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1,574 results for “atmospheres”

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dryad32/100

Data underlying the publication: Callisto's atmosphere: First evidence for H2 and constraints on H2O

<p>We explore the parameter space for the contribution to Callisto's H corona observed by the Hubble Space Telescope (Roth et al. 2017a) from sublimated H<sub>2</sub>O and radiolytically produced H<sub>2</sub> using the Direct Simulation Monte Carlo (DSMC) method. The spatial morphology of this corona produced via photo- and magnetospheric electron impact-induced dissociation is described by tracking the motion of and simulating collisions between the hot H atoms and thermal molecules including a near-surface O<sub>2</sub> component. Our results indicate that sublimated H<sub>2</sub>O produced from the surface ice, whether assumed to be intimately mixed with or distinctly segregated from the dark non-ice or ice-poor regolith, cannot explain the observed structure of the H corona. On the other hand, a global H<sub>2</sub> component can reproduce the observation, and is also consistent with enhanced electron densities observed at high altitudes by <em>Galileo</em>'s plasma-wave instrument (Gurnett et al. 1997, 2000), providing the first evidence of H<sub>2</sub> in Callisto's atmosphere. The range of H<sub>2</sub> surface densities explored, under a variety of conditions, that are consistent with these observations is ∼(0.4-1)×10<sup>8</sup> cm<sup>-3</sup>. The simulated H<sub>2</sub> escape rates and estimated lifetimes suggest that Callisto has a neutral H<sub>2</sub> torus. We also place a rough upper limit on the peak H<sub>2</sub>O number density (&lt;∼10<sup>8</sup> cm<sup>-3</sup>), column density (&lt;∼10<sup>15</sup> cm<sup>-2</sup>), and sublimation flux (&lt;∼10<sup>12</sup> cm<sup>-2</sup> s<sup>-1</sup>), all of which are 1-2 orders of magnitude less than that assumed in previous models. Finally, we discuss the implications of these results, as well as how they compare to Europa and Ganymede.</p>

opencc-zeroJun 2022View details →
dryad32/100

Data from: Atmospheric N deposition alters co-occurrence, but not functional potential among saprotrophic bacterial communities

The use of co-occurrence patterns to investigate interactions between micro-organisms has provided novel insight into organismal interactions within microbial communities. However, anthropogenic impacts on microbial co-occurrence patterns and ecosystem function remain an important gap in our ecological knowledge. In a northern hardwood forest ecosystem located in Michigan, USA, 20 years of experimentally increased atmospheric N deposition has reduced forest floor decay and increased soil C storage. This ecosystem-level response occurred concomitantly with compositional changes in saprophytic fungi and bacteria. Here, we investigated the influence of experimental N deposition on biotic interactions among forest floor bacterial assemblages by employing phylogenetic and molecular ecological network analysis. When compared to the ambient treatment, the forest floor bacterial community under experimental N deposition was less rich, more phylogenetically dispersed and exhibited a more clustered co-occurrence network topology. Together, our observations reveal the presence of increased biotic interactions among saprotrophic bacterial assemblages under future rates of N deposition. Moreover, they support the hypothesis that nearly two decades of experimental N deposition can modify the organization of microbial communities and provide further insight into why anthropogenic N deposition has reduced decomposition, increased soil C storage and accelerated phenolic DOC production in our field experiment.

opencc-zeroDec 2014View details →
zenodo32/100

WRF simulation of atmospheric pressure and temperature around flight 08 of the SOUTHTRAC Campaign

<p>Atmospheric pressure (p) and temperature (T) from numerical model WRF every 15 min and at 0.5 / 3 km vertical / horizontal resolution up to 60 km height are included. The whole time and geographical area of the flight are covered. Zipped netcdf format.</p>

opencc-by-4.0Jun 2022View details →
zenodo32/100

WRF simulation of atmospheric velocity components around flight 08 of the SOUTHTRAC Campaign

<p>The three atmospheric velocity components (zonal u, meridional v, vertical w) from numerical model WRF every 15 min and at 0.5 / 3 km vertical / horizontal resolution up to 60 km height are included. The whole time and geographical area of the flight are covered. Zipped netcdf format.</p>

opencc-by-4.0Jun 2022View details →
zenodo32/100

Surrogate modelling for the forecast of Seveso-type atmospheric pollutant dispersion

<p>Online resource 1 - Test-data response for GIM model.</p> <p>Online resource 2 - Test-data response for RGI model.</p>

opencc-by-4.0Jul 2022View details →
zenodo32/100

On the application of an observations-based machine learning parameterization of surface layer fluxes within an atmospheric large-eddy simulation model: Article Data

