Earth System Science Data Discussions最新文献

{"title":"A detailed radiostratigraphic data set for the central East Antarctic\u0000Plateau spanning the last half million years","authors":"M. Cavitte, D. Young, R. Mulvaney, C. Ritz, J. Greenbaum, G. Ng, S. Kempf, E. Quartini, G. Muldoon, J. Paden, M. Frezzotti, J. Roberts, C. Tozer, D. Schroeder, D. Blankenship","doi":"10.5194/essd-2020-393","DOIUrl":"https://doi.org/10.5194/essd-2020-393","url":null,"abstract":"Abstract. We present an ice-penetrating radar data set which consists of 26 internal reflecting horizons (IRHs) that cover the entire Dome C area of the East Antarctic plateau, the most extensive to date in the region. This data set uses radar surveys collected over the space of 10 years, starting with an airborne international collaboration in 2008 to explore the region, up to the detailed ground based surveys in support of the Beyond EPICA – Oldest Ice (BE-OI) European Consortium. Through direct correlation with the EPICA-DC ice core, we date 19 IRHs that span the past four glacial cycles, from the beginning of the Holocene to over 350 ka. We indirectly date and provide stratigraphic information for seven older IRHs using an 1-D ice flow inverse model, going back to an estimated 700 ka. Depth and age uncertainties are quantified for all IRHs and provided as part of the data set. The IRH data set presented in this study is available at the U.S. Antarctic Program Data Center (USAP-DC) (https://doi.org/10.15784/601411, Cavitte et al., 2020) and represents a contribution to the SCAR AntArchitecture program.\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133306203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"INGe: Intensity-ground motion dataset for Italy","authors":"I. Oliveti, L. Faenza, A. Michelini","doi":"10.5194/essd-2020-372","DOIUrl":"https://doi.org/10.5194/essd-2020-372","url":null,"abstract":"Abstract. In this paper we present an updated and homogeneous earthquake data set for Italy compiled by joining the Italian Macroseismic Database DBMI15 and the Engineering Strong-Motion (ESM) accelerometric data bank. The database has been compiled through an extensive procedure of selection and revision based on two main steps: 1) the removal of several earthquakes in DBMI15 because the data source has been considered to be largely unreliable and 2) the extraction of all the localities reporting intensity data which are located within 3 km from the accelerograph stations that recorded the data. The final data set includes 323 recordings from 65 earthquakes and 227 stations in the time span 1972–2016. The events are characterized by magnitudes in the range 4.0–6.9 and depths in the range 0.3–45.0 km. Here, we illustrate the data collection and the properties of the database in terms of recording, event and station distributions as well as Mercalli-Cancani-Sieberg (MCS) macroseismic intensity points. Furthermore, we discuss the most relevant features of engineering interest showing several statistics with reference to the most significant metadata (such as moment magnitude, several distance metrics, style of faulting etc). The data set can be downloaded from data repository Zenodo at https://doi.org/10.13127/inge.1 (Oliveti et., 2020).","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"os-48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127785366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatially explicit global gross domestic product (GDP) data set consistent with the Shared Socioeconomic Pathways","authors":"Tingting Wang, F. Sun","doi":"10.5281/ZENODO.4350027","DOIUrl":"https://doi.org/10.5281/ZENODO.4350027","url":null,"abstract":"Abstract. The increasing demand of ScenarioMIP is calling for GDP projections of high resolution for the future Shared Socioeconomic Pathways (SSPs) in both socioeconomic development and in climate change of adaption and mitigation research. While to date the global GDP projections for five SSPs are mainly provided at national scales, and the gridded data set are very limited. Meanwhile, the historical GDP can be disaggregated using nighttime light (NTL) images but the results are not open accessed, making it cumbersome in climate change impact and socioeconomic risk assessments across research disciplines. To this end, we produce a set of spatially explicit global Gross Domestic Product (GDP) that presents substantial long-term changes of economic activities for both historical period (2005 as representative) and for future projections under all five SSPs with a spatial resolution of 30 arc-seconds. Chinese population in SSP database were first replaced by the projections under the two-children policy implemented since 2016 and then used to spatialize global GDP using NTL images and gridded population together as fixed base map, which outperformed at subnational scales. The GDP data are consistent with projections from the SSPs and are freely available at