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10,016 results for “Observation”
A case study on the impact of interplanetary coronal mass ejection on the Martian O(1S) 557.7 nm dayglow emission using ExoMars TGO/NOMAD-UVIS observations: First Results
<p>This study presents the impact of interplanetary coronal mass ejection (ICME) on the O(1S) 557.7 nm dayglow emission in the Martian atmosphere using instruments onboard ExoMars-TGO and MAVEN spacecrafts.</p>
Individual colors of the NEOROCKS objects observed between 2022 and 2023.
Open the record for dataset details and reuse information.
Dataset used in Kittel et al., 2017 (https://doi.org/10.5194/hess-2017-549), including model files and processed remote sensing observations (CryoSat-2 radar altimetry and GRACE total water storage)
<p>Dataset used in</p> <p>Kittel, C. M. M., Nielsen, K., Tøttrup, C., Bauer-Gottwein, P., 2017.Informing a hydrological model of the Ogooué with multi-mission remote sensing data. Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-549</p> <p>The dataset contains</p> <p>Model files:</p> <ul> <li>River delineation of the Ogooué river based on the SRTM 3 arc-second DEM </li> <li>Climate input data for the Ogooué model subbasins (TRMM and FEWS-RFE precipitation and ECMWF temperature)</li> <li>Parameter files</li> </ul> <p>Processed remote sensing data:</p> <ul> <li>CryoSat-2 satellite altimetry data over the Ogooué River from July 2010 to February 2015</li> <li><strong> </strong>Water mask derived from Sentinel-1 SAR, used to filter CryoSat-2 data</li> <li>GRACE TWS time series for the Ogooué basin</li> </ul> <p>The data is provided in a .zip file with a README.txt file providing additional information and details on the data, including where to obtain similar/original datasets.</p> <p>(c) Author(s) and Technical University of Denmark (DTU) 2018</p>
Fig. 57 in The Southeast Asian Pholcus halabala species group (Araneae, Pholcidae): new data from field observations and ultrastructure
Fig. 57. Known distributions of species tentatively assigned to the Pholcus halabala species group.
Fig. 17 in The Southeast Asian Pholcus halabala species group (Araneae, Pholcidae): new data from field observations and ultrastructure
Fig. 17. Known distribution of the core group of the Pholcus halabala species group.
Fig. 110 in The Southeast Asian Pholcus halabala species group (Araneae, Pholcidae): new data from field observations and ultrastructure
Fig. 110. Known distribution of the Pholcus krabi species group.
INTEGRAL observations of FRB180301
<p>INTEGRAL observations of FRB180301</p>
Selected CO2 and Meteorological Data from BErkeley Atmospheric CO2 Observation Network
<p>Selected CO<sub>2</sub> and meteorological data from BErkeley Atmospheric CO<sub>2</sub> Observation Network (BEACO<sub>2</sub>N) for use in the characterization of the heterogeneity of greenhouse gas concentrations around the San Francisco Bay Area and the constraint of CO<sub>2 </sub>emissions from mobile sources.</p>
Observation data and numerical model files for river plumes in Pallanza Bay of Lake Maggiore, Italy
<p>Data includes observation data collected from three deployments in Pallanza Bay of Lake Maggiore, Italy. Observation data includes velocity and thermistor chain data from deployments in 2012 and 2014, which captured a series of river plume discharges from the Toce River. Also included are numerical model source files and scenario files for simulations of river plumes into Pallanza Bay. </p>
Animated plots of the spectrum and polarisation of Cassiopeia A based on a 24 hour observation with LOFAR Station IE613 (LBA)
<p>This collection of animated plots over time of the variation in channel flux for the linear polarisation channels XX, XY and YY and Stokes Parameters U, V, I and Q against frequency for Cassiopeia A as observed at LOFAR station SE607 between 2018-04-06 and 2018-04-07 using the LBA</p>
Animated plots of the spectrum and polarisation of Cassiopeia A based on a 24 hour observation with LOFAR Station IE613 (LBA)
