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658 results for “doppler”
Flume Experiment Testing the Impact of Artificial Streambank Roots on Velocity, Reynold's Shear Stress, and Turbulent Kinetic Energy using an Acoustic Doppler Profiler
The data published here is expected to accompany one publicly available dissertation (Chapter 4 of dissertation) and one separate journal publication. Once published and available online, the metadata will be updated with the relevant article information. The journal article/dissertation will have additional information regarding the published datasets and the methods used to collect the data. All data collected from these studies, and the accompanying Acoustic Doppler Profiler MATLAB files, are presented here. Journal Article title: Impact of Flexible and Rigid Artificial Roots on Stream Hydrodynamics
Characterization of Wind Turbine Wakes with Nacelle-Mounted Doppler LiDARs and Model Validation in the Presence of Wind Veer
<p>Dataset of the paper "Characterization of Wind Turbine Wakes with Nacelle-Mounted Doppler LiDARs and Model Validation in the Presence of Wind Veer" published in Remote Sensing [1].</p> <p>[1] Brugger P, Fuertes FC, Vahidzadeh M, Markfort CD, Porté-Agel F. Characterization of Wind Turbine Wakes with Nacelle-Mounted Doppler LiDARs and Model Validation in the Presence of Wind Veer. <em>Remote Sensing</em>. 2019; 11(19):2247. https://doi.org/10.3390/rs11192247.</p>
Field measurements of wake meandering at a utility-scale wind turbine with nacelle-mounted Doppler lidars
<p>Dataset of the paper " Dataset of the paper "Characterization of Wind Turbine Wakes with Nacelle-Mounted Doppler LiDARs and Model Validation in the Presence of Wind Veer" published in Remote Sensing [1]. " published in Wind Energy Science [1].</p> <p>[1] Brugger, P., Markfort, C., and Porté-Agel, F.: Field measurements of wake meandering at a utility-scale wind turbine with nacelle-mounted Doppler lidars, Wind Energ. Sci., 7, 185–199, https://doi.org/10.5194/wes-7-185-2022, 2022.</p>
W0TBR April 2024 Eclipse WWV Doppler Shift
<h2><strong>April 2024 Solar Eclipse Data via W0TBR</strong></h2> <p>W0TBR recorded Doppler drift of 15MHz WWV/WWVH carrier signals prior to and subsequent to the April 8 2024 solar eclipse.</p> <p>Although the W0TBR station was not in the direct path of the solar eclipse - with about only 33% occlusion at maximum shadow - the Doppler shift was recorded to determine any effect as compared to other shifts to be recorded within the direct eclipse path or within the midpoint of the signal path between WWV/WWVH and the recording station.</p> <p>W0TBR is located in Grid CN85qn - Lat. 45.555N & Lon. 122.623W at an elevation of 68.5m ASL.</p> <p>Antenna used is dual band inverted V fan dipole resonant on 20 and 17 meters with an apex at 10 meters above average terrain and tuned for max signal at 15MHz.</p> <p>Antenna feed is terminated at each end with 1:1 balun to minimize noise and non-resonant effects.</p> <p>Radio used is a Flex 1500 SDR stabilized with a 10MHz OCXO. Radio was tuned to 14.999MHz USB with AGC deactivated and RF gain fixed at value of 45/100.</p> <p>Received +/- 1kHz signal was directly fed through Conexant audio chip of HP 600G3 computer into Spectrum Lab (SpecLab) software.</p> <p>SpecLab (V 2.99 b15) was configured similar to that used by WA9VNJ for the 2017 solar eclipse recordings: 512K FFTs with 75% overlap resulting in readings every 12 seconds.</p> <p>SpecLab time, peak frequency and amplitude data were recorded from 0143 UTC to 2359 UTC on April 08 2024 and saved to a text file.</p> <p>Screen shots of the frequency shifts (+/- 3Hz) were taken each two hours for a total of six hours around the local maximum solar shadow which began about 1733 UTC, peaked at about 1825 UTC and ended about 1919 UTC. Note that the original SpecLab screenshots are in vertical time orientation; in order to provide a comparable view where time is on the horizontal axis the views are inverted and ‘stitched’ together for the final view’s full six hour period.</p>
Flume Erosion Testing of Unamended and Organic Matter Amended Soil Samples Using an Acoustic Doppler Profiler, 2021
This data accompanies a publication titled "Soil Amended with Organic Matter Increases Fluvial Erosion Resistance of Cohesive Streambank Soil". Briefly, fluvial erosion testing was conducted on soil samples using an indoor flume channel. Soil samples were previously collected from the riparian zone of a river near Virginia Tech's campus in Blacksburg, VA, USA. The soil was subsequently air-dried and stored until use. Prior to erosion testing, soil samples were amended with varying amounts of organic matter (0%, 1%, and 4% OM by mass), compacted to a bulk density of 0.95 KilogramsPerCubicCentiMeters in growth containers, and allowed to mature in a greenhouse setting for 50 days prior to flume erosion testing. An Acoustic Doppler Profiler (ADP) was used to measure soil erosion and collect three-dimensional velocity data during erosion tests; raw velocity and soil depth data for each sample tested were stored in MATLAB files. Follow testing, the soil remaining from each sample was collected, stored, and analyzed for aggregate stability, soil organic matter (SOM), and extracellular polymeric substances (EPS). Additionally, soil temperature, water temperature, and volumetric water content were also measured prior to or during erosion testing. Data collected from this study, and the accompanying ADP MATLAB files, are presented here.
