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115 results for “vertical profile”
Vertical Profiles of Convection-Permitting Simulations for Predicting Thunderstorm Occurrence
<p>This repository contains datasets for training and evaluation of the machine learning (ML) models in K. Vahid Yousefnia et al., <em>Inferring Thunderstorm Occurrence from Vertical Profiles of Convection-Permitting Simulations: Physical Insights from a Physical Deep Learning Model</em>, 2024 (submitted to <em>Artificial Intelligence for the Earth Systems,</em> preprint available at https://arxiv.org/abs/2409.20087).</p>
Air/Snow temperature vertical profiles at different nodes of the 'Limnopolar Lake' CALM site, in Byers Península Livingston Island, Antarctica (2013-2022)
<div> <div> </div> </div> <div> <p>Air or seasonal snow temperature data were collected at different heights above the ground between 2013 and 2022 using an array of temperature micro-loggers (iButton models by Maxim) mounted on vertical wooden masts. These measurements were conducted at various nodes within the 100x100 m 'Limnopolar Lake' CALM site (A25) grid of the PERMATHERMAL network, managed by the University of Alcalá, Madrid, Spain, to monitor active layer thickness on Byers Peninsula, Livingston Island, South Shetland Islands, Antarctica.</p> <p>In 2013, nine arrays were installed at nodes with relative coordinates (00,00), (00,05), (00,10), (05,00), (05,05), (05,10), (10,00), (10,05), and (10,10). Measurements were taken at heights of 2.5, 5, 10, 15, 20, 25, 30, and 40 cm above the ground surface using DS1921G iButton loggers, which recorded air/snow temperatures every 4 hours. This experiment, referred to as 'Mini', was active for only one year and is now discontinued.</p> <p>Between 2017 and 2022, three arrays were installed at nodes (00,00), (05,05), and (10,10). These arrays measured air/snow temperatures at heights of 2.5, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, and 160 cm above the ground surface using DS1922L iButton loggers, which recorded temperatures every 3 hours. This experiment, referred to as 'HR', has also been discontinued.</p> </div>
Air/Snow temperature vertical profiles at different sites in Livingston Island, Antarctica (2006-2023)
<p>Air or seasonal snow temperature data collected at different heights above the ground (2.5, 5, 10, 20, 40, 80, and 160 cm), generally recorded every 3 hours between 2006 and 2023, using an array of temperature micro-loggers (iButton models by Maxim) mounted along a vertical wooden mast. These measurements were taken at various stations of the PERMATHERMAL network, managed by the University of Alcalá, Madrid, Spain, to monitor the thermal dynamics of frozen soils on Livingston Island, South Shetland Islands, Antarctica.</p>
Air/Snow temperature vertical profiles at different sites in Deception Island, Antarctica (2008-2023)
<p>Air or seasonal snow temperature data collected at different heights above the ground (2.5, 5, 10, 20, 40, 80, and 160 cm), generally recorded every 3 hours between 2006 and 2023, using an array of temperature micro-loggers (iButton models by Maxim) mounted along a vertical wooden mast. These measurements were taken at various stations of the PERMATHERMAL network, managed by the University of Alcalá, Madrid, Spain, to monitor the thermal dynamics of frozen soils on Deception Island, South Shetland Islands, Antarctica.</p>
Air/Snow temperature vertical profiles at different nodes of the 'Crater Lake' CALM site in Deception Island, Antarctica (2012-2023)