<p>NetCDF datatset of presented results from&nbsp;the publication titled &quot;On the application of an observations-based machine learning parameterization of surface layer fluxes within an atmospheric large-eddy simulation model&quot; in the&nbsp;Journal of Geophysical Research - Atmospheres, Paper&nbsp;#2021JD036214R.</p>

opencc-by-4.0Jul 2022View details →
zenodo32/100

Data for "Characteristics and Variability of Winter Northern Pacific Atmospheric River Flavors"

<p>The repository contains data used in &quot;(Zhou et al. 2022) Characteristics and Variability of Winter Northern Pacific Atmospheric River Flavors&quot;, which are outputs from Zhou et al. (2018) tracking algorithm, including lifecycle-related&nbsp;variables such as area, precipitation, 850hPa wind speed, IVT, IWV, locations (latitude and longitude), AR frequency, and landfall precipitation.&nbsp;</p>

opencc-by-3.0-usAug 2022View details →
zenodo32/100

Martian atmospheric spectral end-members retrieval from ExoMars Thermal Infrared TIRVIM data

<p>Here we investigated new thermal infrared data from the TIRVIM instrument of the ExoMars TGO with the main goal of carefully identifying Martian atmospheric dust and water ice clouds components. A methodology based on principal component and target transformation factor analysis techniques has been applied. Based on our results, this methodology can correctly recover both atmospheric dust and water ice aerosols spectral shapes and their abundances in the Martian atmosphere.</p> <p>The processed TIRVIM data and retrievals used in our&nbsp;work&nbsp;are available here.&nbsp;<br> <br> <strong><em>File uploaded:</em></strong></p> <p><strong>Alemanno_2022_Martian_atmospheric_spectral_end-members_retrieval_from_ExoMars_Thermal_Infrared_TIRVIM_data.zip </strong></p> <p>containing:</p> <ul> <li><strong>Data Set S1</strong> - Alemanno_2022_Martian_atmospheric_spectral_end-members_retrieval_from_ExoMars_Thermal_Infrared_TIRVIM_data</li> <li><strong>Text S1</strong> - Alemanno_2022_Martian_atmospheric_spectral_end-members_retrieval_from_ExoMars_Thermal_Infrared_TIRVIM_data.README</li> <li><strong>Data Set S2</strong> - PCA_components</li> <li><strong>Data Set S3</strong> - PCA_eigenvalues_variance</li> <li><strong>Data Set S4</strong> - TES_endmembers_orginal_target-transform</li> </ul> <p><strong>Description:</strong></p> <p><strong>Data Set S1</strong> &ndash; Martian atmospheric spectral end-members retrieved from ExoMars Thermal Infrared TIRVIM data</p> <p><strong>Text S1</strong> &ndash; description of the data contained in Dataset S1</p> <p><strong>Data Set S2</strong> &ndash; &nbsp;PCA_components retrieved from TIRVIM data</p> <p><strong>Data Set S3</strong> &ndash; PCA eigenvalues variance for each retrieved component of the dataset S2</p> <p><strong>Data Set S4</strong> &ndash; &nbsp;smoothed TES endmembers target-transformed</p> <p><strong>If you use this data set in your own work, please cite this DOI:</strong></p> <p><strong>10.5281/zenodo.7032738</strong></p> <p><strong>Please also cite this work:</strong></p> <p><strong>Alemanno G. et al. (2022), Spectral Atmospheric End-Members Retrieval from ExoMars Thermal InfraRed (TIRVIM) Data.&nbsp;53rd Lunar and Planetary Science Conference, held 7-11 March, 2022 at The Woodlands, Texas. LPI Contribution No. 2678, 2022, id.1885.</strong></p> <p><strong>Alemanno G. et al. (2022),&nbsp;Martian atmospheric spectral end-members retrieval from ExoMars Thermal Infrared (TIRVIM) data, JGR Planets, doi:&nbsp;10.1029/2022JE007429</strong></p>

opencc-by-4.0Aug 2022View details →
zenodo32/100

The Impending Opacity Challenge in Exoplanet Atmospheric Characterization

<p>Cross-section required for running retrieval with https://github.com/disruptiveplanets/tierra.</p> <p>These cross-sections were generated using&nbsp;https://github.com/disruptiveplanets/TierraCrossSection</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-bySep 2022View details →
zenodo32/100

