JuanCastillo29/space-mission-intelligence-data huggingface dataset:
Although the AMEC can be generally described with the four typologies defined above, there are some variations and extra features worth mentioning.
In some images taken early in the season (Ls 249º and 253º) of appearance of the AMEC phenomenon, the tail of a cloud of Type I morphology is very thin, and the bright head and the dark elongated shadow of the tail dominate the image (Figure 9f). The brightness of the cloud and the visibility of the shadow might be affected by the observation geometry.
Images often show the presence of hazes close to the AMEC. At dawn, the hazes are already visible in the night side of the terminator (see Figure 5a) and they persist into the early hours (see animations in supporting information). Later in the season (after Ls 275º) the AMEC is sometimes accompanied by less diffuse structures, forming cones that extend from its head at an angle of 30º-60º relative to the tail axis (Figure 9g).
In Figure 9h, the tail splits into two sections with slightly different directions (see animation S2 in supporting material), probably due to changes in the intensity and direction of the winds. Finally, the morphology of the tail is sometimes suggestive of bursts of cloud activity in the head advected by winds. Figure 9i shows a ~50 km wide blob detaching from the head to the tail at 8.0 LTST, in a configuration that can be described as type III. This observation continued with a transition to morphology IV, as can be seen in animation S3 in the supporting information.

[Figure: Figure 9. Morphology of the AMEC cloud: (a) Scheme of different AMEC features over a synthetic representation, including the head, neck and tail. Panels b-e. Examples of different morphologies. (b) Type I morphology. 2018-09-18, Ls 256º, LTST 8.5. (VMC observation 180326). (c)  Type II morphology. 2018-10-18, Ls 270º, LTST 7.1. (VMC observation 180362 ). (d) Type III morphology. 2018-10-20, Ls 272º, LTST 7.9. (VMC observation 180366). (e) Type IV morphology. 2018-11-06, Ls 283º, LTST 8.1. (VMC observation 180397). Panels (f-i) Examples of other features. (f) Bright head with a long dark tail that is probably the shadow projected by the optically thin tail. 2018-09-13, Ls 249º, LTST 7.5. (VMC observation 180306). (g) Hazes in almost symmetrical angles occur ~50º relative to the cloud tail. 2018-11-28, Ls 296º, LTST 6.6. (VMC observation 180424). (h) Two tails at once. 2018-10-22, Ls 274º, LTST 7.4 (VMC observation 180371). (i) Blob in the head being torn off from the head of the cloud (see animation S1 in supporting information). 2018-10-20, Ls 273º, LTST 8.1. (VMC observation 180366).]
In addition to the marked daily cycle, the AMEC showed a longer-term variability throughout the MY 34. The phases of the daily cycle discussed in section 4.2 were quite regular during the majority of the period studied, with the exception of some early anomalies, marked as red diamonds in Figure 6a. Cloud type I occurs only in this early season, and in these anomalies the cloud usually develops later in the sol, and the cloud length is shorter at any given LTST. For example, on the 19 September there was no cloud at 6.1 LTST, and the cloud was shorter than usual at 8.0 LTST (VMC observations 180317 and 180318). We also find clouds shorter than usual in VMC observation 180329 on the 25 September at 6.9 LTST (Figure 10f), and in the OMEGA observation in orbit 18612 on the 17 September at 7.5 LTST (Figure 3b). This difference in behavior at the beginning of the season was possibly due to the remaining presence of abundant dust from the GDS 2018 (Guzewich et al., 2018).
Figure: Figure 10. Altitude of the AMEC relative to the areoid from different observations. (a) Shadow of the cloud at high resolution as observed by HRSC. This image has been enhanced to improve shadow visibility, for the equivalent color image refer to Fig. 3d. Acquired on  2018-09-21, Ls 254º, LTST 8.5, (orbit 18627). (b,c) AMEC cloud seen at the limb, clearly visible on the western flank (left of the volcano position, indicatedwith dark blue arrows), with hazes and a]