<p>Air or seasonal snow temperature data were collected at different heights above the ground between 2012 and 2023 using an array of temperature micro-loggers (iButton models by Maxim) mounted on vertical wooden masts. These measurements were conducted at various nodes within the 100x100 m 'Crater Lake' CALM site (A16) grid of the PERMATHERMAL network, managed by the University of Alcalá, Madrid, Spain, to monitor active layer thickness in Deception Island, South Shetland Islands, Antarctica.</p> <p>In 2012, nine arrays were installed at nodes with relative coordinates (00,00), (00,05), (00,10), (05,00), (05,05), (05,10), (10,00), (10,05), and (10,10). Measurements were taken at heights of 2.5, 5, 10, 15, 20, 25, 30, and 40 cm above the ground surface using DS1921G iButton loggers, which recorded air/snow temperatures every 4 hours. This experiment, referred to as 'Mini', was active until early 2021.</p> <p>Between 2017 and 2023, four arrays were installed at nodes (00,010), (05,05), (06,00), and (10,00). These arrays measured air/snow temperatures at heights of 2.5, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, and 160 cm above the ground surface using DS1922L iButton loggers, which recorded temperatures every 3 hours. Three of the arrays of this experiment, referred to as 'HR', has also been discontinued in early 2021, althought one of them was active until early 2024.</p>
BALTRAD_VPTS - Vertical profiles of biological targets derived from European weather radars
<p><em>BALTRAD_VPTS - Vertical profiles of biological targets derived from European weather radars</em> is a vertical profile time series dataset published by the <a href="https://www.inbo.be/en">Research Institute for Nature and Forest (INBO)</a>. It contains animal movement data derived from 151 European weather radars in 18 countries, with varying coverage from 2012 to 2023. These data were created by processing weather radar data - provided by the Operational Programme for the Exchange of Weather Radar Information (<a href="https://www.eumetnet.eu/activities/observations-programme/current-activities/opera/">OPERA</a>) - with methods optimized for extracting bird targets. The resulting data are vertical profile time series (VPTS), containing the density, speed and direction of biological targets within a weather radar (<code>radar</code>) volume, grouped into altitude bins (<code>height</code>) and measured over time (<code>datetime</code>). The data are also available in the <a href="https://aloftdata.eu/browse/?prefix=baltrad/">Aloft bucket</a>.</p> <div> <div>See Desmet et al. (2025, <a href="https://doi.org/10.1038/s41597-025-04641-5">https://doi.org/10.1038/s41597-025-04641-5</a>) for a more detailed description of this dataset.</div> </div> <h2>Files</h2> <p>VPTS data in this deposit are organized per country (.tgz file), radar (directory), year (directory) and month (.csv.gz file). Fields in the data follow the <a href="https://aloftdata.eu/vpts-csv/">VPTS CSV</a> format and are described in <code>vpts-csv-table-schema.json</code>. An overview of what data are available is provided in <code>coverage.csv</code>. Radar metadata can be found at <a href="https://aloftdata.eu/radars/">https://aloftdata.eu/radars/</a>.</p> <ul> <li><strong>coverage.csv</strong>: coverage of the VPTS data, representing the number of unique hours, heights, source files and records for each radar and date combination.</li> <li><strong>vpts-csv-table-schema.json</strong>: technical description of the fields in the VPTS data.</li> <li><strong>be.tgz</strong>: VPTS data from 2 radars in Belgium.</li> <li><strong>ch.tgz</strong>: VPTS data from 5 radars in Switzerland.</li> <li><strong>cz.tgz</strong>: VPTS data from 2 radars in Czechia.</li> <li><strong>de.tgz</strong>: VPTS data from 20 radars in Germany.</li> <li><strong>dk.tgz</strong>: VPTS data from 5 radars in Denmark.</li> <li><strong>ee.tgz</strong>: VPTS data from 2 radars in Estonia.</li> <li><strong>es.tgz</strong>: VPTS data from 15 radars in Spain.</li> <li><strong>fi.tgz</strong>: VPTS data from 13 radars in Finland.</li> <li><strong>fr.tgz</strong>: VPTS data from 26 radars in France.</li> <li><strong>hr.tgz</strong>: VPTS data from 7 radars in Croatia.</li> <li><strong>il.tgz</strong>: VPTS data from 1 radar in Israel.</li> <li><strong>nl.tgz</strong>: VPTS data from 3 radars in the Netherlands.</li> <li><strong>no.tgz</strong>: VPTS data from 11 radars in Norway.</li> <li><strong>pl.tgz</strong>: VPTS data from 8 radars in Poland.</li> <li><strong>pt.tgz</strong>: VPTS data from 3 radars in Portugal.