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658 results for “doppler”
Dry run for Eclipse data gathering. Method, Doppler and amplitude vs time
<p>The station here is setup to receive two frequencies simultaneously. SpectrumLab is setup to do simultaneous FFT calculations and tabulate Doppler Shift and signal amplitude data for each frequency. The radio used is a K3 in the CW mode with AGC off. The main and subrx of the K3 are identical and phase locked. The antenna is a multiband Vee antenna facing north averaging 15' high. FFT parameters are adjusted for a bin width of 0.186 Hz with the SL peak detection algorithm turned on to determine the peak frequency within the bin. 75% overlap. A data point is obtained every 1.3 seconds. Doppler shift is determined via the heterodyne method differencing the station pitch and the reference oscillator (offset in freq). Both oscillators are locked to a Rubidium standard.</p> <p>The attached plots are the station setup, Doppler shifts for CHU 14670 kHz and 15000 kHz, and the amplitudes of each. </p> <p> </p>
2017 Solar Eclipse Doppler and signal strengths
<p>K3KO 30.210666N,81.603833W Jacksonville FL. No .wav file. Antenna Vee pointed north.K3 rx. CHU 14.670 MHz and WWV 15 MHz measured.</p> <p>Rb locked reference oscillators. Methodology described in *. doc file upload</p>
FFT and WAV files of 10MHz WWV Doppler shift during 8-21-2017 Solar eclipse
<p>HL Serra N6NC</p> <p>San Diego CA 32-50-36N 117-16-16W</p> <p>FFT and WAV files started 1415UT-2300UT 8-21-2017 [FFT file starts 24 hrs earlier for comparison FFTs)</p> <p>Omnidirectional 8" "active antenna"</p> <p>Rcvr Racal RA 6790 in USB mode</p> <p>Rcvr and HP-3325A GPSDO-controlled 10 MHz.</p> <p>Tuned rcvr to 9,999,000 Hz in USB mode to record in SpecLab the offset from 1000Hz beat note of 10 MHz signal.</p> <p>Very little if any Doppler shift of signal during eclipse, probably because I am located on the same side of the eclipse totality as WWV in Boulder CO. Besides rcvr, I tracked WWV frequency with GPSDO-controlled HP-3325 and scope comparing the tuned HP frequency with the rcvr's 455kHz IF to find recorded FFT offset. HP stable for two days showing WWV freq as 10,000,000.013 Hz by watching unmoving Lissajous figure on scope, so no visually perceptible Doppler excursions in frequency detected, but the FFT data will show whatever frequency movement there might have been.</p> <p> </p> <p>73, Larry N6NC</p>
Dataset related to the publication "Sub-Doppler optical-optical double-resonance spectroscopy using a cavity-enhanced frequency comb probe"
<p>The files contain </p><p>1. Binary files with normalized and interleaved double-resonance spectra recorded with three different pump transitions and two different relative pump-probe polarizations, indicated in the file name. These spectra are the results of 5 measurements.</p><p>2. Binary file with 45 normalized and interleaved double-resonance spectra recorded with pump on the R(2, <i>F2</i>) transition and parallel relative pump-probe polarization.</p><p>2. Data for Figures 4, S1 and S3 in the paper.</p><p> </p>
Doppler lidar wind profiles from Granada
<p>This is data set includes Doppler wind lidar quantities which were calculated from measurements performed between 2016 and 2020 at <em>Andalusian Global Observatory of the Atmosphere</em>, AGORA, in particular, at the UGR station, Andalusian Institute for Earth System Research (IISTA-CEAMA) in Granada, Spain (37.16ºN, 3.61ºW, 680 m a.s.l.).</p> <p>The system is a Doppler lidar Stream Line (Halo Photonics), which is part of ACTRIS-Cloudnet (Illingworth et al., 2007). The system laser emits at 1.5 μm and the detector is heterodyne using fiber-optic technology. The measurements for this data set consisted of conical scans with constant elevation of 75° and 12 equidistant azimuth points performed every 10 min. A more detailed description of the instrument can be found in (Ortiz-Amezcua et al., 2022)</p>
