Earth and Space Science最新文献

{"title":"Calibrating Strain Measurements: A Comparative Study of DAS, Strainmeter, and Seismic Data","authors":"Chih-Chieh Chien,&nbsp;Peter Gerstoft,&nbsp;William Hatfield,&nbsp;Leo Hollberg,&nbsp;Bradley P. Lipovsky,&nbsp;John-Morgan Manos,&nbsp;Robert J. Mellors,&nbsp;Dale P. Winebrenner,&nbsp;Mark A. Zumberge","doi":"10.1029/2024EA003940","DOIUrl":"https://doi.org/10.1029/2024EA003940","url":null,"abstract":"<p>Significant interest has developed in using optical fibers for seismology through Distributed Acoustic Sensing (DAS). However, converting DAS strain measurements to actual ground motions can result in errors and uncertainties due to imperfect coupling of the fiber to the earth and instrument response functions. To address this, we conducted a comparative analysis of strain data recorded by DAS, Optical Fiber Strainmeters (OFSs), and estimates derived from seismic data. This study used dark fibers in a commercial cable connecting two islands in Puget Sound, Washington, USA. The cable extends from a telecommunication substation on Whidbey Island, through an underground conduit, and across Saratoga Passage to Camano Island. The strain along the cable was recorded using OFS Michelson interferometers and a DAS interrogator, with a broadband seismometer positioned at one end. Comparing a teleseismic earthquake recording showed that summed DAS channels agreed well with OFS recordings. The amplitude discrepancies between the measurements and the seismometer's estimated strain indicated poor coupling between the cable and the earth. We also evaluated DAS amplitude response using a piezoelectric cylinder (PZT) to generate ground truth strain. The findings revealed a notable amplitude decrease in DAS recordings at lower frequencies, highlighting the need for amplitude calibration. Moreover, some underwater signals in the study area were strongly correlated with the velocity of the tidal current. These signals can be localized through coherence calculations between the DAS and OFS recordings.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003940","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143423565","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}

{"title":"Local Time Variations of Quiet Time Meridional Winds During Solar Minimum Solstices Based on ICON Observations and Numerical Simulations","authors":"Tingting Yu,&nbsp;Xuguang Cai,&nbsp;Zhipeng Ren,&nbsp;Huixin Liu,&nbsp;Liuhui Qiu,&nbsp;Han Ma,&nbsp;Shaoyang Li,&nbsp;Kun Wu","doi":"10.1029/2024EA003880","DOIUrl":"https://doi.org/10.1029/2024EA003880","url":null,"abstract":"<p>ICON observations were used to investigate local time (LT) and latitudinal variations of thermospheric meridional winds in the middle-high thermosphere (160–300 km) during quiet times in 2020 June and December. At middle-low latitudes (10°S–40°N), meridional winds were predominantly equatorward in the summer hemisphere while mostly poleward in the winter hemisphere. The meridional winds showed that the diurnal variation was dominant between ∼20°N and ∼40°N, but the semi-diurnal variation played a leading role at lower latitudes (below ∼20°N) during solstice months. Thermosphere-Ionosphere Electrodynamics General Circulation Model reproduced the ICON observed meridional wind variations qualitatively. A model diagnostic analysis shows that the pressure gradient force dominated the semi-diurnal variation of the winds, while the Coriolis force played a leading role in the diurnal variation in June. In December, LT variations of meridional winds were primarily driven by pressure gradient and ion drag forces. During both months, the vertical viscosity was important, tending to balance the effects of pressure gradients. Additionally, semi-diurnal variations of low-latitude meridional winds in June were more affected by upward propagating tides than those in December.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003880","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143397195","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}

