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10,016 results for “Observation”
Model Output for: "MESSENGER observations of Mercury's planetary ion escape rates and their dependence on true anomaly angle"
<p>In the manuscript titled ‘MESSENGER Observations of Mercury’s Planetary Ion Escape Rates and Their Dependence on True Anomaly Angle’, submitted to Geophysical Research Letters, we provide an analysis of test sodium ion (Na+) particles. These test particles, integral to our research, are illustrated in Figure 4. This dataset contains an ASCII file with detailed information and descriptions of these test particles.</p>
Data for evaluation of modelled versus observed NMVOC compounds at EMEP sites in Europe
<p>Data (model outputs, emission files, python scripts) for the publication of "<span>Evaluation of modelled versus observed NMVOC compounds at </span><span>EMEP sites in Europe".</span></p>
Intermittent Lobe Reconnection under Prolonged Northward Interplanetary Magnetic Field Condition: Insights from Cusp Spot Event Observations
<p>SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America. <br>We would like to thank British Antarctic Survey (https://www.bas.ac.uk/project/superdarn) and the University of Saskatchewanan (https://superdarn.ca) for hosting the SuperDARN data mirrors access. <br>The EISCAT dataset is available from the Madrigal database (http://millstonehill.haystack.mit.edu). <br>We acknowledge the use of DMSP/SSUSI data provided by the Johns Hopkins University Applied Physics Laboratory (https://cdaweb.gsfc.nasa.gov). <br>Additionally, the OMNI dataset is available from the OMNIWeb service online of NASA/GSFC's Space Physics Data Facility's (https://spdf.gsfc.nasa.gov/pub/data/omni/).</p>
Reprocessing of Three-Decade GNSS Observations: Millimeter-Level Global Velocity Field and Plate Motion Model Refinement
<p>The accurate and reliable Terrestrial Reference Frame (TRF) functions as a unified spatiotemporal datum crucial for solid earth research, encompassing disciplines such as geodesy and geodynamics. High-precision GNSS velocity field products stand out as pivotal foundational data for the maintenance of the TRF. This dataset encapsulates the outcomes of two GNSS velocity field refinement products: Global GNSS Velocity Model 2020 (GGVM2020) and the Global Interpolation Velocity Model 2020 (GIVM2020). GGVM2020 comprises velocity values and formal errors derived from over 3000 GNSS sites worldwide. And GIVM2020 incorporates speed values from approximately 2000 grid points on land globally, with a grid spacing of 3 degrees.</p>
Simulation details for: Radar signatures and surface observations of elevated convection associated with damaging surface winds
<p>Identifying radar signatures indicative of damaging surface winds produced by convection remains a challenge for operational meteorologists, especially within environments characterized by strong low-level static stability and convection for which inflow is presumably entirely above the planetary boundary layer. Numerical model simulations suggest the most prevalent method through which elevated convection generates damaging surface winds is via "up-down" trajectories, where a near-surface stable layer is dynamically lifted and then dropped with little to no connection to momentum associated with the elevated convection itself. Recently, a number of unique convective episodes during which damaging surface winds were produced by apparently elevated convection coincident with mesoscale gravity waves were identified and cataloged for study. A novel radar signature indicative of damaging surface winds produced by elevated convection is introduced through six representative cases. One case is then explored further via a high-resolution model simulation and related to the conceptual model of "up-down" trajectories. Understanding the processes responsible for, and radar signature indicative of, damaging surface winds produced by gravity-wave coincident convection will help operational forecasters identify and ultimately warn for a previously underappreciated phenomenon that poses a threat to lives and property.</p>
Magnetic field enhancements in the interplanetary solar wind: Diverse processes manifesting a uniform observation type?
