Geoscience Data Journal最新文献

{"title":"A basin-wide carbon-related proxy dataset in arid China","authors":"Yu Li,&nbsp;Yaxin Xue,&nbsp;Mingjun Gao,&nbsp;Zhansen Zhang,&nbsp;Simin Peng,&nbsp;Junjie Duan","doi":"10.1002/gdj3.274","DOIUrl":"https://doi.org/10.1002/gdj3.274","url":null,"abstract":"<p>Closed basin accounts for about one-fifth of the global land area and is an important part of the global terrestrial carbon cycle. Due to its relatively close geographical environment and independent carbon cycling system, it is an ideal place to study regional carbon cycling. Here we present a carbon-related proxy dataset for the Shiyang River Basin in the eastern part of the Hexi Corridor. The dataset collected carbon-related indicator data for 997 sediment samples from 14 profiles, 92 surface sediment samples and 25 groundwater samples. It includes total nitrogen (TN), total organic carbon (TOC), inorganic carbon (IC), carbon-nitrogen ratio (C/N), organic carbon isotopes (δ¹³C_org), carbonate carbon isotopes (δ¹³C_carb), oxygen isotopes (δ¹⁸O) and other proxy indicator data, as well as profile and groundwater age data. These data will play an important role in studying organic carbon sinks, inorganic carbon sinks, carbon cycling processes and environmental changes in the closed basin. This dataset can be downloaded from https://doi.org/10.5281/zenodo.10252702.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.274","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119141","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":"Completion of the Central Italy daily precipitation instrumental data series from 1951 to 2019","authors":"Gamal AbdElNasser Allam Abouzied,&nbsp;Guoqiang Tang,&nbsp;Simon Michael Papalexiou,&nbsp;Martyn P. Clark,&nbsp;Eleonora Aruffo,&nbsp;Piero Di Carlo","doi":"10.1002/gdj3.267","DOIUrl":"https://doi.org/10.1002/gdj3.267","url":null,"abstract":"<p>Precipitation is a critical part of the global hydrological cycle that determines the distribution of water resources. It is also an essential meteorological variable used as input for hydroclimatic models and projections. However, precipitation data frequently lack complete series, especially at daily and sub-daily precipitation stations, which are usually large, bulky, and complex. To address this, gap filling is commonly used to produce complete hydrometeorological data series without missing values. Several gap-filling methods have been developed and improved. This study seeks to fill the gaps of 201 daily precipitation time series in Central Italy by localizing the approach used to generate the Serially Complete dataset for the Planet Earth (SC-Earth). This method combines the outcome of 15 strategies based on four various gap-filling techniques (quantile mapping, spatial interpolation, machine learning, and multi-strategy merging). These strategies employ the daily dataset of the neighbouring stations and the matched ERA5 data to estimate missing values at the target stations. Both raw data and the final serially complete station datasets (SCDs) underwent comprehensive quality control. Many accuracy indicators have been utilized to evaluate the performance of the strategies' estimations and the final SCD, such as Correlation Coefficient (CC), Root mean square error (RMSE), Relative bias (Bias %), and Kling-Gupta efficiency (KGE″). Multi-strategy merging strategy based on the Modified Kling-Gupta efficiency (MS₁) shows the highest performance as an individual precipitation gap-filling strategy. However, the machine learning strategy using random forest (ML₃) has the most outstanding share in the final estimates among all other strategies. In the end, the temporal–spatial performance of the final SCD is promising and depends on the pattern of the missing values (MV%). The mean values of KGE″, CC, variability (<i>α</i>), and bias term (<i>β</i>) are 0.9, 0.93, 1.064, and 4.98 × 10⁻⁷, respectively.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.267","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118995","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":"High-resolution atmospheric CO2 concentration data simulated in WRF-Chem over East Asia for 10 years","authors":"Min-Gyung Seo,&nbsp;Hyun Mee Kim,&nbsp;Dae-Hui Kim","doi":"10.1002/gdj3.273","DOIUrl":"10.1002/gdj3.273","url":null,"abstract":"<p>In this study, high-resolution CO₂ concentration data were generated for East Asia to analyse long-term changes in atmospheric CO₂ concentrations, as East Asia is an important region for understanding the global carbon cycle. Using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), atmospheric CO₂ concentrations were simulated in East Asia at a resolution of 9 km for a period of 10 years (2009–2018). The generated CO₂ concentration data include CO₂ concentrations, biogenic CO₂ concentrations, anthropogenic CO₂ concentrations, oceanic CO₂ concentrations, biospheric CO₂ uptake, biospheric CO₂ release and meteorological variables at 3-h intervals. The simulated high-resolution CO₂ concentrations, biogenic CO₂ concentrations and anthropogenic CO₂ concentrations are stored in NetCDF-4 (Network Common Data Form, version 4) format and are available for download at https://doi.org/10.7910/DVN/PJTBF3. The simulated annual mean surface CO₂ concentrations in East Asia were 391.027 ppm in 2009 and 412.949 ppm in 2018, indicating an increase of 21.922 ppm over the 10-year period with appropriate seasonal variabilities. The monthly mean CO₂ concentrations in East Asia were verified using surface CO₂ observations and satellite column-averaged CO₂ mole fraction (XCO₂) from Orbiting Carbon Observatory 2 (OCO-2). Based on surface CO₂ observations and OCO-2 XCO₂ concentrations, the average root-mean-square error (RMSE) of the simulated CO₂ concentrations in WRF-Chem was 2.474 and 0.374 ppm, respectively, which is smaller than the average RMSE of the low-resolution CarbonTracker 2019B (CT2019B) simulation. Therefore, the simulated high-resolution atmospheric CO₂ concentrations in East Asia in WRF-Chem over 10 years are reliable data that resemble the observed values and could be highly valuable in understanding the carbon cycle in East Asia.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"1024-1043"},"PeriodicalIF":3.3,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.273","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142264428","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":"The Irish drought impacts database: A 287-year database of drought impacts derived from newspaper archives","authors":"Eva Jobbová,&nbsp;Arlene Crampsie,&nbsp;Conor Murphy,&nbsp;Francis Ludlow,&nbsp;Robert McLeman,&nbsp;Csaba Horvath,&nbsp;Natascha Seifert,&nbsp;Therese Myslinski,&nbsp;Laura Sente","doi":"10.1002/gdj3.272","DOIUrl":"10.1002/gdj3.272","url":null,"abstract":"<p>Understanding of past droughts has been mostly shaped by meteorological data, with relatively less known about the human aspects of droughts, their socio-economic impacts, as well as choices people make in response to droughts in different environmental and socio-political contexts. The lack of data that systematically record and categorize drought impacts is an important reason for this disparity. In this paper, we present an Irish drought impacts database (IDID) containing 6094 newspaper reports and 11,351 individual impact records for the island of Ireland, covering the period 1733–2019. Relevant articles were identified through systematic searching of the Irish Newspaper Archives, and recorded impacts were categorized using a modified version of the classification scheme employed by the European drought impact inventory (EDII). Drawing on the wealth and diversity of content provided by the newspapers, the IDID database provides information on the documented temporal and geographical extent of drought events, their socio-economic and political contexts, their consequences, mitigation strategies employed and their change over time. The IDID also facilitates analysis of long-term patterns in drought incidence, individual impact categories, as well as detailed insight into the impacts of individual drought events over nearly three centuries of Ireland's history. In addition, by allowing an examination of the coherence between meteorological records and identified impacts, it advances our understanding of the influences that contemporary economic, political, environmental and societal events had on the human experience, perception and impact of droughts. This new open-access database, therefore, provides opportunities for improving understanding of drought vulnerability and is an important step in developing greater capacity to cope with and respond to future droughts on the island of Ireland.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"1007-1023"},"PeriodicalIF":3.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.272","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142213341","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":"Analysis and evaluation of the usefulness of open data for research projects—The case of the BrineRIS project","authors":"Justyna Górniak-Zimroz,&nbsp;Magdalena Worsa-Kozak,&nbsp;Karolina Szostak","doi":"10.1002/gdj3.269","DOIUrl":"10.1002/gdj3.269","url":null,"abstract":"<p>Open research data refer to publicly available scientific information that can be accessed free of charge, usually provided by public data sources. Users must comply with specific requirements set by the institutions providing the data and always acknowledge the source of the data when processing, transmitting, storing or publishing it. One of the tasks of the BrineRIS project is the mapping of brine resources, requiring reliable data on the location of exploration facilities, environmental characteristics, brine exploitation parameters and formal and legal information. These data come from a review of various archives, databases and survey results. Initially, information on the location of the sources should be obtained, which may be available in publicly accessible databases. Next, geological and hydrogeological parameters, which can be obtained from scientific papers and reports, are useful. An important part of the project is also the analysis of legal regulations concerning water extraction and environmental protection. Therefore, data should be obtained from various sources, such as public administration, state institutions or research units. These will serve to develop the database needed to perform further analyses within the BrineRIS research project. It is therefore crucial to carefully collect, analyse and assess the usefulness of the data.