Examining Cloud Properties at Gale Crater with MSL and TGO/CaSSIS
Notice bibliographique
Résumé
The Mars Science Laboratory (MSL) has been observing clouds around Gale Crater since its landing in 2012 (MY 31). While MSL takes a number of different cloud observations, the Zenith and Suprahorizon Movies (ZM & SHM) are notable for being captured since nearly the start of the mission at all times of year and throughout the sunlit hours. These observations have been used to characterize the clouds’ variability, behaviour, altitudes and various scattering properties including opacity [E.g. 1,2,3,4]. Cloud opacities over Gale show very little interannual or diurnal variability, especially during the Aphelion Cloud Belt (ACB) season, a repeated yearly period of increased water-ice cloud formation around Mars aphelion [4].MSL-derived cloud opacities have been compared with water-ice cloud opacity retrievals from MARCI on board the Mars Reconnaissance Orbiter (MRO) and EXI on board the Emirates Mars Mission [4]. However, both instruments have very large fields of view, and MRO’s sun-synchronous orbit means that it only captures images at the same time of day. Our goal is to derive opacities from another orbital dataset using cloud images from the Colour and Stereo Surface Imaging System (CaSSIS) and examine and compare cloud properties at Gale Crater.CaSSIS is the main imaging system of the ExoMars Trace Gas Orbiter (TGO). It takes colour-infrared images from an altitude of ~400 km at a resolution of ~4 m/px using four broadband filters spanning 400-1100 nm. The images may be up to ~9.5 km wide and ~50 km long [5]. As TGO is not in a sun-synchronous orbit, it is able to capture images at various times of day and a wider range of incidence and phase angles. Its high resolution enables us to easily determine the size and spacing of the cloud features we observe from the ground with MSL. From the spacings for these features, an altitude may be inferred, something we attempt to constrain from the ground with MSL [2].Figure 1: Temporal distribution of MSL cloud movies and CaSSIS images acquired over Gale Crater. Note that not all observations contain clouds.We are examining the nearly 75 images taken by CaSSIS over Gale Crater for the presence of clouds. From these images we can derive the cloud opacities and compare these values with those previously derived from surface observations by MSL [4]. We are also interested in comparing images taken both from the surface and from orbit at near the same time. Additionally, as the ACB season is the best time of year to reliably capture cloud images, we intend to image the Gale Crater area with CaSSIS in hopes of coordinating with MSL cloud movies. [1] J. E. Moores et al., “Atmospheric movies acquired at the Mars Science Laboratory landing site: Cloud morphology, frequency and significance to the Gale Crater water cycle and Phoenix mission results,” Advances in Space Research, vol. 55, no. 9, pp. 2217–2238, 2015, doi: 10.1016/j.asr.2015.02.007.[2] C. L. Campbell et al., “Estimating the altitudes of Martian water-ice clouds above the Mars Science Laboratory rover landing site,” Planetary and Space Science, vol. 182, p. 104785, Mar. 2020, doi: 10.1016/j.pss.2019.104785.[3] A. C. Innanen, C. W. Hayes, B. E. Koch Nichol, and J. E. Moores, “Four Mars Years of ACB Phase Function Observations from the Mars Science Laboratory Show Low Interannual and Diurnal Variability and Suggest Irregular Water–ice Crystal Geometry,” Icarus, vol. 429, p. 116437, Mar. 2025, doi: 10.1016/j.icarus.2024.116437.[4] C. W. Hayes, J. L. Kloos, A. C. Innanen, C. L. Campbell, H. M. Sapers, and J. E. Moores, “Five Mars Years of Cloud Observations at Gale Crater: Opacities, Variability, and Ice Crystal Habits,” Planet. Sci. J., vol. 5, no. 2, p. 51, Feb. 2024, doi: 10.3847/PSJ/ad2202.[5] N. Thomas et al., “The Colour and Stereo Surface Imaging System (CaSSIS) for the ExoMars Trace Gas Orbiter,” Space Sci Rev, vol. 212, no. 3, pp. 1897–1944, Nov. 2017, doi: 10.1007/s11214-017-0421-1.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».