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607 results for “wind data”
Wind Solar Wind Experiment (SWE) Faraday Cup, Solar Wind Plasma Reduced Ion Distribution Functions, 92 s Data
WIND Solar Wind Experiment, SWE, Faraday cup data: this data set contains three-dimensional measurements of ions in the energy range 150 eV to 8 keV. Placed 15° above and below equatorial plane of the spacecraft, the Faraday Cups measure ion charge flux as a function of epoch, cup number, orientation angle, and bias grid potential. For each time point, a full spectrum is comprised of charge flux measurements at the two Faraday cup sensors at 20 azimuth angles for each of 31 energy-per-charge windows with 1240 data points per spectrum. Spectra are built up over approximately 92 s intervals. The effective area of the Faraday cup sensor as a function of incidence angle onto the cup is also provided.
First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) CSU Wind Profiler Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to seek the basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987) a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud system.The CSU wind profiler is a five beam wind profiler with high and low modes of operation. The wind profiler is a clear air doppler radar and operates at a frequency of 404.37 MHz. It operated with a height resolution of 250m and measured radial velocities up to about 15km.
Wind Solar Wind Experiment (SWE) Thermal Plamsa Moments, Key Parameter (K0), 99 s Data
Wind SWE Key Parameter data: proton density, thermal speed, flow velocity vectors, and spacecraft position vectors. Various versions differ slightly from each other. The version at MIT has flow velocity vectors experessed bby using Geocentric Solar Ecliptic, GSE, Cartesian and spherical representations and GSE Cartesian position vectors. The version available via nssdcftp and FTPBrowser has temperature instead of thermal speed and has no flow direction angles. The CDAWeb version has flow velocity and spacecraft position vectors in both GSE and Geocentric Solar Magnetospheric, GSM, coordinates, flow dynamic pressure, NmV^2, and velocity and density quality flags. The data were progressively despiked in passing from CDAWeb to MIT to nssdcftp/FTPBrowser.Use of the Quality Variables:Quality flags are set in the analysis program that generates the KP data. Previous descriptions of their meaning were out of date.Good data is indicated by a quality flag equal to 0.The quality flags for each parameter are given as integers 4 bytes long, integer*4.The individual bits for each quality value are set or cleared in the analysis code by adding or subtracting a power of 2 as follows. To set the first bit, add 1, the second bit, add 2, the third bit, add 4, the fourth bit, add 8, and so on. See the table below.+------------------------------------------------------------------------------------------------------------------------------+| Bit | Set Value | MEANING ||------------------------------------------------------------------------------------------------------------------------------|| 1 | 1 | Three point parabolic fits to proton peaks were not attempted. || 2 | 2 | Non-linear least squares fit was not attempted. || 3 | 4 | Three point parabolic fits to proton peaks failed. || 4 | 8 | Non-linear least squares fit failed. || 5 | 16 | Alpha parameters not valid since the non-linear least squares fit was done for protons only. || | | Not enough good energy channels to do simultaneous alpha fit. This value applies to iqual_core(5) only. || 6 | 32 | Analysis code unable to get good value for spin period. || 7 | 64 | SWE instrument in mode 1, calibration state mode. Key parameters are produced in mode 1, science mode. || 8 | 128 | Three point fits done for cup 1 only. Split collector ratio of currents used to get the north/south angle. || | | Either cup 2 turned off, or cup 2 densities were low indicating noise associated with vibration. || 9 | 256 | Fewer than ten fc_blocks in spectrum. Analysis skipped. || 10 | 512 | Alpha particle non-linear fit produced values of density and thermal speed that do not seem reasonable. || 11 | 1024 | Three point parabolic fits to proton peaks done for cup 2 only. Probably Cup 1 is turned off. || | | The ratio of currents on split collectors used to get north/south angle. || 12 | 2048 | Single width windows. Delta E over E 6.5% instead of the default 13%. || 13 | 4096 | Tracking mode operation. || 14 | 8192 | Limited tracking mode scan, not a full scan. |+------------------------------------------------------------------------------------------------------------------------------+Particular flag settings:+-------------------------------------------------------------------------------------------+| Flag Value | Meaning ||-------------------------------------------------------------------------------------------|| 4098 | Tracking mode operation is full scan (4096) and No non-linear fits (2) || 14338 | Tracking mode operation is full scan (4096) and Limited tracking mode (8192) |+-------------------------------------------------------------------------------------------+Comments:* Note that in bit 4 of the quality flag the non-linear fit may be reported as good for protons and, at the same time, not good for alphas.* Non-linear fits are not done for Key Parameters, KPs, but those parameter values are excellent and should be used to do science.* Non-linear fits are available are available in this data product, but they have problems which suggests strongly that the KP paramete
Data from Doppler-Wind Lidar (DWL) measurements at Berlin – Rothenburgstrasse (BEROTH) from 2022-10-06 to 2022-10-24 [RAW]
<p>Original data files from DWL measurements.</p>
Data from Doppler-Wind Lidar (DWL) measurements at Berlin – Rothenburgstrasse (BEROTH) from 2022-10-05 to 2022-10-24 [RAW]
<p>Original data files from DWL measurements.</p>
Data from Doppler-Wind Lidar (DWL) measurements at Berlin – Friedrichstadt (BEFRIE) from 2021-07-15 to 2022-10-01 [RAW]
<p>Original data files from DWL measurements.</p> <p> </p> Part 1 of 2.