</li> <li><strong>se.tgz</strong>: VPTS data from 22 radars in Sweden.</li> <li><strong>si.tgz</strong>: VPTS data from 2 radars in Slovenia.</li> <li><strong>sk.tgz</strong>: VPTS data from 4 radars in Slovakia.</li> </ul> <h2>Acknowledgements</h2> <p>This dataset was processed using infrastructure provided by the University of Amsterdam, SURF Cooperative, Ghent University and the Research Institute for Nature and Forest (INBO). It was mainly supported by the <a href="https://globam.science/">GloBAM project</a>, funded through the 2017-18 Belmont Forum and BiodivERsA joint call for research proposals under the BiodivScen ERA-Net COFUND programme.</p>
UVA_VPTS - Vertical profiles of biological targets derived from weather radars in Belgium, Germany and the Netherlands
<p><em>UVA_VPTS - Vertical profiles of biological targets derived from weather radars in Belgium, Germany and the Netherlands</em> is a vertical profile time series dataset published by the <a href="https://www.inbo.be/en">Research Institute for Nature and Forest (INBO)</a>. It contains animal movement data derived from 24 weather radars in Belgium, Germany and the Netherlands, with varying coverage from 2008 to 2023. These data were created by processing weather radar data - provided by the Royal Meteorological Institute of Belgium (<a href="https://www.meteo.be/">RMI</a>), German Meteorological Service (<a href="https://www.dwd.de/">DWD</a>) and Royal Netherlands Meteorological Institute (<a href="https://www.knmi.nl/">KMNI</a>) - with methods optimized for extracting bird targets. The resulting data are vertical profile time series (VPTS), containing the density, speed and direction of biological targets within a weather radar (<code>radar</code>) volume, grouped into altitude bins (<code>height</code>) and measured over time (<code>datetime</code>). The data are also available in the <a href="https://aloftdata.eu/browse/?prefix=uva/">Aloft bucket</a>.</p> <p>See Desmet et al. (2025, <a href="https://doi.org/10.1038/s41597-025-04641-5">https://doi.org/10.1038/s41597-025-04641-5</a>) for a more detailed description of this dataset.</p> <h2>Files</h2> <p>VPTS data in this deposit are organized per country (.tgz file), radar (directory), year (directory) and month (.csv.gz file). Fields in the data follow the <a href="https://aloftdata.eu/vpts-csv/">VPTS CSV</a> format and are described in <code>vpts-csv-table-schema.json</code>. An overview of what data are available is provided in <code>coverage.csv</code>. Radar metadata can be found at <a href="https://aloftdata.eu/radars/">https://aloftdata.eu/radars/</a>.</p> <ul> <li><strong>coverage.csv</strong>: coverage of the VPTS data, representing the number of unique hours, heights, source files and records for each radar and date combination.</li> <li><strong>vpts-csv-table-schema.json</strong>: technical description of the fields in the VPTS data.</li> <li><strong>be.tgz</strong>: VPTS data from 3 radars in Belgium.</li> <li><strong>de.gz</strong>: VPTS data from 18 radars in Germany.</li> <li><strong>nl.gz</strong>: VPTS data from 3 radars in the Netherlands.</li> </ul> <h2>Acknowledgements</h2> <p>This dataset was processed using infrastructure provided by the University of Amsterdam, SURF Cooperative, Ghent University and the Research Institute for Nature and Forest (INBO). It was mainly supported by the <a href="https://globam.science/">GloBAM project</a>, funded through the 2017-18 Belmont Forum and BiodivERsA joint call for research proposals under the BiodivScen ERA-Net COFUND programme.</p>
Vertical profiles of in-situ biogenic silica (bSi) from discrete rosette bottle samples from CCE-LTER starting with cruise P1706.
Samples are taken at discrete depths from rosette bottles in the California Current Ecosystem and measured for biogenic silica (bSi) concentration to create bSi depth profiles. Diatom community and physiology affect biogenic silica concentration. These data are being used to investigate the effects of Fe limitation on carbon and silica cycling in the CCE.