WWV Doppler Shift Recording by AD8Y, 2.5 MHz, no GPSDO
<p>Doppler shift data from WWV on 2.5 MHz.</p> <p><strong>Callsign:</strong> AD8Y</p> <p><strong>Radio:</strong> Icom 7610</p> <p><strong>GPSDO:</strong> No</p> <p><strong>Antenna: </strong>Dipole, shorter than 1/2 wavelength.</p> <p><strong>Coordinates:</strong> (41.4067594 -75.6675467)</p> <p><strong>Elevation:</strong> 914.8 feet</p> <p> </p> <p>This dataset is part of the Frequency Analysis Network project, collected according to the same process as the data for the Festival of Frequency Measurement (10.5281/zenodo.3707210). </p>
WWV Doppler Shift Recording by AD8Y, 5 MHz, no GPSDO
<p>Doppler shift data from WWV on 5 MHz.</p> <p><strong>Callsign:</strong> AD8Y</p> <p><strong>Radio:</strong> Kenwood TS-450</p> <p><strong>GPSDO:</strong> No</p> <p><strong>Antenna:</strong> Random wire vertical</p> <p><strong>Coordinates:</strong> (41.4067594 -75.6675467)</p> <p><strong>Elevation:</strong> 914.8 feet</p> <p><strong>Notes:</strong> The TXCO is intermittently calibrated against a GPSDO, but the system cannot be run off the GPSDO because signal leakage from it overwhelms the signal from WWV. Data collection was interrupted on some dates, including 31 December 2019 and 16 January 2020. </p> <p> </p> <p>This dataset is part of the Frequency Analysis Network project, collected according to the same process as the data for the Festival of Frequency Measurement (10.5281/zenodo.3707210). </p>
LAPSE-RATE ground-based Doppler lidar datasets from Univ Colorado Boulder
<p>This dataset includes measurements obtained using the University of Colorado Windcube v1 lidars during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign. This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. </p> <p>On 14 July, both lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th. Moffat School data starts on the 15th.</p> <p>Bad or missing data is set to -9999.0 for all fields.</p> <p>The a1 and the a2 datafiles are identical except that the a2 files include beam information (0, 90, 180, or 270) that was omitted from the a1 files.</p>
Data for the Manuscripts of "Variability of Jakarta Rain-Rate Characteristics Associated with the Madden-Julian Oscillation and Topography" and "Subdaily Rain-Rate Properties in Western Java Analyzed Using C-Band Doppler Radar"
<p>This archive consists of the post-processed data of C-Band Doppler Radar (CDR) over Jakarta and surrounding regions for the studies of "Variability of Jakarta Rain-Rate Characteristics Associated with the Madden-Julian Oscillation and Topography" and "Subdaily Rain-Rate Properties in Western Java Analyzed Using C-Band Doppler Radar".</p> <p>The dataset is a gridded rainfall data derived from the local relationship of Z (reflectivity) from the CDR and rainfall (R) from stations. The derived rainfall data are in daily estimates from 2009 to 2012 with the format in NetCDF files.</p> <p>The CDR data were obtained from the projects “Hydrometeorological Array for Intraseasonal Variation-Monsoon Automonitoring (HARIMAU)” (JFY 2005-2009), and the Science Technology Research Partnership for Sustainable Development (SATREPS) “Maritime Continent Center of Excellence (MCCOE) (JFY 2009-2013) of the Japan Science and Technology Agency (JST)/Japan International Cooperation Agency(JICA) under a collaboration of the Agency for the Assessment and Application of Technology (BPPT)-Indonesia and Japan Agency for Marine-earth Science and Technology (JAMSTEC)-Japan.</p>
3D output of idealized large-eddy simulations with varying speed and surface heating to assess Doppler lidar scan patterns
<p><span>This dataset consists of nine idealized large-eddy simulations that were designed to systematically investigate the ability of different Doppler lidar scan patterns to measure the 3-dimensional wind vector at one point or in one profile. For more information, please see the documentation.</span></p>