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"948-973"},"PeriodicalIF":3.3,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.269","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142213366","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":"LETKF-based Ocean Research Analysis (LORA) version 1.0","authors":"Shun Ohishi,&nbsp;Takemasa Miyoshi,&nbsp;Takafusa Ando,&nbsp;Tomohiko Higashiuwatoko,&nbsp;Eri Yoshizawa,&nbsp;Hiroshi Murakami,&nbsp;Misako Kachi","doi":"10.1002/gdj3.271","DOIUrl":"10.1002/gdj3.271","url":null,"abstract":"<p>Local ensemble transform Kalman filter (LETKF)-based Ocean Research Analysis (LORA) version 1.0 datasets for western North Pacific (WNP) and Maritime Continent (MC) regions (LORA-WNP and -MC, respectively) are released through the JAXA-RIKEN Ocean Analysis website. The LORA datasets are created using an eddy-resolving LETKF-based ocean data assimilation system with satellite sea-surface temperature, salinity, and height data and with in-situ temperature and salinity data assimilated daily. The LORA datasets include 128-member ensemble analyses at the sea surface (2D), each term of mixed-layer temperature and salinity budget equations, and the related variables (2D) such as mixed-layer depth and heat and freshwater fluxes as well as system grid information and analysis ensemble mean and spread (3D), from August 2015 to January 2024 (as of June 2024). The LORA datasets are useful for geoscience research and practical applications, especially for particle tracking, boundary conditions of atmospheric models, and research on spatiotemporal variations in sea-surface temperature and salinity.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"995-1006"},"PeriodicalIF":3.3,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.271","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142213367","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 global database of tsunami deposits","authors":"María Teresa Ramírez-Herrera,&nbsp;Oswaldo Coca","doi":"10.1002/gdj3.270","DOIUrl":"https://doi.org/10.1002/gdj3.270","url":null,"abstract":"<p>Geomorphic environments play a crucial role in influencing the preservation and characteristics of tsunami deposits. This paper introduces a global database of tsunami deposits, encompassing information on deposit locations, thematic data such as geomorphic environments and proxies and bibliographic details. Additionally, the database features maps incorporating environmental parameters and the precise locations of tsunami deposits. The primary utility of this database lies in assessing progress and identifying gaps in knowledge. It also involves analysing the relationship between environmental parameters and interpreting areas with varying probabilities of tsunami deposit preservation. The files are readily compatible with GIS software and can seamlessly integrate into spatial databases associated with tsunamis or other hazards. This contributes significantly to disaster risk management, enhancing preparedness and response efforts by providing a comprehensive historical dataset on tsunamis. Future applications of the database include the incorporation of modern deposits, boulders and new data from paleotsunami and historical studies. By enhancing data with thematic information, such as dating techniques and creating timelines, the database facilitates a more comprehensive understanding. The correlation between geomorphic environments and proxies aids in selecting sampling sites and identifying suitable proxies for analysis. Encouraging an open-access approach, this database invites all interested researchers to include and modify additional information. The information compiled for this database serves multiple purposes: (1) assessing the global distribution of tsunami deposits; (2) identifying knowledge gaps in tsunami deposits; (3) guiding the selection of study areas for further research and finally; (4) enabling a meta-analysis of the information gathered.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"974-994"},"PeriodicalIF":3.