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1,977 results for “2007”

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zenodo40/100

NERC MSTRF Sky-Camera Time-Lapse Video for 2007-09-30 14:30 UTC (showing Altocumulus clouds displaying both undulatus and lenticularis features).

<p>A time-lapse video showing Altocumulus clouds displaying both undulatus and lenticularis features. A lower cloud layer can be seen moving in a different direction at the beginning of the sequence. Contrails and cirrus clouds can be seen at higher levels. This video has been created from images taken by the NERC MST Radar Facility&#39;s Sky-Camera, which is located near Aberystwyth in West Wales. The images are freely available, under an Open (UK) Government License, from http://tinyurl.com/nerc-mstrf-sky-camera/ . For an explanation of the atmospheric phenomena that can be seen, download the resource available at http://cedadocs.ceda.ac.uk/1259/ .</p>

opencc-by-4.0Jul 2017View details →
zenodo40/100

NCAS CDAO Sky-Camera Time-Lapse Video for 2007-10-04 05:30 UTC (showing Cumulus mediocris clouds).

<p>A time-lapse video showing Cumulus mediocris clouds (with occasional Cirrus clouds and contrails at a higher level). The Cumulus clouds are in a continuous state of change. Many can be seen to form and/or to evaporate within the field of view. The evaporating clouds give rise to ragged Cumulus fractus formations. This video has been created from images taken by the Sky-Camera at the National Centre for Atmospheric Science (NCAS) Capel Dewi Atmospheric Observatory (CDAO) near Aberystwyth, UK - formerly known as the Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar Facility. The images are freely available under a UK Open Government Licence from http://tinyurl.com/nerc-mstrf-sky-camera/ . For more details visit http://mst.nerc.ac.uk .</p>

opencc-by-4.0Dec 2019View details →
zenodo40/100

NERC MSTRF Sky-Camera Time-Lapse Video for 2007-05-29 03:00 UTC.

<p>A time-lapse video showing the development of Cumulus congestus clouds, leading to a Rain Shower and a Rainbow. This video has been created from images taken by the NERC MST Radar Facility&#39;s Sky-Camera, which is located near Aberystwyth in West Wales. The images are freely available, under an Open (UK) Government License, from http://tinyurl.com/nerc-mstrf-sky-camera/ . For an explanation of the atmospheric phenomena that can be seen, download the resource available at http://cedadocs.ceda.ac.uk/1259/ .</p>

opencc-by-4.0Jun 2017View details →
zenodo40/100

NCAS CDAO Sky-Camera Time-Lapse Video for 2007-05-21 03:00 UTC (showing Altocumulus undulatus clouds).

<p>A time-lapse video showing Altocumulus undulatus clouds. The cloud layer initially appears to be of Stratocumulus type, with relatively poorly-defined undulatus elements. However, the layer soon breaks up to give well-defined Altocumulus undulatus. Cirrus clouds and contrails can be seen at a higher level towards the end of the sequence. This video has been created from images taken by the Sky-Camera at the National Centre for Atmospheric Science (NCAS) Capel Dewi Atmospheric Observatory (CDAO) near Aberystwyth, UK - formerly known as the Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar Facility. The images are freely available under a UK Open Government Licence from http://tinyurl.com/nerc-mstrf-sky-camera/ . For more details visit http://mst.nerc.ac.uk .</p>

opencc-by-4.0Dec 2019View details →
zenodo40/100

NCAS CDAO Sky-Camera Time-Lapse Video for 2007-09-04 17:50 UTC (showing Stratocumulus clouds that develop wave-like asperitas features).

<p>A time-lapse video showing Stratocumulus clouds that develop wave-like asperitas features. During the early part of the sequence, there appear to be layers of cloud at two distinct levels. These are lit differently by the setting sun. The asperitas features begin to appear approximately half way through the sequence. Altocumulus undulatus clouds can be seen towards the end. This video has been created from images taken by the Sky-Camera at the National Centre for Atmospheric Science (NCAS) Capel Dewi Atmospheric Observatory (CDAO) near Aberystwyth, UK - formerly known as the Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar Facility. The images are freely available under a UK Open Government Licence from http://tinyurl.com/nerc-mstrf-sky-camera/ . For more details visit http://mst.nerc.ac.uk .</p>

opencc-by-4.0Dec 2019View details →
zenodo40/100

Backtracked trajectories of passive particles in the Virgin Islands Basin (2007-2017) using Ocean Parcels

