Geoscience Data Journal最新文献

{"title":"Intra-Island Variation in Wind Patterns on Sub-Antarctic Marion Island","authors":"J. Schoombie,&nbsp;K. J. Craig,&nbsp;K. A. Goddard,&nbsp;D. W. Hedding,&nbsp;W. Nel,&nbsp;P. C. le Roux","doi":"10.1002/gdj3.70035","DOIUrl":"https://doi.org/10.1002/gdj3.70035","url":null,"abstract":"<p>Sub-Antarctic Marion Island provides a critical habitat for pelagic species, yet its terrestrial ecosystem faces increasing threats from climate change. Despite being situated in one of the windiest regions globally, the impact of changing wind patterns at the intra-island scale remains poorly understood. Existing datasets lack the spatial resolution necessary to capture fine-scale wind dynamics across the island. This study aimed to address this gap by presenting high-resolution wind speed and direction data to investigate the effects of wind on terrestrial systems. We present two complementary datasets: (1) wind measurements collected from 17 stations distributed across the island between May 2018 and March 2021, and (2) computational fluid dynamics (CFD) simulations providing wind vectors and associated properties at a 30 × 30 m resolution for heights up to 200 m above ground level. The data reveal significant differences in wind speed and direction across different geographical sectors of Marion Island. Notably, anemometers situated in the south recorded more frequent gale-force winds, while the western stations experienced calmer conditions. By using the observed wind direction frequencies, a weighted average vector plot was generated from the CFD simulations, providing an island-scale representation of spatial wind patterns across the island. These datasets offer valuable insights into variations in wind patterns, including upstream and downstream effects, and serve as a crucial resource for studying wind-driven processes affecting the landscape and ecosystem, such as seed dispersal.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223875","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":"MRMinerals and MineralTD: Machine-Readable Mineral Formula and Compositions Data Set for Data-Driven Research","authors":"Tamanna,&nbsp;Dominik C. Hezel,&nbsp;Horst R. Marschall","doi":"10.1002/gdj3.70036","DOIUrl":"https://doi.org/10.1002/gdj3.70036","url":null,"abstract":"<p>Artificial intelligence (AI) is being increasingly applied in the geosciences, particularly in fields like mineralogy, where it supports tasks such as mineral classification, automated thin-section image analysis, or mineral exploration targeting. Such tasks require large structured and standardized data sets, which are currently not available. We build two databases to fill this gap: (i) <i>MRMinerals</i> contains a list of the 400 most common and geologically significant minerals, including major rock-forming minerals, key accessory minerals, and economically important ore minerals with machine-readable formulas as the key feature. (ii) <i>MineralTD</i> contains a large training data set with 10,000+ compositions for each of the 400 minerals in MRMinerals. MineralTD is split into two subdatasets: <i>MineralTDMeasured</i> and <i>MineralTDSynthetic</i>. MineralTDMeasured contains approximately 140,000 mineral compositions from the open-access geochemical databases and repositories GEOROC, Pangaea, PetDB, RRUFF, and ESMD. MineralTDSynthetic contains synthetic mineral compositions, generated using machine-readable formulas from MRMinerals, with at least 10,000 compositions per mineral. MineralTD is annotated with metadata, such as mineral frequency, rock classification, data source, and methods used to provide a full understanding of the individual data set. The MRMinerals and MineralTD are ready-to-use open access data sets that enable scalable, data-driven research in mineralogy, e.g., ML applications.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223876","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":"Integrated Global Radiosonde Archive Toolkit (IGRAT): A Python Library for Radiosonde Data Analysis","authors":"Peter T. Phan,&nbsp;Hamed D. Ibrahim","doi":"10.1002/gdj3.70034","DOIUrl":"https://doi.org/10.1002/gdj3.70034","url":null,"abstract":"<p>Integrated Global Radiosonde Archive Toolkit (IGRAT) is a software that allows users to process data from the Integrated Global Radiosonde Archive. The archive provides global radiosonde observations in a text-based format that requires additional manipulation to make it suitable for analysis. IGRAT provides an easy-to-use set of tools to streamline this preprocessing step, allowing users to readily visualise temporal and spatial patterns, plot atmospheric profiles, and export processed data sets in the more standard formats. IGRAT is accessible through a Python library and web interface, and users can adopt it to their preferred workflow. IGRAT significantly reduces preprocessing time before analysis, making it suitable for applications in climate research, meteorology and atmospheric sciences. IGRAT is fully open-source, allowing the community to make contributions as well as modify IGRAT for personal use.