http://doi.org/10.5281/zenodo.4350027 (Wang and Sun, 2020). We also provide another set of spatially explicit GDP using the global LandScan population as fixed base map, which is recommended at county or even smaller scales where NTL images are limited. Our results highlight the necessity and availability of using gridded GDP projections with high resolution for scenario-based climate change research and socioeconomic development that are consistent with all five SSPs.","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121417940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"University of Nebraska UAS profiling during LAPSE-RATE","authors":"A. Islam, A. Shankar, A. Houston, Carrick Detweiler","doi":"10.5194/essd-2020-374","DOIUrl":"https://doi.org/10.5194/essd-2020-374","url":null,"abstract":"Abstract. This paper describes the data collected by the University of Nebraska-Lincoln (UNL) as part of the field deployment during the Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) flight campaign in July 2018. UNL deployed two multirotor unmanned aerial systems (UASs) at various sites in the San Luis Valley (Colorado, USA) for data collection in support of three science missions: convection-initiation, boundary layer transition, and cold air drainage flow. We conducted 172 flights resulting in over 1300 minutes of cumulative flight time. Our novel design for the sensor housing onboard the UAS was employed in these flights to meet the aspiration and shielding requirements of the temperature/humidity sensors, and attempt to separate them from the mixed turbulent airflow from the propellers. Data presented in this paper include time-stamped temperature and humidity data collected from the sensors, along with the three-dimensional position and velocity of the UAS. Data are quality controlled and time-synchronized using a zero-order-hold interpolation without additional post processing. The full dataset is also made available for download at (https://doi.org/10. 5281/zenodo.4306086 (Islam et al. , 2020)).\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127717076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Last Interglacial (sensu lato, ~130 to 75 ka) sea level history from cave deposits: a global standardized database","authors":"O. Dumitru, V. Polyak, Y. Asmerom, B. Onac","doi":"10.5194/essd-2020-387","DOIUrl":"https://doi.org/10.5194/essd-2020-387","url":null,"abstract":"Abstract. Cave deposits are powerful archives for reconstructing past sea levels as they are generally protected from weathering and erosion by their location and can be dated with U-series methods. Two main categories of cave deposits are recognized as sea level indicators: phreatic overgrowth on speleothems (POS) and submerged vadose speleothems (SVS). POS have the great advantage that they precipitate on preexisting vadose supports at a brackish water level equivalent to sea level when air-filled chambers of coastal caves are flooded by rising sea. SVS are also useful, but sea level is inferred indirectly as periods of growth provide constraints on maximum sea level positions, whereas growth hiatuses, sometimes difficult to observe, may indicate times when cave passages are submerged by sea high stands, hence they record minimum sea level elevations. Here we describe a compilation that summarizes the current knowledge of MIS 5 (sensu lato) sea level captured by cave deposits. We used the framework of the World Atlas of Last Interglacial Shorelines (WALIS), a comprehensive sea level database, to provide a standardized format in order to facilitate scientific research on MIS 5 sea level. The discussion is MIS 5e-centered, but records that capture MIS 5c and 5a are also included. We present the data from 59 cave deposits (26 sea-level index points and 33 limiting points) in coastal caves located in eight different locations, and we include the spatial coverage, the samples used and their accuracy as indicators of sea level, the isotopic characteristics used to generate the U-Th chronologies, and their scientific relevance to understand past sea-level changes. The paper also emphasizes how some of these indicators are useful not only for the information they offer about the eustatic sea level, but more importantly: i) those from tectonically stable areas provide information on Earth deformation and regional ice sheet histories, thus refining the glacial isostatic adjustments models and ii) those from active regions can constrain regional tectonic uplift rates. The standardized sea-level database presented here is the first of its kind derived from cave deposits and contains all the information needed to assess former paleo relative sea level and the chronological constraints associated with them. The database is available open-access at http://doi.org/10.5281/zenodo.4313861 (Dumitru et al., 2020).