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1,574 results for “atmospheres”
Dataset for "Surface-Atmosphere Decoupling Prolongs Cloud Lifetime Under Warm Advection Due To Reduced Entrainment Drying"
<p>Dataset for "Surface-Atmosphere Decoupling Prolongs Cloud Lifetime Under Warm Advection Due To Reduced Entrainment Drying". The LES model used is the System for Atmospheric Modeling (SAM) model (http://rossby.msrc.sunysb.edu/~marat/SAM.html). </p>
Atmospheric Dust Source Contributions and Synoptic Scale Adjustments in the East Asian Region in April of 2021
<p>The WRF-Chem simulations were conducted to assess the source contributions to the concentrations and ratios across the East Asian region in April 2021. The WRF-Chem baseline was compiled, and sensitivity simulations were conducted regarding the source contributions to the concentrations of PM10 BASE, PM10 Anthro, PM10 Dust, and PM10 Biomass. </p> <p>In our dataset, you can find PM10 concentrations of WRF-Chem baseline simulations and other sensitivity-simulated PM10 concentrations of multi-sources of anthropogenic, wind-blown dust, and biomass-burning emissions. Furthermore, model meteorological variables of air temperature, wind, surface level pressure, and geopotential height can be found here.</p> <p>If you have any difficulty downloading these datasets, please feel free to contact the first author, kimhsung@gmail.com. All references and acknowledgments can be found in our paper.</p> <p> </p>
Supplementary Figures for "Patchy Forsterite Clouds in the Atmospheres of Two Highly Variable Exoplanet Analogs" (Vos+ 2023)
<p>Supplementary figures for "Patchy Forsterite Clouds in the Atmospheres of Two Highly Variable Exoplanet Analogs" (Vos et al. 2023; doi: 10.3847/1538-4357/acab58). The figures show posterior distributions from the retrievals for models that were not chosen as the preferred model. </p>
Data of Atmospheric Turbulent Characteristics under Summer Shamal in Coastal Qatar
<p>Here are the data for the figures in the paper 'Atmospheric Turbulent Characteristics under Summer Shamal in Coastal Qatar'. The data are in '.mat' which can be easily processed through MATLAB.</p>
Data for Widespread detection of chlorine oxyacids in the Arctic atmosphere: Villum Research Station and Ny-Ålesund observations
<p>The data includes:</p> <p>1) Data for the time series of HClO3 and HClO4 together with relevant data from the Villum Research Station observations.</p> <p>2) Data for the time series of HClO3 from Ny-Ålesund observation.</p> <p>3) Data of the estimated cross-section and photolysis rate of HClO3 and HClO4.</p> <p>Data are also available from the corresponding authors upon request. </p>
Codes and data related to the article: Renard et al. Floods and Heavy Precipitation at the Global Scale: 100-year Analysis and 180-year Reconstruction. Journal of Geophysical Research - Atmospheres.
<p>This package contains R codes and data related to the article:</p> <p>B. Renard, D. McInerney, S. Westra, M. Leonard, D. Kavetski, M. Thyer and J.-P. Vidal. Floods and Heavy Precipitation at the Global Scale: 100-year Analysis and 180-year Reconstruction. <em>Journal of Geophysical Research - Atmospheres</em>. DOI: <a href="https://doi.org/10.1029/2022JD037908">10.1029/2022JD037908</a></p> <p><strong>Analyses</strong></p> <p>This folder contains the R scripts used to set up models, analyse results and prepare figures. See README file for details.</p> <p><strong>ShinyApp</strong></p> <p>This folder contains an interactive Shiny App to explore the data and the results from the article.</p> <p>An online version can be found at <a href="https://hydroapps.recover.inrae.fr/HEGS-paper">https://hydroapps.recover.inrae.fr/HEGS-paper</a></p> <p> </p>
Atmospheric methane since the LGM was driven by wetland sources
<p>Companion data set to Kleinen et al. (2023):<br> Thomas Kleinen, Sergey Gromov, Benedikt Steil, and Victor Brovkin<br> Atmospheric methane since the LGM was driven by wetland sources<br> Climate of the Past, 2023</p> <p>Model output from the MPIESM model, model experiments base and MWM.<br> See Kleinen et al. (2023) for details.</p> <p>Timeseries data plotted in all Figures:<br> Global mean temperature, total land carbon; CH4 concentrations and fluxes; NO and RC fluxes; atmospheric lifetimes.</p> <p>Time axis in netcdf files is negative years before present, i.e. year -20000 is 20000 years before present (present=1950 CE).<br> Time is represented as absolute time YYMMDD.f, with YY negative year BP, MM mmonth and DD day, f is fractional daytime.<br> </p>
Data for "A large gas-phase source of esters and other accretion products in the atmosphere"
<p>The data used in the preparation of the manuscript "A large gas-phase source of esters and other accretion products in the atmosphere". The data set includes the full mass spectra of all of the isotope labelled experiments show in the Fig. 3 of the manuscript (MS_data.zip), and the files for the quantum chemical calculations throughout the manuscript (Final-QC-out.zip).</p>
Raw and analyzed data for manuscript "Atmospheric non-thermal plasma reduction of natively oxidized iron surfaces"
