Earth and Space Science最新文献

筛选
英文 中文
Analyzing the Inversion Performance of a Permanent Urban Column GHG Network: An OSSE Perspective 基于OSSE视角的永久城市柱状温室气体网络反演性能分析
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-27 DOI: 10.1029/2024EA004175
Jun Zhang, Jia Chen, Kai Wu, Haoyue Tang
{"title":"Analyzing the Inversion Performance of a Permanent Urban Column GHG Network: An OSSE Perspective","authors":"Jun Zhang,&nbsp;Jia Chen,&nbsp;Kai Wu,&nbsp;Haoyue Tang","doi":"10.1029/2024EA004175","DOIUrl":"https://doi.org/10.1029/2024EA004175","url":null,"abstract":"<p>Observations of atmospheric columns offer an effective approach to monitoring greenhouse gas (GHG) emissions, as they are less sensitive to the dynamics of atmospheric transport in comparison to in situ measurements. MUCCnet, the world's first permanent urban ground-based column network, has been utilized as an innovative method for measuring column GHGs. We present here an observing system simulation experiment framework to characterize the behavior of this unique network in estimating urban CO<sub>2</sub> emissions. An assumed in situ tower-based network (AISTnet) is performed to improve our understanding of MUCCnet's observing performance. We conduct a set of Bayesian atmospheric inversions to validate the current network deployment strategy and analyze its sensitivity to large point sources (LPSs). From our base inversions, we found overall good consistency between MUCCnet and AISTnet inversions, with nearly all grid cells showing corrections in the same direction during the inversions. While the sensitivities of in situ CO<sub>2</sub> synthetic observations are approximately an order of magnitude higher than those of column measurements, the column measurements have the advantage of broader coverage. This leads to larger uncertainty reduction around the site locations in the AISTnet inversions, while the MUCCnet inversions present larger values over the area away from the network. The inaccurate information of the LPSs provided in the prior estimate can adversely impact the estimated emissions. Our results suggest that MUCCnet is less sensitive to LPSs errors compared to AISTnet. The findings of this work can contribute valuable insights for advancing future observing strategies in an urban environment.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA004175","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multi-Spectral Field Study of Planetary Analog Material in Extreme Environments—Alteration Products of Volcanic Deposits of Vulcano/Italy 极端环境下行星模拟物质的多光谱场研究——意大利Vulcano火山沉积物蚀变产物
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-27 DOI: 10.1029/2024EA004036
K. Stephan, K. Rammelkamp, M. Baqué, S. Schröder, A. Pisello, K. Gwinner, G. Ortenzi, P. Irmisch, F. Sohl, V. Unnithan
{"title":"Multi-Spectral Field Study of Planetary Analog Material in Extreme Environments—Alteration Products of Volcanic Deposits of Vulcano/Italy","authors":"K. Stephan,&nbsp;K. Rammelkamp,&nbsp;M. Baqué,&nbsp;S. Schröder,&nbsp;A. Pisello,&nbsp;K. Gwinner,&nbsp;G. Ortenzi,&nbsp;P. Irmisch,&nbsp;F. Sohl,&nbsp;V. Unnithan","doi":"10.1029/2024EA004036","DOIUrl":"https://doi.org/10.1029/2024EA004036","url":null,"abstract":"<p>The potential of multi-spectral investigations for planetary exploration strongly depends on the specific geologic environment and related science questions. In this work, we used a visible-near infrared spectrometer, a laser-induced breakdown spectroscopy (LIBS) instrument, and a Raman spectrometer for studying acid alteration of volcanic deposits in the field as an analog for what can be potentially observed on Mars. These deposits were studied on Vulcano, one of the Aeolian Islands/Italy, where volcanic deposits are affected by active hydrothermal alteration processes and fumarolic activity. The results show that VIS-NIR spectroscopy is sufficient to identify the major minerals formed through the alteration process. This is the only technique that can identify and characterize hydrated silica, the major alteration residue, whose spectral properties vary depending on environmental conditions and the formation process. However, only LIBS spectra allow a detailed insight into the geochemistry of the pristine volcanic deposits, which is needed to define the starting point of the alteration process. LIBS also indicated the existence of chemical elements for which no corresponding mineral could be identified in the VIS-NIR data, presumably since their spectral signature is masked by strongly absorbing species. These minerals, however, could be confirmed in the Raman spectra—nicely completing the achieved results and highlighting the high potential of the sensor suite for our study.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA004036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Retrospective Mapping of Global Snow and Ice Cover Beyond the Satellite Observational Era 卫星观测时代以后全球冰雪覆盖回顾制图
