aerosol model coupled with a three-dimensional general circulation model for Mars (MarsCAM-CARMA). We demonstrated that IDPs are necessary to reproduce the vertical and horizontal distribution of the observed water ice clouds in the middle atmosphere. To capture the impact of IDPs under different dynamical regimes, we show results at both equinox (heliocentric longitude (Ls = 180°)) and solstice (Ls = 270°) as these represent extremes of the climate. We note that clouds form in cold troughs of the diurnal and semidiurnal tide, and, as a result, clouds in the middle atmosphere may act as signposts for local dynamics19,20. We show that water ice clouds are radiatively active and influence local and large-scale dynamical systems. We close with an analysis of the radiative-dynamical impact of IDP-induced clouds on local thermal tides as well as on the large-scale Hadley circulation.

Simulated cloud fields and Mars Climate Sounder data

IDP ice nuclei are critical for the formation of water ice clouds that have been observed in the middle atmosphere and at mid latitudes. In Fig. 1, we compare the simulated night-time water ice opacity at an 11.9 μm wavelength at the Northern Fall Equinox (Ls = 180) in simulations with and without IDPs to observational data from the Mars Climate Sounder (MCS) averaged over five Mars years (MY 29–33). Other Mars years without major dust storms show a similar cloud opacity. Data in the contour plots are zonally averaged and temporally averaged during the night-time over a period of 10 sol to demonstrate the averaged impact of the IDPs. MCS observations are averaged zonally and over 5° in Ls, which is equivalent to about 10–15 sol. A more complete description of data binning for the MCS observations and GCM data is provided in the Supplementary Information. Changes to the vertical structure of the clouds are particularly significant in night-time profiles. This is because tropospheric clouds that cap dust layers will necessarily form at lower altitudes at night when the mixed layer is smaller. As a result, there is less overlap during the night between the meteoric clouds and clouds that cap dust layers.

Fig. 1: The addition of IDPs is important for the formation of middle atmosphere cloud layers at mid and high latitudes.
figure 1

a–c, Simulated 3 a.m. zonal average water ice extinction (km−1) at an 11.25 μm wavelength versus pressure for simulations without (a) and with (b) IDPs compared with the MCS observations averaged over MY 29–33 (c). Data and simulations are from ~10 sol near Ls = 180°. Contour levels (black lines) cover the range of 1 × 10−6 to 1 × 10−2 with 0.1 order of magnitude intervals. Altitudes range from ~0 to 60 km.

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At Ls = 180°, observations of the night-time middle atmosphere midlatitude clouds (~40–60° N and S) are reproduced only in simulations with a source of IDPs. Without IDPs (Fig. 1a), the cloud extinction falls to values below the instrument signal-to-noise level (~10−6 km−1) at pressures below 100 Pa everywhere but in the aphelion cloud belt between 30° S and 30° N. With IDPs (Fig. 1b), simulations reproduce the observed M-shaped, double peak structure in the cloud opacity (Fig. 1c). Extinctions are greatest at the equator near 100 Pa and in the midlatitudes near 20 Pa. Notably, both simulations with and without IDPs match the cloud base pressure of the well-known aphelion cloud belt near 300–100 Pa (ref. 31). The simulated cloud base pressure represents a meaningful improvement over other Mars GCM cloud models14,15, which is in part due to the explicit treatment of the size distribution of mineral dust ice nuclei in MarsCAM-CARMA. We discuss this model improvement in more detail in Methods.

Thermal controls on cloud formation

We found that the seasonal and zonal structure of the planetary thermal tides controls the locations and times at which the middle atmosphere cloud formation is most likely. In contrast, cloud formation in the lower atmosphere is often forced by topography, which plays a secondary role for the middle atmosphere clouds. We found that the dynamic and thermal conditions that promote the middle atmosphere cloud formation at Ls = 180° are present in simulations with and without IDPs. Figure 2 shows the zonal average daytime (3 p.m.) minus night-time (3 a.m.) temperature difference versus pressure (coloured contours). A large positive temperature difference indicates that the night-time temperatures are significantly colder than the daytime values and cloud formation should be enhanced at night. The same overall thermal pattern is produced in both simulations without (Fig. 2a) and with (Fig. 2b) IDPs. However, as noted in Fig. 1, without a source of ice nuclei, high extinctions due to clouds do not occur at mid latitudes (Fig. 2a, contour lines) at pressures below 100 Pa even under thermally favourable conditions. By contrast, high cloud extinctions in simulations with IDPs (Fig. 2b, contour lines) occur in the same atmospheric regions or just below the largest positive temperature difference (yellow colours) to form an M shaped pattern in latitude (Fig. 1). Middle atmosphere water ice clouds modify the amplitude and phase of the thermal tide at low pressures. Above 100 Pa, clouds radiatively warm the night-time atmosphere and thereby weaken the daytime/night-time temperature difference. Simulations with IDPs (Fig. 2b) show a weaker temperature variance at high altitudes than observed by the MCS, which has a maximum amplitude of ~6.5 K at 40–10 Pa (Fig. 2c). At these pressures, gravity waves may contribute to larger amplitude thermal tides. Gravity wave parameterizations are not included in MarsCAM-CARMA but represent a fruitful area for future research.