\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128230014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"“A Global Compilation of U-series Dated Fossil Coral Sea-level Indicators for the Last Interglacial Period (MIS 5e)” by Peter M. Chutcharavan and Andrea Dutton","authors":"P. Chutcharavan, A. Dutton","doi":"10.5194/essd-2020-381","DOIUrl":"https://doi.org/10.5194/essd-2020-381","url":null,"abstract":"Abstract. This dataset is a comprehensive, global compilation of published uranium series (U-series) dated fossil coral records from ~150–110 thousand years ago, as well as associated elevation measurements and sample metadata. In total, 1312 U-series measurements from 994 unique coral colonies are included in the current version of the dataset, all of which have been normalized and recalculated using the same decay constant values. Two example geochemical screening criteria have been included to assist users with identifying altered fossil corals that display geochemical open-system behaviour, and the originally published interpretations on age quality have been preserved within the sample metadata. Additionally, a clear distinction has been made between coral colonies that are in primary growth position, which may be used for relative sea-level reconstructions and colonies that have been transported/reworked, which cannot be used for these purposes. Future research efforts involving fossil coral sea-level reconstructions should emphasize an integrated and holistic approach that combines careful assessment of U-series age quality with high-precision surveying techniques and detailed facies/stratigraphic observations. This database is available at http://doi.org/10.5281/zenodo.4309796 (Chutcharavan and Dutton 2020).\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126335637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mineral element stocks in the Yedoma domain: a first assessment in\u0000ice-rich permafrost regions","authors":"Arthur Monhonval, S. Opfergelt, Elisabeth Mauclet, B. Pereira, Aubry Vandeuren, G. Grosse, Lutz Schirrmeister, M. Fuchs, P. Kuhry, J. Strauss","doi":"10.5194/essd-2020-359","DOIUrl":"https://doi.org/10.5194/essd-2020-359","url":null,"abstract":"Abstract. With permafrost thaw, significant amounts of organic carbon (OC) previously stored in frozen deposits are unlocked and become potentially available for microbial mineralization. This is particularly the case in ice-rich regions such as the Yedoma domain. Excess ground ice degradation exposes deep sediments and their OC stocks, but also mineral elements, to biogeochemical processes. Interactions of mineral elements and OC play a crucial role for OC stabilization and the fate of OC upon thaw, and thus regulate carbon dioxide and methane emissions. In addition, some mineral elements are limiting nutrients for plant growth or microbial metabolic activity. A large ongoing effort is to quantify OC stocks and their lability in permafrost regions, but the influence of mineral elements on the fate of OC or on biogeochemical nutrient cycles has received less attention. The reason is that there is a gap of knowledge on the mineral element content in permafrost regions. Here, we use a portable X-ray fluorescence device (pXRF) to provide (i) the first large-scale Yedoma domain Mineral Concentrations Assessment (YMCA) dataset ( https://doi.pangaea.de/10.1594/PANGAEA.922724 ; Monhonval et al., in review), and (ii) estimates of mineral element stocks in never thawed (since deposition) ice-rich Yedoma permafrost and previously thawed and partly refrozen Alas deposits. The pXRF method for mineral element quantification is non-destructive and offers a complement to the classical dissolution and measurement by optical emission spectrometry (ICP-OES) in solution. This allowed a mineral element concentration (Si, Al, Fe, Ca, K, Ti, Mn, Zn, Sr and Zr) assessment on 1292 sediment samples from the Yedoma domain with lower analytical effort and affordable costs relative to the classical ICP-OES method. pXRF measured concentrations were calibrated using standard alkaline fusion and ICP-OES measurements on a subset of 144 samples (R2 from 0.725 to 0.996). The results highlight that (i) the most abundant mineral element in the Yedoma domain is Si (2739 ± 986 Gt) followed by Al, Fe, K, Ca, Ti, Mn, Zr, Sr, and Zn, and that (ii) Al and Fe (598 ± 213 and 288 ± 104 Gt) are present in the same order of magnitude than OC (327–466 Gt).","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115303571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"More dynamic than expected: An updated survey of surging glaciers\u0000in the Pamir","authors":"F. Goerlich, T. Bolch, F. Paul","doi":"10.5194/essd-2020-79","DOIUrl":"https://doi.org/10.5194/essd-2020-79","url":null,"abstract":"Abstract. The investigation of surging glaciers using remote sensing has recently seen a strong increase as freely available satellite data and digital elevation models (DEMs) can provide detailed information about surges that often take