Acceleration‐Related Glitch Patterns in Apollo Seismic Data and Implications for Future Lunar Seismic Observation.
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| Title: | Acceleration‐Related Glitch Patterns in Apollo Seismic Data and Implications for Future Lunar Seismic Observation. |
|---|---|
| Authors: | Liu, Xin1,2 (AUTHOR), Xiao, Zhuowei1,2 (AUTHOR), Li, Juan1,2,3 (AUTHOR) juanli@mail.iggcas.ac.cn |
| Source: | Journal of Geophysical Research. Planets. Oct2025, Vol. 130 Issue 10, p1-21. 21p. |
| Subject Terms: | *Seasonal temperature variations, Sunrise & sunset, Moon, Measurement uncertainty (Statistics), Space flight to the moon, Sensor placement, Seismic surveys, Deep learning |
| Company/Entity: | Apollo program (U.S.) |
| Abstract: | Apollo seismic data have significantly advanced our understanding of the Moon's internal structure and seismic activity. Beyond these scientific insights, the data also contain numerous glitches caused by the harsh lunar environment. Characterizing these glitches is crucial for improving future lunar seismic observations, which is particularly timely and important given upcoming lunar missions carrying new seismometer payloads. In this study, we combined deep learning and template matching to identify and catalog acceleration‐related glitches in the Apollo seismic data, revealing distinct temporal patterns correlated with lunar diurnal and seasonal cycles. Concentrations of glitches near lunar sunrise and sunset are likely caused by rapid temperature variations. Daytime glitches are associated with shadows cast by nearby objects or lunar eclipses. We also detect elliptically polarized glitches, differing from the linear polarization typical of Martian glitches and warranting further investigation. Our glitch catalogs reveal significantly fewer glitches during lunar nighttime compared to daytime, providing valuable insights for optimizing observation timing. Furthermore, variations in daytime glitch patterns across stations highlight the significant impact of station location and instrument deployment on data quality, demanding careful consideration in future lunar missions. In summary, this study compiles acceleration‐related glitch catalogs from Apollo seismic data, enhancing our understanding of the impacts of the lunar environment on seismic observations and providing valuable references for optimizing seismic observation strategies and instrument deployment in upcoming lunar missions. Plain Language Summary: The Apollo seismic data greatly advanced our understanding of the Moon's internal structure. However, the harsh lunar environment also produced numerous brief, transient, and often repetitive signals, generally referred to as "glitches." These glitches offer valuable lessons for the design and deployment of future lunar seismic experiments, yet they remain incompletely understood. In this study, we used a combination of deep learning and template matching to identify and catalog acceleration‐related glitches in the Apollo seismic data. We discovered that glitches often occur around lunar sunrise and sunset due to rapid surface temperature changes. Aside from the lunar sunrise and sunset, additional glitches are linked to moving shadows from nearby objects or lunar eclipses, while glitch activity during lunar night is significantly lower. We also observed a group of glitches with elliptical polarization, differing from the linearly polarized ones seen in Martian data. Furthermore, the number and type of glitches vary by station, showing that instrument placement and environmental conditions strongly affect data quality. Our results contribute to the understanding of Apollo seismic data and provide a guide for optimizing seismometer deployment and observation schedules in future lunar seismic missions. Key Points: We compiled acceleration‐related glitch catalogs from Apollo seismic data from 1969 to 1977 via deep clustering and matrix profileGlitch patterns mainly relate to drastic temperature shifts triggered by lunar sunrise, sunset, nearby shadows, and even lunar eclipsesProvides valuable references for optimizing observation timing and deployment strategies in future lunar seismic observations [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Geophysical Research. Planets is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 188963863 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Acceleration‐Related Glitch Patterns in Apollo Seismic Data and Implications for Future Lunar Seismic Observation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Liu%2C+Xin%22">Liu, Xin</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xiao%2C+Zhuowei%22">Xiao, Zhuowei</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Juan%22">Li, Juan</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> juanli@mail.iggcas.ac.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Geophysical+Research%2E+Planets%22">Journal of Geophysical Research. Planets</searchLink>. Oct2025, Vol. 130 Issue 10, p1-21. 