Simulated Atmospheric Response to Large‐Scale Dust Forcing and Implications for Martian Dust Storm Growth

Martian dust, composed of micrometer-sized mineral particles, is a key parameter of the Martian atmosphere because of its high mobility and capacity to form dust storms and alter the heat balance of the atmosphere. These dust storms are part of the Martian dust cycle and can occur over a wide range of spatial and time scales (from sub-km to planetary scale, and from the minute to months). The dust studies are mostly concentrated on regional storms (> 2000 km), which are detected using UV-VIS global imagers [1, 2] or thermal-IR spectrometers [3]. These observations provide information about the frequency and size of the storms. However, some characteristics of the dust cycle remain uncertain, such as the exact mechanisms of storm formation and growth processes, with implications for the predictability of dust storms and Global Dust Storms (GDS, storm at a planetary scale). Thus, it is important to study dust activity at a local scale, such as the local dust storms (< 2000 km) which have not been massively detected (some detections by [2] and a few individual storm characterisations as [4]). We focus our work on detecting dust storms in the OMEGA/Mars Express (near-IR imaging spectrometer) dataset, which has a high enough spatial resolution (0.36-4.8 km/px) to detect local dust storms. More precisely, we develop a method to detect automatically dust storms using dust optical depth computation (at 0.9 µm) made by [5] from late Martian Year 26 to early MY 30 (including the MY 28 GDS). The 1st-level detection is to exclude OMEGA observations that are least likely to contain dust storms (dust optical depth < 1.25). Then the 2nd-level detection principle is to identify pixel clusters of high optical depth within individual observations to identify storms, to confirm the detection using different criteria (e.g., decrease of surface reflectance) and to extract key characteristics of the storm (e.g., size, centroid, local time).Figure 1: Spatial distribution of the dust storms (local and regional) detected with OMEGA/MEx from late MY 26 to early MY 30 (without MY 28 GDS period). The background corresponds to a topography map (MOLA/MGS). With this 2-level method, we detected 287 dust storms (excluding the MY 28 GDS period during which 114 detections have been made) composed of 283 local and 4 regional. Here we summarised our results that will be presented in detail during the conference (notably by separating the local and regional dust storms). From the spatial distribution of the detections (Figure 1), we notice some known preferential areas such as the flushing dust storm channels (e.g., Acidalia-Chryse, Utopia-Isidis, see [1]) or Hellas Planitia, as well as next to the southern polar cap. The seasonal distribution of the detected storms (Figure 2) shows many detections in the Ls=240-270° period, particularly in MY 27, and also during the Ls=330-360° period, notably in MY 29. Interestingly, only a few storms were reported during these periods using UV-VIS imagery [1], suggesting that our method may be capturing local-scale events that were previously undetected. Another strength of OMEGA data is the local time coverage during the Mars Express mission, allowing the study of the time dependence. We noticed many detections from 10:00 to 18:00 with an increase (compared to the OMEGA local time coverage) at the end of the afternoon (16:00-18:00), and also some detections early in the morning (04:00-06:00).Figure 2: Seasonal distribution of the dust storms (local and regional) detected with OMEGA/MEx from late MY 26 to early MY 30 (without MY 28 GDS period). We also worked on the MY 28 GDS onset, for which one doubt remains about the formation area, specifically, whether it originated in Noachis (southern hemisphere) or Chryse (northern hemisphere). More precisely, the question is whether the precursory storm observed in Noachis initiated the GDS independently, or whether it was dependent on the one in Chryse. The consecutive OMEGA observations of these two areas (during the storms) show high dust optical depth values for Noachis and Chryse, but separated from each other by low optical depths, which could be interpreted as two separate clouds, and therefore a GDS onset in Noachis. We are currently working to evaluate the dust altitude by comparing dust optical depth retrievals at different wavelengths [6].