Selected data analysed in the JGR Atmosphere manuscript " An application of the maximum entropy production method in the WRF Noah land surface model"

<p>The control experiment (hereafter WRF-CTL) and&nbsp;the MEP experiment (hereafter WRF-MEP) simulations results&nbsp;interpolated to the observation stations.&nbsp;The simulation period was&nbsp;1 June to 31 August 2015 with 30 hours&nbsp;from 12:00 UTC (20:00 Beijing time (BJT)) each day, and the latest 24-hour&nbsp;outputs are provided.</p>

opencc-by-4.0Sep 2022View details →
zenodo32/100

Model output dataset used in "Sensitivity of Heavy Convective Precipitation Simulations to Changes in Land-atmosphere Exchange Processes over China"

<p>This dataset accompanies the paper by Zhang et al. &quot;Sensitivity of Heavy Convective Precipitation Simulations to Changes in Land-atmosphere Exchange Processes over China&quot;.</p> <p>Three heavy precipitation events were modeled using the WRF v3.9 model:</p> <p>(1) The_21_July_Beijing_Rainstorm_Simulation<br> (2) The_30_July_Ningxia_rainstorm_Simulation<br> (3) The_19_June_Jiangxi_rainstorm_Simulation</p> <p>Furthermore, three cases were designed for each heavy precipitation event: (1) control experiment (DEFAULT), using the default M-O option (<em>C<sub>zil</sub></em> ~ 0); (2) constant <em>C<sub>zil</sub></em> (CZIL0.01, CZIL0.05, CZIL0.1, CZIL0.3, CZIL0.5 and CZIL0.8), with <em>C<sub>zil</sub></em> values of 0.01, 0.05, 0.1, 0.3, 0.5, and 0.8; (3) a dynamic canopy-height dependent <em>C<sub>zil</sub></em> (NEWCZIL).</p> <p>Plain Language Summary for this paper:<br> Over recent decades, the frequent occurrence of heavy precipitation events has caused devastating ecological and socioeconomic impacts, such as agriculture losses, infrastructure damage, and casualties. High-resolution atmospheric modeling at a convection-permitting grid spacing (&le;4 km) provides valuable applications for predicting heavy precipitation. Precipitation can be strongly affected by the energy and moisture exchanges between land surface and atmosphere. However, the representation of land-atmosphere interactions in atmospheric models and the responses of precipitation to land-atmosphere exchange efficiency remain great uncertainties. This study performed 3-km high-resolution atmospheric modeling with a dynamic vegetation-type-dependent land-atmosphere exchange scheme for three typical heavy precipitation events that occurred over areas with different dominant land-cover types. The results showed that land-atmosphere exchange efficiency mainly affected the precipitation intensity as well as the onset and peak time of precipitation. The dynamic exchange scheme modifies the efficiency of land-atmosphere exchanges to match local land cover conditions and could reproduce well the field observations, especially the intensity and location of the heaviest rainfall which usually serve as the most concerned variable in a major rainstorm event. Our findings show that the dynamical scheme could help achieve more accurate precipitation simulations.</p>

opencc-by-4.0Sep 2022View details →
zenodo32/100

Dataset for "Number-size distribution and CCN activity of atmospheric aerosols in the western North Pacific during spring pre-bloom period: Influences of terrestrial and marine sources, J. Geophys. Res. Atmos."

<p>A cruise observation was conducted over the western North Pacific Ocean in March 2015. The dataset in the excel sheet contains aerosol number-size distributions and CCN number concentrations along with ship positions and date/time. This dataset is for Kawana et al. in Journal of Geophysical Research: Atmospheres.</p> <p>Kaori Kawana, Yuzo Miyazaki, Yuko Omori, Hiroshi Tanimoto, Sara Kagami, Koji Suzuki, Youhei Yamashita, Jun Nishioka, Yange Deng, Hikari Yai, and Michihiro Mochida: Number-size distribution and CCN activity of atmospheric aerosols in the western North Pacific during spring pre-bloom period: Influences of terrestrial and marine sources, J. Geophys. Res. Atmos.</p>

opencc-by-4.0Sep 2022View details →
zenodo32/100

Calculation results for "Atmospheric oxidation of imine derivative of piperazine initiated by OH radical"

<p>Results from quantum chemical calculations done for publication titled &quot;Atmospheric oxidation of imine derivative of piperazine initiated by OH radical&quot;.</p>

opencc-by-4.0Sep 2022View details →
zenodo32/100

A high spatial resolution dataset for anthropogenic atmospheric mercury emissions in China during 1998-2014