<p>This collection of animated plots over time of the variation in channel flux for the linear polarisation channels XX, XY and YY and Stokes Parameters U, V, I and Q against frequency for Cassiopeia A as observed at LOFAR station IE613 between 2018-04-06 and 2018-04-07 using the LBA</p>
Data for "Why Climate Sensitivity may be Constrained by Observable Natural Variability"
<p>Surface temperature and top-of-atmosphere radiation data from a 700-yr CO<sub>2</sub>-doubling experiment performed with the fully-coupled CESM1. Given on the CAM5 native grid (1 degree nominal resolution) as annual means. </p> <p>Data include annual TS (radiative surface temperature; in K), FLNT (net longwave radiation out at top-of-atmosphere), FSNT (net shortwave radiation in at top-of-atmosphere), FLNTC (net clear-sky longwave radiation out at top-of-atmosphere) and FSNTC (net clear-sky shortwave radiation out at top-of-atmosphere).</p>
Lithosphere removal (delamination) following continental collision: shape and complexity of observables predicted from 3D numerical models
<p>Upload contains most essential data files from the manuscript. The raw data amount to several TB and cannot be uploaded.</p> <p><strong>1 Model data</strong></p> <p><em>1.1 Models covered</em></p> <p>Relatively frequent output is available for the reference model (<em>R</em> in paper, see Table S2), prefixed <em>dp10</em>. Limited output is uploaded for models with geometric variations (<em>OSM -> dp19, TSM->dp26</em>).</p> <p><em>1.2 Types of data</em></p> <p>Most files are visualisation files (ending *.<em>vtr</em>). These are intended for loading into the visualisation software Paraview. Files starting with <em>comp_</em> contain the lithological composition field; other visualisation files hold the fields of selected physical parameters. Note that as of the design of the study, the maximum file size allowed for loading into Paraview is ca. 2 GB. This limits the number of fields available according to model size - larger models (geometrical variations) hold therefore less fields.</p> <p>Binary files with ending *.<em>prn</em> are saved model states, from which programs can be rerun.</p> <p>Time information mapping step numbers to years is provided in <em>times...txt</em>.</p> <p> </p> <p><strong>2 Software for reproduction</strong></p> <p>The numerical code is not in the public domain, and its use is restricted. A pre-compiled binary is provided and allows reproduction of the main/reference model. We present the input files; however, these cannot be changed freely (equivalent to software distribution), and changes will lead to termination of the program.</p> <p><em>2.1 Requirements, preparation and use</em></p> <p>The code is compiled on CentOS with gcc 4.8.2. There is no library dependency, apart from the intrinsic OpenMP and glibc (>= 2.17). The following requirements <em>must</em> be satisfied in order to run it:</p> <ul> <li>Linux OS (tested on CentOS and Fedora)</li> <li>> 160 GB shared memory</li> </ul> <p>The following provisions are recommended:</p> <ul> <li>16 cores</li> <li>high bandwidth storage</li> <li>storage space <em>O</em>(TB)</li> </ul> <p>To prepare, simply unzip the provided snapshot <em>clsd_reproduce_gcc_CentOS.zip</em> in an appropriate directory (cluster). The input file <em>init.t3c</em> sets the initial conditions; the input file <em>mode.t3c </em>controls solver and file output. <em>file.t3c</em> is the pointer to the last output step; if a model snapshot is available as binary dump (*.prn file), setting the pointer to its number allows restarting.</p> <p>For normal usage, create initial condition with executable <em>in3mg</em>, and subsequently run <em>i3mg</em>. This will create snapshots and *.vtr visualisation files.</p> <p> </p> <p>High-performance computing facilities, runtime (months), proper software environment, and training in use of the code, or in the use of the visualisation software, are not provided.</p> <p> </p>
Animated Plots of the variance of observed data from LOFAR Station IE613
<p>This series of animated plots illustrates the variation of the linear polarisation channels and Stokes parameters for an observation of CasA from LOFAR station IE613 against altitude and azimuth throughout the frequency range of LOFAR HBA.</p>
