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594 results for “Mission”
Supplementary data for "BepiColombo mission confirms stagnation region of Venus and reveals its large extent"
<p>Dataset of the data presented in the figures of Persson et al. (2022), Nature Communications, "BepiColombo mission confirms stagnation region of Venus and reveals its large extent". https://doi.org/10.1038/s41467-022-35061-3</p> <p>Full author team:</p> <p>M. Persson<sup>1</sup>*, S. Aizawa<sup>1</sup>, N. André<sup>1</sup>, S. Barabash<sup>2</sup>, Y. Saito<sup>3</sup>, Y. Harada<sup>4</sup>, D. Heyner<sup>5</sup>, S. Orsini<sup>6</sup>, A. Fedorov<sup>1</sup>, C. Mazelle<sup>1</sup>, Y. Futaana<sup>2</sup>, L.Z. Hadid<sup>7</sup>, M. Volwerk<sup>8</sup>, G. Collinson<sup>9</sup>, B. Sanchez-Cano<sup>10</sup>, A. Barthe<sup>1</sup>, E. Penou<sup>1</sup>, S. Yokota<sup>11</sup>, V. Génot<sup>1</sup>, J.A. Sauvaud<sup>1</sup>, D. Delcourt<sup>7</sup>, M. Fraenz<sup>12</sup>, R. Modolo<sup>13</sup>, A. Milillo<sup>6</sup>, H.-U. Auster<sup>5</sup>, I. Richter<sup>5</sup>, J.Z.D. Mieth<sup>5</sup>, P. Louarn<sup>1</sup>, C.J. Owen<sup>14</sup>, T.S. Horbury<sup>15</sup>, K. Asamura<sup>3</sup>, S. Matsuda<sup>16</sup>, H. Nilsson<sup>2</sup> M. Wieser<sup>2</sup>, T. Alberti<sup>6</sup>, A. Varsani<sup>8</sup>, V. Mangano<sup>6</sup>, A. Mura<sup>6</sup>, H. Lichtenegger<sup>8</sup>, G. Laky<sup>8</sup>, H. Jeszenszky<sup>8</sup>, K. Masunaga<sup>3</sup>, C. Signoles<sup>1</sup>, M. Rojo<sup>1</sup>, G. Murakami<sup>3</sup></p> <p><sup>1</sup>Institut de Recherche en Astrophysique et Planétologie, Centre National de la Recherche Scientifique, Université Paul Sabatier - Toulouse III, Centre National d’Etudes Spatiales, Toulouse, France</p> <p><sup>2</sup>Swedish Institute of Space Physics, Kiruna, Sweden</p> <p><sup>3</sup>Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, Japan</p> <p><sup>4</sup>Department of Geophysics, Graduate School of Science, Kyoto University, Kyoto, Japan</p> <p><sup>5</sup>Institute for Geophysics and Extraterrestrial Physics, Technische Universität Braunschweig, Braunschweig, Germany</p> <p><sup>6</sup>Institute of Space Astrophysics and Planetology, Istituto Nazionale di Astrofisica, Rome, Italy</p> <p><sup>7</sup>Laboratoire de Physique des Plasmas (LPP), Centre National de la Recherche Scientifique, Observatoire de Paris, Sorbonne Université, Université Paris Saclay, École Polytechnique, Institut Polytechnique de Paris</p> <p><sup>8</sup>Space Research Institute, Austrian Academy of Sciences, Graz, Austria</p> <p><sup>9</sup>National Aeronautic and Space Administration, Goddard Space Flight Center, Greenbelt, Maryland, USA</p> <p><sup>10</sup>School of Physics and Astronomy, University of Leicester, Leicester, UK</p> <p><sup>11</sup>Department of Earth and Space Science, Graduate School of Science, Osaka University, Japan</p> <p><sup>12</sup>Max-Planck-Institute for Solar System Research, Göttingen, Germany</p> <p><sup>13</sup>Laboratoire Atmosphères, Milieux, Observations Spatiales, Institut Pierre Simon Laplace, Université Versailles Saint Quentin en Yvelines, Université Paris-Saclay, Université Pierre Marie Curie, Centre National de la Recherche Scientifique, Guyancourt, France</p> <p><sup>14</sup>Mullard Space Science Laboratory, University College London, Holmbury St. Mary, UK </p> <p><sup>15</sup>Imperial College London, South Kensington Campus, London, UK </p> <p><sup>16</sup>Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa, Japan</p> <p> *Corresponding author. Email: <a href="mailto:moa.persson@irap.omp.eu">moa.persson@irap.omp.eu</a></p>