<p> Raw and analyzed data for manuscript "Atmospheric non-thermal plasma reduction of natively oxidized iron surfaces"</p>
Data set for figure 2-4 from publication "Missed Evaporation from Atmospherically Relevant Inorganic Mixtures Confounds Experimental Aerosol Studies",
<p>Data set for figure 2-4 from publication "Missed Evaporation from Atmospherically Relevant Inorganic Mixtures Confounds Experimental Aerosol Studies".</p>
Supplementary data for the manuscript entitled "Evolution of the convective boundary layer in a WRF simulation nested down to 100 m resolution during a cloud-free case of LAFE 2017 and comparison to observations" (JGR Atmospheres)
<p>This dataset contains additional material to reproduce the simulation and some of the figures of the manuscipt entitled "Evolution of the convective boundary layer in a WRF simulation nested down to 100 m resolution during a cloud-free case of LAFE 2017 and comparison to observations" in the Journal of Geophysical Reasseach - Atmospheres.</p>
ARTS Absorption Lookup Table for a Wide Range of Atmospheric Conditions
<p><strong>General description</strong></p> <p>This dataset provides an absorption lookup table for the Atmospheric Radiative Transfer Simulator (ARTS). The data is stored in the ARTS XML data format.</p> <p>The dataset consists of the following files:</p> <ul> <li>abs_lookup.xml <em>Meta data describing the lookup table in ASCII format</em></li> <li>abs_lookup.xml.bin <em>The grids and absorption cross section in binary format</em></li> </ul> <p>The lookup table covers wavenumbers from 10 to 3,250 cm<sup>-1</sup>. It is valid for surface temperatures between 200 to 400 Kelvin and water vapor mixing ratios from 4e-5 up to 0.4.</p> <p>The spectral coverage in combination with the wide range of validity make the lookup table suitable to calculate radiative fluxes even in extreme climates.</p> <p>The dataset includes absorption cross-sections for the following species:</p> <ul> <li> CH4</li> <li> CO</li> <li> CO2</li> <li> H2O</li> <li> N2</li> <li> N2O</li> <li> O2</li> <li> O3</li> </ul> <p><strong>Usage with the radiative-convective equilibrium model konrad</strong></p> <p>The lookup table can be used by the ARTS radiation class provided by the radiative-convective equilibrium (RCE) model konrad. This allows the user to perform RCE simulations with line-by-line longwave radiation. The environment variable ``KONRAD_LOOKUP_TABLE`` is used to tell the model where the lookup table is located:</p> <pre><code class="language-bash">export KONRAD_LOOKUP_TABLE="path/to/abs_lookup.xml"</code></pre> <p> </p> <p><strong>References</strong><br> ARTS: <a href="https://radiativetransfer.org">radiativetransfer.org</a><br> konrad: <a href="https://github.com/atmtools/konrad">github.com/atmtools/konrad</a><br> </p>
Simultaneous observations of atmospheric vertical potential gradient from coastal Antarctic Stations Bharati and Maitri
<p><strong>Simultaneous dual station observations of the atmospheric electric potential gradient (PG) at Bharati and Maitri studied for the period 2014-2016, bring out a new regional diurnal pattern of fair-weather PG for the coastal Antarctic region, perhaps the ubiquitous characteristics of the PG for the coastal Antarctic region. It is a broad minimum in the Carnegie-type PG variation. The surface wind distorts the fair-weather diurnal pattern of PG over Bharati more significantly than at Maitri. Katabatic wind effect over Bharati PG than Maitri PG is the sharper slope gradient of the ice sheet over Bharati than over Maitri as a consequence the katabatic wind streamlines drain over the Lambert glacier, located close to Bharati station. The wind speed significantly affects the Bipolar Air Ion Concentration (BAIC) by accumulation and dispersion. The concentration is maximum when the wind speed is minimum. Obviously, the PG is minimum during these hours. This particular signature distorts the expected global pattern of the PG at Bharati. Data quality is improved by measuring the PG using the EFM flush mounted with ground EFM rather than from an elevated site. Perhaps this position reduces the wind effects on the PG and favours the detection of globally representative data.</strong></p>
Data files for Atmospheric Gravity Wave and Instability Observations from the International Space Station using the Near InfraRed Airglow Camera (NIRAC)
<p>The files in this set are data obtained from the NIRAC airglow imager on the International Space Station. The files are named for a JGR paper by J. Hecht et al. entitled Atmospheric Gravity Wave and Instability Observations from the International Space Station using the Near InfraRed Airglow Camera (NIRAC). These files are for plots in Figures 5,7,10,11,17,18, and 19 in the submitted paper. The files are published here so as to be available for review. This paper should appear in JGR Atmospheres sometime in late 2023 or early 2024. The files that are text files are meant to be read with IDL as discussed in the readme file. </p>
Air-Sea fluxes of CO2 in the Indian Ocean between 1985 and 2018: A synthesis based on Observation-based surface CO2, hindcast and atmospheric inversion models.