<p>Interlaced magnetic flux ropes are a subject of investigation in various space environments, including the solar corona, interplanetary solar wind, and magnetosheath. In this study, we utilize a Hall Magnetohydrodynamics (MHD) model to replicate these interactions within selected regions. By employing plasma flow to propel two flux ropes of various parameters towards each other, we examine the effect of their relative helicity on the ensuing process. Our simulations, coupled with vector analysis, found the existence of flux ropes with opposing helicity along their axes (counter-helical) in some of the resultant interactions. These findings underscore the need to identify and study counter-helical flux ropes in space. The study presented here contributes new comprehension of space plasma dynamics and new insights into the solar wind in control of space weather.</p>
Data for: JWST COMPASS: NIRSpec/G395H Transmission Observations of the Super-Earth TOI-836b
<p>Data and models accompanying the publication "JWST COMPASS: NIRSpec/G395H Transmission Observations of the Super-Earth TOI-836b". Here we include:</p> <ul> <li>Data, ExoTiC-JEDI light curves and transmission spectrum of JWST NIRSpec/G395H transit observations</li> <li>Data, Eureka! light curves and transmission spectrum of JWST NIRSpec/G395H transit observations</li> <li>Models, PICASO models and data shown in Figure 5</li> </ul> <p>Manuscript DOI: [] and [paper link]</p>
Mesosphere/lower thermosphere 3-dimensional spatially resolved winds observed by Chinese multistatic meteor radar network using the newly developed VVP method
<p>This dataset supports the article "Mesosphere/lower thermosphere 3-dimensional spatially resolved winds observed by Chinese multistatic meteor radar network using the newly developed VVP method" . The data are provided in MatLab format.</p>
Converging findings of climate models and satellite observations on the positive impact of European forests on cloud cover
<p>Overview:<br>This repository hosts a comprehensive dataset resulting from a Space for Time (S4T) analysis (<em>Duveiller et al. 2018</em>). The dataset spans monthly data from 2004 to 2014, providing detailed insights into cloud cover dynamics and land cover characteristics. Leveraging observations from the Cloud CCI MODIS-Aqua dataset (<em>Stengel et al. 2017</em>) and RegCM5 (<em>Giorgi et al. 2023</em>) model outputs at 0.05 degrees resolution, it offers valuable resources for researchers studying atmospheric and terrestrial interactions.</p> <p>Contents:</p> <p>s4t_ESACCI.zip:<br>Output of the space-for-time algorithm applied to the Global MODIS-Aqua cloud cover data for low, medium, and high clouds.<br>s4t_RegCM5.zip:<br>Output of the space for time algorithm applied to the European RegCM5 cloud data for low, medium, and high clouds.<br>Variables:</p> <p>Cloud Area Fractions:<br>Includes low (cll), medium (clm), and high (clh) cloud area fractions, expressed as percentages.<br>Cloud layers are categorized based on cloud top pressure (CTP), following the convention of the International Satellite Cloud Climatology Project.</p>
Insights into Internal Solitary Waves East of Dongsha Atoll from Integrating Geostationary Satellite and Mooring Observations
<p>The dataset used to produce the figures in the manuscript. All the data are in MATLAB file format. </p>
Satellite Precipitation Products data performance evaluation with observed datasets
<p>Datasets used for evaluation of Satellite Precipitation Products (SPPs). We used Three open-source datasets from different sources for our evaluation of the SPPs applicability in real-time flood forecasting.</p>
Gridded MDA8 surface ozone observations for the EU and US during 1993-2014
<p>Maximum daily eight-hour average (MDA8) surface ozone derived from gridded hourly observational datasets for the European and US domain [Schnell et al., 2014; 2015; Schnell and Prather, 2017], according to the MDA8 nomenclature of the European Union [EUR-LEX, 2008]. Note, we use a 358-day calendar, i.e. all months have 30 days except for February (28 days).</p> <p>EUR-LEX. (2008). Directive 2008/50/EC of the European parliament and of the council of 21 May 2008 on ambient air quality and cleaner air for Europe (2008/50/EC). Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32008L0050</p> <p>Schnell, J. L., Holmes, C. D., Jangam, A., Prather, M. J. (2014). Skill in forecasting extreme ozone pollution episodes with a global atmospheric chemistry model. Atmos Chem Phys, 14(15), 7721-7739. doi:10.5194/acp-14-7721-2014</p> <p>Schnell, J. L., Prather, M. J., Josse, B., Naik, V., Horowitz, L. W., Cameron-Smith, P., Bergmann, D., Zeng, G., Plummer, D. A., Sudo, K., Nagashima, T., Shindell, D. T., Faluvegi, G., Strode, S. A. (2015). Use of North American and European air quality networks to evaluate global chemistry–climate modeling of surface ozone. Atmos. Chem. Phys., 15(18), 10581-10596. doi:10.5194/acp-15-10581-2015</p> <p>Schnell, J. L., Prather, M. J. (2017). Co-occurrence of extremes in surface ozone, particulate matter, and temperature over eastern North America. Proceedings of the National Academy of Sciences, 114(11), 2854-2859. doi:10.1073/pnas.1614453114</p>
Plastic damage in sea ice - model outputs and observations.
<p>Sea ice model outputs and observations analyzed in the paper: "On the sensitivity of sea ice deformation statistics to plastic damage".</p> <p>For the outputs, there is one file every 6 hours (for January 2002). Each folder represents one experiment with the associated snapshot files each containing a matrix of the given variable.</p> <p>The observations are the 3-day gridded velocity derivatives. The files are numpy arrays (.npy) containing time slices for every 3-day period for January 2002.</p> <p> </p> <p><strong>1. Naming convention of the files</strong></p> <p><em>Model outputs</em></p> <p>The folders are named according to the model configuration following the names used in (Savard and Tremblay, 2024):</p> <p>"Model name" + ( + "configuration" + )</p> <p>The files in each configuration follow the following convention:</p> <p>"Variable" + "year" + _ + "month" + _ + "day" + _ + "hour" + _ + "minutes" + . + "experiment number"</p> <p>There is also an info file, which provides the numerical parameters used in each run:</p> <p>info + . + "experiment number"</p> <p><em>Observations</em></p> <p>The files are the velocity derivatives:</p> <p>"partial derivative" + .npy</p> <p>There is also a mask for the period of January-February-March:</p> <p>mask80JFM.npy</p> <p> </p> <p><strong>2. Variables included</strong></p> <ul> <li><em>u,v</em> : sea ice velocity in the x,y directions (in m/s);</li> <li><em>A</em>: ice concentration per grid cell (0 -- 1);</li> <li><em>h</em>: mean ice thickness per grid cell (in m);</li> <li><em>dam</em>: plastic damage per grid cell (0 -- 1); </li> <li><em>div</em>: sea ice divergence per grid cell (in s^-1);</li> <li><em>shear</em>: sea ice shear per grid cell (in s^-1).</li> </ul> <p> </p> <p><strong>4. Recommended citation usage</strong></p> <p>If <em>any</em> or <em>all</em> simulations included in the current archive are used in a future study, we ask to cite this archive and the plastic damage paper (Savard and Tremblay, 2024). If the observations provided here are used in a future study, we ask to cite this archive and the original paper in which the data is used (Kwok, 1997).</p> <p>The original RGPS 3-day gridded dataset can be accessed here: https://asf.alaska.edu/data-sets/derived-data-sets/seaice-measures/sea-ice-measures-data-products/</p> <p> </p>
Figure 11 in Non-aggressive competition between males of Srilankametrus yaleensis (Kovařík et al., 2019) (Scorpionidae), and other types of agonistic behavior observed in scorpions
Figure 11. Dinorhax rostrumpsittaci (Simon, 1877), two males in threatening condition.
Figure 4 in Non-aggressive competition between males of Srilankametrus yaleensis (Kovařík et al., 2019) (Scorpionidae), and other types of agonistic behavior observed in scorpions
Figure 4. Escaping stage (right male (A2) fled).
Dataset for the research article titled "Evaluation of Reanalysis and Satellite Products against Ground-based Observations in a Desert Environment "
Open the record for dataset details and reuse information.