Assessing suspended sediment fluxes with acoustic doppler current profilers: case study from large rivers in Russia
<p>The dataset contains measurements of water discharge by Teledyne RDInstruments RioGrande WorkHorse ADCP unit with a working frequency of 600kHz mounted on a moving boat in 6 areas over large rivers of Russia. The dataset comprises the four largest Arctic Siberian rivers and included continuous ADCP measurements done in 2018-2020 at constant crossection at each river located upper from the impact of recipient seas (tides, surges) near the cities of Salekhard (Ob River), Igarka (Yenisey River), Zhigansk (Lena river) and Chersky (Kolyma River). Another area includes ADCP measurements over 20 transects (named S1…S26, fig. 2) in the lower 200 km of the river Selenga on 27-31July 2018. Additionally, the dataset contains ADCP measurements at 38 points along the Moskva River (named M1, M2…) and 17 tributaries (named T01, T02…) done during 2019-2020.</p> <p>This is a supporting material to a manuscript submitted to «Big Earth Data» journal</p>
Vallée de la Sionne Snow Avalanche n. 20213009: GEODAR radar, Doppler radar and infrasound data
<p>This repository hosts infrasound, GEODAR radar, and Doppler radar data collected within a large powder snow avalanche (No. 20213009) that occurred naturally at the Vallée de la Sionne test site in Switzerland.</p> <p>These datasets complement and are described in the following publication:</p> <p>B. Sovilla, E. Marchetti, M. Kyburz, A. Köhler, P. Huguenin, I. Calic, M.J. Kohler, E. Surinach, and C. Pérez-Guillén, under review. "The dominant source mechanism of infrasound generation in powder snow avalanches," submitted to Geophysical Research Letters.</p>
Data supporting the conclusions of Atmospheric boundary layer classification with Doppler lidar
<p>This is data set includes Doppler wind lidar quantities which were calculated from Halo Photonics Streamline measurements between 2 September 2015 and 16 November 2016 at Hyytiälä, Finland and between 1 January 2015 and 31 December 2016 at Jũlich, Germany. The data set also includes the respective boundary layer classification results generated from the calculated lidar quantities from both of the sites.</p>
Pioneer 11 Doppler Tracking Data
<p>This Pioneer 11 Doppler tracking data set was created by John Anderson from NAVIO format. The file is ASCII text, and is a collection of Doppler data records ordered sequentially.</p>
Pioneer 10 Doppler Tracking Data
<p>This Pioneer 10 Doppler tracking data set was created by John Anderson from NAVIO format. The file is ASCII text, and is a collection of Doppler data records ordered sequentially.</p>
Vertically pointing doppler radar profiles (24 GHz Metek MRR-2) at Concordia Station (Dome C, Antarctica), aggregated to 5min, monthly netCDF archive
<p>Vertical profiles along the first three kilometres of atmosphere above the ground (from 300 to 3000 m AGL) of equivalent radar reflectivity factor (Ze), Doppler velocity (W) and Doppler spectral width (Sw) from a 24-GHz vertically pointing Micro Rain Radar MRR-2 by METEK GmbH positioned at Concordia Station (Dome C, Antarctica).</p> <p>Metadata available at <a href="https://antarcticdatacenter.cnr.it/geonetwork/srv/eng/catalog.search#/metadata/6dc25ff0-4c03-4ca8-af0d-cba06a411dc2" target="_blank" rel="noopener">https://antarcticdatacenter.cnr.it/geonetwork/srv/eng/catalog.search#/metadata/6dc25ff0-4c03-4ca8-af0d-cba06a411dc2</a> </p> <p>--------------------------------------------------------------------</p> <p>Example of netCDF file structure:</p> <h2><strong>File "DMC_MRR_MeK_201901_5min.nc"</strong></h2> <pre><strong> dimensions</strong>: <em>range </em>= 31; <em>time </em>= UNLIMITED; // (7736 currently) <strong>variables</strong>: float <em>Ze</em>(range=31, time=7736); :description = "Equivalent reflectivity factor relative to the most significant peak, dealiased, 5min non-logarithmic average. NaN means clear sky at the specified height."; :units = "dBZ"; :_ChunkSizes = 31U, 1U; // uint long <em>time_UTC(time=7736);</em> :description = "Measurement time. Timestamp indicates the end of the aggregation interval, e.g. 01-Mar-2020 00:05:00 represents the average of the variables between 01-Mar-2020 00:00:01 and 01-Mar-2020 00:05:00."; :time_zone = "UTC"; :units = "Seconds since 1970-01-01 00:00:00 (Unix time)."; :_ChunkSizes = 512U; // uint float <em>W</em>(range=31, time=7736); :description = "Mean Doppler Velocity of the most significant peak, dealiased, 5min average. Value not available in clear-sky conditions."; :units = "m s^-1"; :_ChunkSizes = 31U, 1U; // uint float <em>height</em>(range=31, time=7736); :description = "Height above instrument."; :units = "m"; :_ChunkSizes = 31U, 1U; // uint float <em>spectralWidth</em>(range=31, time=7736); :description = "Doppler Spectral Width of the most significant peak, dealiased, 5min average. Value not available in clear-sky conditions."; :units = "m s^-1"; :_ChunkSizes = 31U, 1U; // uint // <strong>global attributes</strong>: :<em>title </em>= "Micro rain radar data processed with IMProToo (Maahn, M. and Kollias, P., 2012), aggregated to 5min, monthly netCDF archive."; :<em>comment </em>= "IMProToo has been developed for improved snow measurements. Note that this data has been processed regardless of precipitation type."; :<em>time_label </em>= "Jan 2019"; :<em>source </em>= "Micro Rain Radar 2 (MRR-2), METEK GmbH, at DMC (Antarctica), frequency: 24 GHz, power: 50 mW, antenna diameter: 60 cm [https://metek.de/product/mrr-2/]"; :<em>institution </em>= "CNR-INO, Florence (IT)"; :<em>contact_person </em>= "Gianluca Di Natale, CNR-INO, Florence (IT), gianluca.dinatale@ino.cnr.it"; :<em>location </em>= "Concordia Station (Dome C, Antarctica, 75°06\'S, 123°21\'E, 3233 m a.s.l.)"; :<em>author </em>= "Giacomo Roversi, Ca\' Foscari University, Venice (IT) and CNR-ISAC, Rome (IT), g.roversi@isac.cnr.it"; :<em>creation_date </em>= "22-Oct-2024 17:32:24 UTC"; :<em>coverage </em>= "Monthly coverage (Jan 2019): 90.3226 %"; :<em>time_resolution </em>= "5 minutes"; :<em>history </em>= "Created with IMProToo v0.107 [https://github.com/maahn/IMProToo], aggregated to 5 minutes temporal resolution with an average of the 1-minute values if least 3 out of 5 are not NaN."; </pre>
Hurricane Michael - SAMURAI analysis files created from NOAA P-3 tail Doppler radar data
<p>This repository contains analyses of Hurricane Michael created from quality controlled data from the NOAA P3 tail Doppler radar. The TDR data can be found in its raw format at the following link under the folders 20181008H1, 20181009H1, 20181009H2, and 20181010H1:</p> <p><a href="http://seb.noaa.gov/pub/acdata/2018/RADAR/">https://seb.noaa.gov/pub/acdata/2018/RADAR/</a></p> <p>The analyses are the topic of the manuscript 'Vertical Vortex Development in Hurricane Michael (2018) during Rapid Intensification' which is in review as of dataset publication. Please cite the manuscript when using this data as it contains methodological information on how the analyses were created. More information about the center fix times each analysis file is related to are available in the manuscript. Code to run the SAMURAI analysis tool which created these files, information on how SAMURAI works, and directions can be found at the following 2 links:</p> <p><a href="http://github.com/mmbell/samurai">https://github.com/mmbell/samurai</a></p> <p><a href="http://wiki.lrose.net/index.php/SAMURAI">http://wiki.lrose.net/index.php/SAMURAI</a></p>
Vertically pointing doppler radar profiles (24 GHz Metek MRR-2) at Mario Zucchelli Station (Terra Nova Bay, Antarctica), aggregated to 5min, monthly netCDF archive