21p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Seasonal+temperature+variations%22">Seasonal temperature variations</searchLink><br /><searchLink fieldCode="DE" term="%22Sunrise+%26+sunset%22">Sunrise & sunset</searchLink><br /><searchLink fieldCode="DE" term="%22Moon%22">Moon</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement+uncertainty+%28Statistics%29%22">Measurement uncertainty (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Space+flight+to+the+moon%22">Space flight to the moon</searchLink><br /><searchLink fieldCode="DE" term="%22Sensor+placement%22">Sensor placement</searchLink><br /><searchLink fieldCode="DE" term="%22Seismic+surveys%22">Seismic surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink> – Name: SubjectCompany Label: Company/Entity Group: Su Data: <searchLink fieldCode="DE" term="%22Apollo+program+%28U%2ES%2E%29%22">Apollo program (U.S.)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Apollo seismic data have significantly advanced our understanding of the Moon's internal structure and seismic activity. Beyond these scientific insights, the data also contain numerous glitches caused by the harsh lunar environment. Characterizing these glitches is crucial for improving future lunar seismic observations, which is particularly timely and important given upcoming lunar missions carrying new seismometer payloads. In this study, we combined deep learning and template matching to identify and catalog acceleration‐related glitches in the Apollo seismic data, revealing distinct temporal patterns correlated with lunar diurnal and seasonal cycles. Concentrations of glitches near lunar sunrise and sunset are likely caused by rapid temperature variations. Daytime glitches are associated with shadows cast by nearby objects or lunar eclipses. We also detect elliptically polarized glitches, differing from the linear polarization typical of Martian glitches and warranting further investigation. Our glitch catalogs reveal significantly fewer glitches during lunar nighttime compared to daytime, providing valuable insights for optimizing observation timing. Furthermore, variations in daytime glitch patterns across stations highlight the significant impact of station location and instrument deployment on data quality, demanding careful consideration in future lunar missions. In summary, this study compiles acceleration‐related glitch catalogs from Apollo seismic data, enhancing our understanding of the impacts of the lunar environment on seismic observations and providing valuable references for optimizing seismic observation strategies and instrument deployment in upcoming lunar missions. Plain Language Summary: The Apollo seismic data greatly advanced our understanding of the Moon's internal structure. However, the harsh lunar environment also produced numerous brief, transient, and often repetitive signals, generally referred to as "glitches." These glitches offer valuable lessons for the design and deployment of future lunar seismic experiments, yet they remain incompletely understood. In this study, we used a combination of deep learning and template matching to identify and catalog acceleration‐related glitches in the Apollo seismic data. We discovered that glitches often occur around lunar sunrise and sunset due to rapid surface temperature changes. Aside from the lunar sunrise and sunset, additional glitches are linked to moving shadows from nearby objects or lunar eclipses, while glitch activity during lunar night is significantly lower. We also observed a group of glitches with elliptical polarization, differing from the linearly polarized ones seen in Martian data. Furthermore, the number and type of glitches vary by station, showing that instrument placement and environmental conditions strongly affect data quality. Our results contribute to the understanding of Apollo seismic data and provide a guide for optimizing seismometer deployment and observation schedules in future lunar seismic missions. Key Points: We compiled acceleration‐related glitch catalogs from Apollo seismic data from 1969 to 1977 via deep clustering and matrix profileGlitch patterns mainly relate to drastic temperature shifts triggered by lunar sunrise, sunset, nearby shadows, and even lunar eclipsesProvides valuable references for optimizing observation timing and deployment strategies in future lunar seismic observations [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Geophysical Research. Planets is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1029/2025JE009277 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 1 Subjects: – SubjectFull: Seasonal temperature variations Type: general – SubjectFull: Sunrise & sunset Type: general – SubjectFull: Moon Type: general – SubjectFull: Measurement uncertainty (Statistics) Type: general – SubjectFull: Space flight to the moon Type: general – SubjectFull: Sensor placement Type: general – SubjectFull: Seismic surveys Type: general – SubjectFull: Deep learning Type: general – SubjectFull: Apollo program (U.S.) Type: general Titles: – TitleFull: Acceleration‐Related Glitch Patterns in Apollo Seismic Data and Implications for Future Lunar Seismic Observation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liu, Xin – PersonEntity: Name: NameFull: Xiao, Zhuowei – PersonEntity: Name: NameFull: Li, Juan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 21699097 Numbering: – Type: volume Value: 130 – Type: issue Value: 10 Titles: – TitleFull: Journal of Geophysical Research. Planets Type: main |
| ResultId | 1 |
