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708 results for “Global dataset”
Improved version: A global dataset of spatially-dependent extreme sea levels
<p>These files provide an improved version of the global dataset of spatially-dependent extreme sea levels (Li et al. 2023), and can be used to assess coastal flood risk considering realistic spatial dependence structure in any coastal regions around the globe.</p> <p>We made improvements by:</p> <ul> <li>Estimating inter-cluster dependence by considering cluster connectivity;</li> <li>Calculating the year information for generated sythetic events.</li> </ul> <p>More details on the new dataset can be found in Li et al. (2024) of which a preprint doi will be provided soon. If you plan to use it or have used it, feel free to contact me and please cite our 2024 paper.</p> <p> </p> <p>References:</p> <p>Li, H., Haer, T., Couasnon, A., Enríquez, A. R., Muis, S., & Ward, P. J. (2023). A spatially-dependent synthetic global dataset of extreme sea level events. Weather and Climate Extremes, 41, 100596. https://doi.org/10.1016/j.wace.2023.100596</p> <p>Li, H., Eilander, D., Ward, P. J., & Haer, T. (2024). Improving global-scale coastal risk estimates by considering spatial dependence. Submitted. Preprint: <a href="https://doi.org/10.22541/essoar.172641608.83190937/v1">10.22541/essoar.172641608.83190937/v1</a>. </p> <p> </p>
Global PM2.5 Dataset: Hybrid Calibration of CAMS and MERRA-2 PM2.5 Reanalysis Products during 2017-2019
<p>By integrating two reanalysis PM<sub>2.5</sub> products (CAMSRA, MERRA-2), a <strong>global daily hybrid-calibrated PM<sub>2.5</sub> concentration dataset</strong> is generated through the proposed CM-HC scheme with ERT model. This products include <strong>1095</strong> global PM<sub>2.5</sub> GeoTIFF files, starting from Jan 01, 2017 to Dec 31, 2019 (about <strong>0.95GB</strong> memory after uncompressing this zip file).</p> <p>To prove the superiority of this product, some experiments are implemented as follows: comparing with 1) two original products; 2) results of two separate calibration schemes with ERT; 3) results of CM-HC with other three ML models (RF, GBDT, XGBoost). Above analyses include two aspects, that is, the accuracy results and mapping effects. More details can be viewed at the thesis.</p> <p>One <strong>GeoTIFF</strong> file includes one-day calibrated PM<sub>2.5</sub> data. It is worth noting that the files contain the data of ocean area, however, our thesis only shows the results of land area in order to visually display the mapping effect before and after calibrating. Also, there is no site on the sea to validate in our study.</p>
Global PM2.5 Dataset: Hybrid Calibration of CAMS and MERRA-2 PM2.5 Reanalysis Products during 2017-2019
<p>By integrating two reanalysis PM<sub>2.5</sub> products (CAMSRA, MERRA-2), a <strong>global daily hybrid-calibrated PM<sub>2.5</sub> concentration dataset</strong> is generated through the proposed CM-HC scheme with ERT model. This products include <strong>1095</strong> global PM<sub>2.5</sub> GeoTIFF files, starting from Jan 01, 2017 to Dec 31, 2019 (about <strong>0.95GB</strong> memory after uncompressing this zip file).</p> <p>To prove the superiority of this product, some experiments are implemented as follows: comparing with 1) two original products; 2) results of two separate calibration schemes with ERT; 3) results of CM-HC with other three ML models (RF, GBDT, XGBoost). Above analyses include two aspects, that is, the accuracy results and mapping effects. More details can be viewed at the thesis.</p> <p>One <strong>GeoTIFF</strong> file includes one-day calibrated PM<sub>2.5</sub> data. It is worth noting that the files contain the data of ocean area, however, our thesis only shows the results of land area in order to visually display the mapping effect before and after calibrating. Also, there is no site on the sea to validate in our study.</p>
Abundance decline in the avifauna of the European Union reveals global similarities in biodiversity change: Input datasets & species results
<p>This archive contain the two input datasets of bird population estimates and trend estimates underpinning the journal article: <strong>Abundance decline in the avifauna of the European Union reveals global similarities in biodiversity change. </strong>It also contains the species level results obtained from the Bayesian hierarchical model described in section 2.2.1 of the paper.</p>
Qatar Peninsula' High Vulnerability to Oil Spills and its Implication for the Potential Disruption in Global Gas Supply (Datasets)