Atmospheric, hydrodynamic and water quality observations from environmental-quality stations, water level sensors, acoustic Doppler velocimeters, and meteorological stations located at the Guadalquivir river estuary (2008 - 2010)
<p>The dataset included in this repository was obtained during the project entitled “Propuesta metodológica para diagnósticar las consecuencias de las actuaciones humanas en el estuario del Guadalquivir” funded by the Autoridad Portuaria de Sevilla (APS), by the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía), CTM2011-22580, MedEX (CTM2008-04036-E) and PR11-RNM-7722. The data were collected in real time from 2008 until 2010 with a remote monitoring system installed by the Institute of Marine Sciences of Andalusia (ICMAN-CSIC) (Navarro et al., 2011).</p> <p> </p> <p>The environmental quality station recorded turbidity, temperature, conductivity, normalized turbidity, dissolved oxygen, oxygen, oxygen saturation, percentage of oxygen saturation, fluorescence, normalized fluorescence, and salinity every thirty minutes. Current data were measured every 15 minutes by means of acoustic current profilers. The former datasets were obtained at several depths and different locations along the Guadalquivir estuary. Water level sensors recorded the position of the free water surface every 10 minutes at several locations along the Guadalquivir estuary. Wind velocity and direction and solar radiation were measured every 10 minutes in a meteorological station at the mouth of the Guadalquivir estuary.</p> <p>Brief description of dataset.</p> <ul> <li> <p>velocities.csv (in m/s)</p> </li> <li> <p>Turbidity.csv (in Volts), temperature (in Celsius), conductivity (in Siemens/m), normalized turbidity (in FNU), dissolved oxygen (mg/L), oxygen (in Volts), fluorescence (in Volts), normalized fluorescence (in Volts), oxygen saturation (mg/L), percentage of oxygen saturation (%), salinity (in PSU).</p> </li> <li> <p>qual_Salmedina.csv, R_mean (mean radiative flux in W/m²), R_max (max radiative flux in W/m²), Rel_humidity (relative humidity in %), D_mean (wind mean direction in degrees), D_max (wind maximum direction in degrees), D_sig (standard deviation of the wind direction in degrees), V_mean (mean wind velocity in m/s), V_max (maximum wind velocity in m/s), V_sig (standard deviation of the wind velocity in m/s), P_atm_mean (mean atmospheric pressure in mbar), T_mean (mean air temperature in Celsius), T_max (maximum air temperature in Celsius), T_sig (standard deviation of the air temperature in Celsius).</p> </li> <li> <p>Sealevel.csv (in meters)</p> </li> </ul> <p>A wide description of the datasets can be found in Navarro et al (2011).</p> <p>Contact person: infogdfa@ugr.es (or mcobosb@ugr.es)</p>
Doppler lidar datasets of UDINE measurement campaign at TROPOS Leipzig, Germany
<p>The Doppler lidar dataset of the Up- and Downdraft in Drop and Ice Nucleation Experiment (UDINE, 2010-2013) is published. This dataset is part of the publication Bühl et al., "Impact of vertical air motions on ice formation rate in mixed-phase cloud layers", NPJ Climate and Atmospheric Science, 2019.</p> <p>Time-height resolved measurements of mean vertical Doppler velocity of aerosol and cloud particles over the measurement site. Most data is recorded in vertical stare with 2s measurement time. Files are in NetCDF-format and contain the following variables:</p> <p>amp(time,height): The signal strength (SNR) recorded by the data acquisition.<br> data(time,height): The first moment of the main peak in the Doppler spectrum<br> heightresolution: The resolution of the data acquisition in nanoseconds<br> measurement_time(time,datetime): Time of recording in human readable format [YYYYMMDD,hhmmss]<br> scanposition(time,scanposition): Two element array with position of the scanner in [azimuth,off-zenith-angle]<br> shots(time): The number of shots used for averaging. Spectra are averaged at a rate of 750 shots/s so this variables indicates if the system has functioned nominally.</p>
Wind fields from aggregated retrievals from the WIRA-C Doppler wind radiometer in tropical and arctic lattitudes