{"title":"Characteristics of Regional Hourly Extreme Precipitation With Different Durations Over the Northeast Plain, China During Summer","authors":"Yaxin Yu,&nbsp;Xiaoke Xu,&nbsp;Qi Yan,&nbsp;Jinglong Lu,&nbsp;Yue Yu","doi":"10.1029/2024EA003973","DOIUrl":"https://doi.org/10.1029/2024EA003973","url":null,"abstract":"<p>Regional extreme precipitation events (REPEs) are the focus of current research with a large coverage long-term duration. The characteristics of REPE in the summer remain unclear over the Northeast Plain of China (NPC), one of the only four major black soil distribution areas in the world. This study investigates the spatial, diurnal, sub-seasonal and long-term trend characteristics of REPE over NPC in the summer of 2000–2020 based on the Multi-satellite Retrievals precipitation data GPM-IMERG. The results show that the amount and intensity of total REPE increase from north to south of NPC in the summer of 2000–2020 and the frequency of total REPE mainly concentrates in the middle of NPC. The primary peak of the total REPE amount is at 18:00 (BJT) with a large centre cross the middle of NPC. The secondary peak is between 2:00 (BJT) and 5:00 (BJT) with the large centre located in the southern NPC. The REPE mainly happens in the summer months of July-August during 2000–2020 over NPC, and the large centre of amount and intensity locates in the southern NPC. The intensity of total REPE exhibits a significantly increase during the summer of 2000–2020. The amount, frequency, and intensity of REPE with a duration of more than 19 hr show the significant enhancement. The findings of this study provide the basic features of REPE over NPC in summer on an hourly scale.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003973","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388975","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}

{"title":"Wind Profile Characteristics That Warn of Summertime Flash Heavy Rain Events Over the Middle Reaches of the Yangtze River Basin","authors":"Jingyu Wang,&nbsp;Xiaokang Wang,&nbsp;Huiling Yuan,&nbsp;Chunguang Cui,&nbsp;Xiaofang Wang,&nbsp;Lin Liu","doi":"10.1029/2024EA003902","DOIUrl":"https://doi.org/10.1029/2024EA003902","url":null,"abstract":"<p>Forecasting and early warnings for summertime flash heavy rain events (FHREs) in the middle Yangtze River basin (MYRB) pose significant challenges. This study examined variations in lower tropospheric wind profiles hours before these FHREs using reanalysis data and wind profile radar observations. The findings highlight wind accelerations, directional shifts, and associated vertical shears preceding FHREs, providing valuable insight for severe weather warnings. During the summers of 2010–2019, FHREs occurred most frequently and contributed significantly to total precipitation during the Meiyu period, compared to before and after. Meiyu FHREs also exhibit longer durations and nocturnal peaks. Spatially, FHRE frequency increases from northwest to southeast, with higher frequencies in the topographic areas. The discernible moisture influx 4 hr before FHREs primarily comes from southwesterly and easterly winds below 700 hPa. Before FHRE, weaker easterly winds dominated western MYRB, while strong southerly winds prevailed in the east, influenced by mesoscale cyclonic shear and low-level jets. Detailed wind changes below 4 km altitude show that over the southeastern MYRB, accelerated west-southwest winds are observed 3–4 hr before FHREs, while southerly components near the boundary layer top intensified 2 hr earlier. Within 1 hr before FHREs, the wind speeds sharply increase to peak. East of the western mountains, southwesterly winds strengthen 5 hr prior, then weaken as they shift to northerlies just before FHREs, accompanied by reinforced northerlies near the surface. Over the western mountainous area, southeasterly components below 2 km altitude increase 4 hr before FHREs, although at lower speeds.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003902","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388964","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}