<p>Outputs of oil spill dispersal simulations performed backward in time using OpenDrift for the following study:</p> <p>Anselain, T., Heggy, E., Dobbelaere, T., & Hanert, E. (2022). Qatar Peninsula’ High Vulnerability to Oil Spills and its Implication for the Potential Disruption in Global Gas Supply. <em>Nature Sustainability</em>. In press.</p>
New global dataset on historical water-related conflict and cooperation events
<p>The water-related conflict and cooperation events database was created as a part of a larger project: "The missing link: how does the climate affect human conflicts and collaborations through water?" where the goal is to increase understanding of how people and the climate affect water flows and how, in turn, these changes affect cooperation and conflicts over water. Formas, project 2017-00,608 support this project.</p> <p>The database includes a collection of cooperation and conflict events between 1951 and 2019. The Transboundary Freshwater Dispute Database (2010) and WCC (Pacific Institute, Oakland, CA, 2022) were used as data on water-related acts of cooperation and conflict over time. As TFDD cooperation data ends in 2008, cooperation events were extended following a similar methodology as was used in the creation of TFDD. Further, geographic locations and regional classifications were added to all events, which can be used to create visualizations and extract subsets of the database for different parts of the world. The database methodology flow chart included in the files gives a brief overview of steps taken to prepare and process the data into the database.</p> <p>The openly available scientific article in Science of the Total Environment (STOTEN) highlight findings using this dataset and gives further explanations relating to the database. The article can be found here: <a href="https://doi.org/10.1016/j.scitotenv.2023.161555">https://doi.org/10.1016/j.scitotenv.2023.161555</a>.</p>
GSDR-I Global Sub-Daily Precipitation Indices - Dataset
<p>Gauge and gridded time series indices and supplementary statistics from GSDR-I (an observation-based dataset of global sub-daily precipitation indices)</p>
Dataset for "Assessing the aerosols, clouds and their relationship over the northern Bay of Bengal using a global climate model"
<p><strong>The dataset is organized into two ZIP folders as described below.</strong></p> <p><strong>1. Model simulation dataset:</strong> This folder (<strong>merged_data_files</strong>) contains 2 folders.</p> <ol> <li>Netcdf files of CESM experiments output for the study. A total of 8 experiments have been performed which can be identified by the filenames (CAM5, CAM5G, Q6, Q48, Q96, UV6, UV6Q48). Each experiment has a total of 360 time steps corresponding to daily output December-January-February (DJF) months of 2006-2010. It is to be noted that all the simulated cloud variables are from the MODIS COSP simulator output and have been restricted to low clouds (grids with cloud top pressure less than 680 hPa have been excluded). Following are the variables in each of the netcdf file of experiments which are analysed in the research article: <ol> <li> <p>AODVISEXT - Aerosol optical depth visible range</p> </li> <li> <p>LCODEXTLOW - MODIS Liquid Cloud Optical Thickness</p> </li> <li> <p>LCFEXTLOW - MODIS Liquid Cloud Fraction</p> </li> <li> <p>LCEREXTLOW - MODIS Liquid Cloud Particle Size</p> </li> <li> <p>LWPEXTLOW - MODIS Cloud Liquid Water Path</p> </li> <li> <p>CTPEXTLOW - MODIS Cloud Top Pressure</p> </li> <li> <p>CDNC - Cloud droplet number concentration</p> </li> </ol> </li> <li>CSV files of CTP-COT joint histogram output for each experiment averaged over the study region during DJF season for 2006-2010.</li> </ol> <p><strong>2. Study region shapefile:</strong> This folder (<strong>study_region_shapefile</strong>) contains the shapefile having the outline of the northern Bay of Bengal region which is our study region. The ACI sensitivities discussed in the article have been calculated using the spatial average of data points extracted for this region for the December-January-February months for the years 2006-2010 (360 time steps).</p>
Dataset for: Indirect nitrous oxide emission factors of fluvial networks can be predicted by dissolved organic carbon and nitrate from local to global scales