Fig. 2: Clouds form where the thermal tide is strongest.
figure 2

a–c, The coloured contours show a simple estimate for the amplitude of the diurnal tide ((temperature at 3 p.m. – temperature at 3 a.m.)/2) for simulations without (a) and with (b) IDPs compared with the observed temperature variance from the MCS (c). A positive value means that night-time temperatures are lower than daytime temperatures. Cloud extinction contours (black lines) are superimposed and range from 1 × 10−6 to 1 × 10−2 with 0.25 intervals. Clouds form where the temperature difference is greatest and at locations where the phase amplifies night-time cold troughs (red regions at pressures below 100 Pa). At this season (Ls = 180°), middle atmosphere clouds form preferentially at ~30–60° N and S (Fig. 1).

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IDPs modify the vertical extent of the polar hood

The addition of IDPs similarly modifies the distribution of the middle atmosphere clouds at the northern hemisphere winter solstice (Ls = 270°). The most notable example at this season, shown in Fig. 3, is that micrometeoroid cloud seeding enhances the vertical extent of the polar hood from the surface to near our model top at ~2–3 Pa. Observations of the extinction of polar hood clouds at a wavelength of 11.9 μm in the northern hemisphere wintertime polar vortex show high values greater than 5 × 10−3 throughout the middle atmosphere from the surface to approximately 1 Pa (ref. 32). Polar hood clouds nucleate on dust particles transported to polar latitudes in the descending branch of the Hadley cell. In simulations without a source of meteoric smoke particles, the middle atmosphere is aerosol depleted; the few dust particles transported to the polar regions are nucleated, grow rapidly and sediment. Simulated polar hood clouds are confined to altitudes well below those in the observations and approach the observed extinctions only below 100 Pa. By contrast, in simulations with IDPs, the wintertime Hadley circulation directs meteoric smoke particles poleward at high altitude where they accumulate. Nascent cloud particles compete for limited water vapour and cannot grow to large sizes. Smaller particles stay elevated for longer periods of time and increase the cloud extinction at all pressures. IDPs may therefore be particularly important in dynamically isolated or aerosol-poor regions of the Martian atmosphere.

Fig. 3: Wintertime polar hood clouds are too shallow in simulations without IDPs.
figure 3

IDPs transported from above into the polar vortex seed cloud formation at high altitudes and limit atmospheric drying by snowfall. a,b, Simulated 3.a.m. zonal average water ice extinction (log10 of extinction km−1) at 11.25 μm versus pressure for simulations without (a) and with (b) IDPs. c, MCS data are averaged over multiple years (MY 29–33) and over approximately 10 sol near Ls = 270° (northern winter solstice).

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Below 100 Pa, simulated polar hood cloud opacities are higher than those observed by MCS (Fig. 3). If simulated cloud particle sizes are too small and cloud particles are too numerous, the opacity will be overestimated. Discrepancies between simulated and observed cloud extinction probably results from choices for microphysical parameterizations such as the contact angle and sticking coefficient that impact cloud nucleation and growth efficiencies. MCS observations do not extend to the surface in the polar clouds because the extinction along the limb exceeds the observational limit (white regions). Also, low altitude clouds at this time of year are underestimated throughout the tropics. In Supplementary Fig. 9, we show that the simulated water vapour is also low at this season by as much as 5 precipitable micrometres (pr µm) in the tropics. As a result, cloud extinctions will be reduced. Similarly, the observed cloud structure between 30 and 60° N at ~5 Pa forms in a night-time cold trough that is not reproduced in simulations. The diurnal and semidiurnal tides are sensitive to the atmospheric dust load, especially during the dusty season between Ls ~180–330°. Discrepancies in the middle altitude cloud field are probably a response to the atmospheric dust opacity that modifies the atmospheric temperature (Supplementary Fig. 7) and tidal structure. We discuss the seasonal distribution of mesospheric ice clouds in the Supplementary Fig. 1.