<p>Vertical profiles along the first kilometre of atmosphere above the ground (from 105 to 1050 m AGL) of equivalent radar reflectivity factor (Ze), Doppler velocity (W) and Doppler spectral width (Sw) from a 24-GHz vertically pointing Micro Rain Radar MRR-2 by METEK GmbH positioned at Mario Zucchelli Station (Terra Nova Bay, Antarctica).</p> <p>Metadata available at <a href="https://antarcticdatacenter.cnr.it/geonetwork/srv/api/records/6fe32f1f-247e-493d-9cd3-88714e5b38ef" target="_blank" rel="noopener">https://antarcticdatacenter.cnr.it/geonetwork/srv/api/records/6fe32f1f-247e-493d-9cd3-88714e5b38ef</a></p> <p>--------------------------------------------------------------------</p> <p>Example of netCDF file structure: </p> <h2>File "MZS_MRR_MeK_201912_5min.nc"</h2> <pre><strong> dimensions</strong>: <em>range </em>= 31; <em>time </em>= UNLIMITED; // (8928 currently) <strong>variables</strong>: float <em>Ze</em>(range=31, time=8928); :description = "Equivalent reflectivity factor relative to the most significant peak, dealiased, 5min non-logarithmic average. NaN means clear sky at the specified height."; :units = "dBZ"; :_ChunkSizes = 31U, 1U; // uint long <em>time_UTC</em>(time=8928); :description = "Measurement time. Timestamp indicates the end of the aggregation interval, e.g. 01-Mar-2020 00:05:00 represents the average of the variables between 01-Mar-2020 00:00:01 and 01-Mar-2020 00:05:00."; :time_zone = "UTC"; :units = "Seconds since 1970-01-01 00:00:00 (Unix time)."; :_ChunkSizes = 512U; // uint float <em>W</em>(range=31, time=8928); :description = "Mean Doppler Velocity of the most significant peak, dealiased, 5min average. Value not available in clear-sky conditions."; :units = "m s^-1"; :_ChunkSizes = 31U, 1U; // uint float <em>height</em>(range=31, time=8928); :description = "Height above instrument."; :units = "m"; :_ChunkSizes = 31U, 1U; // uint float <em>spectralWidth</em>(range=31, time=8928); :description = "Doppler Spectral Width of the most significant peak, dealiased, 5min average. Value not available in clear-sky conditions."; :units = "m s^-1"; :_ChunkSizes = 31U, 1U; // uint // <strong>global attributes</strong>: :<em>title </em>= "Micro rain radar data processed with IMProToo (Maahn, M. and Kollias, P., 2012), aggregated to 5min, monthly netCDF archive."; :<em>comment </em>= "IMProToo has been developed for improved snow measurements. Note that this data has been processed regardless of precipitation type."; :<em>time_label </em>= "Dec 2019"; :<em>source </em>= "Micro Rain Radar 2 (MRR-2), METEK GmbH, at MZS (Antarctica), frequency: 24 GHz, power: 50 mW, antenna diameter: 60 cm [https://metek.de/product/mrr-2/]"; :<em>institution </em>= "CNR-ISAC, Rome (IT)"; :<em>contact_person </em>= "Luca Baldini, CNR-ISAC, Rome (IT), l.baldini@isac.cnr.it"; :<em>location </em>= "Mario Zucchelli Station (Terra Nova Bay, Antarctica, 74°42\'S, 164°07\'E, 15 m a.s.l.)"; :<em>author </em>= "Giacomo Roversi, Ca\' Foscari University, Venice (IT) and CNR-ISAC, Rome (IT), g.roversi@isac.cnr.it"; :<em>creation_date </em>= "22-Oct-2024 17:40:46 UTC"; :<em>coverage </em>= "Monthly coverage (Dec 2019): 100 %"; :<em>time_resolution </em>= "5 minutes"; :<em>history </em>= "Created with IMProToo v0.107 [https://github.com/maahn/IMProToo], aggregated to 5 minutes temporal resolution with an average of the 1-minute values if least 3 out of 5 are not NaN."; </pre>
Aerodynamic characterisation of porous fairings : pressure drop and Laser Doppler Velocimetry measurements
<p>Aviation has become a mass transportation industry, and all prospective studies foresee growth in this sector. Among the challenges, noise in the vicinity of airports has gone from a marginal annoyance to a real public health concern. To address this problem, as well as others such as fuel consumption, aircraft manufacturers are considering radically new aircraft architectures that could enter service quickly. In the meantime, however, the noise of traditional aircraft must be reduced significantly. Aircraft noise, during takeoff and landing, results primarily from a combination of (i) engine noise, which is generated by the fan and jet, and (ii) airframe noise, primarily due to the landing gear (LG) and high lift devices (HLD), the latter including slats and trailing edge flaps, which are deployed at low speeds to increase lift. During takeoff, engine noise remains dominant, while on approach and landing, engines operate at low speeds (typically 50% of N1), and airframe noise becomes a significant contributor, especially for newer aircraft equipped with latest generation turbofans. Its mitigation is therefore of primary interest.