<p>These data sets contain the retrieved wind fields from aggregated retrievals from the WIRA-C Doppler wind radiometer from two campaigns.</p> <p>The first campaign took place in the southern hemisphere at the Maïdo observatory on La Réunion Island (France), located in the Indian ocean at 21°S, 55°E. Data from April, May and June 2017 are included.</p> <p>For the second (and still ongoing) campaign, WIRA-C is located at the ALOMAR observatory on Andøya (Norway) at 69°N, 16°E. Data from September, October and November are included.</p>
Non-relativistic abberation and Doppler shift as experienced in walking with different velocities relative to falling rain
<p>Non-relativistic aberration and Doppler shift as experienced in walking with different velocities relative to falling rain. The scenario on the left (standing) shows the orientation of the umbrella for maximum protection of a person at rest perpendicular to the falling drops. On the right (walking), the situation for a person with an umbrella moving relative to the scenario on the left is shown. The bottom panels depict the related velocities and how they are added. vr is the velocity of the raindrops in the frame of reference of the ground, vr′ that in the frame of references of the person with the umbrella, with (right) and without (left) velocity vP with respect to the ground. Note, in the frame of reference of the person the ground moves with −vP. The arrival angle and rate of the raindrops depend on the velocities and are described with aberration and Doppler shift, respectively.</p> <p>Figure adapted from Hoffmann (1983).</p>
Intermediate data products for: Moored Turbulence Measurements using Pulse-Coherent Doppler Sonar (Zippel et al. 2021, Journal of Atmospheric and Oceanic Technology)
<p>This repository contains some of the intermediate data products needed to reproduce the results in the <em>Journal of Atmospheric and Oceanic Technology</em> article "Moored Turbulence Measurements using Pulse-Coherent Doppler Sonar" by S.F. Zippel, J. T. Farrar, C. J. Zappa, U. Miller, L. St. Laurent, T. Ijichi, R. A. Weller, L. McRaven, S. Nylund, and D. Le Bel. Specifically, this material should allow reproduction of Figures 3, 5-7, 12 and 13. Reproduction of Figures 8-11 also requires data from associated glider deployments nearr the SPURS-1 mooring, which may be requested from co-author L. St. Laurent.</p> <p>Code to do the analysis and make the plots is here: https://github.com/zippelsf/MooredTurbulenceMeasurements</p> <p>Matlab data files:</p> <p>(1) 677404_burst1865.mat</p> <p>Single-burst data used for the example spectral fit in Figure 7. The burst was collected during the SPURS-1 project at 21.5m depth. The data collection and processing methods are described in detail in Section 2. </p> <p>(2) 811604_burst0510.mat (Single-burst data used in the unwrapping example, Figure 5)</p> <p>(3) 8116_dissipation_timeseries.mat (Used for associated ancillary data in Figure 6)</p> <p>(4) 913411_burst2879.mat (Single-burst data, used for ancillary data to make Figure 3).</p> <p>(5) BuoyancyFlux_b.mat</p> <p>Ocean buoyancy flux estimates for SPURS-2 dataset, created from the 1-hr "met" and "flux" files available on the UOP website, and using the Gibbs SeaWater (GSW) toolbox to estimate "alpha" and "beta". The estimated buoyancy fluxes were used for Figure 12.</p> <p>(6) BuoyancyFlux_c.mat</p> <p>Ocean buoyancy flux estimates for SPURS-1 dataset, created from the 1-hr "met" and "flux" files available on the UOP website, and using the Gibbs SeaWater (GSW) toolbox to estimate "alpha" and "beta". The estimated buoyancy fluxes were used for Figure 12.</p> <p>(7) SPURS1_dissipation_grid_v1d.mat</p> <p>Gridded TKE dissipation rates for SPURS-1 dataset. Processing of these data is described extensively in Section 2. Data used in Figures 8-13. Dissipation rates also available on NASA's PODAAC.</p> <p>(8) spurs1_met_1hr.mat (Processed met data from SPURS-1 mooring. Also available on WHOI's UOP website.)</p> <p>(9) SPURS2_dissipation_grid_v1c.mat</p> <p>Gridded TKE dissipation rates for SPURS-2 dataset. Processing of these data is described extensively in Section 2. Data used in Figures 12. Dissipation rates also available on NASA's PODAAC.</p>