{"title":"Aura Ozone Monitoring Instrument (OMI) Collection 4 Formaldehyde Products","authors":"Zolal Ayazpour,&nbsp;Gonzalo González Abad,&nbsp;Caroline R. Nowlan,&nbsp;Kang Sun,&nbsp;Hyeong-Ahn Kwon,&nbsp;Christopher Chan Miller,&nbsp;Heesung Chong,&nbsp;Huiqun Wang,&nbsp;Xiong Liu,&nbsp;Kelly Chance,&nbsp;Ewan O’Sullivan,&nbsp;Lei Zhu,&nbsp;Corinne Vigouroux,&nbsp;Isabelle De Smedt,&nbsp;Wolfgang Stremme,&nbsp;James W. Hannigan,&nbsp;Justus Notholt,&nbsp;Xiaoyu Sun,&nbsp;Mathias Palm,&nbsp;Cristof Petri,&nbsp;Kimberly Strong,&nbsp;Amelie N. Röhling,&nbsp;Emmanuel Mahieu,&nbsp;Dan Smale,&nbsp;Yao Té,&nbsp;Isamu Morino,&nbsp;Isao Murata,&nbsp;Tomoo Nagahama,&nbsp;Rigel Kivi,&nbsp;Maria Makarova,&nbsp;Nicholas Jones,&nbsp;Ralf Sussmann,&nbsp;Minqiang Zhou","doi":"10.1029/2024EA003792","DOIUrl":"https://doi.org/10.1029/2024EA003792","url":null,"abstract":"&lt;p&gt;This study presents the ozone monitoring instrument (OMI) Collection 4 formaldehyde (HCHO) retrieval developed with the Smithsonian Astrophysical Observatory's (SAO) Making Earth System Data Records for Use in Research Environments (MEaSUREs) algorithm. The retrieval algorithm updates and makes improvements to the NASA operational OMI HCHO (OMI Collection 3 HCHO) algorithm, and has been transitioned to use OMI Collection 4 Level-1B radiances. This paper describes the updated retrieval algorithm and compares Collection 3 and Collection 4 data products. The OMI Collection 4 HCHO exhibits remarkably improved stability over time in comparison to the OMI Collection 3 HCHO product, with better precision and the elimination of artificial trends present in the Collection 3 during the later years of the mission. We validate the OMI Collection 4 HCHO data product using Fourier-Transform Infrared (FTIR) ground-based HCHO measurements. The climatological monthly averaged OMI Collection 4 HCHO vertical column densities (VCDs) agree well with the FTIR VCDs, with a correlation coefficient of 0.83, root-mean-square error (RMSE) of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;2.98&lt;/mn&gt;\u0000 &lt;mo&gt;×&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;msup&gt;\u0000 &lt;mn&gt;0&lt;/mn&gt;\u0000 &lt;mn&gt;15&lt;/mn&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $2.98times 1{0}^{15}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; molecules &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mtext&gt;cm&lt;/mtext&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{cm}}^{-2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, regression slope of 0.79, and intercept of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;8.21&lt;/mn&gt;\u0000 &lt;mo&gt;×&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;msup&gt;\u0000 &lt;mn&gt;0&lt;/mn&gt;\u0000 &lt;mn&gt;14&lt;/mn&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $8.21times 1{0}^{14}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; molecules &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mtext&gt;cm&lt;/mtext&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{cm}}^{-2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;. Additionally, we compare the monthly averaged OMI Collection 4 HCHO VCDs to OMPS ","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003792","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396874","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}