detached layer of aerosols east of Arsia Mons (right of the blue arrow). These images were acquired 48 seconds apart on 2018-11-03, Ls 281º, LTST 6.5, (VMC observation 180390). (d) Map of the region showing limb trajectories for b and c panels. (e) Head of the cloud imaged during twilight. Hazes also appear around the head in twilight (indicatedwith arrows). 2018-10-01, Ls 261º, LTST 5.3, (VMC observation 180340). (f) Shadow of the cloud shortly after dawn. 2018-09-25, Ls 257º, LTST 6.9, (VMC image 180329). (g) Graph showing the topographic profile (red profile at the bottom) as well as the altitude of the cloud shown in panels (a) (blue line) and (e) (orange line), where gray areas indicate the uncertainty in altitude. Also shown is the altitude and minimum thickness of the cloud shown in panel (f).
We searched for the AMEC phenomenon in a survey of available images taken by Mars orbiters. We only found suitable observations (in the expected ranges of LTST and Ls) in MYs 29 to 33 (see Figure 2). We also include an observation in MY12, corresponding to the Viking 2 spacecraft. Poor coverage of earlier observations does not allow us to reveal the full seasonal cycle of the cloud appearance, but a conservative estimation from our observations is that it takes place between Ls = 220°-320º, although its lifespan might be longer (see Figure 2).

[Figure: Figure 11 shows examples of images of the cloud in different MYs and in the following subsections we explore potential interannual variability of the AMEC features.]

When comparing the onset date of the phenomenon for the available MYs (see Figure 2), we see that the earlier appearances were in MY31 (Ls 226º) and MY32 (Ls 233°). In MY34 we have suitable VMC observations at these Ls that do not show the AMEC phenomenon (see Figure 2 and Table S1), suggesting that the onset of the AMEC season that year was delayed in comparison with MYs 31 and 32. This delay is possiblyrelated to the occurrence of the MY34 GDS, and the progressive clearingof dust in the atmosphere (Guzewich et al., 2019; Sánchez-Lavega et al., 2019).

[Figure: Figure 11. Images of the AMEC phenomenon seen in different MYs. All images are projected onto cylindrical maps. Spatial scale is indicated in each panel. (a) MY 12. 1977-08-11, Ls 314º (Viking Orbiter 2 observation 356b33). (b) MY 29. 2009-07-2, Ls 296º (VMC observation 090025). (c) MY 30. 2011-03-21, Ls 258º (VMC observation 110005). (d) MY31. 2012-12-15, Ls 226º (VMC observation 120060). (e) MY 32. 2014-12-13, Ls 252º (MCC product MCC_MRD_20141213T134802312_D_GDS). (f) MY32. 2015-01-04, Ls 266º (MCC product]

MCC_MRD_20150104T063053645_D_D32). (g) MY 33.  2016-12-25, Ls 287º, (VMC observation 160150). (h) MY33. 2017-01-05, Ls 294º, (HRSC observation in orbit 16486) (i) MY33. 2017-01-08, Ls 296º (VMC observation 170010). (j) MY 33. 2017-01-01, Ls 291º (HRSC observation in orbit 16472).

[Figure: Figure 12.  Length and Curvature of the AMEC in MYs 29-33 (Analogous to Figure 6). Panel a. Length of the AMEC as a function of local time. Color code indicates MY. The linear fit corresponds to all data except for MY 33 (indicated with diamond shaped markers),. Panel b. Outline of the tail of the cloud over a topographic map as in Figure 6b. The area occupied by the cloud trajectories in MY 34 (Fig. 6b) is indicated by a background white shadow for comparison.]
[Figure: Figure 12a shows the length of the AMEC as a function of LTST for MYs 29-33, measured only in the images where the complete cloud was visible. The global trend of growth with LTST is similar in MYs 29-32, and a linear fit to data corresponding to those four years indicates an expansion velocity of 130 ± 20 ms-1, slower than in MY34. The fit is not as good as in Fig. 6 (which contained 25]