place in remote or inaccessible regions. Apart from analysing individual surges, satellite information is increasingly used to collect capable data on surging glaciers. Related inventories have recently been published for several regions in High Mountain Asia including the Karakoram, parts of the Pamir and western Kunlun Shan, but information for the entire Pamir is solely available from a historic database listing about 80 glaciers with confirmed surges. Here we present an updated inventory of confirmed glacier surges for the Pamir that considers results from earlier studies and is based on a systematic analysis of Landsat image time series (1988 to 2018) and DEM differences. Actively surging glaciers were identified from animations, flicker images and the typical elevation change patterns. Selected historic and contemporary very high-resolution imagery were used to confirm surges. In total, we identified 206 spatially distinct surges within 186 glacier bodies, mostly clustered in the northern and central part of the Pamir. Where possible, minimum and maximum glacier extents were digitized, but often interacting tributaries made a clear separation challenging. Most surging glaciers (n = 70) are found in the larger size classes (> 10 km2), but two of them are very small ( https://doi.pangaea.de/10.1594/PANGAEA.914150 (Goerlich et al., 2020).","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129198644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes in China's anthropogenic emissions during the COVID-19 pandemic","authors":"B. Zheng, Qiang Zhang, G. Geng, Q. Shi, Y. Lei, K. He","doi":"10.5194/essd-2020-355","DOIUrl":"https://doi.org/10.5194/essd-2020-355","url":null,"abstract":"Abstract. The COVID-19 pandemic lockdowns led to a sharp drop in socio-economic activities in China in 2020, including reductions in fossil fuel use, industry productions, and traffic volumes. The short-term impacts of lockdowns on China's air quality have been measured and reported, however, the changes in anthropogenic emissions have not yet been assessed quantitatively, which hinders our understanding of the causes of the air quality changes during COVID-19. Here, for the first time, we report the anthropogenic air pollutant emissions from mainland China during the first eight months of 2020 by using a bottom-up approach based on the near real-time data. The COVID-19 lockdown was estimated to have reduced China's anthropogenic emissions substantially between January and March in 2020, with the largest reductions in February. Emissions of SO2, NOx, CO, NMVOCs, and primary PM2.5 were estimated to have decreased by 29 %, 31 %, 27 %, 26 %, and 21 %, respectively, in February 2020 compared to the same month in 2019. The reductions in anthropogenic emissions were dominated by the industry sector for SO2 and PM2.5 and were contributed approximately equally by the industry and transportation sectors for NOx, CO, and NMVOCs. With the spread of coronavirus controlled, China's anthropogenic emissions rebounded in April and since then returned to the comparable levels of 2019 in August 2020. The provinces in China have presented nearly synchronous decline and rebound in anthropogenic emissions, while Hubei and the provinces surrounding Beijing recovered slower due to the extension of lockdown measures. The reduction ratios of anthropogenic emissions from 2019 to 2020 can be accessed from https://doi.org/10.6084/m9.figshare.c.5214920.v1 (Zheng et al., 2020) by species, month, sector, and province.\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114273684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MIS 5e sea-level proxies in the eastern Mediterranean coastal region","authors":"B. Mauz, D. Sivan, E. Galili","doi":"10.5194/essd-2020-357","DOIUrl":"https://doi.org/10.5194/essd-2020-357","url":null,"abstract":"Abstract. Mediterranean raised beaches were subject to Quaternary research since the early years of the 20th century. The uniqueness of a warm-loving molluscs fauna immigrating into the Mediterranean made the coastline a prime subject for studying Quaternary sea-level changes. Today, we have a detailed picture of this historically important coastline characterised by tectonically dormant coastal zone alternating with zones that are subject to subsidence or uplift. As part of the Word Atlas of last interglacial shorelines (WALIS) database we compiled 21 MIS 5e proxies for the for the eastern Mediterranean area available at http://doi.org/10.5281/zenodo.4274178 (Israel; Sivan and Galili, 2020) and at http://doi.org/10.5281/zenodo.4283819 (Turkey, Egypt, Tunisia; Mauz, 2020). All these datapoints are sea-level indicators of variable quality situated between −1 ± 4 m and 7 ± 2 m resulting in a reconstructed MIS 5e palaeo-sea level situated between −1 ± 4 m and 13 ± 10 m.","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132404181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}