{"title":"Exploring Machine Learning's Potential for Estimating High Resolution Daily Snow Depth in Western Himalaya Using Passive Microwave Remote Sensing Data Sets","authors":"Srinivasarao Tanniru,&nbsp;Dhiraj Kumar Singh,&nbsp;Kamal Kant Singh,&nbsp;Raaj Ramsankaran","doi":"10.1029/2024EA003849","DOIUrl":"https://doi.org/10.1029/2024EA003849","url":null,"abstract":"<p>Snow depth (SD) exhibits high spatiotemporal heterogeneity in Western Himalaya (WH), and its knowledge is essential for applications related to water resources, disaster management, climate, etc. However, due to inclement weather and rugged topographical conditions, only a sparse network of SD monitoring stations exists in WH. Spaceborne passive microwave (PMW) remote sensing data sets provides valuable information about SD; however, only a limited PMW SD studies that cover subregions of WH are available. Different machine learning (ML) methods viz. support vector machine, random forest, and Extremely Randomized Trees (ERT) were tested for estimating SD. Based on our preliminary assessment of these ML approaches, the current study utilizes ERT approach to estimate daily SD over the entire WH region. The ERT SD model is developed using PMW brightness temperature data sets from Advanced Microwave Scanning Radiometer-2 (AMSR-2), snow cover duration (SCD), and other auxiliary parameters (i.e., location, elevation, vegetation cover, etc.) during the winter period between 2012–2013 and 2019–2020. The data between 2012–2013 and 2017–2018 is used for training the model, whereas the data between 2018–2019 and 2019–2020 is used for testing the model. The results demonstrate: (a) The ERT SD model has shown improved SD estimates compared to the available PMW remote sensing-based operational SD products and empirical PMW SD models. (b) In general, with an increase in SD, the mean absolute error of SD retrievals has increased in all SD products/models. (c) Unlike the operational AMSR2 SD product, and Northern Hemisphere Machine Learning SD product, the ERT SD model retrievals have shown better consistency with MODIS snow cover. (d) The developed model has shown a wider range in SD retrievals as compared to other products considered in this study.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003849","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388968","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}

{"title":"Spatio-Seasonal Risk Assessment of Upward Lightning at Tall Objects Using Meteorological Reanalysis Data","authors":"Isabell Stucke,&nbsp;Deborah Morgenstern,&nbsp;Gerhard Diendorfer,&nbsp;Georg J. Mayr,&nbsp;Hannes Pichler,&nbsp;Wolfgang Schulz,&nbsp;Thorsten Simon,&nbsp;Achim Zeileis","doi":"10.1029/2024EA003706","DOIUrl":"https://doi.org/10.1029/2024EA003706","url":null,"abstract":"<p>This study investigates lightning at tall objects and evaluates the risk of upward lightning (UL) over the eastern Alps and its surrounding areas. While uncommon, UL poses a threat, especially to wind turbines, as the long-duration current of UL can cause significant damage. Current risk assessment methods overlook the impact of meteorological conditions, potentially underestimating UL risks. Therefore, this study employs random forests, a machine learning technique, to analyze the relationship between UL measured at Gaisberg Tower (Austria) and 35 larger-scale meteorological variables. Of these, the larger-scale upward velocity, wind speed and direction at 10 m and cloud physics variables contribute most information. The random forests predict the risk of UL across the study area at a 1 <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mtext>km</mtext>\u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> ${text{km}}^{2}$</annotation>\u0000 </semantics></math> resolution. Strong near-surface winds combined with upward deflection by elevated terrain increase UL risk. The diurnal cycle of the UL risk as well as high-risk areas shift seasonally. They are concentrated north/northeast of the Alps in winter due to prevailing northerly winds, and expanding southward, impacting northern Italy in the transitional and summer months. The model performs best in winter, with the highest predicted UL risk coinciding with observed peaks in measured lightning at tall objects. The highest concentration is north of the Alps, where most wind turbines are located, leading to an increase in overall lightning activity. Comprehensive meteorological information is essential for UL risk assessment, as lightning densities are a poor indicator of lightning at tall objects.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003706","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388963","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}