<p>This data set contains 14 hindcast models (CCSM-WHOI.nc, CESC_ETHZ.nc, CNRM-ESM2-1.nc, EC_Earth3.nc, FESOM_REcoM_LR.nc, MOM6_Princeton.nc, MPIOM_HAMOCC.nc; MRI-ESM2-1.nc, NorESM-OC1.2.nc, ORCA1-LIM3-PISCES.nc, ORCA025-EOMAR.nc, Plankotom12, INCOIS-BIO-ROMS.nc, ROMS-NYUAD.nc), nine empirical models (CMEMS-LSCE-FFNN.nc, CSIRML6.nc, Jena-MLS.nc, JMAMLR.nc, Spco2_LDEO_HPD.nc, SOMFNN.nc, NIES-MLR3.nc, UOEX-WAT20.nc, OceanSODAETHZ.nc) and CO2 flux climatology data (CO2_Climatology.nc). This data set also has two atmospheric inversion models output and those are - MACTM (MACTM.nc) and CAMSv20r1 (CMSv20r1.zip format and inside the zip folder files are .nc format).</p>
Multi-fidelity Gaussian Process Emulation for Atmospheric Radiative Transfer Models
<p>This repository contains several datasets of spectral atmospheric transfer functions (i.e. path radiance, transmittances, spherical albedo) simulated with MODTRAN6 atmospheric radiative transfer model. The simulations are stored in hdf5 files using the Atmospheric Look-up table Generator (ALG) toolbox (<a href="https://doi.org/10.5194/gmd-13-1945-2020">https://doi.org/10.5194/gmd-13-1945-2020</a>). Each dataset has an associated .xml file that includes the configuration of ALG/MODTRAN6 executions. All datasets include the input atmospheric/geometric variables that are summarized in the following table. Each dataset file has a random distribution (based on latin hypercube sampling) these input variables with varying number of points (e.g. train500.h5 contains 500 samples). The <em>reference </em>dataset contains 10000 samples and was used as reference for evaluating Gaussian Processes emulators.</p> <table> <tbody><tr> <th>Input Variables</th> <th>Units</th> <th>Min</th> <th>Max</th> </tr> </tbody><tbody> <tr> <td>O3 column concentration</td> <td>atm-cm</td> <td>0.25</td> <td>0.45</td> </tr> <tr> <td>Columnar Water Vapor</td> <td>g/cm2</td> <td>0.2</td> <td>4</td> </tr> <tr> <td>Aerosol Optical Thickness</td> <td>-</td> <td>0.04</td> <td>0.6</td> </tr> <tr> <td>Asymmetry parameter</td> <td>-</td> <td>0.5</td> <td>0.85</td> </tr> <tr> <td>Angstrom exponent</td> <td>-</td> <td>0.1</td> <td>2</td> </tr> <tr> <td>Single Scattering Albedo</td> <td>-</td> <td>0.8</td> <td>1</td> </tr> <tr> <td>Surface elevation</td> <td>km</td> <td>0</td> <td>2.5</td> </tr> <tr> <td>Solar Zenith Angle</td> <td>deg</td> <td>0</td> <td>70</td> </tr> <tr> <td>Relative Zenith Angle</td> <td>deg</td> <td>0</td> <td>180</td> </tr> </tbody> </table> <p> </p>
Top-of-the-atmosphere radiative forcing by aerosol due to continuous OCS injection near the tropical tropopause simulated by EMAC