Nadir and Occultation for Mars Discovery (NOMAD) onboard ExoMars Trace Gas Orbiter (TGO) started  science measurements on 21 April, 2018. Here, we present results on the retrievals of water vapor vertical distributions in the Martian atmosphere from three years of TGO/NOMAD science operations.  NOMAD is a spectrometer operating in the spectral ranges between 0.2 and 4.3 μm onboard ExoMars TGO. NOMAD has 3 spectral channels: a solar occultation channel (SO – Solar Occultation; 2.3–4.3 μm), a second infrared channel capable of nadir, solar occultation, and limb sounding (LNO – Limb Nadir and solar Occultation; 2.3–3.8 μm), and an ultraviolet/visible channel (UVIS – Ultraviolet and Visible Spectrometer, 200–650 nm). The infrared channels (SO and LNO) have high spectral resolution (λ/dλ~10,000–20,000) provided by an echelle grating used in combination with an Acousto Optic Tunable Filter (AOTF) which selects diffraction orders. The sampling rate for the solar occultation measurement is 1 second, which provides a good vertical sampling step (~1 km) with higher resolution (~2 km) from the surface to 200 km. Thanks to the instantaneous change of the observing diffraction orders achieved by the AOTF, the SO channel is able to measure five or six different diffraction orders per second in solar occultation mode. In this study, we analyze the solar occultation measurements at diffraction order 134 (3011-3035 cm-1), order 136 (3056-3080 cm-1), order 168 (3775-3805 cm-1), and order 169 (3798-3828 cm-1) acquired by the SO channel in order to investigate water vapor vertical distributions.Knowledge of the water vapor vertical profile is important to understand the water cycle and its escape process. Solar occultation measurements by two new spectrometers onboard TGO - NOMAD and Atmospheric Chemistry Suite (ACS) - allows us to daily monitor the water vapor vertical distributions through the whole Martian Year and obtain a good latitudinal coverage for every ~20° of Ls. In 2018, for the first time after 2007, a global dust storm occurred on Mars. It lasted for more than two months (from June to August). Moreover, following the global dust storm, a regional dust storm occurred in January 2019. The NOMAD and ACS observations therefore fully cover the majority of the global and regional dust storms and offer a unique opportunity to study the trace gases distributions during the dust storms. We analyzed those datasets and found a significant increase of water vapor abundances in the middle atmosphere (40-100 km) during the global dust storm from June to mid-September 2018 and the regional dust storm in January 2019. In particular, water vapor reaches very high altitude, at least 100 km, during the global dust storm (Aoki et al., 2019, Journal of Geophysical Research, Volume124, Issue12, Pages 3482-3497, doi:10.1029/2019JE006109). A GCM simulation explained that dust storm related increases of atmospheric temperatures suppress the hygropause, hence reducing ice cloud formation and so allowing water vapor to extend into the middle atmosphere (Neary et al., 2020, Geophysical Research Letters, accepted, Volume47, Issue7, e2019GL084354, doi: 10.1029/2019GL084354). This study presents the results with the extended dataset, which covers a full Mars year. The extended dataset newly includes aphelion season that involves interesting phenomena such as sublimation of water vapor from the northern polar cap and formation of the equatorial cloud belt, which are known as key periods to understand the large north-south hemispheric asymmetries of Mars water vapor. Yet, only a few papers report the water vapor vertical distributions in the aphelion season. The extended dataset also includes the southern summer season (dusty season) in MY 35, which will allow us to compare the water vapor distributions in the global dust storm year with those in the non-global dust storm year. In the presentation, we will discuss the water vapor vertical profiles as well as the aerosols vertical distributions retrieved from the three-year measurements of the TGO/NOMAD.