Doppler spectra collected by a transect of three MRR-PRO during the POPE 2020 campaign at Princess Elisabeth Antarctica
<p>This repository contain the datasets of Doppler spectra collected by three K-band Doppler profiling radars (MRR-PRO) deployed in a transect across the Sør Rondane Mountains, in the vicinity of the Belgian research base Princess Elisabeth Antarctica (PEA).</p> <p>The measurement campaign has been conducted by the Environmental Remote Sensing Laboratory (LTE) of the École Polytechnique Fédérale de Lausanne (EPFL), with the logistical support of the International Polar Foundation (IPF).</p> <p>The datasets are described in the article “Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica”, by Alfonso Ferrone and Alexis Berne. The article was submitted to Earth System Science Data in August 2022, and is available at the following URL: <a href="https://doi.org/10.5194/essd-2022-295">https://doi.org/10.5194/essd-2022-295</a> .</p> <p>This repository complements "Radar and ground-level measurements collected during the POPE 2020 campaign at Princess Elisabeth Antarctica", uploaded on Zenodo at: <a href="https://doi.org/10.5281/zenodo.7428690">https://doi.org/10.5281/zenodo.7428690</a> . The radar variables in the MRR-PRO data files contained in the latter have been computed from the raw spectra stored in the current repository.</p> <p> </p> <p><strong>Content of the archives</strong></p> <p>- <em>MRR_PRO_23_raw_spectra.zip,</em><br> This archive contains the Doppler spectra collected by the MRR-PRO 23, deployed at the lowest altitude in the transect, at1543 m above mean sea level (a.m.s.l.), at the following coordinates: latitude 72° 6’ 50.4” S, longitude 23° 30’ 50.4” E.</p> <p>- <em>MRR_PRO_06_raw_spectra.zip,</em><br> This archive contains the Doppler spectra collected by the MRR-PRO 06, deployed at approximately 2000 m a.m.s.l. of altitude, at the following coordinates: latitude 72° 7’ 4.8” S, longitude 23° 20’ 49.2” E.</p> <p>- <em>MRR_PRO_22_raw_spectra.zip,</em><br> This archive contains the Doppler spectra collected by the MRR-PRO 22, deployed at the highest location in the transect (2360 m a.m.s.l.), at the following coordinates: latitude 72° 13’ 37.2” S, longitude 23° 11’ 27.6” E.</p> <p> </p> <p><strong>Content of the NetCDF4 files</strong></p> <p>A “short name” is associated to each variables in the NetCDF4 files stored in the three archives.</p> <p>The relevant variables in each data file are:<br> – the raw spectral power, identified in the files by the short name “spectrum_raw”;<br> – the transfer function, used to convert the raw spectral power to spectral reflectivity, as described in Ferrone et al. (2022), and identified in the files by the short name “transfer_function”.</p> <p> </p> <p><strong>References</strong></p> <p>Ferrone, A., Billault-Roux, A.-C., and Berne, A.: ERUO: a spectral processing routine for the Micro Rain Radar PRO (MRR-PRO), Atmospheric Measurement Techniques, 15, 3569–3592, https://doi.org/10.5194/amt-15-3569-2022, 2022</p> <p>Ferrone, A., and Berne, A., Radar and ground-level measurements collected during the POPE 2020 campaign at Princess Elisabeth Antarctica (1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7428690, 2023</p>
TEAMx-PC22 (TEAMx pre-campaign 2022) - ACINN Doppler wind lidar data sets (SL88, SLXR142)