Vertical profiles of stable water isotopes and thermodynamic properties from research flights during the L-WAIVE field campaign in June 2019
<p>This datasets contains the measurements of stable water isotopes conducted during the Lacustrine-Water vApor Isotope inVentory Experiment (L-WAIVE) field campaign taking place in June 2019 in the Annecy valley in the French Alps (Chazette et al. 2021). The measurements were conducted using a Picarro laser spectrometer L2130-i that was installed on an ultralight aircraft. The Picarro measurements of atmospheric humidity are merged measurements of thermodynamic properties by a fast-response temperature and humidity probe (iMet XQ-2; see also Chazette et al. 2021) interpolated on 10s temporal resolution.</p> <p>The data is provided on a one file per flight. All variables are described in README.</p> <p>This dataset has been used in Thurnherr et al. (submitted) for a comparison study of stable water isotopes measurements from various platforms and COSMOiso model simulations.</p>
Vertical profiles of air temperature, relative humidity, wind speed and direction observed using UAV over the Mukhrino peatland in June 2022
<p>Vertical profiles of air temperature and relative humidity were measured using the iMetXQ2 sensor onboard DJI Phantom 4 quad-copter; vertical profiles of wind speed and direction were obtained from the Phantom 4 flight logs as produced by the DJI proprietary algorithm. </p>
Global characterization of the ocean's internal gravity wave vertical wavenumber spectrum from Argo float profiles
<p>Oceanic internal gravity wave energy levels E (m^2/s^2), vertical wavenumber spectral slopes s, and vertical wavenumber scale m* (1/m) estimated by fitting the Garrett Munk model vertical wavenumber shape function to strain spectra obtained from Argo float hydrographic profiles based on the finestructure method, as discussed in Pollmann (2020): "Global Characterization of the Ocean’s Internal Wave Spectrum" (<em>Journal of Physical Oceanography</em> 50.7: 1871-1891). The paper and hence this dataset are a contribution to the Collaborative Research Centre TRR181 ‘Energy Transfers in Atmosphere and Ocean’ funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Projektnummer 274762653. The hydrographic profiles used in this study were collected and made freely available by the International Argo Program and the national programs that contribute to it (http://www.argo.ucsd.edu, http://argo.jcommops.org). The Argo Program is part of the Global Ocean Observing System.</p> <p>Please cite Pollmann (2020) when using this dataset.</p> <p>This dataset includes:</p> <p>a) energy density (m^2/s^2) binned into 1°x1° horizontal bins and averaged into 3 depth bins (300-500 m, 500-1000 m, 1000-2000 m)</p> <p>b) vertical wavenumber spectral slopes binned into 1°x1° horizontal bins and averaged into 3 depth bins (300-500 m, 500-1000 m, 1000-2000 m)</p> <p>c) vertical wavenumber scale m* (1/m) binned into 1°x1° horizontal bins and averaged into 3 depth bins (300-500 m, 500-1000 m, 1000-2000 m)</p> <p>d) latitude and longitude, defined such that, e.g., E(10,10) represents energy levels in the bin bounded by lat(10), lat(11) as well as lon(10), lon(11)</p>
Vertical profiles and integrated time series of bird density and flight speed vector (19.09.2016-10.10.2016)
<p><strong>Description</strong></p> <p>This dataset contains the vertical profiles and integrated time series of bird density and flight speed (NS and EW) used in Nussbaumer (2019) [open access: <a href="https://www.mdpi.com/2072-4292/11/19/2233">https://www.mdpi.com/2072-4292/11/19/2233</a>]. Data are stored in a JavaScript Object Notation (JSON) file for each radar, with the following structure:</p> <pre><code>{ "name" : "bejab", //code name of the radar (http://eumetnet.eu/wp-content/themes/aeron-child/observations-programme/current-activities/opera/database/OPERA_Database/index.html) "lat" : 51.1917, //Latitude "lon" : 3.0642, //Longitude "height" : 50, //Height of the radar antenna [m] a.s.l. "maxrange" : 25, //Maximum range [km] used for profile "alt" : [100, 300,...], "time" : ["19-Sep-2016 00:00:00", "19-Sep-2016 