Mars dust storms are an interdisciplinary field of research. They impact the entry-descent-landing operations of spacecraft, the energy production by the solar panels of Mars rovers and landers, and others. As can be foreseen, dust storms are also critical for the future human exploration of Mars. Dust storm research is directly aligned with the Emirates Mars Mission (EMM) science objective on the lower atmosphere, and with the science objective of correlating the lower and upper atmosphere [1,2]. First results of EMM dust storm research were reported in [3].EMM has a high-altitude orbit and provides data products for studies of the Mars atmosphere and surface with a near-hemispheric view. Moreover, EMM can provide information on dust storm activity every few hours or less. EMM observed multiple dust storms during the primary mission, including a large regional dust storm in Sep. and Oct. 2022.The focus of this presentation are unique dust storm observations by the EMM camera EXI [4]. We study a subset of dust storms, which is of particular interest to our research. The formation and growth of dust storms is followed at a (sub-)hourly time scale. This includes results on the dust storm morphology, wind direction, wind speed, surface dust lifting, etc.. Based on that, the implications for the physics and dynamics of dust storms are considered.[1] Amiri, H.E.S., Brain, D., Sharaf, O. et al. The Emirates Mars Mission. Space Sci Rev 218, 4 (2022). https://doi.org/10.1007/s11214-021-00868-x[2] Almatroushi, H., AlMazmi, H., AlMheiri, N. et al. Emirates Mars Mission Characterization of Mars Atmosphere Dynamics and Processes. Space Sci Rev 217, 89 (2021). https://doi.org/10.1007/s11214-021-00851-6[3] Gebhardt, C., Guha, B. K., Young, R. M. B., & Wolff, M. J. (2022). A frontal dust storm in the northern hemisphere at solar longitude 97—An unusual observation by the Emirates Mars mission. Geophysical Research Letters, 49, e2022GL099528. https://doi.org/10.1029/2022GL099528[4] Jones, A.R., Wolff, M., Alshamsi, M. et al. The Emirates Exploration Imager (EXI) Instrument on the Emirates Mars Mission (EMM) Hope Mission. Space Sci Rev 217, 81 (2021). https://doi.org/10.1007/s11214-021-00852-5

Analysing some martian atmospheric characteristics associated with a dust storm over the Lunae Planum region during October 2014

<p>High Latitude Dust (HLD) contributes 5% to the global dust budget, but HLD measurements are sparse. Iceland has the largest area of volcaniclastic sandy desert on Earth where dust is originating from volcanic, but also glaciogenic sediments. Total Icelandic desert areas cover 44,000 km<sup>2</sup> which makes Iceland the largest Arctic as well as European desert. Icelandic volcanic dust can be transported distances > 1700 km towards the Arctic and deposited on snow, ice and sea ice. It is estimated that about 7% of Icelandic dust can reach the high Arctic (N>80°). It is known that about 50% of Icelandic dust storms occurred during winter or subzero temperatures in the southern part of Iceland. The vertical distributions of dust aerosol in high atmospheric profiles during these winter storms and long-range transport of dust during polar vortex condition were unknown.</p><p>Dust observations from Iceland provide dust aerosol distributions during the Arctic winter for the first time, profiling dust storms as well as clean air conditions. Five winter dust storms were captured during harsh conditions.  Mean number concentrations during the non-dust flights were < 5 particles cm<sup>-3 </sup>for the particles 0.2-100 µm in diameter and > 40 particles cm<sup>-3</sup> during dust storms. A moderate dust storm with > 250 particles cm<sup>-3</sup> (2 km altitude) was captured on 10<sup>th</sup> January 2016 as a result of sediments suspended from glacial outburst flood Skaftahlaup in 2015. Similar particle number concentrations were reported previously in the Saharan air layer. Detected particle sizes were up to 20 µm close to the surface, up to 10 µm at 900 m altitude, up to 5 µm at 5 km altitude, and submicron at altitudes > 6 km.</p><p>Dust sources in the Arctic are active during the winter and produce large amounts of particulate matter dispersed over long distances and high altitudes. HLD contributes to Arctic air pollution and has the potential to influence ice nucleation in mixed-phase clouds and Arctic amplification.</p><p> </p><p>Reference:</p><p>Dagsson-Waldhauserova, P., Renard, J.-B., Olafsson, H., Vignelles, D., Berthet, G., Verdier, N., Duverger, V., 2019. Vertical distribution of aerosols in dust storms during the Arctic winter. <strong>Scientific Reports </strong>6, 1-11.</p>

687: The relationship of type of feedback to learning during simulation: a randomized clinical trial

A review of the dust storms observed on Mars is made. This includes the seasonal and interannual variability of planet- encircling and regional dust storms. Although there is a significant interannual variability, planet-encircling dust storms have been observed to form during the southern spring and summer seasons, while regional dust storms tend to occur more frequently. Some aspects of possible mechanisms associated with the origin, maintenance and decay of the dust storms are also discussed.

<p>For the first time, four surface stations are currently operating on Mars, three rovers, Curiosity in Gale crater (4.6°S, 137.4°E; since 6 August 2012), Perseverance in Jezero crater (18.4°N, 77.5°E; since 18 February 2021), Zhurong in Utopia Planitia (25.1°N, 109.9°E; since 14 May 2021), and the platform Insight in Elysium Planitia (4.5°N, 135.6°E; since 26 November 2018) [1]. All these stations are equipped with a suite of meteorological sensors and cameras. For the first time, simultaneous data can be obtained on the meteorological magnitudes from the instruments onboard these stations allowing a comparative and complementary study of the global and local atmospheric dynamics of Mars. In addition, a battery of up to 8 orbiters are currently studying the planet [2]. In order to interpret and put in context the meteorological measurements at the surface by these stations, we present here a study of the atmospheric disturbances based of images of Mars obtained from cameras in two orbiters: the Visual Monitoring Camera (VMC) onboard Mars Express [3], and the MARCI camera onboard Mars Reconnaissance Orbiter [4, 5]. The period covered by this study extends from the arrival of Perseverance (February 2021) and up to the present with VMC images (Ls ~ 5° – 295°) and up to February 2022 with MARCI images (Ls ~ 170°).</p> <p> </p> <p>We first report on the disturbances that evolved at the edge of the North Polar Cap (latitudes ~ 40°N to 70°N) during the springtime season in the northern hemisphere. These are dust storms and synoptic-scale cloud systems with arc, frontal, irregular and spiral shapes, typically growing from the baroclinic instabilities in the intense eastward jet present in this epoch of the Martian year, that leave their imprint in the surface pressure, temperature and winds [6] (Figures 1a-b).  We also report on the evolution of the aphelion cloud belt (Ls ~ 0° – 180°) in the location of the surface stations. Finally, we present an analysis of dust storms that evolved at other latitudes, but taking particular interest in those that formed and evolved at the location of the stations, as was the case in early January 2022 when a regional dust storm impinged the Perseverance rover (Figure 1c).</p> <p><img src="" alt="" width="1020" height="978" /></p> <p><strong>Figure 1. </strong>Images of atmospheric disturbances: (a) MARCI polar map for 1 April 2021 showing dust storms at the edge of the North Polar Cap; (b) VMC image of the annular baroclinic cyclone in 3 November 2021; (c) VMC image showing a regional dust storm approaching Perseverance rover (red cross) in 4 January 2022 (SE = South East).</p> <p><strong>References</strong></p> <p>[1] Wikipedia: https://en.wikipedia.org/wiki/List_of_artificial_objects_on_Mars</p> <p>[2] Wikipedia: https://en.wikipedia.org/wiki/List_of_Mars_orbiters</p> <p>[3] Sánchez-Lavega, A. et al., Icarus 299, 194-205 (2018)</p> <p>[4] Bell III, J. F. et al., J.<em> </em>Geophys. Res. Planets 114, E003315, 1-41 (2009)</p> <p>[5] Ordóñez-Etxeberria, I. et al., in Mars Atmospheric Modelling and Observation, MAMO, Paris, 14-17 June (2022)</p> <p>[6] Barnes, et al., <em>The Global Circulation, in The Atmosphere and Climate of Mars</em> (edts. R. M. Haberle, R. Clancy, F. Forget, M. D. Smith and R. W. Zurek), Chapter 9, pp. 228-294, Cambridge University Press, Cambridge, U.K. (2017)</p>

