Temperature regime and water/hydroxyl behavior in the crater Boguslawsky on the Moon

Wöhler, Christian; Grumpe, A.; Berezhnoy, A. A.; Феоктистова, Е. А.; Evdokimova, N. A.; Kapoor, K.; Шевченко, В. В.

doi:10.1016/j.icarus.2016.12.026

Cited by 29 publications

(34 citation statements)

References 68 publications

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“…Similarly, it is unclear how the reduction in UV photon flux that controls the photoionization loss of water competes with these two other effects. Although models have been suggested to explain some of these effects (Farrell et al, 2017;Jones et al, 2018;Tucker et al, 2019;Wöhler, Grumpe, Berezhnoy, Feoktistova, et al, 2017), there is no consensus on what controls the equilibrium abundance. Measuring the abundances of water across regions where at least one of these variables is controlled would provide insight into the mechanisms that produce surface water.…”

Section: Introductionmentioning

confidence: 99%

Surface Water at Lunar Magnetic Anomalies

Garrick‐Bethell

2019

Geophysical Research Letters

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The presence of water on the lunar surface has been confirmed by multiple Earth-based and orbital observations. However, the origins of this water and the factors that control its stability at different latitudes are still debated. Magnetic anomalies on the Moon systematically reduce solar wind flux while locally keeping other confounding variables constant, which provides a natural laboratory for understanding the contribution of solar wind to lunar surface water. We find that water mapped with Moon Mineralogy Mapper data exhibit strong suppressions at magnetic anomalies, indicating that reduced solar wind flux prevents the formation of water. Our results support the hypothesis that the solar wind contributes significantly to the presence of the lunar surface water. Future missions and studies focusing on how magnetic fields affect water production can provide essential clues about how surface water is formed on the Moon and other airless bodies. Plain Language SummaryThe presence of water and/or hydroxyl molecules on the Moon has been confirmed by multiple observations. However, the origins of the lunar surface water are still unknown. The water may arise from three possible origins: solar wind, impacts, and the lunar interior. Lunar magnetic anomalies provide a natural laboratory to assess which of the three sources may dominate. Strong magnetic fields can significantly reduce the energy and flux of solar wind particles reaching the surface while keeping other conditions unchanged, such as temperature and UV photon flux. In this study, we examined water maps derived from orbital data at magnetic anomalies across the lunar surface. We confirmed that the water content at anomalies is much lower than the surrounding regions, providing direct evidence that solar wind contributes substantially to the lunar surface water production. Future missions and studies may help quantify how magnetic fields affect the formation rate of water by solar wind implantation. These results may be important for understanding solar wind water formation on other airless bodies. Key Points:• The spatial correlation between 3-μm water absorption features from Moon Mineralogy Mapper (M 3 ) data and lunar lithospheric magnetic fields is assessed • Magnetic anomalies exhibit strong water suppressions that are not artifacts of thermal corrections • Strong suppression of water features at magnetic anomalies suggests that lunar surface water mostly originates from solar wind implantation Supporting Information:• Supporting Information S1

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Section: Introductionmentioning

confidence: 99%

Surface Water at Lunar Magnetic Anomalies

Garrick‐Bethell

2019

Geophysical Research Letters

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“…For a region in Mare Imbrium, the H 2 O/OH absorption depth has been found to decrease to a near-zero value, whereas in a highland region south of Mare Humboldtianum, the H 2 O/OH absorption depth decreases at midday to about 50% of its morning value ( 4 ). For the region around the lunar crater Boguslawsky located in the illuminated southern polar nearside highlands, the H 2 O/OH absorption strength has been found to decrease from a high level in the lunar morning to a lower but still nonzero level at midday ( 5 ). For estimation of the same method for surface temperature estimation and thermal emission removal as in this paper has been used in the study by Wöhler et al ( 5 ).…”

Section: Introductionmentioning

confidence: 99%

“…For the region around the lunar crater Boguslawsky located in the illuminated southern polar nearside highlands, the H 2 O/OH absorption strength has been found to decrease from a high level in the lunar morning to a lower but still nonzero level at midday ( 5 ). For estimation of the same method for surface temperature estimation and thermal emission removal as in this paper has been used in the study by Wöhler et al ( 5 ). For a few selected points on the lunar surface, Bandfield et al ( 6 ) found that the H 2 O/OH absorption band is present not only at high latitudes but also at low latitudes under both oblique and steep illumination.…”

Section: Introductionmentioning

confidence: 99%

Time-of-day–dependent global distribution of lunar surficial water/hydroxyl

et al. 2017

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“…We extracted band I and band II spectral parameters from a topographically and thermally corrected M 3 global mosaic constructed using a previously published framework (Wöhler et al 2014(Wöhler et al , 2017aGrumpe et al 2019). The level 1B M 3 radiance dataset with a spatial resolution of 140 m/pixel (Pieters et al 2009) has been resampled to a 20 pixels per degree (1.5 km/pixel at the equator) global mosaic.…”

Section: Methodsmentioning

confidence: 99%

Global mapping of lunar refractory elements: multivariate regression vs. machine learning

Bhatt

Wöhler²,

Grumpe³

et al. 2019

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Context. The quantitative estimation of elemental concentrations at the spatial resolution of hyperspectral near-infrared (NIR) images of the lunar surface is an important tool for understanding the processes relevant for the origin and evolution of the Moon. Aims. We aim to map the abundances of the elements Fe, Ca, and Mg at a typical accuracy of about 1 wt.% at the spatial resolution of the Moon Mineralogy Mapper (M3) instrument on-board Chandrayaan-1 lunar mission. Methods. The NIR reflectance of the lunar regolith is an integrated response to the presence of refractory elements and soil alteration processes. Our approach was to define a combination of spectral parameters that are robust with respect to the effects of soil maturity. We calibrated the spectral parameters with respect to elemental abundances measured by the Lunar Prospector Gamma Ray Spectrometer (LP GRS) and the Kaguya GRS (KGRS). For this purpose, we compared a classical multivariate linear regression (MLR) approach and the machine learning based support vector regression (SVR) technique applied to M3 global observations. Results. The M3-based global elemental maps are consistent in distribution and range with the LP GRS and KGRS elemental maps and do not show artifacts in immature areas such as small fresh craters. The results derived using MLR and SVR are compared to sample-based ground truth data of the Apollo and Luna sample-return sites, where the root-mean-square deviations obtained by the two regression models are similar. Conclusions. The main advantage of the proposed new algorithm is its ability to minimize artifacts due to space-weathering effects. The elemental maps of Mg and Ca provide additional information and reveal structures not always visible in the Fe map. The global elemental abundance maps derived for the fully calibrated M3 observations might thus serve as important tools to investigate the lunar geology and evolution.

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Temperature regime and water/hydroxyl behavior in the crater Boguslawsky on the Moon

Cited by 29 publications

References 68 publications

Surface Water at Lunar Magnetic Anomalies

Surface Water at Lunar Magnetic Anomalies

Time-of-day–dependent global distribution of lunar surficial water/hydroxyl

Global mapping of lunar refractory elements: multivariate regression vs. machine learning

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