00:05:00",...], "dens" : [[...],...], //Vertical profile of bird density [1/km3] "u" : [[...],...], //Vertical profile of bird flight speed in East(+)/West(-) [m/s] "v" : [[...],...], //Vertical profile of bird flight speed in North(+)/South(-) [m/s] "denss" : [...], //Integrated profile of bird density [1/km2] "us" : [...], //Integrated profile of bird flight speed in East(+)/West(-) [m/s] "vs" : [...], //Integrated profile of bird flight speed in North(+)/South(-) [m/s] }</code></pre> <p> </p> <p><strong>Procedure</strong></p> <p>The raw data are downloaded on the <a href="http://enram.github.io/data-repository/">ENRAM repository</a>,( see Dokter (2011) and (2019) for more details) and processed according to the procedure described below.</p> <ol> <li>Of the 84 radars contributing data during the study period, 11 radars are discarded because of their poor quality due to S-band radar type, poor processing or large gaps (temporal or altitude cut). The same radars were removed in Nilsson et al. (2019).In addition, the 4 radars from Bulgaria and Portugal were excluded because of their geographic isolation.</li> <li>The full vertical profile was discarded when rain was present at any altitude bin. A dedicated MATLAB GUI was used to visualise the data and manually set bird densities to “not-a-number” in such cases. </li> <li>Zones of high bird densities can sometimes be incorrectly eliminated in the raw data. To address this, Nilsson et al. (2019) excluded problematic time or height ranges from the data. Here, in order to keep as much data as possible, the data was manually edited to replace erroneous data either with “not-a-number”, or by cubic interpolation using the dedicated MATLAB GUI.</li> <li>Due to ground scattering,the lower altitude layers are sometimes contaminated by errors or excluded in the raw data. We vertically interpolated bird density by copying the first layer without error into to the lower ones. This approach is relatively conservative as bird migration intensity usually decreases with height in the absence of obstacles, and more so in autumn (Bruderer, 2018)</li> <li>The vertical profiles are vertically integrated from the radar altitude and up to 5000 m asl.</li> <li>The data recorded during daytime are excluded. Daytime is defined at each radar by the civil dawn and dusk (6° below horizon).</li> <li>Finally, the data of 10 radars with high temporal resolution (5-10minutes) was down-sampled to 15 minutes to preserve a balanced representation of each radar.</li> </ol> <p>The resulting cleaned vertical-integrated time series of nocturnal bird density can be viewed in vp_corrected.zip.</p> <p>More details and illustrations are available in Nussbaumer (2019) [open access: <a href="https://www.mdpi.com/2072-4292/11/19/2233">https://www.mdpi.com/2072-4292/11/19/2233</a>], </p> <p><strong>Acknowledgement</strong></p> <p>We acknowledge the <a href="http://eumetnet.eu/activities/observations-programme/current-activities/opera/">European Operational Program for Exchange of Weather Radar Information (EUMETNET/OPERA)</a> for providing access to European radar data, faciliated through a research-only license agreement between EUMETNET/OPERA members and <a href="http://enram.eu/">ENRAM</a>.</p> <p> </p> <p><strong>References</strong></p> <p>Bruderer, B.; Liechti, F. Variation in density and height distribution of nocturnal migration in the south of israel. <em>Israel Journal of Zoology</em> <strong>1995</strong>, <em>41</em>, 477–487. <a href="http://doi.org/10.1080/00212210.1995.10688815">doi:10.1080/00212210.1995.10688815</a>.</p> <p>Dokter A. M. , F. Liechti, H. Stark, L. Delobbe, P. Tabary, and I. Holleman, “Bird migration flight altitudes studied by a network of operational weather radars,” <em>J. R. Soc. Interface</em>, vol. 8, no. 54, pp. 30–43, Jan. <strong>2011</strong>. <a href="http://doi.org/10.1098/rsif.2010.0116">doi:10.1098/rsif.2010.0116</a></p> <p>Dokter A. M. , P. Desmet, J. H. Spaaks, S. van Hoey, L. Veen, L. Verlinden, C. Nilsson, G. Haase, H. Leijnse, A. Farnsworth, W. Bouten, and J. Shamoun‐Baranes, “bioRad: biological analysis and visualization of weather radar data,” <em>Ecography </em>(Cop.)