data from MY 34 only), as it must reflect a degree of interannual variability. The trend in MY 33 is different, and the AMEC is often considerably shorter in length than expected from the general trend in other years, resembling the “early anomalies” reported for MY 34 in section 4.2 (e.g. compare Fig. 11g with Fig. 10f). The expansion direction of the cloud is similar to MY34, initially to the west, and curving towards the north (Figure 12b). An exception to this is MY 33, when the cloud expanded initially southward of Arsia Mons, but keeping its northward pointing concavity.
Few observations in previous years were acquired after 9 LTST and before noon, the local time around which the AMEC had always detached from Arsia Mons in MY 34. MY 33 is an exception to this, as VMC observed past 9 LTST on several occasions. Unlike in MY34, in images before 10 LTST, the cloud had not clearly detached from Arsia Mons, and no elongated cloud was found between 10 and 12 LTST.
In general, morphologies of the cloud in all years are similar to those reported in section 5.2 for MY34. For example, Figure 11c shows a morphology resembling types II or III discussed in section 5.2; Figure 11d shows a clear case of type I and Figure 11e resembles type II. Figure 11h corresponds to type III, indicating that the dark feature usually observed in the neck in low-resolution images of this morphology is the result of a lack of thick clouds in the area. Figure 11g closely resembles the early anomaly depicted in Figure 10f. Figures 11f and 11i have no clear equivalent in MY 34, and it is worth mentioning that both were obtained at a local time when the cloud was usually detached in MY 34.
Hazes and conical shapes such as those reported in section 5.3 are also found in VMC images from the previous years, as in Fig. 11b and 11c, which show hazes southward of the AMEC. The high-resolution images in Fig. 11f,h show hazes southward of the elongated cloud, and extended hazes in the west in the vicinity of the terminator.
If we concentrate on specific features of the AMEC observed at high resolution, the sol-to-sol variability prevails over the seasonal evolution, as is apparent in Figs. 11h,j, obtained by HRSC only four sols apart and almost at the same local time.
We do not have any limb or twilight observations from previous years, and thus all our estimations of height are obtained by analyzing the shadow of the cloud in high-resolution images. The HRSC image obtained in orbit 16486 in MY 33 (Fig. 11h) shows the AMEC casting a prominent shadow at 8.1 LTST that gives a cloud altitude of 40-45 km above the areoid. The MCC observations of the shadow at Ls 252º(Fig. 11e) at 6.7 LTST gives an altitude of 34±3 km above the areoid. Another MCC observation on 4 January 2015 (Fig. 10f) at 9.2 LTST shows the projected shadow from the head from which we derive an altitude of 45±2 km. All these altitudes are in very good agreement with those reported previously in section 6 for MY 34.
In this paper, we report the formation of an extremely Elongated Cloud in the early hours of the morning, extending to the west from the Arsia Mons volcano (AMEC, Arsia Mons Elongated Cloud). We analyze several features of this cloud phenomenon and its changes as a function of Local Time, Solar Longitude, and MY. In our study, we have focused on the occurrence of the AMEC phenomenon during MY 34, which started during the decaying phase of a Global Dust Storm (GDS 2018), and we have also presented observations of the phenomenon in previous MYs.
Morphologically, the AMEC has two main regions (Fig. 9a): the head, a bright cloud approximately round in shape but with texture, of an average size of 125 km in diameter, that forms above the western flank of the volcano at longitude 237ºE and latitude 8.5ºS-10ºS;  and second the long tail that grows and expands westward toward the terminator during the morning hours at speeds of around 170 ms-1 in MY 34 (slower in other years) The elongated cloud attains a maximum length of 1800 km but its width typically remains below 200 km. The head reaches maximum altitudes of 40 – 50 km above the areoid. We find that the AMEC follows a daily cycle with head formation around sunrise(5.7  LTST), followed by its expansion and detachment from the volcano point origin at 8.5 LTST. In the following hours, the cloud becomes thinner and more turbulent, evaporating whilst new thin clouds grow locally over Arsia Mons, as observed in the afternoon in previous MYs (Wang & Ingersoll, 2002; Benson et al., 2003; 2006).
Due to the fact that the AMEC phenomenon occurs at the Martian sunrise, we have few observations that show the details of the head formation in high resolution. One of the best images of the earlier head morphology was obtained by Viking Orbiter 2 in MY12 (Ls 308°)
part of this work.
The AMEC phenomenon develops during the season of maximum insolation at the volcano (daily average at the Top of the Atmosphere TOA ranges from  200 to 225 Wm-2; see Fig. 3 in Sánchez-Lavega et al. 2019) with the perihelion occurring at Ls 251° and the southern solstice at Ls 270°. The AMEC season is also the  period when dust injection in the atmosphere and 28 the development of dust storms on Mars take place (Kahre et al., 2017;