{"title":"Impact of NWP Model Configuration and Training Sample Characteristics on Random Forest-Based Day-1 Convective Outlook Guidance","authors":"Aaron Johnson,&nbsp;Xuguang Wang","doi":"10.1029/2024EA003822","DOIUrl":"https://doi.org/10.1029/2024EA003822","url":null,"abstract":"<p>This study aims to quantify and better understand the impact of an upgrade to the configuration of an FV3 (Finite Volume cubed-sphere) LAM (Limited Area Model) convection-allowing ensemble on the skill of the RF models trained on cases before the upgrade and forecast on cases after the upgrade. Specifically, Random Forest (RF) models were used to produce probabilistic forecasts of severe weather, significant severe weather, and individual hazards of wind, hail, and tornado for the purpose of day-1 convective outlook guidance. The RF models are trained and forecast on different subsets of the available data set of forecast cases from the spring seasons of 2019 and 2021 (before the FV3 LAM upgrade) and 2022 (after the upgrade) and evaluated both quantitatively and qualitatively. It is found for most predictands that the RF models forecasting 2022 (2019/2021) cases are statistically significantly more skillful when trained on other cases from the 2022 (2019/2021) data set using a leave-one-out approach. However, within the 2019/2021 data set, training on cases from a different year than the year being forecast also leads to statistically significant degradations of skill, apparently at least in part due to the different sample climate between 2019 and 2021. For this particular NWP (Numerical Weather Prediction) model configuration change, the consistency in sample climate between training and forecast cases is at least as important as consistency in model configuration. Finally, increases in skill resulting from increasing the number of forecast cases used to train the RF levels off around 30 forecast cases.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003822","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380831","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}

{"title":"A Drone-Based Thermophysical Investigation of Barringer Meteorite Crater Ejecta","authors":"Cole A. Nypaver,&nbsp;Bradley J. Thomson,&nbsp;Jeffrey E. Moersch,&nbsp;David A. Kring","doi":"10.1029/2024EA003984","DOIUrl":"https://doi.org/10.1029/2024EA003984","url":null,"abstract":"<p>Impact cratering processes are ubiquitous throughout our solar system, and the distribution and modification of impact ejecta are sensitive to variable environmental and geologic surface conditions. Here we examine the scale dependency of orbital versus field-based remote sensing data sets of a terrestrial impact structure by comparing low-resolution (90 m/pixel) orbital with high-resolution (23 cm/pixel) drone-based thermophysical data to measure ejecta distribution patterns of Meteor Crater in northeast Arizona, USA. Our results indicate that the thermophysical properties of the Meteor Crater ejecta blanket are well constrained at the scale of orbital data resolution. However, when high-resolution, drone-based data are binned using previously mapped unit boundaries, no clear correlations between thermophysical properties and surface composition are observed. A trend of increasing apparent thermal inertia with surface rock population is observed. These results indicate that significant ejecta distribution variability can exist below the resolution of orbital thermophysical remote sensing data. In addition to providing insights into how remote sensing data can improve field-based geologic mapping campaigns and impact crater analyses, our results place constraints on how the accuracy of geologic maps may be affected by surface erosion.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003984","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380832","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}

{"title":"A Nanoindentation Study of Attenuation in Geological Materials","authors":"Nir Z. Badt,&nbsp;Ron Maor,&nbsp;David L. Goldsby","doi":"10.1029/2024EA003870","DOIUrl":"https://doi.org/10.1029/2024EA003870","url":null,"abstract":"<p>The dissipation of elastic strain energy, or attenuation, in Earth materials contributes to a range of geophysical phenomena, such as the damping of seismic waves and tidal heating of planetary bodies. We present a new method for measuring attenuation in single crystals of minerals and in reference materials over a frequency range of 1–10⁻⁴ Hz via nanoindentation. In the experiments, we measure the phase lag between a sinusoidal load applied to the nanoindenter tip and the sinusoidal displacement of the tip into and out of the tested sample, which provides a measure of the inverse quality factor Q⁻¹, or attenuation, of the sample. Experiments were conducted on polymethyl methacrylate (PMMA), indium, halite, olivine and quartz. Attenuation spectra from our tests on PMMA and indium are in excellent agreement with reported values from previous studies. We quantified the natural damping of the nanoindenter and showed that it becomes comparable to that of the samples only at frequencies greater than 0.1 Hz, and is much less than that of the samples at frequencies below 0.1 Hz.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003870","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362688","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}