., vol. 42, no. 5, pp. 852–860, May <strong>2019</strong>. <a href="http://doi.org/10.1111/ecog.04028">doi: 10.1111/ecog.04028</a></p> <p>Nilsson, C.; Dokter, A.M.; Verlinden, L.; Shamoun-Baranes, J.; Schmid, B.; Desmet, P.; Bauer, S.; Chapman, J.; Alves, J.A.; Stepanian, P.M.; Sapir, N.;Wainwright, C.; Boos, M.; Górska, A.; Menz, M.H.M.; Rodrigues, P.; Leijnse, H.; Zehtindjiev, P.; Brabant, R.; Haase, G.; Weisshaupt, N.; Ciach, M.; Liechti, F. Revealing patterns of nocturnal migration using the European weather radar network. <em>Ecography </em><strong>2019</strong>, <em>42</em>, 876–886. <a href="http://doi.org/10.1111/ecog.04003">doi:10.1111/ecog.04003</a>.</p> <p>Nussbaumer R., L. Benoit, G. Mariethoz, F. Liechti, S. Bauer, and B. Schmid, “A Geostatistical Approach to Estimate High Resolution Nocturnal Bird Migration Densities from a Weather Radar Network,” <em>Remote Sens</em>., vol. 11, no. 19, p. 2233, Sep. <strong>2019</strong>. <a href="https://www.mdpi.com/2072-4292/11/19/2233">doi: 10.3390/rs11192233</a></p> <p> </p> <p> </p>
Text-fig. 8. Eospondylus cf. primigenius (STÜRTZ) "Červený lom" quarry near Praha-Klukovice, Loděnice Limestone, Lower Devonian, Pragian, NM L 36910, x 25. Left lateral plate, outer view. The surface leading to the vertical ridge flairs outward. The height profile leaves uncovered part of the side of the arm vertebra. in Isolated Ossicles Of The Family Eospondylidae Spencer Wright, 1966, In The Lower Devonian Of Bohemia (Czech Republic) And Correction Of The Systematic Position Of Eospondylid Brittlestars (Echinodermata: Ophiuroidea: Oegophiurida)
Text-fig. 8. Eospondylus cf. primigenius (STÜRTZ) "Červený lom" quarry near Praha-Klukovice, Loděnice Limestone, Lower Devonian, Pragian, NM L 36910, x 25. Left lateral plate, outer view. The surface leading to the vertical ridge flairs outward. The height profile leaves uncovered part of the side of the arm vertebra.
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>
Vertical Microstructure Profiler (VMP-2000) data from Investigator cruise IN2018 V05
<p>VMP-2000 CTD and microstructure data from IN2018_v05</p> <p>measured temperature [C]</p> <p>salinity [PSU]</p> <p>pressure [Dbars]</p> <p>rate of dissipation of kinetic energy [W/kg]</p> <p>rate of dissipation of thermal variance [C^2/s]</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>
OMPS-NPP L2 LP USask Aerosol Extinction Vertical Profile swath daily V1.2
<p>The USask OMPS-LP L2 2D Aerosol v1.2 product provides stratospheric aerosol extinction retrievals performed at the University of Saskatchewan for the central slit of the Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP) instrument on the Suomi-NPP satellite. The two-dimensional retrieval algorithm accounts for variation in the along orbital track dimension, retrieving an entire orbit simultaneously instead of treating each image independently. Stratospheric aerosol is retrieved from approximately the thermal tropopause to 30 km on a 1 km grid with a vertical resolution of approximately 2 km, and is assumed to be sulfate aerosol following a log-normal particle size distribution.</p> <p>Each file contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-82 to +82 degrees latitude), and there are about 14.5 orbits per day, each has typically 160 profiles with an along orbital track sampling of 125 km. The files are written using NetCDF4.</p>
Vertical plant profiles for Dassenbos (NL, 2014-2018, TLS); Wytham Woods (UK, 2022, LEAF) & Northern Australia (2021-2022, LEAF)