<p>Streams and rivers are important sources of nitrous oxide (N<sub>2</sub>O), a powerful greenhouse gas. Estimating global riverine N<sub>2</sub>O emissions is critical for the assessment of anthropogenic N<sub>2</sub>O emission inventories. The indirect N<sub>2</sub>O emission factor (EF<sub>5r</sub>) model, one of the bottom-up approaches, adopts a fixed EF<sub>5r</sub> value to estimate riverine N<sub>2</sub>O emissions based on IPCC methodology. However, the estimates have considerable uncertainty due to the large spatiotemporal variations in EF<sub>5r</sub> values. Factors regulating EF<sub>5r</sub> are poorly understood at the global scale. Here, we combine 4-year in situ observations across rivers of different land use types in China, with a global meta-analysis over six continents, to explore the spatiotemporal variations and controls on EF<sub>5r</sub> values. Our results show that the EF<sub>5r</sub> values in China and other regions with high N loads are lower than those for regions with lower N loads. Although the global mean EF<sub>5r</sub> value is comparable to the IPCC default value, the global EF<sub>5r</sub> values are highly skewed with large variations, indicating that adopting region-specific EF<sub>5r</sub> values rather than revising the fixed default value is more appropriate for the estimation of regional and global riverine N<sub>2</sub>O emissions. The ratio of dissolved organic carbon to nitrate (DOC/NO<sub>3</sub><sup>-</sup>) and NO<sub>3</sub><sup>-</sup> concentration are identified as the dominant predictors of region-specific EF<sub>5r</sub> values at both regional and global scales because stoichiometry and nutrients strictly regulate denitrification and N<sub>2</sub>O production efficiency in rivers. A multiple linear regression model using DOC/NO<sub>3</sub><sup>-</sup> and NO<sub>3</sub><sup>-</sup> is proposed to predict region-specific EF<sub>5r</sub> values. The good fit of the model associated with easily obtained water quality variables allows its widespread application. This study fills a key knowledge gap in predicting region-specific EF<sub>5r</sub> values at the global scale and provides a pathway to estimate global riverine N<sub>2</sub>O emissions more accurately based on IPCC methodology.</p> <p>This dataset is a global integrated N<sub>2</sub>O dataset including data from 4-year (2017-2020) in situ measurements of six large rivers in China, 3-year (2018-2020) in situ measurements of urban river networks in Beijing of China, and 825 measurements from 70 published papers over six continents. The data includes dissolved N<sub>2</sub>O concentration, biogeochemical (DOC, NO<sub>3</sub><sup>-</sup>, NH<sub>4</sub><sup>+</sup>, temperature, and DO), climatological (climate zones), and geographic (region, location, and land cover) information.</p>
Dataset: Global market drivers for sustainable cephalopod food systems
<p>1. Aquatic food systems are important contributors to global food security to satisfy an intensifying demand for protein-based diets, but global economic growth threatens marine systems. Cephalopod (octopus, squid, cuttlefish) fisheries can contribute to food security; however their sustainable exploitation requires understanding connections between nature's contributions to people (NCP), food system policies and human wellbeing.</p> <p>2. Our global literature review methodology examined what is known about cephalopod food systems, value chains and supply chains and associated market drivers. For analysis, we followed the IPBES conceptual framework to build a map of the links between cephalopod market drivers, NCP and good quality of life (GQL). Then we mapped cephalopod food system dynamics onto IPBES (in)direct drivers of change relating to catch, trade and consumption.</p> <p>3. This research contributes knowledge about key factors relating to cephalopods that can support transitions towards increased food security: the value of new aquatic food species; food safety and authenticity systems; place-based innovations and empowerment of communities; and consumer behaviour, lifestyle and motivations for better health and environmental sustainability along the food value chain. We outline requirements for a sustainable, equitable cephalopod food system policy landscape that values nature's contributions to people, considers UN Sustainable Development Goals and emphasises the role of seven overlapping IPBES (in)direct drivers of change: Economic, Governance, Sociocultural and Socio-psychological, Technological, Direct Exploitation, Natural Processes and Pollution. We present a novel market-based adaptation of the IPBES conceptual framework – our 'cephalopod food system framework', to represent how the cephalopod food system functions and how it can inform processes to improve sustainability and equity of the cephalopod food system.