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-26 DOI: 10.1029/2024EA004171
Kingsley K. Kumah, Omid Zandi, Ali Behrangi
{"title":"Retrospective Mapping of Global Snow and Ice Cover Beyond the Satellite Observational Era","authors":"Kingsley K. Kumah,&nbsp;Omid Zandi,&nbsp;Ali Behrangi","doi":"10.1029/2024EA004171","DOIUrl":"https://doi.org/10.1029/2024EA004171","url":null,"abstract":"<p>Monitoring Earth's snow and ice cover is essential for diverse applications, including climate studies, hydrological forecasting, and precipitation mapping. This study develops and evaluates methodologies to extend the Global Multisensor Automated Snow and Ice Mapping System (GMASI) records prior to its July 1987 inception, reconstructing high-resolution global snow and ice cover data. Using ERA5 reanalysis variables, three machine learning (ML) approaches—ML-E (ML with ERA5 predictors only), ML-EC (ML with ERA5 and Climatology-based predictors), and ML-ECC (ML with ERA5 predictors, Climatology-based predictors, and additional Consistency Checks)—were tested alongside climatological and fractional cover-based methods. Validation against GMASI (1988–1991) shows that ML-EC and ML-ECC achieve superior alignment, with the latter offering marginal accuracy gains. Both methods demonstrated stable daily estimates, with mean percentage biases for snow and ice cover remaining below 3% during validation. Their high accuracy is further reflected in probabilities of detection (POD) exceeding 97% across key surface types. Across all methods, there was a general tendency to underestimate snow-free areas and overestimate snow-covered regions in the Northern Hemisphere, while classification challenges in the Southern Hemisphere were more pronounced over snow-free land and Antarctic sea ice. The ML-EC approach was subsequently applied to extend the GMASI record back to 1980, capturing seasonal and interannual variability consistent with GMASI-era trends. These results underscore the potential of ML techniques to extend snow and ice cover records as far back as the beginning of the reanalysis era (1940–present), providing invaluable insights for climate analysis and operational applications.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA004171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Global Distribution of Low Frequency Family Marsquakes From Deep-Learning-Based Polarization Estimation 基于深度学习极化估计的低频族震全球分布
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-26 DOI: 10.1029/2025EA004303
Quanhong Li, Zhuowei Xiao, Jinlai Hao, Juan Li
{"title":"Global Distribution of Low Frequency Family Marsquakes From Deep-Learning-Based Polarization Estimation","authors":"Quanhong Li,&nbsp;Zhuowei Xiao,&nbsp;Jinlai Hao,&nbsp;Juan Li","doi":"10.1029/2025EA004303","DOIUrl":"https://doi.org/10.1029/2025EA004303","url":null,"abstract":"<p>The seismometer has recorded thousands of marsquakes. Accurately locating these events is crucial for understanding Mars' internal structure and geological evolution. With only a single station, determining the location, especially the accurate back-azimuth, is more challenging than on Earth. Deep learning, being data-driven, can learn patterns of complex noise that are difficult for traditional methods to model, making it promising for improving back-azimuth estimation of marsquakes. However, challenges arise when applying deep learning to estimate marsquake polarization due to the limited quantity and low signal-to-noise ratios (SNR) of the data. In this study, we trained deep learning models for learning the noise patterns preceding marsquakes to address these challenges. By combining the proposed Sliding Window Inference and Featured-Training (SWIFT) to handle the high uncertainty in P phase picking, we are able to estimate polarizations of low frequency family marsquakes with improved accuracy. As a result, we have further improved the localization of marsquakes by relocating 56 events, including seven Quality C events with epicentral distances over 90°. For two Martian impact events with ground-truth locations, S1000a and S1094b, our deviations are only ∼5.65° and ∼2.72°. Our results reveal a new identified clustered seismicity zone around compressional structures in Hesperia Planum, including seven marsquakes with magnitudes from 2.7 to 3.6. Marsquakes are also widely distributed along the northern lowlands, the dichotomy boundary, and the higher-latitude southern highlands, suggesting a globally distributed pattern. Our renewed marsquake locations provide new insights into the tectonic interpretation of marsquakes.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004303","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Collaborative and Reproducible Planetary Science Through the Europlanet GMAP JupyterHub Processing Environment 通过Europlanet GMAP JupyterHub处理环境的协作和可复制行星科学