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145224527","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":"WRFtailor: A Toolkit for Tailoring the WRF Model Input Data","authors":"Amirhossein Nikfal","doi":"10.1002/gdj3.70031","DOIUrl":"10.1002/gdj3.70031","url":null,"abstract":"<p>WRFtailor is an open-source toolkit offering a set of distinct functionalities to customise and tailor the Weather Research and Forecasting (WRF) model input data, such as WPS geographical data or WRF/Chem emissions data. Before running the toolkit, the user should specify an area of interest (AOI) from the WRF input file, a variable to be tailored within the AOI, and a polynomial of variables that will replace the specified variable. WRFtailor is a Linux-based toolkit, written in Shell and NCAR Command Language (NCL) scripts, and is available at https://github.com/anikfal/wrftailor.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101445","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":"Lundisim: Model Meshes for Flow Simulation and Scientific Data Compression Benchmarks","authors":"Laurent Duval,&nbsp;Frédéric Payan,&nbsp;Christophe Preux,&nbsp;Lauriane Bouard","doi":"10.1002/gdj3.70030","DOIUrl":"10.1002/gdj3.70030","url":null,"abstract":"<p>The volume of scientific data produced for and by numerical simulation workflows is increasing at an incredible rate. This raises concerns either in computability, interpretability, and sustainability. This is especially noticeable in earth science (geology, meteorology, oceanography, and astronomy), notably with climate studies. We highlight five main evaluation issues: efficiency, discrepancy, diversity, interpretability, availability. Among remedies, lossless and lossy compression techniques are becoming popular to better manage dataset volumes. Performance assessment—with comparative benchmarks—requires open datasets shared under FAIR principles (Findable, Accessible, Interoperable, Reusable), provided in a MWE (Minimal Working Example) with ancillary data for reuse. We share <span>Lundi</span>_sim, an exemplary faulted geological mesh. It is inspired by the SPE10 comparative Challenge. It is not meant to be compared to the latter for reservoir simulation. It is instead tailored—with power-of-two dimensions and additional faults—to both more challenging fluid displacement and upscaling methods, and allowing versatile compression benchmarks. Enhanced by porosity/permeability datasets, this dataset proposes four distinct subsurface environments. They were primarily designed for flow simulation in porous media. Several consistent resolutions (with HexaShrink multiscale representations) are proposed for each model. We also provide a set of reservoir features for reproducing typical two-phase flow simulations on all <span>Lundi</span>_sim models in a reservoir engineering context. This dataset is chiefly meant for benchmarking and evaluating data size reduction (upscaling) or genuine composite mesh compression algorithms. It is also suitable for other advanced mesh processing workflows in geology and reservoir engineering, from visualisation to machine learning. <span>Lundi</span>_sim meshes are available at 10.5281/zenodo.14641958.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101444","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":"Microclimate, Soil and Plant Dataset From a Mediterranean Urban Canyon With Irrigated Planters","authors":"Martina Garcia de Cezar,&nbsp;Bruno Cheviron,&nbsp;François Liron,&nbsp;Séverine Tomas,&nbsp;Laurent Aprin,&nbsp;Kevin Orlando,&nbsp;Justine Catel,&nbsp;Geoffrey Froment,&nbsp;Cyril Dejean","doi":"10.1002/gdj3.70033","DOIUrl":"10.1002/gdj3.70033","url":null,"abstract":"<p>Dataset obtained from a fully instrumented experimental urban street canyon, located on a research site in Montpellier (France, Mediterranean climate) and monitored between 21 July 2023 and 31 July 2024. This east–west canyon consists of two parallel concrete walls (height 2.3 m, length 12 m, width 5 m). Three nearly adjacent planters (height 0.9 m, length 2.3 m, width 0.8 m) are aligned along its inner north wall and contain climbing plants of the <i>Lonicera japonica</i> species. Three other nearly adjacent planters (height 0.9 m, length 2.3 m, width 1.1 m) are aligned along its inner south wall and contain shrub plants of the <i>Abelia grandiflora</i> species. Each planter includes 11 sensors to measure soil temperature, water content and matric potential, collecting data every 10 min. Drip irrigation was used and each series of planters received identical irrigation amounts. The irrigation strategy changed several times, to monitor the impacts of irrigation on the overall water balance of the soil–plant–atmosphere system, especially on the local microclimatic variables. A dense network of 102 sensors was