</p> <p>4. This synthesised knowledge provides the basis for diagnosing opportunities (e.g. high demand for products) and constraints (e.g. lack of data about how supply chain drivers link to cephalopod NCP) to be considered regarding the role of cephalopods in transformations towards a resilient and more diversified seafood production system. This social-ecological systems approach could apply to other wild harvest commodities with implications for diverse marine species and ecosystems and can inform those working to deliver marine and terrestrial food security while preserving biodiversity.</p>
A common resequencing‐based genetic marker dataset for global maize diversity
<p>Maize (<em>Zea mays ssp. mays</em>) populations exhibit vast amounts of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole genome resequencing strategies, identifying millions of segregating single-nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies, and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here we employ resequencing data from 1,276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of ~366 million segregating variants and ~46 million high confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering time genes using previously published trait datasets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.</p>
Sensitivity of the global ocean carbon sink to the ocean skin in a climate model : IPSL-CM6 dataset
<p>Daily outputs of 2000-2014 historical run with IPSL-CM6 (Boucher et al. 2020) with Bellenger et al. (2017) parameterization of the ocean skin (Bellenger et al. 2023)</p> <p>CM62-OSCO2-hist-2000-2014-1D.nc contains air-sea CO2 fluxes:</p> <p>F_CTL : Prognostic classical bulk flux from the control (CTL) run</p> <p>F_MBL_CTL : Diagnostic flux using the interactive ocean skin and the equilibrium model (Woolf et al. 2016) from the CTL run</p> <p>F_TBL_CTL : Diagnostic flux using the interactive ocean skin and the rapid model (Woolf et al. 2016) from the CTL run</p> <p>F_Wat_CTL : Diagnostic flux using a uniform ocean skin (Watson et al. 2020) from the CTL run</p> <p>F_MBL_CPL: Prognostic flux using the interactive ocean skin and the equilibrium model from the coupled (CPL) run</p> <p>CM62-OSCO2-hist-2000-2014-1D_oceanskin.nc contains ocean skin related outputs:</p> <p>tos / sos : Temperature / salinity of the ocean model's first level</p> <p>t_int / s_int : Temperature /salinity at the interface</p> <p>t_mbl / s_mbl : Temperature /salinity at the base of the Mass Boundary Layer (MBL)</p> <p>t_tbl : Temperature at the base of the Thermal Boundary Layer (TBL)</p> <p><em>Bellenger H., K. Drushka, W. E. Asher, G. Reverdin, M. Katsumata, and M. Watanabe: Extension of the prognostic model of sea surface temperature to rain-induced cool and fresh lenses, J. Geophys. Res. Oceans, 122, 484–507</em></p> <p>Bellenger, H., Bopp, L., Ethé, C., Ho, D., Duvel, J. P., Flavoni, S., Guez L., T. Kataoka, X. Perrot, L. Parc, and M. Watanabe (2023). Sensitivity of the global ocean carbon sink to the ocean skin in a climate model. Journal of Geophysical Research : Oceans, 128, e2022JC019479. <a href="https://doi.org/10.1029/2022JC019479">https://doi.org/10.1029/2022JC019479</a></p> <p><em>Boucher, O., and coauthors, 2020: Presentation and evaluation of the IPSL-CM6A-LR climate model, Journal of Advances in Modeling Earth System, 12, e2019MS002010, doi:</em><a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2019MS002010"><em>10.1029/2019MS002010</em></a></p> <p><em>Watson A. J., U. Schuster, J. D. Shutler, T. Holding, I. G. C. Ashton, P. Landschützer, D. K. Woolf, and L. Goddijn-Murphy, 2020: Revised estimates of ocean-atmosphere CO<sub>2</sub> flux are consistent with carbon inventory, Nature Comm., 11:4422, https://doi.org/10.1038/s41467-020-18203-3</em></p> <p><em>Woolf, D. K., P. E. Land, J. D. Shutler, L. M. Goddijn-Murphy, and C. J. Donlon, 2016: On the calculation of air-sea fluxes of CO2 in the presence of temperature and salinity gradients, J. Geophys. Res. Oceans, 121, 1229-1248.</em></p> <p> </p> <p> </p>
Dataset : Global mangrove root production and its controls
<p>This Dataset include root production reported in individual mangrove root production studies published until the 23 March 2022.</p> <p>Alongside of this data, it reports associated environmental data and metadata.</p> <p>For full methodology report to the methodology section of the article: "Global mangrove root production, its controls and roles in the blue carbon budget of mangroves" by Arnaud et al. 2023 (Global Change Biology).</p>