Time-lapse observations of snow bedforms in the Colorado Front Range, 2016-2017
<p><strong>Description:</strong> Time-lapse imagery of snow surfaces on Niwot Ridge, in the Colorado Front Range, between March 2016 and April 2017.</p> <p><strong>Purpose:</strong> Videos show the evolution of snow bedforms, including the formation and movement of snow dunes, snow ripples, and sastrugi. Used to analyze the modes of bedform movement, and to constrain the weather conditions in which they form.</p> <p><strong>Equipment, details + weather data: </strong>Time-lapse cameras are Day6 Plotwatcher Pros. They take images every 10s during daylight hours. The cameras are located at -40.054307, -105.590764, 150m upwind of the Niwot Ridge LTER Saddle Station. Bedform movement can thus be correlated with climate and precipitation data from the station, provided at niwot.colorado.edu</p> <p><strong>Filenames:</strong> Files are named yymmddAA.avi, where yy/mm/dd is the date of the recording. When multiple recordings were made in one day, there will be a yymmddAB.avi, yymmddAC.avi, etc. Some filenames are annotated with a description, eg 170226AA-sastrugi.avi. On a few dates (November 2016) the cameras recorded incorrect dates; on these days, the dates in the filenames are to be preferred.</p> <p>Date and time in video: the date, time and temperature are recorded in the bottom of the videos. The date and time are generally accurate, but if they differ from the date in the filename, that date is to be preferred and the time disregarded. Temperature in the film is generally colder than temperature recorded by the nearby weather station, and we generally disregarded it in favor of climate data from niwot.colorado.edu.</p> <p><strong>Data format:</strong> Data are presented as .avi files, which may be run by most video players. Data were originally recorded with proprietary .tlv file extension. The .tlv format is equivalent to .avi; if any .tlv files are found, simply rename them as .avi files and play as usual.</p> <p><strong>Acknowledgements:</strong> This research was supported by a Department of Energy Computational Science Graduate Fellowship (DE-FG02-97ER25308), by a University of Colorado Chancellor's Fellowship, and by the National Science Foundation via support for the Boulder Creek Critical Zone Observatory (EAR-1331828).<br> Field equipment was funded by the American Alpine Club; the Colorado Scientific Society; and a Patterson Award from the University of Colorado Department of Geological Sciences. Field assistants were funded by the University of Colorado Undergraduate Research Opportunities Program. Logistical support and climate data were provided by the NSF-supported Niwot Ridge Long-Term Ecological Research Project and the University of Colorado Mountain Research station.</p>
GRB 070306: Observing log and results from photometry
<p>Observation log and photometric results of GRB 070306 from Jaunsen et al. (2008), Ap.J. 681, p.453-461</p> <p> </p>
Mechanisms behind the low-cloud optical depth response to temperature in ARM site observations - datasets and scripts
<p>Datasets used in the analysis of the article Mechanisms behind the low-cloud optical depth response to temperature in ARM site observations, which was submitted to and subsequently published in Journal of Geophysical Research-Atmosphere. DOI: 10.1029/2018JD029359</p>
Observations of low-latitude traveling ionospheric disturbances by a 630-nm airglow imager and the CHAMP satellite over Indonesia