installed to monitor wind direction and velocity, air temperature, relative humidity, radiation, grey globe temperature and rainfall at 1.3 m above the ground, which is a standardised measurement height for determining the variables used to quantify thermal comfort indices. This dataset supports (i) understanding thermal, radiative and aerodynamic processes in urban canyons, (ii) detecting irrigation impact on microclimate, (iii) validating CFD-based microclimate models and (iv) identifying methods to manage urban heatwaves through water resource optimisation. By encompassing a full year of seasonal and climatic variability, this study is the first to evaluate the combined effects of vegetation type and irrigation on urban thermal comfort in a Mediterranean context, providing a significant contribution to urban microclimate research.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050882","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":"Multi-Year Glaciological and Meteorological Observations on Debris-Covered Kennicott Glacier, Alaska, 2016–2023","authors":"Eric Ivan Petersen,&nbsp;Regine Hock,&nbsp;Michael G. Loso,&nbsp;Wanqin Guo,&nbsp;Cameron Markovsky,&nbsp;Ruitang Yang,&nbsp;Haidong Han,&nbsp;Donghui Shangguan,&nbsp;Shichang Kang","doi":"10.1002/gdj3.70032","DOIUrl":"10.1002/gdj3.70032","url":null,"abstract":"<p>Despite increasing availability of satellite-derived products, in situ glacier observations are pivotal to accurately monitor glacier change and to calibrate and validate glacier models. However, comprehensive multi-variable field observations are especially rare on large glaciers and on debris-covered glaciers. Here we present extensive field observations from Kennicott Glacier, a heavily debris-covered glacier in central Alaska covering more than 400 km². The multi-year data set includes point glacier mass balances, meteorological data from several weather stations on and off the glacier, debris thickness and temperature, ice cliff back wasting derived from time-lapse photography of horizontal stakes drilled into several cliffs, and bathymetry, water temperature, and water level of proglacial and supraglacial lakes. Cumulated summer melt of more than 8 m was observed at the lowest clean-ice sites. Melt rates over clean ice correlate well with elevation, while the rates over debris-covered ice lack any strong elevation dependence. Melt rates drop exponentially with increasing debris thickness and tend to be much lower than for clean ice at similar elevations. Melt rates determined for ice cliffs in areas of otherwise continuous debris cover were up to 10× those for debris-covered ice, and even exceeded standard clean ice melt rates. Debris-cover thickness measurements at 150 sites vary from &lt; 1 to 69 cm with an average of 17 ± 11 cm (±standard deviation). Debris thickens down-glacier, but with high spatial variability–thickness was observed to vary by tens of cm within a ~15 m radius. Depth-averaged thermal heat conductivity derived from supraglacial debris temperature profiles at 12 sites ranges from 0.53 to 1.86 W m⁻¹ K⁻¹. Interconnected proglacial lakes covered 1.61 km² in 2018 with observed water depths of more than 60 m in the two largest lakes. The dataset can be downloaded at https://doi.org/10.5281/zenodo.14625691 (Petersen, Hock, Loso, Guo, et al., 2024) and will be useful for glaciological and glacier meteorological studies.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037559","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":"SCIBA: A Geo-Dataset of Damaging Rainfall Related Landslides and Floods Throughout 113 Years on a Mediterranean Study Area","authors":"Olga Petrucci,&nbsp;Michele Mercuri,&nbsp;Massimo Conforti","doi":"10.1002/gdj3.70026","DOIUrl":"10.1002/gdj3.70026","url":null,"abstract":"<p>This paper introduces SCIBA, a novel dataset documenting floods (F) and landslides (L) triggered by rainfall that affected the road-railway network in the municipalities of Scilla and Bagnara (Calabria, Italy) between 1911 and 2024. The study addresses the central research question: How can historical rainfall-induced flood and landslide events be systematically documented and used to improve predictive models for early warning systems in transport infrastructure? In response, SCIBA offers a comprehensive, spatially and temporally detailed dataset aimed at supporting the Disaster Risk Reduction (DRR) community and researchers developing empirical models for forecasting rainfall thresholds that precede F and L events. The unique contribution of this work lies in the systematic compilation and georeferencing of 281 historical FL events—a rare and valuable resource in a context where such data are typically fragmented or unavailable. SCIBA bridges this gap through extensive archival research, such as the State Archive, the Regional Civil Protection archive, and ANAS, the agency responsible for state roads in the region. All the records include the spatial references (geographic