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-23 DOI: 10.1029/2025EA004251
G. Nodjoumi, C. H. Brandt, J. E. Suárez-Valencia, E. Luzzi, M. Valiante, A. P. Rossi
{"title":"Collaborative and Reproducible Planetary Science Through the Europlanet GMAP JupyterHub Processing Environment","authors":"G. Nodjoumi,&nbsp;C. H. Brandt,&nbsp;J. E. Suárez-Valencia,&nbsp;E. Luzzi,&nbsp;M. Valiante,&nbsp;A. P. Rossi","doi":"10.1029/2025EA004251","DOIUrl":"https://doi.org/10.1029/2025EA004251","url":null,"abstract":"<p>JupyterHub is an open-source system enabling multiple users to access individual computational environments. This facilitates collaborative development and execution of Jupyter notebooks, Python scripts, and other tools among researchers and educators through a unified interface. Through the integration of container technologies, including Docker, JupyterHub achieves seamless scalability for numerous users while maintaining efficient computational resource management. This flexible approach is especially useful in specialized areas like planetary data science, which requires robust and reproducible workflows to manage large volumes of mission data. The Europlanet Geologic MApping of Planetary surfaces (GMAP) project employs a Docker-based JupyterHub deployment to centralize essential data processing tools, such as the Integrated Software for Imagers and Spectrometers (ISIS) and the NASA Ames Stereo Pipeline (ASP). These open-source tools facilitate tasks ranging from image calibration and map projection to stereogrammetry and 3D modeling. The deployment of these elements within Docker containers facilitates simplified installation and consistent performance across disparate hardware configurations. The use of pre-configured image formats within ISIS, ASP, and other GIS and Python libraries allows planetary scientists to efficiently process raw data into analytical products, including Digital Terrain Models. Additionally, JupyterHub's architecture enables secure collaboration via authentication methods (e.g., OAuth, GitHub), with concurrent provision for private and shared data directories. This integrated framework promotes reproducible research by streamlining the sharing of scripts, notebooks, and workflows. The GMAP JupyterHub platform significantly accelerates scientific discovery through the reduction of technical barriers, the promotion of standardization, and the provision of global access to planetary data science resources.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004251","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Improving OCO-2 X C O 2 ${X}_{{mathbf{C}mathbf{O}}_{mathbf{2}}}$ Retrievals Through the Scaling of Singular Value Decomposition-Based Temperature and Water Vapor Profiles 基于奇异值分解的OCO-2 X C o2 ${X}_{{mathbf{C}mathbf{O}}_{mathbf{2}}}$检索改进
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-23 DOI: 10.1029/2024EA003975
R. R. Nelson, S. S. Kulawik, C. W. O’Dell, J. McDuffie, A. Eldering
{"title":"Improving OCO-2 \u0000 \u0000 \u0000 \u0000 X\u0000 \u0000 \u0000 C\u0000 O\u0000 \u0000 2\u0000 \u0000 \u0000 \u0000 ${X}_{{mathbf{C}mathbf{O}}_{mathbf{2}}}$\u0000 Retrievals Through the Scaling of Singular Value Decomposition-Based Temperature and Water Vapor Profiles","authors":"R. R. Nelson,&nbsp;S. S. Kulawik,&nbsp;C. W. O’Dell,&nbsp;J. McDuffie,&nbsp;A. Eldering","doi":"10.1029/2024EA003975","DOIUrl":"https://doi.org/10.1029/2024EA003975","url":null,"abstract":"&lt;p&gt;NASA's Orbiting Carbon Observatory-2 (OCO-2) has the goal of accurately estimating column-averaged dry-air mole fractions of carbon dioxide (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;X&lt;/mi&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mi&gt;O&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${X}_{{mathrm{C}mathrm{O}}_{mathrm{2}}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;). In order to fit the measured radiances, many parameters besides &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{mathrm{2}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; are included in the optimal estimation state vector, including atmospheric water vapor and temperature. The current operational &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;X&lt;/mi&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mi&gt;O&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${X}_{{mathrm{C}mathrm{O}}_{mathrm{2}}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; retrieval