The data for "Search for gravitational-lensing signatures in the full third observing run of the LIGO–Virgo network"
<p>This material is part of several data products associated with the publication "Search for gravitational-lensing signatures in the full third observing run of the LIGO–Virgo network" from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the paper (<a href="https://arxiv.org/abs/2304.08393">arXiv</a>) and the related material linked from this page.</p><p><strong>Data release</strong></p><p>This data release contains plotting scripts, jupyter notebooks and datasets for the figures / tables in the aforementioned paper. Each script/notebook have detailed instructions and comments.</p><p><strong>How to download all files from this page</strong></p><p>If you would like to download all files on this page, we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>:</p><p>pip install zenodo_get zenodo-get RECORD_ID_OR_DOI</p><p>where the record ID for the most recent version of this page is v5 and IDs for other versions can be found in the Versions section at the side of this page.</p>
Data from the micrometeorological tower of the Antarctic Modeling Observation System (ATMOS) project of the 40th Brazilian Antarctic Operation (OPERANTAR XL) to calculate the CO2 flux (FCO2)
<p>Micrometeorological tower data obtained by the "Antarctic Modeling Observation System" (ATMOS) project. These data were collected in the southern summer of 2021/2022 during the 40th Brazilian Antarctic Operation (OPERANTAR XL) and were used to calculate CO2 fluxes (FCO2).</p> <p>A 9 m high metal micrometeorological tower was installed on the bow of the Polar Ship Almirante Maximiano, 8.75 m above sea level, for sampling atmospheric variables. In the tower, the Motion Pack II was installed, on the main shaft of the tower, to determine the ship's movement in the orthogonal directions xp, yp and zp of the platform's coordinate system, at a frequency of 20 Hz. As well as, a GPS (Global Positioning System) and an electronic compass, to determine the ship's geographic position and speed. The movement of the ship influences wind speed measurements, and as a solution, a wind speed correction was carried out.<br>An IRGASON sensor (Campell Scientific®) was placed on the secondary shaft of the tower, configured to perform measurements at 20 Hz. The IRGASON has an open path infrared gas analyzer that measures the concentrations of CO2 and water vapor (H2O), a three-dimensional sonic anemometer, which measures the 3 vector components of the wind, and a thermohygrometer that measures air temperature and humidity. From the IRGASON collections, it is possible to calculate the CO2 flux using the Vortex Covariance method.</p>
LI-COR (LI-850) sensor data obtained by the Antarctic Modeling Observation System (ATMOS) project during the 40th Brazilian Antarctic Operation (OPERANTAR XL) and were used to calculate the partial pressure of CO2 (pCO2)
<p>LI-COR (LI 850) sensor data obtained by the "Antarctic Modeling Observation System" (ATMOS) project. These data were collected in the southern summer of 2021/2022 during the 40th Brazilian Antarctic Operation (OPERANTAR XL) and were used to calculate the partial pressure of seawater CO2 (pCO2sea)</p> <p>The LI-850 carbon dioxide analyzer was installed in the laboratory aft of H41 together with a balancer to measure the CO2 concentration of the water. The collection system occurs as follows: the ship's saltwater piping system collects seawater, when this water enters the balancer it generates turbulence. The turbulence generated causes the CO2 present in the water to come into balance with the air. The air that comes out of the balancer is pumped into the LI-850, by its internal pump, and thus, the equipment measures the concentration of CO2 present in the water. To ensure that the air inside the balancer is actually balanced with the seawater, the air leaving the LI-850 is pumped back into the balancer, closing the circuit. From these data it is possible to calculate pCO2sea.</p>
Hourly surface ozone observations across China
<p>Historical monitoring data of air quality sites across China (2014-2022) obtained by the China National Environmental Monitoring Center (CNEMC; <a href="https://air.cnemc.cn:18007/">https://air.cnemc.cn:18007/</a>). The file named <strong>Station_information.csv</strong> contains details about the stations, including the city location, latitude, longitude, and elevation (m).<strong> </strong>The <strong>ozone.zip </strong>file encompasses ozone concentration data from 2014 to 2022, featuring columns for date, hour, and surface ozone concentrations at each station code(ug/<span>m<sup>3</sup></span>; Beijing time: UTC+8:00). Further information about the data is available from scholar Xiaolei Wang, who also offers additional data for download on his personal webpage (<a href="https://quotsoft.net/air/">https://quotsoft.net/air/</a>).</p>
ScienceDex guides
Understand access before you commit
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.