Radiative impact of mesospheric water ice clouds

Although it is well-known that tropospheric clouds broadly influence the Martian climate via radiative-dynamic feedbacks17,18,20,21,33,34,35, the radiative impact of IDP-seeded clouds in the middle atmosphere has not been studied. Historically, high-altitude clouds have been overlooked because of their tenuous nature and short-term diurnal variability. However, middle atmosphere water ice clouds may be critical to resolve dynamical discrepancies between observations and previous simulations. For example, numerous observational campaigns have noted a sub-sol component of the sun-synchronous thermal tide20,36,37,38,39,40,41,42. We found that the amplitude of the semidiurnal tide is driven by local radiative feedbacks between IDP-seeded water ice clouds and the surrounding atmosphere.

The diurnal component of the sun-synchronous thermal tide is driven by rapid changes to atmospheric temperature with solar forcing. In an idealized case, as on a planet with no topography, the thermal maximum tracks the subsolar point and moves smoothly across the longitudes as the planet rotates. Simulations without IDPs nearly follow this idealized model. Figure 4a,b shows the difference in temperature from the seasonal mean (Ls = 175–185°) with time and longitude at 46° N at ~5 Pa. We chose 46° N to match the maximum temperature difference between day and night (Fig. 2). Positive values show daytime warming, whereas negative values indicate night-time cooling. The maximum thermal anomaly moves westward with time as the planet rotates. Disruptions to the thermal signal are due to non-migrating tides generated by local topography, variability in the regolith thermal inertia or changes to the local atmospheric dust load42,43,44,45. The semidiurnal mode can be identified at some longitudes in the case with no IDPs (Fig. 4a), but it is comparatively weak and not easily discriminated from the background mean temperature (Supplementary Fig. 2).

Fig. 4: The semidiurnal component of the thermal tide is enhanced by cloud radiative feedbacks.
figure 4

a–d, Temperature anomaly from the 10 sol mean log10 of water ice extinction at 11.25 μm (c,d) for simulations without (a,c) and with (b,d) IDPs at ~5 Pa versus longitude and time. The data show 12 sol near Ls = 180° at 46° N.

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In both simulations with and without IDPs, clouds form in the night-time cold phase of the thermal waves (Fig. 4c,d). However, in simulations with an abundant source of high-altitude ice nuclei, cloud extinction is approximately one order of magnitude larger than in simulations without IDPs. IDP-seeded water ice clouds have a significant radiative impact as discussed in Supplementary Fig. 3. Elevated extinctions induce short-wave radiative heating that strengthens the semidiurnal mode of the diurnal tide and can be observed by comparing the temperatures in Fig. 4 with and without IDPs.

Figure 4a,b shows the temperature deviation from the ~10 sol mean at 46° N. The diurnal signal can be clearly distinguished at most longitudes in both simulations with (Fig. 4a,c) and without (Fig. 4b,d) an IDP source. When IDPs are added, new clouds form with higher opacities (Fig. 4d) and the semidiurnal mode is amplified (Fig. 4b). This change is particularly notable at longitude 245° E where the semidiurnal mode in simulations with IDPs has an equal amplitude to that of the principle diurnal component. In Supplementary Fig. 3, we show the temperature variance and cloud extinction at ~5 Pa at this location (46° N, 245° E). Simulations without IDPs have a weak secondary temperature perturbation at sols ~5, 6, 7 and 8. By contrast, the amplitude of the semidiurnal and the diurnal modes in simulations with IDPs are of equal magnitude and the semidiurnal mode shows a clear enhancement over the non-IDP simulations. Observations of the middle atmosphere semidiurnal tide near solstice show average wave amplitudes with the same strength as that simulated with IDPs (~5–10 K)20,36,40.