<p>This dataset was prepared for a publication by von Hobe et al. (2023):</p> <p><strong>Comment on “An approach to sulfate geoengineering with surface emissions of carbonyl sulfide” by Quaglia et al. (2022)</strong></p> <p>In that publication, the data are displayed in Figure 4.</p> <p>The dataset contains additional stratospheric aerosol forcing for injections of 6 Tg S a<sup>-1</sup> OCS for several years over 5 tropical cities at the tropopause (97 hPa) calculated with the EMAC (ECHAM5/MESSy Atmospheric Chemistry) CCM (e.g. Brühl et al., 2018; Schallock et al., 2023). Data are given for a four year time series starting in January 2017.</p> <p>- - - - - - - - - - - -</p> <p>File format:</p> <p> netCDF</p> <p>Index Variables:</p> <p> time, 10 hourly, as 'day since 1997-01-01' (note that the two variables named time4 and time6 are identical)</p> <p>Parameters:</p> <p> SOLFORCCSO: instantaneous solar radiative forcing at the top of the atmosphere by aerosol due to continuous OCS injection near the tropical tropopause with surface mixing ratios of OCS were fixed to observations</p> <p> TOTFORCCSO: instantaneous total radiative forcing at the top of the atmosphere by aerosol due to continuous OCS injection near the tropical tropopause with surface mixing ratios of OCS were fixed to observations</p> <p> SOLFORCCSO_FREE: instantaneous solar radiative forcing at the top of the atmosphere by aerosol due to continuous OCS injection near the tropical tropopause with surface mixing ratios of OCS allowed to increase from downward transport</p> <p> TOTFORCCSO_FREE: instantaneous total radiative forcing at the top of the atmosphere by aerosol due to continuous OCS injection near the tropical tropopause with surface mixing ratios of OCS allowed to increase from downward transport</p> <p>- - - - - - - - - - - -</p> <p><strong>References:</strong></p> <p>Brühl, C., Schallock, J., Klingmüller, K., Robert, C., Bingen, C., Clarisse, L., Heckel, A., North, P., and Rieger, L.: Stratospheric aerosol radiative forcing simulated by the chemistry climate model EMAC using Aerosol CCI satellite data, Atmos. Chem. Phys., 18, 12845-12857, 10.5194/acp-18-12845-2018, 2018</p> <p>Quaglia, I., Visioni, D., Pitari, G., and Kravitz, B.: An approach to sulfate geoengineering with surface emissions of carbonyl<br> sulfide, Atmos. Chem. Phys., 22, 5757-5773, 10.5194/acp-22-5757-2022, 2022.</p> <p>Schallock, J., Brühl, C., Bingen, C., Höpfner, M., Rieger, L., and Lelieveld, J.: Reconstructing volcanic radiative forcing since 1990, using a comprehensive emission inventory and spatially resolved sulfur injections from satellite data in a chemistry climate model, Atmos. Chem. Phys., 23, 1169-1207, 10.5194/acp-23-1169-2023, 2023.</p> <p>von Hobe, M., Brühl, C., Lennartz, S. T., Whelan, M. E., and Kaushik, A.: Comment on “An approach to sulfate geoengineering with surface emissions of carbonyl sulfide” by Quaglia et al. (2022) , EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-268, 2023.</p>
Regional distribution of annual sea-to-air OCS fluxes for the present day atmosphere with 500 ppt OCS and the two OCS geoengineering scenarios with 4.8 ppb and 35.5 ppb.