<p>This database contains gridded atmospheric mercury emissions in 30 provinces of China by sectors from 1998 to 2014 at the resolution of 1 km&times;1 km. We distribute atmospheric mercury emissions in four sectors, i.e., agriculture, industry, service industry, and residences, based on China&#39;s land use data, enterprise data, road data, and population data. Gridded estimates of the total Hg (THg) and the three species, i.e., gaseous elemental Hg (Hg<sub>0</sub>), gaseous oxidized mercury (Hg<sub>II</sub>), and particulate-bound mercury (Hg<sub>p</sub>), are given separately.</p>

opencc-by-4.0Jun 2022View details →
zenodo32/100

Dataset for "Multidecadal regime shifts in North Pacific subtropical mode water formation in a coupled atmosphere-ocean-sea ice model" by Kim et al., 2022 in Geophysical Research Letters

<p>Kiel Climate Model pre-industrial simulation data used in the Geophysical Research Letters publication titled &ldquo;Multidecadal regime shifts in North Pacific subtropical mode water formation in a coupled atmosphere-ocean-sea ice model&rdquo; by Kim et al., 2022</p>

opencc-by-4.0Sep 2022View details →
zenodo32/100

Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".

<p>The code, scripts, and data used in the paper &quot;Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)&quot;.</p> <ul> <li>All Figures&amp;Table&nbsp;and their corresponding NCL scripts are under the directory of Figs&amp;Table.&nbsp;</li> <li>The modified model code, corresponding original model code, and model run scripts are under the directory of Mods_Scripts.</li> <li>The postprocessing NCL scripts, which select useful variables from simulation results, are under the directory of PostProcessing.</li> <li>The zonal mean data from model results used for making figures and corresponding data processing scripts are under the directory of Model_Results.</li> <li>The FORTRAN code used for offline tests is under the directory of Offline_Code.</li> <li>The&nbsp;code, data, and&nbsp;NCL&nbsp;scripts used&nbsp;for&nbsp;the&nbsp;figures&nbsp;and&nbsp;table&nbsp;in the Appendix are under the directory of Appendix.</li> </ul>

opencc-by-4.0Apr 2022View details →
zenodo32/100

Pickled version of standard MARCS (2011) model atmospheres

<p>Only standard models (spherical and plane parallel) are included with 1.0 Solar mass and microturbulence of 2.0 km/s.</p> <p> </p>

opencc-by-4.0Sep 2017View details →
zenodo32/100

Zenith: A Radiosonde detector for Rapid-Response Ionising Atmospheric Radiation Measurements during Solar Particle Events

<p>Supporting data for journal paper titled &quot;Zenith: A Radiosonde detector for Rapid-Response Ionising Atmospheric Radiation Measurements during Solar Particle Events&quot; published in the AGU journal Space Weather.</p>

opencc-by-4.0Jan 2018View details →
zenodo32/100

Time series used in the manuscript "Causal dependences between the coupled ocean-atmosphere dynamics over the Tropical Pacific, the North Pacific and the North Atlantic"

<p>These 6 files contain time series built using reanalyses datasets of the ECMWF as discussed in the manuscript &quot;Causal dependences between the coupled ocean-atmosphere dynamics over the Tropical Pacific, the North Pacific and the North Atlantic&quot; submitted for discussion in the journal &quot;Earth System Dynamics&quot;.</p>

opencc-by-4.0Jan 2018View details →
zenodo32/100

A qualitative assessment of limits of active flight in low density atmospheres

<p>Supplementary video files for the "A qualitative assessment of limits of active flight in low density atmospheres".&nbsp;<br><br>Supplementary Dataset S1 contains the following video files recorded from the stereo camera no.1:&nbsp;<br><br></p> <p>1) flies_2_N2_gstream1.mp4 - video showing the experiment with flushing with N2 (first repetition).</p> <p>2) flies_2_N2_2_gstream1_1.mp4 - video showing the experiment with flushing with N2 (second repetition).</p> <p>3) flies_2_N2_3_gstream1_1.mp4 - video showing the experiment with flushing with N2 (third repetition).</p> <p>4) flies_1__He_gstream1_1.mp4 - video showing the experiment with flushing with He (first repetition)</p> <p>5) flies_2_He_2_gstream1_1.mp4 - video showing the experiment with flushing with He (second repetition)</p> <p>6) flies_2_He_3_gstream1_1.mp4 - video showing the experiment with flushing with He (third repetition)</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2024View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record