<p><strong>ABSTRACT</strong></p> <p>The data sets found here were collected with <a href="http://acinn.uibk.ac.at/">ACINN</a>'s Doppler wind lidars SL88 and SLXR142 in Innsbruck, Austria, in summer 2022 in the framework of the TEAMx pre-campaign 2022 (TEAMx-PC22). 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 Serafin et al. (2020) and in Rotach et al. (2022).</p> <p><strong>DATA SET DESCRIPTION</strong></p> <p><strong>1. Spatial coverage and locations</strong></p> <p>Measurements with the SL88 and SLXR142 lidar were collected during TEAMx-PC22 in Innsbruck, Austria, at the Campus Innrain of the University of Innsbruck. More specifically, the SLXR142 lidar was located on the rooftop of one of the university buildings (Bruno-Sander-Haus) at Innrain 52f. The SL88 lidar was located in the forecourt of the Campus Innrain, the so-called GEIWI-Forum, next to the Bruno-Sander-Haus. The exact lidar locations are:</p> <ul> <li>SL88: 47.264083°N / 11.384986°E / 575 m MSL</li> <li>SLXR142: 47.26431°N / 11.38529°E / 613 m MSL</li> </ul> <p><strong>2. Temporal coverage</strong></p> <p>The TEAMx-PC22 lasted from mid-May 2022 to early October 2022. However, the SL88 data set contains a shorter period from 11 August to 02 October 2022 (1 Hz data, vertical stares). The SLXR142 data set covers an extended period from 01 May to 31 October 2022 (VAD products, 10-min averages) as this lidar was operated in a semi-permanent mode.</p> <p><strong>3. Instrument details</strong></p> <p><em><strong>General</strong></em></p> <p>Measurements were taken with two scanning Doppler wind lidars, model Stream Line (SL88) and Stream Line XR (SLXR142), manufactured by HALO Photonics. The SL88 and SLXR142 are part of the Innsbruck Atmospheric Observatory (IAO; Karl et al. 2020). Available here are vertical profiles of radial velocity and backscatter data based on vertical stares at 1 Hz for the SL88 lidar and vertical profiles of horizontal winds (10-min averages) derived from plan position indicator (PPI) scans by applying the VAD method for the SLXR142 lidar. PPI scans were performed as continuous motion scans (CSM mode) at an azimuth angle of 70°. For continuous motion scans, the scanner moves continuously (changing its azimuth angle) while data is being acquired.</p> <p><em><strong>Data correction</strong></em></p> <p>No corrections were applied to the data (level0 data).</p> <p><strong>4. Data file structure</strong></p> <p><em><strong>File format</strong></em></p> <p>Provided are data 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. NetCDF data files are zipped together into the following zip files.</p> <p><em><strong>Zip files</strong></em></p> <p>SL88.zip contains netCDF files of SL88 data structured into subdirectories (one subdirectory for each month, yyyymm, and one for each day, yyyymmdd).</p> <p>SLXR142.zip contains netCDF files of SLXR142 data structured into subdirectories (one subdirectory for each month, yyyymm).</p> <p><em><strong>NetCDF files for uncorrected SL88 data</strong></em></p> <p>Stare_88_yyyymmdd_HH_l0.nc contains vertical stare measurements aggregated together in one netCDF file for each hour (uncorrected level0 data).</p> <p><em><strong>NetCDF files for SLXR142 data products</strong></em></p> <p>yyyymmdd.nc contains vertical profiles of the horizontal wind vector derived from PPI scans by applying the VAD technique. Each vertical profile is based on several PPI scans conducted at an elevation angle of 70° within 10 minutes. Hence, each profile represents a 10-min average. Profiles are aggregated together for each day in a separate netCDF file.</p> <p><strong>6. Contact</strong></p> <p>Contact alexander.gohm(at)uibk.ac.at for any questions regarding the data set.</p> <p><strong>7. References</strong></p> <p>Karl, T., A. Gohm, M.W. Rotach, H.C. Ward, M. Graus, A. Cede, G. Wohlfahrt, A. Hammerle, M. Haid, M. Tiefengraber, C. Lamprecht, J. Vergeiner, A. Kreuter, J. Wagner, M. Staudinger, 2020: Studying urban climate and air quality in the Alps: The Innsbruck Atmospheric Observatory. <em>Bulletin of the American Meteorological Society,</em> <strong>101,</strong> E488–E507, <a href="https://doi.org/10.1175/bams-d-19-0270.1">https://doi.org/10.1175/bams-d-19-0270.1</a></p> <p>Serafin, S., M. W. Rotach, M. Arpagaus, I. Colfescu, J. Cuxart, S. F. J. De Wekker, M. Evans, V. Grubišić, N. Kalthoff, T. Karl, D. J. Kirshbaum, M. Lehner, S. Mobbs, A. Paci, E. Palazzi, A. Raudzens Bailey, J. Schmidli, G. Wohlfahrt, B. Zardi, 2020: <em>Multi-scale transport and exchange processes in the atmosphere over mountains: Programme and experiment.