coordinates and place names) and temporal localization (to the day, and in 18.6% of cases, the exact hour). Moreover, each record integrates daily rainfall data from two operational rain gauges (Scilla at 73 m a.s.l. and Bagnara at 30 m a.s.l.) for the day of the event and the preceding 4 days, enabling analysis of both daily and cumulative rainfall as triggering factors. Despite some unavoidable gaps in historical documentation, SCIBA stands out as a ready-to-use dataset that supports the development of cause-effect models for rainfall-induced hazards. Provided in GIS format, the dataset not only enhances understanding of past events but also identifies critical hotspots for monitoring during intense rainfall, contributing directly to emergency planning, traffic management, and the resilience of transport networks.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923841","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":"Recovery of Daily Water Levels in the Sacramento-San Joaquin Delta, 1915–2023","authors":"Serena B. Lee,&nbsp;Steven Dykstra,&nbsp;Reyna Gomez-Sanchez,&nbsp;Cole Wilkenson,&nbsp;Ricardo Estrada,&nbsp;Nick McGuire,&nbsp;David A. Jay,&nbsp;Stefan A. Talke","doi":"10.1002/gdj3.70018","DOIUrl":"10.1002/gdj3.70018","url":null,"abstract":"<p>This manuscript documents the data rescue, digitization, and quality assurance of archival daily maximum and minimum water levels at twenty-five sites within the Sacramento-San Joaquin Delta. The records encompass 1846 total unique years, where 915 years are newly digitized from the 1915–1985 era. The period of record for each gauge location varies from 40 to 109 years (median = 80 years). Quality assurance procedures and datum corrections were applied to both archival and digital records to generate a time series referenced to a common geocentric datum. Both riverine and coastal influences on mean sea level and great diurnal range are evident in the time series. During the winter months, when river discharge is large, mean sea-level increase and great diurnal ranges decrease. The strongest river influence is observed at more landward sites, where daily mean sea levels can increase by 1–10 m. The data also include spatially and interannually varying extreme water levels and show evidence of the influence of seasonal tidal barrier construction/dismantling, which began in the late 1980s. The data records thus enable future analysis of multiple intertwined issues, including sea-level rise, subsidence, tides, climate patterns, atmospheric conditions, shoreline/habitat changes, bathymetric modifications, water resource management, and flood hazards.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923376","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 High-Resolution Hydrological Dataset for Ukrainian River Basins With an Interactive Web Interface","authors":"Valeriy Osypov,&nbsp;Arun Bawa,&nbsp;Nataliia Osadcha,&nbsp;Volodymyr Osadchyi,&nbsp;Oleksii Shevchenko,&nbsp;Andrii Bonchkovskyi,&nbsp;Oleksandr Kostetskyi,&nbsp;Viktor Nikoriak,&nbsp;Yurii Ahafonov,&nbsp;Yevhenii Matviienko,&nbsp;Herman Mossur,&nbsp;Fearghal O'Donncha,&nbsp;Michael Jacobs,&nbsp;Raghavan Srinivasan,&nbsp;Jeff Arnold,&nbsp;Michael J. White","doi":"10.1002/gdj3.70027","DOIUrl":"10.1002/gdj3.70027","url":null,"abstract":"<p>The ongoing and post-war reconstruction of Ukrainian water resources is critical for food production, public health, energy, industry and environmental protection. This effort, the most ambitious in Europe since World War II, faces challenges due to a lack of accessible decision-support tools for managing water ecosystems effectively. In response, we developed a high-resolution hydrological model of the Ukrainian Watershed using the SWAT (Soil and Water Assessment Tool) model to assess water balance across all nine major river basins, covering an area of 873,600 km². The model is integrated into an interactive web interface—named ‘Land &amp; Water’—which provides public access to model inputs and outputs and was designed considering FAIR (Findable, Accessible, Interoperable, Reusable) principles. A multifaceted calibration approach, combining soft and hard methods, ensures balanced performance for surface, lateral and groundwater dynamics. The platform enables users to visualise and download model results, supporting both experts and non-experts in water-related decision making. The study demonstrates how the model helps close critical data gaps—providing estimates of river discharge for transboundary inflows, total and groundwater flow around the Kakhovka reservoir, and potential transpiration and crop growth to assess irrigation needs. Overall, the dataset offers a valuable tool for Ukraine's recovery, fosters transparent water governance, and supports environmental research on water quality, climate adaptation and sustainable agriculture.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923378","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}