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.270","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142435893","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":"Global 24 solar terms phenological MODIS normalized difference vegetation index dataset in 2001–2022","authors":"Jingyu Yang,&nbsp;Taixia Wu,&nbsp;Xiying Sun,&nbsp;Kai Liu,&nbsp;Muhammad Farhan,&nbsp;Xuan Zhao,&nbsp;Quanshan Gao,&nbsp;Yingying Yang,&nbsp;Yuhan Shao,&nbsp;Shudong Wang","doi":"10.1002/gdj3.268","DOIUrl":"10.1002/gdj3.268","url":null,"abstract":"<p>Phenology reflects the life cycle of vegetation, crucial for monitoring global vegetation diversity, ecosystem stability, and agricultural security. However, there is currently no dataset related to phenology. The 24 solar terms (24STs), based on the Sun's annual motion, reflect the changing seasons, temperature fluctuations, and phenological phenomena. They serve as a vital means to characterize vegetation phenology. This study generate a global Normalized Difference Vegetation Index (NDVI) product based on 24STs using Moderate Resolution Imaging Spectroradiometer (MODIS) on the Google Earth Engine (GEE). The 24STs NDVI dataset adopted the maximum value compositing (MVC) to process the NDVI values between two adjacent 24STs. The product has a spatial resolution of 250 m, covering the period from 2001 to 2022. Comparing with the MOD13Q1, good spatiotemporal consistency between the two datasets was observed, confirming the reliability of the 24STs product. However, the 24STs product holds distinct phenological meanings. This product introduces, for the first time, a vegetation index dataset based on the 24STs, enriching the vegetation index dataset and facilitating further research on phenology.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"936-947"},"PeriodicalIF":3.3,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.268","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927324","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":"Southern Ocean sea ice, icebergs, and meteorological data from maritime sources for the period 1929 to 1940","authors":"Dmitry V. Divine,&nbsp;Svetlana Divina,&nbsp;Ole Edvard Bjørge,&nbsp;Elisabeth Isaksson,&nbsp;Harald Dag Jølle,&nbsp;Ivar Stokkeland,&nbsp;Mariela Vasquez Guzman,&nbsp;Sally Wilkinson,&nbsp;Clive Wilkinson","doi":"10.1002/gdj3.265","DOIUrl":"10.1002/gdj3.265","url":null,"abstract":"<p>Maritime historical documentary sources of weather and state of sea surface including sea ice can aid in filling a known climate knowledge gap for the Southern Ocean and Antarctica for the first half of the 20th century. This study presents a data set of marine climate, sea ice and icebergs recovered from a collection of logbooks from mainly Norwegian whaling factory ships that operated in the Southern Ocean during 1929–1940. The data set comprises some 8000 weather and 4000 sea ice/open sea records from austral summers of the study period. This paper further discusses the structure and content of most common Norwegian maritime documentary sources of the period along with the practices of logging information relevant for the study, such as time keeping, positioning and making weather observations. An emphasis was made on recovery of notes on sea ice and icebergs and their interpretation in terms of WMO categories of sea ice concentration. Data, including ship-related metadata from all individual documents are homogenized and structured to a common machine-readable format that simplifies its ingestion into relevant climate data depositories.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"902-920"},"PeriodicalIF":3.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.265","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141883387","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":"Seismic-electromagnetic signals from two monitoring stations in Southern Italy: Electromagnetic time series release","authors":"Ivana Ventola,&nbsp;Marianna Balasco,&nbsp;Michele De Girolamo,&nbsp;Luigi Falco,&nbsp;Marilena Filippucci,&nbsp;Laura Hillmann,&nbsp;Gerardo Romano,&nbsp;Vincenzo Serlenga,&nbsp;Tony Alfredo Stabile,&nbsp;Angelo Strollo,&nbsp;Andrea Tallarico,&nbsp;Simona Tripaldi,&nbsp;Thomas Zieke,&nbsp;Agata Siniscalchi","doi":"10.1002/gdj3.262","DOIUrl":"10.1002/gdj3.262","url":null,"abstract":"<p>The seismic-electromagnetic phenomenon entails the generation of transient electromagnetic signals, which can be observed both simultaneously (co-seismic) and preceding (pre-seismic) a seismic wave arrival. Following the most accredited hypothesis, these signals are mainly due to electrokinetic effects, generated on microscopic scale in porous media containing electrolytic fluids. Thus, the seismic-electromagnetic signals are expected to be suitable for the detection and tracking of crustal fluids. Despite the growing interest in this phenomenon, there is a lack of freely available observational database of earthquake-related electromagnetic signals recorded at co-located seismic and magnetotelluric stations. To fill this gap, we set up two multicomponent monitoring stations in two seismically active areas of Southern Italy: the Gargano Promontory and the High Agri Valley. This work is both aimed to systematically analyse earthquake-generated seismic-electromagnetic recordings and to make the collected database accessible to the scientific community.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"863-872"},"PeriodicalIF":3.3,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.262","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740460","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}