</em> Innsbruck University Press. <a href="https://doi.org/10.15203/99106-003-1">https://doi.org/10.15203/99106-003-1</a></p> <p>Rotach, M. W., S. Serafin, H. C. Ward, M. Arpagaus, I. Colfescu, J. Cuxart, S. F. J. D. Wekker, V. Grubišic, N. Kalthoff, T. Karl, D. J. Kirshbaum, M. Lehner, S. Mobbs, A. Paci, E. Palazzi, A. Bailey, J. Schmidli, C. Wittmann, G. Wohlfahrt, D. Zardi, 2022: A collaborative effort to better understand, measure, and model atmospheric exchange processes over mountains. <em>Bulletin of the American Meteorological Society,</em> <strong>103,</strong> E1282–E1295. <a href="https://doi.org/10.1175/bams-d-21-0232.1">https://doi.org/10.1175/bams-d-21-0232.1</a></p>
Measurement of Absolute Retinal Blood Flow Using a Laser Doppler Velocimeter Combined with Adaptive Optics
<p><strong>Purpose</strong>: Development and validation of an absolute laser Doppler velocimeter (LDV) based on an adaptive optical fundus camera which provides simultaneously high definition images of the fundus vessels and absolute maximal red blood cells (RBCs) velocity in order to calculate the absolute retinal blood flow.\newline<br> <strong>Methods</strong>: This new absolute laser Doppler velocimeter is combined with the adaptive optics fundus camera (rtx1, Imagine Eyes$^\copyright$,Orsay, France) outside its optical wavefront correction path. A 4 seconds recording includes 40 images, each synchronized with two Doppler shift power spectra. Image analysis provides the vessel diameter close to the probing beam and the velocity of the RBCs in the vessels are extracted from the Doppler spectral analysis. Combination of those values gives an average of the absolute retinal blood flow. An in vitro experiment consisting of latex microspheres flowing in water through a glass-capillary to simulate a blood vessel and in vivo measurements on six healthy humans were done to assess the device.\newline<br> <strong>Results</strong>: In the in vitro experiment, the calculated flow varied between 1.75µl/min and 25.9µl/min and was highly correlated (r<sup>2</sup>= 0.995) with the imposed flow by a syringe pump.<br> In the in vivo experiment, the error between the flow in the parent vessel and the sum of the flow in the daughter vessels was between -11% and 36% (mean±sd 5.7±18.5%). Retinal blood flow in the main temporal retinal veins of healthy subjects varied between 0.9 µL/min and 13.2µL/min.</p> <p><strong>Conclusion</strong>: This adaptive optics LDV prototype (aoLDV) allows the measurement of absolute retinal blood flow derived from the retinal vessel diameter and the maximum RBCs velocity in that vessel.</p>
OU/NSSL CLAMPS Doppler Lidar Data from LAPSE-RATE
<p>Doppler lidars transmit pulses of 1.5 um wavelength laser energy into the atmosphere, which scatters off aerosol particles and hydrometeors. The lidar measures the intensity of this return, as well as its radial velocity. The lidar has a scanner which allows the system to scan anywhere in the hemisphere, and typically a fixed scan strategy is used. The Doppler lidar data are provided in three different netCDF files: one containing the stare data (DLFP), one containing the PPI data (DLPPI), and the last containing the processed VAD data (DLVAD). These files are provided in netCDF format.</p> <p>For LAPSE-RATE, the OU DL scan strategy consisted of a 24-point plan position indicator (PPI) scan at 70 degree elevation angle, a 6-point PPI at 45 degrees, and a vertical stare. The sequence ran every 5 minutes with the stare filling in the remaining time after the two PPI scans.</p>
Data presented in "Molecules cooled below the Doppler limit"
<p>Data presented in our paper "Molecules cooled below the Doppler limit". The files give the data that appears in figures 2, 3 and 4 of the paper.</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.
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.