Precipitation Microphysics in Tropical Cyclones: A Global Perspective Using the NASA Global Precipitation Measurement Mission Dual-Frequency Precipitation Radar
<p>This dataset includes all files (in .npy format) that was used to plot distributions of the slopes of vertical profiles of reflectivity in the liquid phase, in the ice phase, and echo top heights using the NASA Global Precipitation Measurement mission Dual-Frequency Precipitation Radar. </p>
Maximizing Societal Benefit Across Multiple Hyperspectral Earth Observation Missions: A User Needs Approach - DATA and CODES
<p>In this repository you will find data elicited from Italian and the NASA Surface Biology and Geology (SBG) Designated Observable users. the first page "read me first" provides a description of the first sheet "User requirements merged" where you will find the reqirements codified for both community of users.</p> <p>Other files include the codes used throug the R software to develop several useful figures.</p>
La Mission Soledad
4th Grade Mission Project - Mission Soledad Source: Objaverse 1.0 / Sketchfab
Dominican Republic Mission Cost Analysis
ClinicalTrials.gov study NCT01872364. IPD Sharing: Not stated. Countries: 1. Publications: 42.
MISSION Severe Asthma Modern Innovative Solutions to Improve Outcomes in Severe Asthma.
ClinicalTrials.gov study NCT02509130. IPD Sharing: Not stated. Countries: 1. Publications: 4.
MiSSION STRONG - Preventing AOS Misuse in the National Guard
ClinicalTrials.gov study NCT02181283. IPD Sharing: NO. Countries: 1. Publications: 2.
Participatory Action Research to Evaluate the Delivery of the MISSION ABC Service Model and Assess Health Service and Clinical Outcomes
ClinicalTrials.gov study NCT03096509. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Allergy Testing of Soldiers Prepared for International Mission
ClinicalTrials.gov study NCT05807958. IPD Sharing: NO. Countries: 1. Publications: 2.
Earlier Diagnosis and Better Treatment Mission Related to the Cohort Programme
ClinicalTrials.gov study NCT05266872. IPD Sharing: NO. Countries: 1. Publications: 1.
Analysis of Heart Rate Variability During Emergency Flight Simulator Missions in Fighter Pilots
ClinicalTrials.gov study NCT04487899. IPD Sharing: NO. Countries: 1. Publications: 5.
MISSION COPD - Modern Innovative SolutionS in Improving Outcomes iN COPD
ClinicalTrials.gov study NCT02534766. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Operational Evaluation of a Photic Countermeasure to Improve Alertness, Performance, and Mood During Nightshift Work on a 105-day Simulated Human Exploration Mission to Mars
ClinicalTrials.gov study NCT01169233. IPD Sharing: Not stated. Countries: 1. Publications: 35.
MISSION-CJ for Justice-Involved Homeless Veterans
ClinicalTrials.gov study NCT04523337. IPD Sharing: NO. Countries: 1. Publications: 2.
Microbiome and Immunosuppression: The Mission Study
ClinicalTrials.gov study NCT04953715. IPD Sharing: NO. Countries: 1. Publications: 3.
Data from: In situ reference datasets from the TropiSAR and AfriSAR campaigns in support of upcoming spaceborne biomass missions
Open the record for dataset details and reuse information.
NASA-SSH Along-Track Sea Surface Height from Standardized Reference Missions Version 1
The NASA-SSH Along-Track Sea Surface Height from Standardized Reference Missions Version 1 dataset produced by NASA provide observations of sea surface height, or sea level, anomaly measured using radar altimeter satellites in the reference mission orbit. These include TOPEX/Poseidon, the Jason series, and Sentinel-6. The data begin in Oct 1992, with data from TOPEX/Poseidon, and continues to the present. In this data set all missions have been referenced to a common baseline, additional quality control has been performed, and errors with wavelengths around one orbital cycle have been reduced. <br>The data consist of along-track observations of sea surface height, collected approximately once per second (1 Hz), and are parsed into files containing one day’s worth of data per file. A flag variable is included to allow users to easily select only valid observations, and a variable containing sea surface height with the flag applied and a small amount along track smoothing (~20 km), is suggested for most users. <br>Additionally, a “basin” flag variable is provided, along with a table defining it. This allows users to easily select all observations from a specific body of water. The basin flag assigns a number to each point corresponding to a specific ocean basin or lake. A table is included with a text description of each basin number. A text version of that table is available (https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/basin_name_table.txt). The basin definitions can be downloaded as a shape file from https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/basin_polygon_files.tar.gz, or as a kml file https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/NASA-SSH_Basins.kmz. <br>New data will be released approximately once per week, with a latency of a few weeks.
NASA-SSH Simple Gridded Sea Surface Height from Standardized Reference Missions Only Version 1
The NASA-SSH Simple Gridded Sea Surface Height from Standardized Reference Missions Only Version 1 dataset produced by NASA provides 2-D maps of sea surface height, or sea level, anomaly once every 7 days. The grids are based on observations of sea surface height from the radar altimeter satellites in the reference mission orbits, including TOPEX/Poseidon, the Jason series, and Sentinel-6. The data begin in Oct 1992 and continue through the present. They are created using the NASA-SSH Along-Track Sea Surface Height from Standardized Reference Missions Version 1 dataset. <br>The grids consist of 10-days worth of observations, which covers approximately 1 complete repeat cycle of observations from the reference missions. The grids are produced on a 0.5-degree latitude and longitude grid, by taking a simple gaussian weighted spatial average with a width of 100 km. The grids are produced every 7 days to allow for easy interpolation in time. However, since they are created using 10-days of data, there is some overlap of information between adjacent time steps. The grids are also created using the basin flags to avoid mixing data from distinct ocean basins (for example, to avoid mixing observations from the Caribbean Sea with observations from the Pacific across the Isthmus of Panama). Connected basins are allowed to share data, however. This is accomplished by using a table of connections between basins. The basin connection table is available (https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/basin_connection_table.txt). The basin definitions can be downloaded as a shape file from https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/basin_polygon_files.tar.gz, or as a kml file https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/NASA-SSH_Basins.kmz. <br>A new grid will be released approximately once per week, with a latency of a few weeks.
Synthetic river datasets built for testing and development of the Surface Water and Ocean Topography mission discharge algorithms
<p><strong>1.Summary</strong></p> <p>Datasets used for testing the performance of discharge estimation algorithms built in support of the Surface Water and Ocean Topography satellite mission. The benchmarking manuscript entitled “Exploring the factors controlling the performance of the Surface Water and Ocean Topography mission discharge algorithms” is currently under review at Water Resources Research. Once the manuscript is accepted, its DOI will be included here.</p> <p><strong>2.File description</strong></p> <p>The dataset is divided into four groups: 1-Ideal data, 2-Varying Temporal Sampling, 3-Measurement Uncertainty, and 4-SWOT Sampling and Uncertainty. Ideal data contains daily measurements with no observational uncertainty. Varying Temporal Sampling downsamples the ideal measurements considering different temporal frequencies with complete sets assuming: 1 measurement every 2 days, 3 days, 4 days, 5 days, 7 days, 10 days, and 21 days. The measurement uncertainty set adds errors to cross-sectional heights and widths, which are used to compute reach average height, width, and slope considering error corruption. The final set SWOT Sampling and Uncertainty accounts for SWOT temporal sampling and measurement uncertainty. Sets containing uncertainty have extra height, width, and slope attributes with the word true appended to the attribute name. Such attributes represent the uncorrupted measurements at the cross-section and reach scales. Height, width, and slopes for the SWOT sampling and Uncertainty dataset containing the value of negative 9999 denote points that are not observed at a particular location and time step.</p> <p>Data will be contained in one NetCDF file per river. The file contains the following groups and variables:</p> <p><strong>/River_Info/</strong></p> <p>Name: River name, data type: char</p> <p>QWBM: Mean annual discharge from the water balance model WBMsed (Cohen et al., 2014)</p> <p>rch_bnd: Reach boundaries measured in meters from the upstream end of the model</p> <p>gdrch: Reaches used in the study. Used to exclude small reaches defined around low-head dams and other obstacles where Manning’s equation should not be applied.</p> <p><strong>/XS_Timeseries/</strong></p> <p>t: Time measured in days since the first day or “0-January-0000” for cases when specific dates were available. Dimension: 1,time step.</p> <p>Z: Bed elevation in meters. Dimension: Cross-section, time step.</p> <p>xs_rch: Reach number for each cross-section. Dimension: Cross-section,1.</p> <p>X: Flow distance measured from the most upstream end of the model to the cross-section (meters). Dimension: Cross-section, 1.</p> <p>longitude: Cross-section longitude in decimal degrees. Dimension: Cross-section,1.</p> <p>latitude: Cross-section latitude in decimal degrees. Dimension: Cross-section,1.</p> <p>W: River width in meters. Dimension: Cross-section, time step.</p> <p>Wtrue: River width in meters. Dimension: Cross-section, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the water surface elevation value with no uncertainty.</p> <p>Q: Discharge (m<sup>3</sup>/s). Dimension: Cross-section, time step.</p> <p>H: Water surface elevation in meters. Dimension: Cross-section, time step.</p> <p>Htrue: Water surface elevation in meters. Dimension: Cross-section, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the water surface elevation value with no uncertainty.</p> <p>A: Cross-sectional area of flow in m<sup>2</sup>. Dimension: Cross-section, time step.</p> <p>P: Wetted perimeter in meters. Dimension: Cross-section, time step.</p> <p>n: Manning’s roughness. Dimension: Cross-section, time step.</p> <p><strong>/Reach_Timeseries/</strong></p> <p>t: Time measured in days since the first day or “0-January-0000” for cases when specific dates were available. Dimension: 1,time step.</p> <p>W: Reach averaged river width in meters. Dimension: Reach, time step.</p> <p>Wtrue: Reach averaged river width in meters. Dimension: Reach, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the width value with no uncertainty.</p> <p>Q: Reach averaged discharge (m<sup>3</sup>/s). Dimension: Reach, time step.</p> <p>H: Reach averaged water surface elevation in meters. Dimension: Reach, time step.</p> <p>Htrue: Reach averaged water surface elevation in meters. Dimension: Reach, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the water surface elevation value with no uncertainty.</p> <p>S: Reach averaged water surface slope in meters per meter. Reach, time step.</p> <p>Strue: Reach averaged water surface slope in meters per meter. Dimension: Reach, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the slope value with no uncertainty.</p> <p>A: Reach averaged area of flow in m<sup>2</sup>. Dimension: Reach, time step.</p> <p><strong>References</strong></p> <p>Cohen, S., A. J. Kettner, and J. P. M. Syvitski (2014), Global suspended sediment and water discharge dynamics between 1960 and 2010: Continental trends and intra-basin sensitivity, <em>Glob. Planet. Change</em>, <em>115</em>, 44-58, doi: <a href="https://doi.org/10.1016/j.gloplacha.2014.01.011">https://doi.org/10.1016/j.gloplacha.2014.01.011</a>.</p> <p> </p>
Reconstruction of magnetospheric storm-time dynamics using cylindrical basis functions and multi-mission data mining
<p>This zip file contains data used to create figures and tables, describing the results of the paper "Reconstruction of magnetospheric storm-time dynamics using cylindrical basis functions and multi-mission data mining", by N. A. Tsyganenko, V. A. Andreeva, and M. I. Sitnov.</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.