Data from Doppler-Wind Lidar (DWL) measurements at Berlin – Lichtenberg (BELICH) from 2021-08-25 to 2022-10-01 [RAW]
<p>Original data files from DWL measurements.</p> Part 2 of 2.
Data from Doppler-Wind Lidar (DWL) measurements at Berlin – Friedrichstadt (BEFRIE) from 2021-07-15 to 2022-10-01 [RAW]
<p>Original data files from DWL measurements.</p> Part 2 of 2.
Data from Doppler-Wind Lidar (DWL) measurements at Berlin – Lichtenberg (BELICH) from 2021-08-25 to 2022-10-01 [RAW]
<p>Original data files from DWL measurements.</p> Part 1 of 2.
Frøya wind data (1Hz).
<p>Herewith we present the extended 1Hz dataset of wind measurements from a Skipheia meteorological station on the island of Frøya on the western coast of Norway, Trondelag.</p> <p>The data binned in 10 min averages can be find at: <a href="https://doi.org/10.5281/zenodo.2557500">https://doi.org/10.5281/zenodo.2557500</a></p> <p>The site represents an exposed coastal wind climate with open sea, land and mixed fetch from various directions. UTM-coordinates of the Met-mast: 8.34251 E and 63.66638 N. See the map for details (NorwegianMapping Authority): <a href="https://www.norgeskart.no/#!?project=norgeskart&layers=1003&zoom=3&lat=7035885.49&lon=539601.41&markerLat=7077031.483032227&markerLon=170902.83203125&panel=searchOptionsPanel&sok=Titranveien">https://www.norgeskart.no/#!?project=norgeskart&layers=1003&zoom=3&lat=7035885.49&lon=539601.41&markerLat=7077031.483032227&markerLon=170902.83203125&panel=searchOptionsPanel&sok=Titranveien</a></p> <p>Presented data were gathered between years 2009-2016.</p> <p>Data&hardware summary:</p> <p>Years 2009-2016: Mast2 equipped with 6 pairs of 2D sonic anemometers at 10, 16, 25, 40, 70, 100 m above the ground, independent temperature measurements at the same heights and near the ground; pressure and relative humidity from local meteostation (Sula, 20 km away).</p> <p>Years 2014-2016: Mast4 equipped with 2 pairs of 2D sonic anemometers at 40 and 100 m above the ground. The distance between the masts is 79 m.</p> <p>Data is binned in years and months and stored in a ‘*.txt’ tab-separated values file.</p> <p>Data column order is described in SkipheiaMast2_header.txt and SkipheiaMast4_header.txt, where WSx is the wind speed (m/s), WDx is the wind direction (360 deg), ATx is the air temperature (deg C) and x designates the instrument number. The instruments are numbered starting from the ground.</p> <p>Example: For Mast2 (6 pairs of anemometers, ground temperature + 6 temperature sensors on the mast) that means that AT0 is the ground temperature. WS1 and WS2 are wind speed records at 10 m level. WS3 and WS4 are wind speed records at 16 m. For Mast4 (2 pairs of anemometers) that means that WS1 and WS2 are wind speed records at 40 m level. WS3 and WS4 are wind speed records at 100 m.</p> <p>Detailed site description with wind climate description can be found in attached analysis: Site analysys.pdf.</p> <p>Additional information and analysis can be found in listed below works, using data from Frøya site:</p> <p>Bardal, L. M., & Sætran, L. R. (2016, September). Spatial correlation of atmospheric wind at scales relevant for large scale wind turbines. In <em>Journal of Physics: Conference Series</em> (Vol. 753, No. 3, p. 032033). IOP Publishing, doi:10.1088/1742-6596/753/3/032033, <a href="https://iopscience.iop.org/article/10.1088/1742-6596/753/3/032033/pdf">https://iopscience.iop.org/article/10.1088/1742-6596/753/3/032033/pdf</a></p> <p>Bardal, L. M., & Sætran, L. R. (2016). Wind gust factors in a coastal wind climate. <em>Energy Procedia,</em> 94, 417-424, <a href="https://doi.org/10.1016/j.egypro.2016.09.207">https://doi.org/10.1016/j.egypro.2016.09.207</a></p> <p>IEA