The radiative impact of the middle atmosphere water ice clouds is not limited to local scales. Middle atmosphere mean atmospheric temperatures show significant changes when clouds seeded on IDPs are considered. Supplementary Fig. 4 shows that at the northern fall equinox (Ls = 180°), tropical and polar mean temperatures at pressures less than 12 Pa are ~10 K greater in simulations with IDPs than in simulations without IDPs, a significant fraction (17–36%) of the maximum amplitude of the observed temperature perturbations at that season. For example, at 46° N and 12 Pa, the mean temperatures are 172 K and 161 K for simulations with and without IDPs, respectively. At the same location, the diurnal tide has an average amplitude of 10 K (Supplementary Fig. 2).

At the largest scales, local warming or cooling modifies the principal meridional overturning circulation and potentially drives large-scale changes to surface winds and atmospheric dust loading17. At Ls = 270°, adding IDPs changes the vertical extent of the northern hemisphere polar hood (Fig. 3) and modifies the zonal distribution of the middle atmosphere clouds at the tropics and southern mid latitudes (Supplementary Fig. 1) and weakens the principal meridional overturning circulation (Supplementary Fig. 5). Radiative heating by IDP-seeded polar clouds (Supplementary Fig. 6) reduces the large-scale downwelling branch of the Hadley cell over the winter pole (Supplementary Fig. 5) and, as a result, limits adiabatic compression and warming (Supplementary Fig. 7). As illustrated in Supplementary Figs. 5–7, the thermally direct circulation is reduced. Compared with simulations that lack IDP, the middle atmosphere is cooled in excess of 25 K at pressures less than 50 Pa and latitudes 30–60° N (Supplementary Fig. 7). Simulations with IDPs better match observations of the North polar temperatures above 10 Pa by MCS32 and are cooler than simulations without IDPs by >20° K. In addition, Supplementary Fig. 12 shows that IDPs lead to much-improved simulations of particle sizes in mid-altitude clouds. Both simulations with and without IDPs underestimate the southern hemisphere temperature (Supplementary Fig. 7). Simulated dust opacities are larger than observed, which contributes to the reduced surface temperatures. Higher opacities shade the surface and reduce temperatures. Radiative cooling by atmospheric dust also impacts the Hadley circulation by weakening the southern hemisphere upwelling. Additional seasons are included in Supplementary Fig. 8.

Our simulations constitute evidence that IDPs influence planetary climate and control the formation pathways and microphysical properties of water ice clouds that form in the Martian middle atmosphere. We found that meteoric smoke particles act as the dominant sites for cloud nucleation above 30 km (~50 Pa) rather than dust lofted from the surface deposits. Simulations generate discrete middle atmosphere ice cloud layers, which are separate from clouds that cap the surface dust layers, and better capture the observed distributions of water ice clouds by MCS (Fig. 1). We also found that the winter poles have enhanced concentrations of micrometeoroids due to the descending air over the winter poles. These polar micrometeoroids cause the polar hood clouds to reach high altitudes, as is observed but not produced in simulations without the micrometeoroids (Fig. 3). We further note that radiatively active water ice clouds in the Martian middle atmosphere strengthen the semidiurnal tide, in agreement with observations (Fig. 4), and influence the mean temperatures as well as the large-scale atmospheric circulation (Supplementary Figs. 5–7).

Methods

Global simulations

For this work, we coupled a size-resolved aerosol microphysics model46,47, CARMA, with a three-dimensional general circulation model, MarsCAM15,48, for Mars. This model includes improvements on Urata and Toon15,48, which include interactive dust lifting as well as coupling with CARMA49. The dust mass is discretized into 50 mass bins with central spherical equivalent radii that range from 0.01 to 82 µm. Water ice particles formed by heterogeneous nucleation28 are modelled as a dust core covered by a water ice shell and are also assumed to be spherical. There are 50 cloud mass bins covering the radius range of 0.0014 to 119.2 µm. Parameterizations for the surface dust lofting are interactive and physically based, following Kahre et al.50 and Newman et al.51. Aerosols are treated as radiatively active. The optical properties of the dust were calculated using real and imaginary indices of refraction versus wavelength based on observations of Mars52. The optical properties of ice are based on laboratory data53. There are limited data about refractive indices for meteoric material; however, the optical depth of the IDPs is not great enough for it to radiatively impact the atmosphere. We therefore do not distinguish the optical properties or physical properties of meteoric dust from those of the Martian surface dust. As meteoric smoke particles are small, we do not observe extensive radiative heating by meteoric smoke at the top of the atmosphere. We note that the use of independently advected dust-size bins represents a meaningful improvement over simulations that define particle populations using prescribed aerosol-size modes with an effective radius and fixed variance. This type of modal size distribution parameterization constrains the transport of small particles to follow the sedimentation of particles with the population’s mean particle radius, whereas independently advected small particles in a sectional model can remain lofted and are efficiently mixed to high altitudes over time. This model improvement allows for a more accurate assessment of the spatial and temporal evolution of dust and cloud particle size distributions.