<p>This dataset was prepared for a publication by von Hobe et al. (2023):</p> <p><strong>Comment on “An approach to sulfate geoengineering with surface emissions of carbonyl sulfide” by Quaglia et al. (2022)</strong></p> <p>In that publication, the data are displayed in Figure 3.</p> <p>Average annual sea-to-air OCS fluxes on a 2.8 ° latitude x 2.8 ° longitude grid for the present day atmosphere and for the two OCS emission scenarios considered by Quaglia et al. (2022) were obtained from a 2003 - 2019 simulation, using a model described in Lennartz et al. (2021).</p> <p>- - - - - - - - - - -</p> <p>File format:</p> <p> netCDF</p> <p>Index Variables:</p> <p> latitude</p> <p> longitude</p> <p>Parameters:</p> <p> ocsem500: mean annual sea-to-air OCS flux calculated for an atmospheric OCS mole fraction of 500 ppt</p> <p> ocsem4800: mean annual sea-to-air OCS flux calculated for an atmospheric OCS mole fraction of 4.8 ppb</p> <p> ocsem35500: mean annual sea-to-air OCS flux calculated for an atmospheric OCS mole fraction of 35.5 ppb</p> <p>- - - - - - - - - - -</p> <p><strong>References:</strong></p> <p>Lennartz, S. T., Gauss, M., von Hobe, M., and Marandino, C. A.: Monthly resolved modelled oceanic emissions of carbonyl<br> sulphide and carbon disulphide for the period 2000–2019, Earth Syst. Sci. Data, 13, 2095-2110, 10.5194/essd-13-2095-2021, 2021.</p> <p>Quaglia, I., Visioni, D., Pitari, G., and Kravitz, B.: An approach to sulfate geoengineering with surface emissions of carbonyl<br> sulfide, Atmos. Chem. Phys., 22, 5757-5773, 10.5194/acp-22-5757-2022, 2022.</p> <p>von Hobe, M., Brühl, C., Lennartz, S. T., Whelan, M. E., and Kaushik, A.: Comment on “An approach to sulfate geoengineering with surface emissions of carbonyl sulfide” by Quaglia et al. (2022) , EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-268, 2023.</p>
Simple Biosphere model version 4.2 (SiB4) simulations for the present day atmosphere with 500 ppt OCS and the two OCS geoengineering scenarios with 4.8 ppb and 35.5 ppb OCS.
<p>This dataset was prepared for a publication by von Hobe et al. (2023):</p> <p><strong>Comment on “An approach to sulfate geoengineering with surface emissions of carbonyl sulfide” by Quaglia et al. (2022)</strong></p> <p>In that publication, the data are displayed in Figures 1 and 2.</p> <p>Simple Biosphere model version 4.2 (SiB4, Haynes et al., 2019; Sellers et al., 1986) was used to calculate (i) the average increase in evapotranspiration anticipated under an elevated OCS scenario for the years 2000-2021 on a 0.5 ° latitude x 0.5 ° longitude grid and (ii) OCS uptake by plants and soils, per month, at baseline (500 ppt) and elevated (4.8 and 35.5 ppb) OCS levels averaged over the years 2000-2021.</p> <p>- - - - - - - - - - -</p> <p><em>File 1: vonHobe_et_al_2023_CarbonylSulfideGeoengineeringScenarios_DeltaEvapotranspiration_GloballyGridded_SiB4.nc</em></p> <p>File Format:</p> <p> netCDF</p> <p>Index Variables:</p> <p> latitude</p> <p> longitude</p> <p>Parameters:</p> <p> percent_diff_et: relative increase in % of evapotranspiration in a scenario where 20% of terrestrial plants exhibit a 50% increase in stomatal conductance under high OCS</p> <p>- - - - - -</p> <p><em>File 2: vonHobe_et_al_2023_CarbonylSulfideGeoengineeringScenarios_BiosphereUptake_MonthlyIntegrated_SiB4.csv</em></p> <p>File Format:</p> <p> comma delimited text file (.csv)</p> <p>Index Variable:</p> <p> time: monthly, format m/dd/yy</p> <p>Parameters:</p> <p> ocs_veg_base: simulated monthly OCS uptake by terrestrial vegetation at an atmospheric OCS mole fraction of 500 ppt</p> <p> ocs_soil_base: simulated monthly OCS uptake by soils at an atmospheric OCS mole fraction of 500 ppt</p> <p> ocs_veg_4.8ppb: simulated monthly OCS uptake by terrestrial vegetation at an atmospheric OCS mole fraction of 4.8 ppb</p> <p> ocs_soil_4.8ppb: simulated monthly OCS uptake by soils at an atmospheric OCS mole fraction of 4.8 ppb</p> <p> ocs_veg_35.5ppb: simulated monthly OCS uptake by terrestrial vegetation at an atmospheric OCS mole fraction of 35.5 ppb</p> <p> ocs_soil_35.5ppb: simulated monthly OCS uptake by soils at an atmospheric OCS mole fraction of 35.5 ppb</p> <p>- - - - - - - - - - -</p> <p><strong>References:</strong></p> <p>Haynes, K. D., Baker, I. T., Denning, A. S., Stöckli, R., Schaefer, K., Lokupitiya, E. Y., and Haynes, J. M.: Representing<br> Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: 1. Implementation in the Simple<br> