Abnormal Phase Structure of Thermal Tides during Major Dust Storms on Mars: Implications for the Excitation Source of High‐altitude Water Ice Clouds

2021 ◽  
Author(s):  
Zhaopeng Wu ◽  
Tao Li ◽  
Jing Li ◽  
Xi Zhang ◽  
Chengyun Yang ◽  
...  
Keyword(s):  
High Altitude ◽  
Phase Structure ◽  
Dust Storms ◽  
Excitation Source ◽  
Ice Clouds ◽  
Water Ice ◽  
Thermal Tides

A Comparison of Aphelion Cloud Belt Phase Functions Before and After the Mars Year 34 Global Dust Storm

2021 ◽  
Author(s):  
Alex Innanen ◽  
Brittney Cooper ◽  
Charissa Campbell ◽  
Scott Guzewich ◽  
Jacob Kloos ◽  
...  
Keyword(s):  
Dust Storm ◽  
Phase Function ◽  
Dust Storms ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Water Ice ◽  
Ice Cloud ◽  
Sky Survey ◽  
Scattering Phase ◽  
Scattering Phase Function

<p>1. INTRODUCTION</p><p>The Mars Science Laboratory (MSL) is located in Gale Crater (4.5°S, 137.4°E), and has been performing cloud observations for the entirety of its mission, since its landing in 2012 [eg. 1,2,3]. One such observation is the Phase Function Sky Survey (PFSS), developed by Cooper et al [3] and instituted in Mars Year (MY) 34 to determine the scattering phase function of Martian water-ice clouds. The clouds of interest form during the Aphelion Cloud Belt (ACB) season (L<sub>s</sub>=50°-150°), a period of time during which there is an increase in the formation of water-ice clouds around the Martian equator [4]. The PFSS observation was also performed during the MY 35 ACB season and the current MY 36 ACB season.</p><p>Following the MY 34 ACB season, Mars experienced a global dust storm which lasted from L<sub>s</sub>~188° to L<sub>s</sub>~250° of that Mars year [5]. Global dust storms are planet-encircling storms which occur every few Mars years and can significantly impact the atmosphere leading to increased dust aerosol sizes [6], an increase in middle atmosphere water vapour [7], and the formation of unseasonal water-ice clouds [8]. While the decrease in visibility during the global dust storm itself made cloud observation difficult, comparing the scattering phase function prior to and following the global dust storm can help to understand the long-term impacts of global dust storms on water-ice clouds.</p><p>2. METHODS</p><p>The PFSS consists of 9 cloud movies of three frames each, taken using MSL’s navigation cameras, at a variety of pointings in order to observe a large range of scattering angles. The goal of the PFSS is to characterise the scattering properties of water-ice clouds and to determine ice crystal geometry.  In each movie, clouds are identified using mean frame subtraction, and the phase function is computed using the formula derived by Cooper et al [3]. An average phase function can then be computed for the entirety of the ACB season.</p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.eda718c85da062913791261/sdaolpUECMynit/1202CSPE&app=m&a=0&c=67584351a5c2fde95856e0760f04bbf3&ct=x&pn=gnp.elif&d=1" alt="Figure 1 – Temporal Distribution of Phase Function Sky Survey Observations for Mars Years 34 and 35" width="800" height="681"></p><p>Figure 1 shows the temporal distributions of PFSS observations taken during MYs 34 and 35. We aim to capture both morning and afternoon observations in order to study any diurnal variability in water-ice clouds.</p><p>3. RESULTS AND DISCUSSION</p><p>There were a total of 26 PFSS observations taken in MY 35 between L<sub>s</sub>~50°-160°, evenly distributed between AM and PM observations. Typically, times further from local noon (i.e. earlier in the morning or later in the afternoon) show stronger cloud features, and run less risk of being obscured by the presence of the sun. In all movies in which clouds are detected, a phase function can be calculated, and an average phase function determined for the whole ACB season.  </p><p>Future work will look at the water-ice cloud scattering properties for the MY 36 ACB season, allowing us to get more information about the interannual variability of the ACB and to further constrain the ice crystal habit. The PFSS observations will not only assist in our understanding of the long-term atmospheric impacts of global dust storms but also add to a more complete image of time-varying water-ice cloud properties.</p>

scholarly journals Strong Variability of Martian Water Ice Clouds During Dust Storms Revealed From ExoMars Trace Gas Orbiter/NOMAD

2020 ◽  
Vol 125 (4) ◽  
Author(s):  
Giuliano Liuzzi ◽  
Geronimo L. Villanueva ◽  
Matteo M.J. Crismani ◽  
Michael D. Smith ◽  
Michael J. Mumma ◽  
...  
Keyword(s):  
Dust Storms ◽  
Trace Gas ◽  
Ice Clouds ◽  
Water Ice

scholarly journals Mesospheric water ice clouds in Mars Year 34-35 as identified in ExoMars UVIS occultation opacities

2021 ◽  
Author(s):  
Paul Streeter ◽  
Graham Sellers ◽  
Mike Wolff ◽  
Jon Mason ◽  
Manish Patel ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Atmospheric Aerosols ◽  
Numerical Models ◽  
Martian Atmosphere ◽  
Dust Storms ◽  
Earth Planet ◽  
Ice Clouds ◽  
Great Opportunity ◽  
Mars Atmosphere ◽  
Water Ice

<p><strong>Introduction:</strong>  Suspended atmospheric aerosols are key components of the martian atmosphere, and their vertical distribution has long been a subject of investigation with orbital observations and modelling. The aerosols found in Mars' atmosphere are mineral dust, water ice, and CO<sub>2</sub> ice, and each have distinct spatiotemporal distributions and radiative effects.</p> <p>Of particular interest for this study is the vertical distribution of atmospheric aerosols. In recent years, dust has been observed to have a more complex vertical distribution structure than previously thought, with the detection of detached dust layers [1] and large plume-like structures during Global Dust Storms (GDS) [2].</p> <p>Water ice distribution is tied to the seasonal behaviour of its associated cloud formations, with seasonally recurring features including the aphelion cloud belt (ACB) [3] and polar hood clouds [4] at tropospheric altitudes, as well as higher altitude mesospheric (>40 km) clouds during Mars’ perihelion season [5] as well as during GDS [6,7].</p> <p>Mars’ low atmospheric temperatures also enable the formation of CO<sub>2</sub> ice clouds, which have been detected at mesospheric altitudes over the tropics/subtropics and generally during the colder aphelion season [5,8]. These are thought to be more ephemeral than their water ice counterparts, with lifetimes as low as minutes [9]. More persistent and optically thicker CO2 ice clouds have been detected at tropospheric altitudes in the polar night [10].</p> <p> The Ultraviolet and Visible (UVIS) Spectrometer [11], part of the Nadir and Occultation for MArs Discovery (NOMAD) spectrometer suite aboard the ExoMars Trace Gas Orbiter (TGO) [12], has now observed the martian atmospheric limb via solar occultations for over 1.5 martian years. This period covers the 2018/Mars Year (MY) 34 GDS and regional dust storm, as well as the entirety of the more typical MY 35. As such, UVIS solar occultation data provides a great opportunity to examine Mars’ vertical aerosol structure.</p> <p><strong>Results: </strong>We present a new UVIS occultation opacity profile dataset, openly available for use by the community. We also discuss particular features of interest in the dataset, and interpret these features by reference to previous published work and by comparison with the MGCM. In particular,<strong> </strong>we focus on notable mesospheric water ice cloud phenomena observed in both MY 34 and MY 35. We describe the spatiotemporal distribution of these features, and the link between specific water ice features and strong atmospheric dust activity from global and regional storms. The MGCM temperature and aerosol opacity fields provide valuable points of comparison with the UVIS dataset, for the purposes of both explanation and validation of the MGCM’s existing parametrizations. The UVIS dataset offers opportunities for further research into the vertical aerosol structure of the martian atmosphere, and improvement of how this is represented in numerical models.</p> <p><strong>References:</strong> [1] Heavens, N. G. et al (2011) <em>JGR (Planets), 116(E4), </em>E04003. [2] Heavens, N. G. et al (2019) <em>GRL, 124</em>(11), 2863-2892. [3] Smith M. D. (2008) <em>Annu. Rev. Earth Planet Sci, 26, </em>191-219. [4] Wang, H. & Ingersoll, A. P. (2002) <em>JGR (Planets), 107(E10), </em>8-1-8-16. [5] Clancy, R. T. et al (2019) <em>Icarus, 328, </em>246-273. [6] Liuzzi G. et al (2020) <em>JGR (Planets), 125</em>(4). [7] Stcherbinine, A. et al (2020) <em>JGR (Planets), 125</em>(3). [8] Aoki, S. et al (2018) <em>Icarus, 302, </em>175-190. [9] Listowski, C. et al (2014) <em>Icarus, 237, </em>239-261. [10] Hayne, P. O. et al (2012) <em>JGR (Planets), 117</em>(E8). [11] Patel, M. R. et al (2017) <em>Appl. Opt., 56</em>(10), 2771-2782. [12] Vandaele, A. C. et al (2015) <em>Planet. Space Sci., 119</em>, 233-249.</p>

scholarly journals Influence of water ice clouds on Martian tropical atmospheric temperatures

2008 ◽  
Vol 35 (7) ◽  
pp. n/a-n/a ◽  
Author(s):  
R. John Wilson ◽  
Stephen R. Lewis ◽  
Luca Montabone ◽  
Michael D. Smith
Keyword(s):  
Ice Clouds ◽  
Water Ice ◽  
Influence Of Water

Nighttime convection in water-ice clouds at high northern latitudes on Mars

Icarus ◽  
2021 ◽  
pp. 114693
Author(s):  
David Hinson ◽  
Huiqun Wang ◽  
John Wilson ◽  
Aymeric Spiga
Keyword(s):  
Ice Clouds ◽  
Water Ice ◽  
Northern Latitudes

A new type of cloud discovered from Earth in the upper Martian atmosphere

2021 ◽  
Author(s):  
Jean Lilensten ◽  
Jean-Luc Dauvergne ◽  
Christophe Pellier ◽  
Marc Delcroix ◽  
Emmanuel Beaudoin ◽  
...  
Keyword(s):  
High Altitude ◽  
Magnetic Anomaly ◽  
Dust Storm ◽  
Large Scale ◽  
Martian Atmosphere ◽  
Ice Clouds ◽  
Large Particles ◽  
Night Side ◽  
Cosmic Particle ◽  
New Type

<p>During the 2020 Mars opposition, we observe from Earth the occurrence of a non-typical large-scale high-altitude clouds system, extending over thousands of km from the equator to 50°S. Over 3 hours, they emerge from the night side at an altitude of 90 (-15/+30) km and progressively dissipate in the dayside. They occur at a solar longitude of 316°, west of the magnetic anomaly and concomitantly to a regional dust storm. Despite their high altitude, they are composed of relatively large particles, suggesting a probable CO<sub>2</sub> ice composition, although H<sub>2</sub>O cannot be totally excluded. Such ice clouds were not reported previously. We discuss the formation of this new type of clouds and suggest a possible nucleation from cosmic particle precipitation.</p>

scholarly journals Cloud Phase Structure: Experimental Data Analysis and Parameterization

2006 ◽  
Vol 63 (2) ◽  
pp. 667-681 ◽  
Author(s):  
I. P. Mazin
Keyword(s):  
Soviet Union ◽  
Phase Structure ◽  
Former Soviet Union ◽  
Experimental Studies ◽  
Frequency Of Occurrence ◽  
Water Ice ◽  
Phase Index ◽  
Stratiform Clouds ◽  
Average Distribution ◽  
Experimental Data Analysis

Abstract In this article, the data collected over 6 yr of daily observations at a network of aircraft sounding (31 stations) in the former Soviet Union, and the data collected by Canadian researchers in field campaigns in the 1990s, are reanalyzed and compared with each other. To describe the cloud phase structure (CPS), the notion of the cloud phase index (CPI)3 is used; that is, the local mass fraction of the ice particles in the total (water + ice) water content. It is concluded that the average distribution of the (CPI)3 values in clouds depends mainly on the temperature, the cloud types, and the scale of averaging. If these characteristics remain unchanged the geographic and seasonal variations of the phase structure are small. It is shown that for averaging scales of the order of 100 m, the frequency of occurrence of liquid clouds [(CPI)3 = 0] varies from approximately 60% at 0°C to 5% at −35°C, and that of the ice clouds from about 5% to 60%. The frequency of occurrence of the mixed clouds only weakly depends on temperature, varying within 30%–40%. The dependence of the cumulative (CPI)3 distribution on temperature in the interval 0.1 < (CPI)3 < 0.7 is close to linear. For stratiform clouds (without going into further details) the coefficients of the linear parameterization are found as a function of temperature. Knowing the (CPI)3 distribution allows one to also estimate the humidity in clouds. The most urgent challenges for the experimental studies of the cloud phase structure are formulated.

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