<br> However, due to the strong integration constraints imposed by other disciplines than acoustics on components such as LGs and HLDs, the development of noise reduction technologies (NRT) on these airframe components has been limited. This lack of breakthroughs is also due to the complexity of flow physics, and thus our still limited knowledge of airframe noise generation mechanisms. The noise of the landing gear, slats and flaps has been studied on a real and reduced scale, mainly on the basis of experimental means. The maturity of numerical simulations now allows to study the mechanisms of the noise sources on various complex configurations. Moreover, numerical simulation methods can be sufficiently accurate to predict the noise generated by such configurations. In order to take the next step in the maturity of numerical prediction, these NIRs must be accurately evaluated and modeled. Experimental data based on academic configurations are therefore needed to validate the new tools and numerical models. One promising NRT is the use of a fairing in front of the landing gear to reduce the noise of this system. The present study aims at collecting an experimental database (pressure drop and turbulence characteristics) of several fairing solutions in order to have validation test cases for CFD simulation and thus develop new models for such complex geometries. The fairing samples are thus tested on the "Acoustic and Aerothermal Bench" (B2A), by measuring the pressure drop of each sample and the flow field by Laser Doppler Velocimetry (LDV). The experimental methodology will be presented first. The database will then be described. Some technical validations will also be proposed on the basis of a comparison with the literature.</p>
TEAMx-PC22 (TEAMx pre-campaign 2022) – DWD Doppler wind lidar data set (SLXR172)
<p>This dataset contains data measured by DWD with a Doppler Wind Lidar SLXR172 during the TEAMx pre-campaign 2022. More details about TEAMx can be found at <a href="http://www.teamx-programme.org/">http://www.teamx-programme.org</a>.</p> <p><strong>DATA SET DESCRIPTION</strong></p> <p><strong>1. Measurement location and time period </strong></p> <p>Measurements with the SLXR172 were collected at the site of Brannenburg (47.741547 N / 12.122187 E / 456 m MSL) between 15.June – 19 October 2022.</p> <p><strong>2. Measurement setup</strong></p> <p>During the measurement period, two different scanning modes were applied:</p> <p>15. June - 26. July 2022 and 13. August – 19. October 2022 (VAD_CSM).</p> <ul> <li><strong>VAD (velocity-azimuth display) scans in </strong><strong>continuous scanning mode</strong><strong> : </strong>These scans were conducted at an elevation angle of 35°. Azimuth angle interval of the CSM data sampling was about 1.1°. </li> </ul> <p>27.July – 12. August 2022 (VAD_RHI)</p> <ul> <li><strong>VAD scans in step-stare mode: </strong>Step-stare scans were conducted at an elevation angle of 35° and with azimuth steps of 15°.</li> <li><strong>RHI (</strong><strong>range-height indicator) scans into the Inn Valley</strong>; The RHI scans were performed for 10 azimuth angles from 151° to 160° and covered elevation angles from 3° to 51°.