Inputs from GABAergic and glutamatergic neurons are suspected to play an important role in regulating the activity of the gonadotropin-releasing hormone (GnRH) neurons. The GnRH neurons exhibit marked plasticity to control the ovarian cycle with circulating estradiol concentrations having profound “feedback” effects on their activity. This includes “negative feedback” responsible for suppressing GnRH neuron activity and “positive feedback” that occurs at mid-cycle to activate the GnRH neurons to generate the preovulatory luteinizing hormone surge. In the present study, we employed brain slice electrophysiology to question whether synaptic ionotropic GABA and glutamate receptor signaling at the GnRH neuron changed at times of negative and positive feedback. We used a well characterized estradiol (E)–treated ovariectomized (OVX) mouse model to replicate negative and positive feedback. Miniature and spontaneous postsynaptic currents (mPSCs and sPSCs) attributable to GABAA and glutamatergic receptor signaling were recorded from GnRH neurons obtained from intact diestrous, OVX, OVX + E (negative feedback), and OVX + E+E (positive feedback) female mice. Approximately 90% of GnRH neurons exhibited spontaneous GABAA-mPSCs in all groups but no significant differences in the frequency or kinetics of mPSCs were found at the times of negative or positive feedback. Approximately 50% of GnRH neurons exhibited spontaneous glutamate mPSCs but again no differences were detected. The same was true for spontaneous PSCs in all cases. These observations indicate that the kinetics of ionotropic GABA and glutamate receptor synaptic transmission to GnRH neurons remain stable across the different estrogen feedback states.

The cascade from local to global dust storms on Mars: Temporal and spatial thresholds on thermal and dynamical feedback

The seasonal and spatial distribution of textured dust storms observed by Mars Global Surveyor Mars Orbiter Camera

This is the first part of a two‐part paper. NASA's Mars 2020 Perseverance rover measured winds on the Jezero crater floor close to the delta of an ancient river. A mostly repeatable diurnal cycle was observed and presented two regimes: (a) a convective regime, from dawn to sunset, with average easterly to southeasterly winds, during which maximum wind speeds were measured, and (b) a nighttime regime with westerly‐northwesterly winds followed by a relatively calm period with highly variable wind directions as a function of sol and time of night. The timing and magnitude of the observed regimes are consistent with primary control by regional and local slope flows. Data suggest that the surface circulation at Jezero region in northern spring and summer is highly unaffected by large‐scale circulation except during particular periods in the diurnal cycle or generally during dust storms, which is supported by MarsWRF model simulations. Consequently, the observed seasonal variability was weak. However, sol‐to‐sol and seasonal variability were measured, most of it during certain nighttime periods. Traveling waves consistent with baroclinic instability were clearly observed in surface winds at Ls ∼ 75°. The early MY36/2022A regional dust storm at Ls ∼ 153° disturbed the wind patterns with changes suggesting enhanced tidal flows. After sunset, the dust storm also produced detectable gravity wave activity, increasing the mixing in the nighttime planetary boundary layer during storm conditions. Inferred wind directions from dust devil movies strongly suggest that prevailing winds continued to be slope‐driven during the late summer, fall and early winter seasons.

In situ observations and output from a numerical model are utilized to examine three dust outbreaks that occurred in the northwestern Sonoran Desert. Via analysis of these events, it is shown that trapped waves generated in the lee of an upwind mountain range produced high surface wind speeds along the desert floor and the observed dust storms. Based on analysis of observational and model output, general characteristics of dust outbreaks generated by trapped waves are suggested, including dust-layer depths and concentrations that are dependent upon wave phase and height above the surface, emission and transport associated with the presence of a low-level jet, and wave-generated high wind speeds and thus emission that occurs far downwind of the wave source. Trapped lee waves are ubiquitous in Earth’s atmosphere and thus it is likely that the meteorological aspects of the dust storms examined here are also relevant to understanding dust in other regions. These dust outbreaks occurred near the Salton Sea, an endorheic inland body of water that is rapidly drying due to changes in water-use management. As such, these findings are also relevant in terms of understanding how future changes in size of the Salton Sea will impact dust storms and air quality there. Significance Statement Dust storms are ubiquitous in Earth’s atmosphere, yet the physical processes underlying dust emission and subsequent transport are not always understood, in part due to the wide variety of meteorological processes that can generate high winds and dust. Here we use in situ measurements and numerical modeling to demonstrate that vertically trapped atmospheric waves generated by air flowing over a mountain are one such mechanism that can produce dust storms. We suggest several features of these dust outbreaks that are specific to their production by trapped waves. As the study area is a region undergoing rapid environmental change, these results are relevant in terms of predicting future dust there.