Wind TCP Task 27 Compendium of IEA Wind TCP Task 27 Case Studies, Technical Report, Prepared by Ignacio Cruz Cruz, CIEMAT, Spain Trudy Forsyth, WAT, United States, October 2018; Chapter 1.8. <a href="https://community.ieawind.org/HigherLogic/System/DownloadDocumentFile.ashx?DocumentFileKey=8afc06ec-bb68-0be8-8481-6622e9e95ae7&forceDialog=0">https://community.ieawind.org/HigherLogic/System/DownloadDocumentFile.ashx?DocumentFileKey=8afc06ec-bb68-0be8-8481-6622e9e95ae7&forceDialog=0</a></p> <p>Domagalski, P., Bardal, L. M., & Sætran, L. Vertical Wind Profiles in Non-neutral Conditions-Comparison of Models and Measurements from Froya. <em>Journal of Offshore Mechanics and Arctic Engineering,</em> doi: 10.1115/1.4041816, <a href="http://offshoremechanics.asmedigitalcollection.asme.org/article.aspx?articleid=2711333&resultClick=3">http://offshoremechanics.asmedigitalcollection.asme.org/article.aspx?articleid=2711333&resultClick=3</a></p> <p>Møller, M., Domagalski, P., & Sætran, L. R. (2019, October). Characteristics of abnormal vertical wind profiles at a coastal site. In <em>Journal of Physics: Conference Series</em> (Vol. 1356, No. 1, p. 012030). IOP Publishing. https://iopscience.iop.org/article/10.1088/1742-6596/1356/1/012030 </p> <p><strong> </strong>Møller, M., Domagalski, P., and Sætran, L. R.: Comparing Abnormalities in Onshore and Offshore Vertical Wind Profiles, Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-40 , in review, 2019. </p>
Data from Doppler-Wind Lidar (DWL) measurements at Paris – Roissy (PAROIS) from 2022-06-14 to 2023-12-11 [RAW]
<p>Original data files from DWL measurements at Roissy Charles de Gaulle Airport.</p> <p>Part 2 of 2.</p>
Data from Doppler-Wind Lidar (DWL) measurements at Paris – Roissy (PAROIS) from 2022-06-14 to 2023-12-11 [RAW]
<p>Original data files from DWL measurements at Roissy Charles de Gaulle Airport.</p> <p>Part 1 of 2.</p>
Data from Doppler-Wind Lidar (DWL) intercomparison measurements at Berlin – Rothenburgstrasse (BEROTH) from 2022-10-05 to 2022-10-24 [RAW]
<p>Original data files from DWL measurements.</p>
Data from Doppler-Wind Lidar (DWL) intercomparison measurements at Berlin – Rothenburgstrasse (BEROTH) from 2022-10-05 to 2022-10-24 [RAW]
<p>Original data files from DWL measurements.</p>
Data from Doppler-Wind Lidar (DWL) intercomparison measurements at Berlin – Rothenburgstrasse (BEROTH) from 2022-10-05 to 2022-10-24 [RAW]
<p>Original data files from DWL measurements.</p>
Data from Doppler-Wind Lidar (DWL) intercomparison measurements at Berlin – Rothenburgstrasse (BEROTH) from 2022-10-05 to 2022-10-24 [RAW]
<p>Original data files from DWL measurements.</p>
Data from Doppler-Wind Lidar (DWL) intercomparison measurements at Berlin – Rothenburgstrasse (BEROTH) from 2022-10-05 to 2022-10-24 [RAW]
<p>Original data files from DWL measurements.</p>
Data from Doppler-Wind Lidar (DWL) measurements at Berlin – TUB Campus Charlottenburg (BETUCC) from 2022-06-22 to 2022-06-28 [RAW]
<p>Original data files from DWL measurements.</p>
Data from Doppler-Wind Lidar (DWL) measurements at Berlin – TUB Campus Charlottenburg (BETUCC) from 2021-09-03 to 2022-09-30 [RAW]
<p>Original data files from DWL measurements.</p>
Data from Doppler-Wind Lidar (DWL) measurements at Berlin – Rothenburgstrasse (BEROTH) from 2022-05-20 to 2022-06-22 [RAW]
<p>Original data files from DWL measurements.</p>
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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.
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DANDI Archive for NWB datasets
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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.