</li> </ul> <p> </p> <p><strong><em>3. Data processing, corrections and filter</em></strong></p> <p>For <strong><em>VAD scans in continuous scanning mode</em></strong> the processed wind fields are provided. The data have not been corrected. The data can be filtered using the parameters R<sup>2 </sup>(coefficient of determination), CN (condition number) and NVRAD (number of radial velocities) as described in Päschke (2015):</p> <p>R<sup>2</sup>> 0.95 and CN<10 and NVRAD>12 </p> <p>Please note that in the postprocessing of the VAD CSM scans, the R<sup>2</sup> filter criterion was set to R<sup>2</sup>>0 in order to include all data and therefore might also include scans where the assumptions of homogeneity are not fulfilled. The parameter qwind is therefore not meaningful due to this configuration and should not be used to filter the data. We recommend the use of the above criterion from Päschke.</p> <p>For scans from the <strong><em>VAD scans in step stare mode</em></strong> as well as the <strong><em>RHI scans</em></strong> the raw data files are provided. They have not been corrected nor filtered.</p> <p><strong>4. Data file structure</strong></p> <p>The data are provided in NetCDF format. File names contain date and time information in UTC. The following wildcard characters are used in the file examples below: yyyy - year; mm - month, dd - day; HH - hour, MM - minute, `SS` - second. Files are sorted in monthly folders.</p> <p>The data are provided in two zip-files.</p> <ul> <li>VAD_CSM contains the processed wind fields from 15. June - 26. July 2022 and from 13. August – 19. October 2022)</li> <li>VAD+RHI the raw data files for 27.July – 12. August 2022.</li> </ul> <p>Raw data files of the VAD CSM scans can be provided upon request.</p> <p><strong>5. Contact</strong></p> <p>Contact Katrin.sedlmeier(at)dwd.de.at for any questions regarding the data set.</p> <p><strong>6. References</strong></p> <p>Päschke, E., Leinweber, R., and Lehmann, V.: An assessment of the performance of a 1.5 μm Doppler lidar for operational vertical wind profiling based on a 1-year trial, Atmos. Meas. Tech., 8, 2251–2266, https://doi.org/10.5194/amt-8-2251-2015, 2015.</p>
Doppler lidar vertical wind profiles from Rzecin during POLIMOS 2018
<p>This is data set includes Doppler wind lidar quantities which were calculated from measurements performed between May and September 2018 at <em>PolWET </em>site in Rzecin, Poland (52.75°N, 16.30°E, 59 m a.s.l.) of the Poznan University of Life Sciences</p> <p>The system is a Doppler lidar Stream Line (Halo Photonics), which is part of ACTRIS-Cloudnet (Illingworth et al., 2007). The system laser emits at 1.5 μm and the detector is heterodyne using fiber-optic technology. The measurements for this data set consisted of continuous vertically pointing measurements with a temporal resolution of 2 s. A more detailed description of the instrument can be found in (Ortiz-Amezcua et al., 2022)</p>
TEAMx-PC22 (TEAMx pre-campaing 2022) – GeoSphere Austria Doppler wind lidar data
<p><strong>ABSTRACT</strong></p> <p><a href="https://www.geosphere.at/">GeoSpere Austria</a> operated a Doppler lidar (<a href="https://metek.de/product/wind-ranger-100-200/">METEK Wind Ranger 200</a>) during the TEAMx pre-campaign 2022 (TEAMx-PC22) from August 17, 2022 to October 3, 2022 next to the <a href="https://oscar.wmo.int/surface/index.html#/search/station/stationReportDetails/0-20000-0-11130">meteorological station at Kufstein</a>, Austria. The wind lidar data from this campaign is provided here. Standard meteorological data is available on the <a href="https://data.hub.geosphere.at/">GeoSphere Austria data hub</a>.</p> <p>The aim of TEAMx-PC22 was to test new instruments, new instrument configurations and new measurement sites to support the planning of the main TEAMx observational campaign (TOC) in 2024/2025. More details about TEAMx can be found at <a href="http://www.teamx-programme.org">http://www.teamx-programme.org</a> as well as in <a href="https://www.uibk.ac.at/iup/buch_pdfs/10.1520399106-003-1.pdf">Serafin et al. (2020) </a>and in <a href="https://journals.ametsoc.org/view/journals/bams/103/5/BAMS-D-21-0232.1.xml">Rotach et al. (2022)</a>.</p> <p><strong>DATA SET DESCRIPTION</strong></p> <p>The windlidar is operated at Kufstein next to the meteorological station (12.1628°E 47.5753°N 490m asl). 1 VAD scan is measured per second, 100 radial measurements per VAD scan.