One barrier to interpreting past studies of cognition and major depressive disorder (MDD) has been the failure in many studies to adequately dissociate the effects of MDD from the potential cognitive side effects of selective serotonin reuptake inhibitors (SSRIs) use. To better understand how remediation of depressive symptoms affects cognitive function in MDD, we evaluated three groups of subjects: medication-naïve patients with MDD, medicated patients with MDD receiving the SSRI paroxetine, and healthy control (HC) subjects. All were administered a category-learning task that allows for dissociation between learning from positive feedback (reward) vs. learning from negative feedback (punishment). Healthy subjects learned significantly better from positive feedback than medication-naïve and medicated MDD groups, whose learning accuracy did not differ significantly. In contrast, medicated patients with MDD learned significantly less from negative feedback than medication-naïve patients with MDD and healthy subjects, whose learning accuracy was comparable. A comparison of subject’s relative sensitivity to positive vs. negative feedback showed that both the medicated MDD and HC groups conform to Kahneman and Tversky’s (1979) Prospect Theory, which expects losses (negative feedback) to loom psychologically slightly larger than gains (positive feedback). However, medicated MDD and HC profiles are not similar, which indicates that the state of medicated MDD is not “normal” when compared to HC, but rather balanced with less learning from both positive and negative feedback. On the other hand, medication-naïve patients with MDD violate Prospect Theory by having significantly exaggerated learning from negative feedback. This suggests that SSRI antidepressants impair learning from negative feedback, while having negligible effect on learning from positive feedback. Overall, these findings shed light on the importance of dissociating the cognitive consequences of MDD from those of SSRI treatment, and from cognitive evaluation of MDD subjects in a medication-naïve state before the administration of antidepressants. Future research is needed to correlate the mood-elevating effects and the cognitive balance between reward- and punishment-based learning related to SSRIs.

It is well known that noise is inevitable in gene regulatory networks due to the low-copy numbers of molecules and local environmental fluctuations. The prediction of noise effects is a key issue in ensuring reliable transmission of information. Interlinked positive and negative feedback loops are essential signal transduction motifs in biological networks. Positive feedback loops are generally believed to induce a switch-like behavior, whereas negative feedback loops are thought to suppress noise effects. Here, by using the signal sensitivity (susceptibility) and noise amplification to quantify noise propagation, we analyze an abstract model of the Myc/E2F/MiR-17-92 network that is composed of a coupling between the E2F/Myc positive feedback loop and the E2F/Myc/miR-17-92 negative feedback loop. The role of the feedback loop on noise effects is found to depend on the dynamic properties of the system. When the system is in monostability or bistability with high protein concentrations, noise is consistently suppressed. However, the negative feedback loop reduces this suppression ability (or improves the noise propagation) and enhances signal sensitivity. In the case of excitability, bistability, or monostability, noise is enhanced at low protein concentrations. The negative feedback loop reduces this noise enhancement as well as the signal sensitivity. In all cases, the positive feedback loop acts contrary to the negative feedback loop. We also found that increasing the time scale of the protein module or decreasing the noise autocorrelation time can enhance noise suppression; however, the systems sensitivity remains unchanged. Taken together, our results suggest that the negative/positive feedback mechanisms in coupled feedback loop dynamically buffer noise effects rather than only suppressing or amplifying the noise.