Automated Detection and Climatological Analysis of Ripple-Scale Gravity Wave Instabilities Using a Squeeze-and-Excitation Convolutional Neural Network
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| Format: | Recurso digital |
| Langue: | anglais |
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2026
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| _version_ | 1866901522069061632 |
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| author | Jiahui, Hu |
| author_facet | Jiahui, Hu |
| contents | <p>This dataset contains the manually labeled ripple training dataset and the derived automated ripple event catalog used in:</p> <blockquote> <p>Hu et al., <em>Automated Detection and Climatological Analysis of Ripple-Scale Gravity Wave Instabilities Using a Squeeze-and-Excitation Convolutional Neural Network</em>, Submitted to EGU Atmospheric Measurement Techniques.</p> </blockquote> <p>The dataset supports reproducible machine-learning-based detection of ripple-scale gravity wave instabilities observed in mesospheric OH airglow imagery over Yucca Ridge Field Station (YRFS), Colorado (40.7°N, 104.9°W).</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18927628 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Automated Detection and Climatological Analysis of Ripple-Scale Gravity Wave Instabilities Using a Squeeze-and-Excitation Convolutional Neural Network Jiahui, Hu Machine Learning/classification Atmospheric science <p>This dataset contains the manually labeled ripple training dataset and the derived automated ripple event catalog used in:</p> <blockquote> <p>Hu et al., <em>Automated Detection and Climatological Analysis of Ripple-Scale Gravity Wave Instabilities Using a Squeeze-and-Excitation Convolutional Neural Network</em>, Submitted to EGU Atmospheric Measurement Techniques.</p> </blockquote> <p>The dataset supports reproducible machine-learning-based detection of ripple-scale gravity wave instabilities observed in mesospheric OH airglow imagery over Yucca Ridge Field Station (YRFS), Colorado (40.7°N, 104.9°W).</p> |
| title | Automated Detection and Climatological Analysis of Ripple-Scale Gravity Wave Instabilities Using a Squeeze-and-Excitation Convolutional Neural Network |
| topic | Machine Learning/classification Atmospheric science |
| url | https://doi.org/10.5281/zenodo.18927628 |