</p> <p>Provided are daily NetCDF data sets, so-called “averaged files”, i.e. 10min averaged profiles calculated from the instantaneous profiles provided by the operational software of the instrument.</p> <p><strong>Description of variables:</strong></p> <table> <tbody> <tr> <td> <p>lat</p> </td> <td> <p> Latitude</p> </td> </tr> <tr> <td> <p>lon</p> </td> <td> <p> Longitude</p> </td> </tr> <tr> <td> <p>alt</p> </td> <td> <p> Altitude</p> </td> </tr> <tr> <td> <p>height</p> </td> <td> <p> Measuring height</p> </td> </tr> <tr> <td> <p>pitch</p> </td> <td> <p> Tilt towards north arrow</p> </td> </tr> <tr> <td> <p>roll</p> </td> <td> <p> Tilt clockwise looking along north arrow</p> </td> </tr> <tr> <td> <p>heading</p> </td> <td> <p> Azimuth alignment (should be zero)</p> </td> </tr> <tr> <td> <p>time</p> </td> <td> <p> Time stamp (seconds since 01.01.1970 00:00 UTC).</p> </td> </tr> <tr> <td> <p>VEL</p> </td> <td> <p> Wind Velocity (vectorial average)</p> </td> </tr> <tr> <td> <p>VEL_SC</p> </td> <td> <p>Wind Velocity (scalar average)</p> </td> </tr> <tr> <td> <p>DIR</p> </td> <td> <p> Direction (vectorial average)</p> </td> </tr> <tr> <td> <p>U</p> </td> <td> <p> West-East wind component</p> </td> </tr> <tr> <td> <p>V</p> </td> <td> <p> South-North wind component</p> </td> </tr> <tr> <td> <p>W</p> </td> <td> <p> Upward wind component</p> </td> </tr> <tr> <td> <p>SU</p> </td> <td> <p>Standard deviation of U</p> </td> </tr> <tr> <td> <p>SV</p> </td> <td> <p>Standard deviation of V</p> </td> </tr> <tr> <td> <p>SW</p> </td> <td> <p>Standard deviation of W</p> </td> </tr> <tr> <td> <p>SVEL</p> </td> <td> <p>Mean square deviation of radial wind components from fitted values</p> </td> </tr> <tr> <td> <p>DQ</p> </td> <td> <p>Fraction of valid radial components per VAD</p> </td> </tr> <tr> <td> <p>MDT</p> </td> <td> <p>Mean distance to target (Measured distance of focus)</p> </td> </tr> <tr> <td> <p>SNR</p> </td> <td> <p>Signal to noise ratio in dB</p> </td> </tr> <tr> <td> <p>SPW</p> </td> <td> <p>Spectral width (for internal use only)</p> </td> </tr> </tbody> </table> <p> </p> <p>Contact: kathrin.baumann-stanzer@geosphere.at</p>
Study of Power Doppler Ultrasound (PDUS) to Measure Response of Secukinumab Treatment in Patients With Active Psoriatic Arthritis (PsA)
ClinicalTrials.gov study NCT02662985. IPD Sharing: UNDECIDED. Countries: 17. Publications: 1.
Direct measurements of 4-dimensional variability in oceanic flow structures with a new towed phased array Doppler sonar
Open the record for dataset details and reuse information.
2012-2013 Sub-ice Current Velocities Recorded with an Acoustic Doppler Current Profiler
Between 26 November 2012 and 22 January 2013, a SonTek Argonaut-XR 1.5 MHz Acoustic Doppler Current Profiler (ADCP) was fixed at the bottom of the Limno Sampling Hole in Lake Hoare, looking downward through the water column. Every 30 seconds, the ADCP measured horizontal and vertical current velocities in six, 50-cm-thick cells between 0.5 and 3.5 m below the lake ice. The observation interval became deeper over time as the ADCP platform melted into the lake ice and the lake ice thinned. Data collected from 26 to 30 November represent pre-discharge data when wind and solar radiation were the only forces acting on the lake. Data from 30 November to 8 December transition from pre-discharge to spring freshet conditions on 6 December. Spring freshet was the most dynamic period observed with highest velocities recorded. Data from 8 to 13 December transitioned from the end of spring freshet on 10 December to summer diurnal discharge conditions. Data from the remaining datasets, 13 to 22 December, 22 to 29 December, 29 December to 6 January, 6 to 13 January, and 13 to 22 January, reflect conditions during summer diurnal stream discharge, especially data from 29 December to 6 January. From these observations, solar radiation, wind, glacial runoff during spring
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.