<p>This dataset was described and used for the analysis of the following publication:<br> <em>StrucNet: A global network for automated vegetation structure monitoring. Brede, B., Newnham, G., Culvenor, D., Armston, J., Bartholomeus, H., Griebel, A., Hayward, J., Junttila, S., Lau, A., Levick, S., Morrone, R., Origo, N., Pfeifer, M., Verbesselt, J. & Herold, M. Remote Sensing in Ecology and Conservation (accepted)</em></p> <p><strong>Any use of this dataset should cite the paper above </strong>(Creative Commons Attribution 4.0 International Public License).</p> <p>Contact: kim.calders@ugent.be</p> <p> </p> <p>================================================<br> Dataset<br> ================================================</p> <p>1) TLS vertical plant profiles Dassenbos. Five-year dynamics of forest structure for the four sampling locations in Dassenbos. Data were collected using the same measurement protocol and data analysis using https://www.pylidar.org/ as described in Calders et al. (2015) using a zenith range of 35-70 degrees for 184-186 (some scans were discarded for quality purposes) measurement days during the period from February 2014 to November 2018. The data repository contains the vertical plant profiles and plotting code (Fig 1 in paper)</p> <p>2) One-year dynamics of vegetation structure for a tropical savanna site in Northern Australia (Fig 2 in paper) and Wytham Woods (Fig 3 in paper). The data repository contains the vertical plant profiles derived from LEAF data and plotting code.</p>
TEAMx-PC22 (TEAMx pre-campaign 2022) – Vertical profiles and Multi-Point In-Situ Measurements at Nafingalm collected with the SWUF-3D UAS fleet
<p>This dataset contains aggregated measurements from a fleet of multicopter UAS. The data was measured during the period 21 June 2022 through 27 June 2022 at Nafingalm, Austria with the SWUF-3D fleet. The data was collected in association to the TEAMx-PC22 field campaign. A maximum of three UAS were operated simultaneously. Processed level-2 data is provided. For level-2 data, time synchronization between individual UAS was done through interpolation, if multiple UAS are operated simultaneously.</p> <p>In this dataset vertical profiles (swuf3dvpro) between 10m and 120m above ground level and time series of UAS hovering for approx. 10 minutes at fixed positions (swuf3dhover) are provided with a temporal resolution of 1 Hz.</p> <p>The data are provided in NetCDF format with metadata and variable descriptions in the style of the SAMD Product standard: Jahnke-Bornemann, Annika. (2022, August 18). The SAMD Product Standard (Standardized Atmospheric Measurement Data) (Version 2.2). http://doi.org/10.25592/uhhfdm.10416</p>
Vertical profiling of the electrical properties of charged desert dust during the pre-ASKOS campaign: Dataset
<p>The zipped files contain the datasets used to produce Figure 1 of the following conference proceedings paper:</p> <p>Vasiliki Daskalopoulou, George Hloupis, Sotirios A. Mallios, Ilias Makrakis, Evangelos Skoubris, Maria Kezoudi, Zbigniew Ulanowski, & Vassilis Amiridis. (2021, July 6). <em>Vertical profiling of the electrical properties of charged desert dust during the pre-ASKOS campaign</em>. 15th International Conference on Meteorology, Climatology and Atmospheric Physics (COMECAP 2021), Ioannina, Greece. https://doi.org/10.5281/zenodo.5076042</p> <p>The repository contains overall:</p> <ol> <li>the ground-based JCI 131 Fieldmill Electrometer data that were acquired during the campaign (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Fieldmill_Ion_counter_Cyprus_campaign.rar">Fieldmill_Ion_counter_Cyprus_campaign.rar</a>)</li> <li>Data from an Alphalab Air Ion counter co-located with the fieldmill (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Fieldmill_Ion_counter_Cyprus_campaign.rar">Fieldmill_Ion_counter_Cyprus_campaign.rar</a>)</li> <li>Data from the five MiniMill electrometers that were launched (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/MiniMills_Cyprus_campaign.rar">MiniMills_Cyprus_campaign.rar</a>)</li> <li>Data from the two of the charge sensors that were launched (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Charge_sensors_Cyprus_campaign.rar">Charge_sensors_Cyprus_campaign.rar</a>)</li> <li>Data from the eleven ion counters that were launched, tethered together with the MiniMills or the charge sensors (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Ion_counters_Cyprus_campaign.rar">Ion_counters_Cyprus_campaign.rar</a>)</li> <li>A campaign calendar with the launches schedule (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Cyprus_campaign_November2019_calendar.pdf">Cyprus_campaign_November2019_calendar.pdf</a>).</li> </ol>
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.