<p>Backtracked trajectories of 100 passive particles released in the Virign Islands Basin daily from 2007-2017. Backtracking is done for 100 days. Surface velocity fields are from GLORYS reanalysis.&nbsp;<br> <br> Corresponding author: Giovanni Seijo-Ellis (giovanni.seijo@colorado.edu)</p>

opencc-by-4.0Dec 2022View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Dec)

<p>2007-Dec SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Nov)

<p>2007-Nov SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Oct)

<p>2007-Oct SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Jun)

<p>2007-Jun SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-May)

<p>2007-May SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Sep)

<p>2007-Sep SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Apr)

<p>2007-Apr SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Aug)

<p>2007-Aug SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Jul)

<p>2007-Jul SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Mar)

<p>2007-Mar SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

SuperDARN Grid data in netCDF format (2007-Feb)

<p>2007-Feb SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroFeb 2023View details →
zenodo40/100

One meter integrated depth velocity (total, ageostrophy, Ekman and Stokes components) fields for the Mediterranean Sea each 6 hours (from 2007 to 2018)

<p>One meter integrated depth surface velocity fields for the Mediterranean Sea from January 2007 to June 2018 calculated following the methodology in Morales-Marquez et al.(2020). This dataset provides the total velocity field, the ageostrophic, Ekman and Stokes components.</p>

opencc-by-4.0Mar 2023View details →
zenodo40/100

Observed and modelled GPP at 61 eddy covariance sites (2007-2018)

<p>In the frame of the ECOPROPHET project, data was collected from in situ observations, remote-sensing sources and models for 61 sites. The objective of this project was to improve our understanding of ecosystem productivity and the role of vegetation phenology as a key determinant of ecosystem carbon, water and energy balances. More info and publications can be found at http://ecoprophet.meteo.be<br> This dataset contains timeseries of observed GPP, modelled GPP (using 15 models), along with key hydrometeorological variables (shortwave radiation, air temperature, vapor pressure deficit and soil moisture).<br> The timeseries are at daily resolution, covering the period 2007-2018 (depending on the data availability per site).<br> The dataset is partly extracted from:</p> <ul> <li>FLUXNET2015 dataset (Pastorello et al., 2020) and the ICOS &rsquo;2018 drought initiative&rsquo; dataset (Drought 2018 Team<br> and ICOS Ecosystem Thematic Centre, 2019). Original dataset available at <a href="https://fluxnet.org/">https://fluxnet.org/</a> and <a href="https://www.icos-cp.eu/data-products/">https://www.icos-cp.eu/data-products/</a> YVR0-4898</li> <li>ERA5 product (Hersbach et al., 2020); Original dataset available at <a href="https://cds.climate.copernicus.eu/">https://cds.climate.copernicus.eu/</a></li> <li>MODIS: Original dataset available at <a href="https://modis.gsfc.nasa.gov/data/">https://modis.gsfc.nasa.gov/data/</a></li> <li>SPOT Vegetation/PROBA V: Original dataset available at <a href="https://land.copernicus.eu/global/">https://land.copernicus.eu/global/</a></li> <li>Downscaled GOME2 SIF product by Duveiller et al. (2020). Original dataset available at <a href="https://doi.org/10.2905/21935FFC-B797-4BEE-94DA-8FEC85B3F9E1">https://doi.org/10.2905/21935FFC-B797-4BEE-94DA-8FEC85B3F9E1</a></li> <li>FluxCom product ensemble (Jung et al., 2020). Original dataset available at <a href="http://fluxcom.org/">http://fluxcom.org/</a></li> </ul> <p><strong>File descriptions</strong>:<br> README.pdf : description<br> EcopropheciesMeta.txt : metadata<br> EcopropheciesDataset.txt : data</p> <p>More details and analysis of the data can be found in:<br> De Pue, J., Wieneke, Bastos, A., S., Barrios, J.M., Liu, L., Ciais, P., Arboleda, A., Hamdi, R., Maleki, M., Maignan, F., Gellens-Meulenberghs, F., Janssens, I., and Balzarolo, M., Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers 2023, Agricultural and Forest Meteorology (submitted)</p>

opencc-by-4.0May 2023View details →
zenodo40/100

Figures 3–6 in A REDESCRIPTION OF ZAVRELIA BRAGREMIA GUO & WANG, 2007 (DIPTERA: CHIRONOMIDAE) Abstract

Figures 3–6. Zavrelia bragremia Guo &amp; Wang, 2007, male. 3, thorax; 4, wing; 5, abdomen, dorsal view; 6, abdomen, ventral view. Scales = 100 μm.

opencc-by-4.0Oct 2017View details →

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Last verified 2026-04-30Open record

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International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

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OpenNeuro

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Last verified 2026-04-29Open record