IDP smoke particles are treated as spherical particles. The global fluence is constant in time and spatially uniform across the model top. A constant ablated mass of 0.4 ton sol−1 is distributed across 20 meteoric dust bins (r = 0.001–0.08 µm) based on the size distribution of ‘dirty ice’ particles at 50 km illustrated by Plane et al.30. Meteor showers or near-Mars encounters with comets (for example, Siding Spring) temporarily enhance the mass fluence54,55 but are not considered here. Simulations of IDP ablation found that H2O molecules are incorporated into the meteoric smoke lattice to form dirty ice particles30. It is therefore possible that nucleation of meteoric material may be more efficient than that on mineral dust even at small radii. However, the contact angle for meteoric material and water vapour in the Mars atmosphere has not been well-constrained in studies to date. We therefore follow conventions in the modelling community and set a constant contact angle, m = 0.95 (refs. 10,56) for meteoric dust.

We found that the dust and hydrological cycles are extremely tightly coupled. Most parameter choices in the model are tabulated in Urata and Toon15,48. Choices for the simulation of polar water ice and snow albedo (0.5 and 0.57 for the northern and southern hemisphere polar caps, respectively), dust wind stress threshold for lifting from the surface deposits (22.5 mN m–2), nucleation contact angle (0.6–0.94 for mineral dust ice nuclei57 and 0.95 for meteoric smoke) and water vapour sticking coefficient for cloud growth (0.93) all interact non-linearly to change the atmospheric dust and water vapour loads, the size and persistence of the cloud particles and the broad radiative feedbacks of the atmospheric aerosols. The choice of contact angle effectively controls the efficiency of nucleation and the number and size of cloud particles. If the value is too high, particles are more numerous and smaller. Simulations with MarsCAM-CARMA match the magnitude of the peak vapour content in the northern hemisphere (~60 pr µm) and southern hemisphere (~35 pr µm) within 5% and 50%, respectively (Supplementary Fig. 9). However, the simulated tropics are slightly drier (~5 pr µm) than observed (~10 pr µm). The observed profiles of the water vapour mixing ratios fall within the error bars of the simulations (Supplementary Fig. 10).

Neither parameterizations for CO2 ice clouds nor the atmospheric condensation of CO2 (except at the surface) are presently included in the model. The CO2 frost point is generally not reached in our simulations (except at the wintertime pole). We therefore ignored CO2 clouds for our study of H2O clouds. Atmospheric dynamics in the polar regions may be impacted by the formation of CO2 ice clouds58. This neglect of the CO2 clouds may introduce biases in the polar temperatures. Studies indicate that meteoric smoke may also be important for high-altitude CO2 cloud nucleation10. It is unlikely that CO2 cloud particles will sediment to lower altitudes because the fall times are relatively long and the particles would evaporate as temperatures rise above the frost point. However, there could be regions of mixed CO2/H2O clouds, especially at levels above the top of our model, where unevaporated CO2 ice particles could act as ice nuclei for H2O ice nucleation.

MCS and simulation data analysis

Simulations are compared with retrievals of water ice opacity and temperature from the MCS observations during MY 29 that use version 5 of the retrieval algorithm59. These data are available as Derived Data Records from the NASA Planetary Data System Atmospheres Node. MCS data binning generate day and night-time zonal profiles at approximately 3 a.m. and 3 p.m. (daytime bins 9 a.m. to 9 p.m. and night-time bins 9 p.m. to 9 a.m.). Data are averaged over 5° of Ls (~10 sol). High opacity along the limb limits the visibility at high pressures; low-altitude observations have a slant opacity limit of 4 × 10−3 km−1 at 12 μm. The MCS pressure grid is set by \(p_i = p_{\mathrm{o}} \exp \left( { - \frac{{i - 10}}{8}} \right)\) where i = 1–105 and po = 610 Pa. Simulation data are processed to match the MCS average schemes32. Day and night-time arrays in the simulations are generated by identifying the longitude of the maximum solar insolation at the surface and the longitude 180° opposite and averaging over 10 sol. Simulation data have no upper or lower limit for extinction, and therefore extend to the model top and surface.