<p>We report the first comparison of ground and satellite measurements of low-latitude traveling ionospheric disturbances (TIDs). Three TID events were simultaneously observed by a 630-nm airglow imager and the CHAMP satellite on April 30, 2006 (event 1), September 28, 2006 (event 2), and April 12, 2004 (event 3) at Kototabang, Indonesia (geographic coordinates: 0.2$^\circ$S, 100.3$^\circ$E, geomagnetic latitude: 10.6$^\circ$S). In 630-nm airglow images of all three events, there are clear southward-moving structures. Events 1 and 2 are a single pulse with horizontal scales of $\sim$500--1000 km. Event 3 shows five wave fronts with a horizontal scale size of 500--1000 km. All three TIDs are medium-scale TIDs. Horizontal wavelengths of both airglow intensity at an average emission altitude of 250 km and CHAMP neutral density variations measured at 400 km are estimated by fitting a sinusoidal function to the observed data. For events 1 and 3, estimated horizontal wavelengths are nearly equal, indicating both instruments are observing the same wave. For event 1, the CHAMP electron density mapped along the geomagnetic field line onto the airglow altitude does not show wave structure similar<br> to the airglow variation. For events 2 and 3, the relationship of electron density and airglow intensity is unclear. These results suggest that the cause of the observed TID is not caused by ionospheric plasma instability but by gravity waves in the thermosphere. According to these results, we conclude that the observed TIDs in all three cases are caused by gravity waves in the thermosphere.</p>
SMART-R2 Ground based C-band mobile radar observations of Hurricane Harvey landfall 2017
<p>This dataset contains radar scans collected by Shared Mobile Atmospheric Research and Teaching Radar #2 (SMART-R2) near Woodsboro, Texas during Hurricane Harvey landfall, 25-26 August 2017.</p> <p>Extract the data on a Unix system with the command "tar zxf hurricane_harvey.smart-r2.tar.gz"</p> <p>Directory harvey/SR2/iris_data/product_raw contains the data. The files are in Sigmet raw product format, documented at:<br> ftp://ftp.sigmet.com/outgoing/manuals/IRIS_Programmers_Manual.pdf</p> <p>Directory hurricane_harvey.smart-r2/SR2/log/ contains the radar operator's log.</p> <p>The deployment was funded by RAPID grant AGS-1759479 from the National Science Foundation, funds from the School of Meteorology at the University of Oklahoma, and a NASA Earth and Space Science Fellowship Program grant 17-EARTH17R-72.</p> <p>For more information, please contact:<br> M. I. Biggerstaff drdoppler@ou.edu<br> G. D. Carrie gordon.carrie-1@ou.edu</p> <p> </p>
Data and code for "Observation and stabilization of photonic Fock states in a hot radio-frequency resonator"
<p>This folder contains all the code necessary to produce the figures of the paper entitled "Observation and stabilization of photonic Fock states in a hot radio-frequency resonator" written by Mario F. Gely, Marios Kounalakis, Christian Dickel, Jacob Dalle, Rémy Vatré, Brian Baker, Mark D. Jenkins and Gary A. Steele</p> <p><strong>Content: </strong></p> <p>data/<br> Contains multiple folders each corresponding to a measurement. <br> These are all time stamped. <br> Inside each of these folders is a python file which corresponds to the measurement script run using the open source STlab library (see version closest to the time stamp on https://github.com/steelelabgit/stlab).<br> There is also a DAT file containing the measurement data and an accompanying text file which provides the name and end values of the swept parameters<br> This data will be opened and manipulated in the ipython notebooks</p> <p>analysis_results/<br> Contains the results of the ipython notebooks _*.ipynb<br> These are run on a computer cluster and generate information used in other ipython notebooks</p> <p>adaptive_rwa_solver_bootstrap_diagonal*.py<br> Libraries used to run the adaptive rotating wave approximation simulations</p> <p>load_data.py<br> Modules used to load data from data/</p> <p>plotting_functions.py<br> Modules used to plot 3D data as well as to generate default matplotlib settings</p> <p>_*.ipynb<br> Notebooks run on a computer cluster (using python 2.7) to generate the information stored in analysis_results/ and used in other ipython notebooks</p> <p>1D_S4BC_S9.ipynb<br> Notebook which generates the figures 1D, S4(B,C) and S9 of the paper. <br> Other notebooks follow this same naming convention</p> <p>*.pdf<br> *.png<br> Plots generated from the ipython notebooks which are then imported in Adobe Illustrator to construct figures</p>
ScienceDex guides
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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.