see also bottom panel of Fig. 3, in Sánchez-Lavega et al., 2019). Therefore, the two phenomena, the AMEC and dust (via GDS and regional storms) occur simultaneously, making the AMEC a good case study for the effect of dust on the dynamics and distribution of water vapor, and the microphysics of orographic cloud formation.
There is possible evidence of the effects of dust storms on afternoon cloud development at Arsia Mons. Benson et al. (2003) reported no afternoon cloud activity in Arsia Mons between Ls 227°-235° during MY 24 at the time of a regional dust storm (Cantor et al., 2001). Later, Benson et al. (2006) also reported less cloud formation over Arsia Mons during the GDS 2001 that took place in MY 25 (Cantor, 2007; Montabone 2015; Strausberg et al., 2005). We have explored the AMEC cases in MYs with Global Dust Storm  (MY12, MY34) and without (MYs 29-33). We use the earliest AMEC observations among all the MYs studied, which corresponds to  Ls 226º in MY 31  (December 2012), as a reference. The Viking Orbiter images of the AMEC described above (MY12, Ls 307° and 317º, July 1977) were obtained during the GDS 1977B that took place between May and October 1977 (Ls 268° - 349°; Pollack et al., 1979), indicating that both phenomena coexisted. In MY 34, we find a faster expansion compared to previous years, and a seasonal delay in the Ls of the onset of the AMEC phenomenon, compared to MYs 31 and 32, and some “early anomalies” occurring at the beginning of the season (captured at Ls 240º-260º), consisting of a later formation of the cloud head and a shorter development of its tail. These features are possibly related to the fact that the onset of the AMEC coincided with the decline of the GDS 2018 (Guzewhich et al., 2019; Montabone et al., 2020; Smith 2019b).
How rare is the AMEC phenomenon? The presence of the Valles Marineris Cloud Trails (VMCT) reported by Clancy et al. (2009; 2014), strongly resembles the AMEC. These VMCT are observed recurrently each MY in the Valles Marineris and Noctis Labyrinthus areas around the perihelion season (Ls around 230º-260º) in the afternoon hours (13-15 LTST). Observed in MY28, the clouds were quite elongated, with lengths of 400-1000 km and widths of 25-75 km, and altitudes as deduced from shadows of around 40-50 km, with the cloud expansion requiring winds over 100 ms-1 (Clancy, 2009). Another feature that might be similar to the AMEC is an elongated cloud that has been reported over Ascraeus Mons (the northern Tharsis volcano), first observed by the Viking orbiters (Carr et al., 1980, figure 141).
hours (13-15 LTST). Observed in MY28, the clouds were quite elongated, with lengths of 400-1000 km and widths of 25-75 km, and altitudes as deduced from shadows of around 40-50 km, with the cloud expansion requiring winds over 100 ms-1 (Clancy, 2009). Another feature that might be similar to the AMEC is an elongated cloud that has been reported over Ascraeus Mons (the northern Tharsis volcano), first observed by the Viking orbiters (Carr et al., 1980, figure 141).

Future observations of the AMEC should focus on detailed and systematic images by spacecraft in non-sun-synchronous orbits in order to track the evolution of the phenomenon as a function of local time and, in the long-term, to monitor its interannual variability (current available orbiters are MEX, MAVEN, MOM and TGO). Wide angle cameras like VMC and MCC are well suited to cover large areas at once and obtain sequences of images that enable the study of the phenomenon globally as a function of LTST, and the EXI instrument onboard the Emirates Mars Mission (EMM) will also have this capability. Some pushbroom scanners, like IUVS or HRSC, can also obtain regular images of large spatial areas that could show this kind of phenomenon. Narrow angle cameras can give details of the cloud morphology at its onset, and spectral imagers (e.g. MEX/OMEGA, TGO/CASSIS, EMM/EXI) and other instruments (e.g. MEX/PFS) can give information on cloud particle sizes and optical depths and retrieve temperatures and water vapor abundances. A good characterization of dust in the atmosphere can help in understanding the connection between dust storms and the varied behavior of the AMEC. All these parameters will enable the future modelling of this outstanding Martian meteorological phenomenon.
This work has been supported by the Spanish project AYA2015-65041-P and PID2019-109467GB-I00 (MINECO/FEDER, UE) and Grupos Gobierno Vasco IT-1366-19. JHB was supported by ESA Contract No. 4000118461/16/ES/JD, Scientific Support for Mars Express Visual Monitoring Camera. The Aula EspaZio Gela is supported by a grant from the Diputación Foral de Bizkaia (BFA). We acknowledge support from the Faculty of the European Space Astronomy Centre (ESAC). Special thanks are due to the Mars Express Science Ground Segment and Flight Control Team at ESAC and ESOC. The contributions by K.C and N.M.S were supported by NASA through the MAVEN project.

A list of observations used in this paper is provided in the Supporting Information. All observations are available in ESA PSA, NASA PDS, and ISRO ISSDC. Specific links are given in the supporting material. We uploaded the images as they were used in this study to a repository publicly available: https://doi.org/10.6084/m9.figshare.c.5212793

We acknowledge Claus Gebhardt and an anonymous reviewer whose comments helped improve and clarify this manuscript.