algorithm (v11) solves for a multiplicative scaling factor on an a priori water vapor profile and an additive offset on an a priori temperature profile. However, simulations have indicated that water vapor and temperature each have 1.5–3 degrees of freedom in the vertical column. This means that the retrieval is limited in its ability to fit the true profiles of temperature and water vapor. Here, we use singular value decomposition to determine the three most explanatory profile “shapes” of water vapor and temperature error, then retrieve a single scaling factor applied to each shape. We assess retrieval errors by comparing to the Total Carbon Column Observing Network (TCCON) and multiple atmospheric &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{mathrm{2}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; inverse models. We find that after applying quality filtering using Data Ordering Genetic Optimization and a custom bias correction, the scatter o","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003975","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identification of the Atmospheric Vortex Shedding Behind the Jeju Island Based on MODIS and ERA5 Data 基于MODIS和ERA5数据的济州岛后方大气涡脱落识别
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-22 DOI: 10.1029/2024EA004022
Chaoyue Wu, Daoyi Chen, Shengli Chen, Yuqi Zhang, Qiao Su, Yihan Zhang
{"title":"Identification of the Atmospheric Vortex Shedding Behind the Jeju Island Based on MODIS and ERA5 Data","authors":"Chaoyue Wu,&nbsp;Daoyi Chen,&nbsp;Shengli Chen,&nbsp;Yuqi Zhang,&nbsp;Qiao Su,&nbsp;Yihan Zhang","doi":"10.1029/2024EA004022","DOIUrl":"https://doi.org/10.1029/2024EA004022","url":null,"abstract":"<p>A fascinating phenomenon often occurs as pairs of vortices in two rows on the leeward of some islands. The satellite remote sensing has been a major facilitator to observe this phenomenon. In this study, we conduct a statistical analysis on the occurrence of vortex street by processing 20-year cloud images from the MODIS remote sensing data around Jeju Island in the northwest of Pacific Ocean. The criteria for forming an atmospheric vortex shedding (VS) are also discussed with ERA5 hourly data. The results indicate that the steady upstream flow reaching a certain speed under a strong temperature inversion is beneficial to the formation of VS. Based on the speed of upstream flow and the intensity of temperature inversion which are selected by machine learning methods, fitting lines are constructed to predict the occurrence of vortices, with an accuracy of more than 98%. This fitting relation can probably be used to parameterize the small-scale VS behind mountains in the meso-scale atmosphere simulation system to improve its accuracy.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA004022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identification of Natural Hydrogen Seeps: Leveraging AI for Automated Classification of Sub-Circular Depressions 天然氢气渗漏的识别:利用人工智能对亚循环凹陷进行自动分类
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-21 DOI: 10.1029/2025EA004227
N. Ginzburg, J. Daynac, S. Hesni, U. Geymond, V. Roche
{"title":"Identification of Natural Hydrogen Seeps: Leveraging AI for Automated Classification of Sub-Circular Depressions","authors":"N. Ginzburg,&nbsp;J. Daynac,&nbsp;S. Hesni,&nbsp;U. Geymond,&nbsp;V. Roche","doi":"10.1029/2025EA004227","DOIUrl":"https://doi.org/10.1029/2025EA004227","url":null,"abstract":"<p>Hydrogen has long been used as an energy vector, but the recent discovery of natural hydrogen (H<sub>2</sub>) opens the door for its use as a direct energy source. Identifying H<sub>2</sub> seepages is therefore crucial to advance exploration. Although the scientific community does not yet fully understand the parameters controlling H<sub>2</sub> leaks from underground, sub-circular depressions (SCDs) appear to be key indicators associated with these emissions. However, distinguishing SCDs from similar landforms remains a challenge. This study leverages open-source multispectral and high-resolution imagery to train a deep learning model (YOLOv8) for classifying rounded landforms and detecting H<sub>2</sub>-related structures (i.e., SCDs). The model achieved 90% accuracy with Google Maps© imagery, outperforming Sentinel-2 multispectral data. Applied to a pre-existing data set from Brazil, the model allowed a large-scale screening, discarding 52% of the structures as non-H<sub>2</sub> emitting ones and pinpointing high-potential areas for field validation. Future enhancements, including, for example, higher-resolution input data and morphometric analysis, would aim to reduce false positives and boost predictive accuracy. This approach significantly improves H<sub>2</sub> exploration efficiency, with global applicability including some region-specific adjustments during post-processing analyses.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004227","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adaptive Super-Resolution for Ocean Bathymetric Maps Using a Deep Neural Network and Data Augmentation 基于深度神经网络和数据增强的海洋水深图自适应超分辨率
