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Enregistrement W3211180976 · doi:10.5194/epsc2021-388

Water-Ice Cloud Thermal Effects at the Phoenix Mission Landing Site

2021· article· en· W3211180976 sur OpenAlexaff
Grace Bischof, Brittney A. Cooper, John E. Moores

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiquePlanetary Science and Exploration
Établissements canadiensYork University
Organismes subventionnairesnon disponible
Mots-clésAtmosphere (unit)Atmospheric sciencesEnvironmental scienceMars Exploration ProgramAtmosphere of MarsPhoenixLongwaveSolar irradianceSnowMartianMartian surfaceRadiationAstrobiologyMeteorologyGeologyPhysicsGeographyOptics

Résumé

récupéré en direct d'OpenAlex

Introduction: On Mars, near-surface and ground temperatures undergo massive diurnal fluctuations. Amplitudes can surpass 70 K between the daily maximum and minimum temperatures [1]. Because Mars’ thin atmosphere is largely transparent to infrared radiation, the solar radiation from the sun and the outgoing longwave radiation from the surface are the primary drivers of the near-surface temperature [2]. However, the influence from the atmosphere is not entirely negligible. It is well known that dust in the atmosphere has a secondary, but measurable, effect on the temperature by scattering visible-band solar radiation and absorbing longwave radiation [3]. This atmospheric thermal effect is not only caused by dust; Water-ice clouds have a similar influence, where outgoing longwave radiation may be absorbed and reflected back toward the ground, resulting in a warming of the near-surface temperature [4]. This project will investigate the amount of flux reflected by water-ice clouds by calculating the thermal forcing at the Phoenix landing site.Background: The Phoenix mission landed in the Martian northern Arctic, at a latitude of 68.2°N in 2008. Phoenix operated for 151 sols, collecting data up to and through the northern summer solstice. About 60 sols into the mission, water-ice clouds were observed both by images taken by the Stereo Surface Imager (SSI) [5] and by backscatter detected using a light detecting and ranging (LIDAR) instrument onboard the lander [6]. On four occasions, by using the LIDAR and SSI together, surface-fog was detected [7]. In the second half of the mission, surface-based clouds formed nightly around 23:00 Local True Solar Time (LTST). By 01:00 LTST, a second clouds base formed at altitudes near 4 km. The clouds dissipated by the late morning, but were observed to linger as the mission progressed past summer solstice [8].Methods: Data for the near-surface air temperature are acquired from the Planetary Data System. Phoenix carried three thin-wire temperature sensors at heights of 1 m, 0.5 m, and 0.25 m off the deck of the lander, itself located 1 m above the surface. Temperature measurements were recorded every 2 s through the duration of a sol, with an approximately 20-minute break, usually occurring around midday. To determine the thermal impacts due to water-ice clouds, an energy balance at the surface is needed. Adapted from [9], the energy balance is given by where G is the net flux into the ground, S is the solar radiation, α is the surface albedo, LW↓ is the longwave radiation downwelling from the atmosphere, LW↑ is the longwave radiation emitted from the surfaced, H is the sensible heat flux, and L is the latent heat flux of water. R describes the additional longwave radiation downwelling from the atmosphere, which we attribute to water-ice clouds. R is maintained as an independent parameter which may be varied throughout a run of the model in 3 hour-intervals. With this energy balance, a subsurface conduction model is used to find the surface temperature at the Phoenix site. At each timestep, the surface temperature is coupled to the air temperature bywhere the terms are described in [9]. The modelled air temperatures are plotted against the air temperature data collected by Phoenix to evaluate the additional flux reflected by clouds (given by R) that is needed for the model to match the data collected in situ.Results and Discussion: Figure 1(a) shows the modelled temperaure plotted against the Phoenix data for sol 3 of the mission. During the midday, R = 0 W m-2 implying there is no flux reflected from water-ice clouds. Moving into the evening, R = 5 W m-2 starting at 21:00 LTST. This increases to 8 W m-2 by 00:00 LTST. At 03:00 LTST, the reflected flux drops back down to 5 W m-2, and is back to 0 W m-2 by 06:00 LTST. This additional flux is not a dominant energy term, as shown in Figure 1(b), but a resulting temperature increase of 2 K is seen. This analysis suggests that clouds were present at the Phoenix landing site earlier than they were detected in images or LIDAR data products. Moving forward, the amount of flux reflected by water-ice clouds will be determined for each sol of the misson. This will show how the reflected flux evolves diurnally – particularly through the nighttime – and as the mission progressed past summer solstice.References:[1] Martínez G.M. et al (2017) Space Sci Rev, 212, 295–338.[2] Savijärvi H. (2014) Icarus, 242, 105–111.[3] Guzewich S.D. et al (2019) Geophys. Res. Lett., 46, 71–79.[4] Wilson R.J. (2007) Geophys. Res. Lett., 34.[5] Moores J.E. et al (2010) JGR: Planets, 115.[6] Whiteway J.A. et al (2009) Science, 325, 68–70.[7] Moores J.E. et al (2011) Geophys. Res. Lett., 38.[8] Dickinson C. et al (2010) Geophys. Res. Lett., 37.[9] Martínez G.M. et al (2014) JGR: Planets, 119, 1822–1838.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,052
Score d'incertitude au seuil0,103

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,010
Tête enseignante GPT0,215
Écart entre enseignants0,205 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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