We acknowledge the use of data from the Mars Orbiter Mission (MOM), first interplanetary mission of the Indian Space Research Organization (ISRO), archived at the Indian Space Science Data Centre (ISSDC).
minor species

Frédéric Schmidt 1, Guillaume Cruz Mermy1, Justin Erwin2, Séverine Robert2, Lori Neary2, Ian R. Thomas2, Frank Daerden2, Bojan Ristic2, Manish R. Patel3, Giancarlo Bellucci4, Jose-Juan Lopez-Moreno5, Ann-Carine Vandaele2
1 Université Paris-Saclay, CNRS, GEOPS, 91405, Orsay, France, 2 Belgian Institute for Space Aeronomy (BIRA-IASB), Avenue Circulaire, 3 B-1180 Brussels Belgium,3 School of Physical Sciences, The Open University, Milton Keynes, MK7 6AA, U.K.,4 INAF-Istituto di Astrofsica e Planetologia Spaziali, Rome, ITALY,5 Instituto de Astrofísica de Andalucía CSIC
One of the main difficulties to analyze modern spectroscopic datasets is due to the large amount of data. For example, in atmospheric transmittance spectroscopy, the solar occultation channel (SO) of the NOMAD instrument onboard the ESA ExoMars2016 satellite called Trace Gas Orbiter (TGO) had produced ∼10 millions of spectra in ∼20000 acquisition sequences since the beginning of the mission in April 2018 until 15 January 2020. Other datasets are even larger with ∼billions of spectra for OMEGA onboard Mars Express or CRISM onboard Mars Reconnaissance Orbiter. Usually, new lines are discovered after a long iterative process of model fitting and manual residual analysis. Here we propose a new method based on unsupervised machine learning, to automatically detect new minor species. Although precise quantification is out of scope, this tool can also be used to quickly summarize the dataset, by giving few endmembers ("source") and their abundances. The methodology is the following: we proposed a way to approximate the dataset non-linearity by a linear mixture of abundance and source spectra (endmembers). We used unsupervised source separation in form of non-negative matrix factorization to estimate those quantities. Several methods are tested on synthetic and simulation data. Our approach is dedicated to detect minor species spectra rather than precisely quantifying them. On synthetic example, this approach is able to detect chemical compounds present in form of 100 hidden spectra out of 104, at 1.5 times the noise level. Results on simulated spectra of NOMAD-SO targeting CH4 show that detection limits goes in the range of 100-500 ppt in favorable conditions. Results on real martian data from NOMAD-SO show that CO2 and H2O are present, as expected, but CH4 is absent. Nevertheless, we confirm a set of new unexpected lines in the database, attributed by ACS instrument Team to the CO2 magnetic dipole.
Keywords: spectroscopy, atmosphere, data mining, machine learning, unsupervised, source separation, non-negative matrix factorization
Preprint submitted to Elsevier December 16, 2020
We propose here to focus on the Nadir and Occultation for MArs Discovery (NOMAD) instrument onboard ESA’s ExoMars Trace Gas Orbiter and especially the Solar Occultation (SO) channel (Vandaele et al., 2015). NOMAD is a compact, high-resolution, dual channel IR spectrometer (SO and LNO) coupled with a highly miniaturized UV-visible spectrometer (UVIS), capable of operating in different observation modes: solar occultation, nadir and limb. The SO channel operates at wavenumbers from 2320 cm−1 to 4550 cm−1
(wavelength 2.2 to 4.3 µm), using an echelle grating with a groove density of 4 lines/mm in a Littrow configuration in combination with an Acousto-Optic Tunable Filter (AOTF) for spectral order selection. The width of the selected spectral ranges is recorded by 320 spectels (spectral element) and varies from 20 to 35 cm−1 depending on the selected diffraction order. The detector is an actively cooled HgCdTe Focal Plane Array. SO achieves an instrument line profile resolution of 0.15 cm−1, corresponding to a resolving power λ/Δλ of approximately 25000. All details of the instrument are available in Neefs et al. 2015 and Vandaele et al. 2018. The orders with the maximum sensitivity to CH4 are: 119, 134 and 136. We will use the data from the beginning of the mission in April 2018 until 15 January 2020, in calibration version 1p0a. Due to temperature change, the spectral registration varies, producing a shift up to ∼10 spectels. We corrected it by aligning the full dataset to a reference spectra (arbitrarily choosen with the maximum band depth of water) by crosscorrelation. No sub-spectel resampling has been performed but a simple shift. When the calibration will be improved, this step will most probably be replaced by a routine correction. The data are available on the ESA/Planetary Science Archive after a 6 months embargo period.