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-19 DOI: 10.1029/2024EA003610
Koshiro Murakami, Daisuke Matsuoka, Naoki Takatsuki, Mitsuko Hidaka, Junji Kaneko, Yukari Kido, Eiichi Kikawa
{"title":"Adaptive Super-Resolution for Ocean Bathymetric Maps Using a Deep Neural Network and Data Augmentation","authors":"Koshiro Murakami,&nbsp;Daisuke Matsuoka,&nbsp;Naoki Takatsuki,&nbsp;Mitsuko Hidaka,&nbsp;Junji Kaneko,&nbsp;Yukari Kido,&nbsp;Eiichi Kikawa","doi":"10.1029/2024EA003610","DOIUrl":"https://doi.org/10.1029/2024EA003610","url":null,"abstract":"<p>Machine learning-based image super-resolution is a robust approach for obtaining detailed bathymetric maps. However, in machine learning using supervised data, dissimilarities in the features of training and target data sets degrades super-resolution performance. In this study, we propose a two-step method to generate training data with features similar to those of the target data using image transformation and composition. The super-resolution model trained using the proposed method on the Central Okinawa Trough data was applied to the bathymetry data around Okinotorishima Islands. The method improved the root mean squared error by up to 14.3% without compromising spatial consistency compared with that observed using conventional approaches, thus demonstrating the potential of combining artificial data generation with machine learning for super-resolution bathymetry mapping of the entire ocean floor. The proposed method, independent of the characteristics of training data, is suggested as a potential alternative to acoustic measurements for expanding areas of detailed bathymetric maps.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003610","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Gap Flows in Nares Strait: Multi-Scale Numerical Model Simulations in Comparison to Aircraft Measurements 纳尔斯海峡的间隙流:多尺度数值模式模拟与飞机测量的比较
IF 2.9 3区 地球科学
Earth and Space Science Pub Date : 2025-05-15 DOI: 10.1029/2024EA003912
Svenja H. E. Kohnemann, Günther Heinemann
{"title":"Gap Flows in Nares Strait: Multi-Scale Numerical Model Simulations in Comparison to Aircraft Measurements","authors":"Svenja H. E. Kohnemann,&nbsp;Günther Heinemann","doi":"10.1029/2024EA003912","DOIUrl":"https://doi.org/10.1029/2024EA003912","url":null,"abstract":"<p>The steep topography of Ellesmere Island and the northern Greenland coast, combined with a stable boundary layer, generates intense low-level winds in Nares Strait, that influence sea ice transport. In Smith Sound, a gap flow forms impacting the most productive North Water Polynya. We use the non-hydrostatic regional climate model CCLM with horizontal resolutions of 14, 5 and 1 km to study these processes for the period of an aircraft-based experiment in June 2010. Additionally, CARRA reanalysis is included. All model data resolve the small channel and represent the stable boundary conditions realistically. The highest winds of around 14 m <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mi>s</mi>\u0000 <mrow>\u0000 <mo>−</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> ${mathrm{s}}^{-1}$</annotation>\u0000 </semantics></math> are present in the exit region of Smith Sound for June 2010. Comparisons with aircraft profiles for potential temperature and wind speed show small biases and correlations higher than 0.84 for CCLM, along with a good representation of the boundary layer structure. Increasing model resolution from 14 to 5 km yields notable improvements in the representation of these variables. CARRA data are similar or better than CCLM data, except for the potential temperature, where a relatively large warm bias was found. Maximum winds occur at gap exit region of Smith Sound and are associated with gravity waves generated by the barrier, resulting in downward flow within the gap. Model simulations offer the advantage of studying the temporal development and the full three-dimensional structure. The wind maximum is influenced by the gap flow structure for mountain Froude numbers less than 1 and by the position and intensity of a low pressure system in Baffin Bay.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003912","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信