ODYM-RECC Copper dataset, used for sector-level estimates for global future copper demand and the potential for resource efficiency
<p>Complete Model database with 105 parameter files used in the ODYM-RECC Copper model (github: https://github.com/SteffiKlose/ODYM-RECC-Copper.git) used for Sector-level estimates for global future copper demand and the potential for resource efficiency (<a href="https://doi.org/10.1016/j.resconrec.2023.106941">https://doi.org/10.1016/j.resconrec.2023.106941</a>)</p> <p>This dataset is based on the Database of the ODYM-RECC v2.4 model, used for the GLOBAL case study on material efficiency and climate change mitigation (https://doi.org/10.5281/zenodo.4671644)</p>
The legacy of one hundred years of climate change for organic carbon stocks in global agricultural topsoils - full dataset
<p>This zip folder contains a txt and a shp file with predicted soil organic carbon stocks for a total of 931149 points on agricultural land across the globe at three different timepoints. The initial value (2018) for the scenarios c (constant carbon input) and v (variable carbon input) was derived from the FAO GSP Global SOC map published in 2018. the values in 1969 and 1919 are the results of backwards modelling with RothC model to estimate past climate change effects on SOC stocks. Details can be found in the publication " The legacy of one hundred years of climate change for organic carbon stocks in global agricultural topsoils" as published in Scientific Reports.</p>
Dataset for Manuscript: Comparing Urban Anthropogenic NMVOC Measurements with Representation in Emission Inventories - A Global Perspective
<p>Urban observations of individual NMVOCs and the calculated or reported emission ratios used for comparison to emission inventories.</p>
A global historical twice-daily (daytime and nighttime) land surface temperature dataset produced by AVHRR observations from 1981 to 2021 (2006–2021)
<ul> <li>Land surface temperature (LST) is a key variable for monitoring and evaluating global long-term climate change. However, existing satellite-based twice-daily LST products only date back to 2000, which makes it difficult to obtain robust long-term temperature variations. We developed the first global historical twice-daily LST dataset (GT-LST), with a spatial resolution of 0.05°, using Advanced Very High Resolution Radiometer Level-1b Global Area Coverage data from 1981 to 2021.</li> <li>Validation with in situ measurements from Surface Radiation Budget sites showed that the overall root-mean-square errors of GT-LST varied from 2.0 K to 3.9 K. Inter-comparison with a common LST product (i.e., MYD11A1) revealed that the overall root-mean-square-difference was approximately 3.2 K.</li> <li>More details of this dataset can be seen in <em>readme.pdf.</em></li> <li>This dataset provides GT-LST product from 2006 to 2021.</li> </ul>
Global Reservoir Storage (GRS) dataset
<p>The Global Reservoir Storage (GRS) dataset is comprised of monthly storage records from 1999 to 2018 for 7,245 reservoirs (6,658 km<sup>3 </sup>total capacity) as reported in Global Reservoir and Dam Database (GRanD) v1.3.</p>
A Global Lake/Reservoir Surface Extent Dataset (GLRSED)
<p>Global lake/reservoir surface water extent is the basic input data for many studies. Although there are some datasets at present, there are problems such as incomplete or spatial inconsistency exist among them due to various reasons like different data sources and dynamic change characteristics of the surface water. Here, a new Global Lake/Reservoir Surface Extent Dataset (GLRSED) that contains spatial extent and basic attributes (e.g., name, area, lake type and source) of 2.17 million lakes/reservoirs was produced based on HydroLAKES, GRanD and OpenStreetMap. By spatially overlaying GLRSED with other auxiliary data, we identified mountain lakes, endorheic lakes, reservoirs, glacier-fed lakes and permafrost-fed lakes, etc. In addition, we calculated the Surface Water and Ocean Topography (SWOT) orbits passing through each lake. The dataset could provide basic data for global lake/reservoir monitoring, as well as the study on the impact of human actions and climate changes on lake/reservoir freshwater availability, etc.</p>
A reference dataset of global gridded average-state specific yield
<p>The uploaded data is related with our manuscript "A reference dataset of global gridded average-state specific yield".</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.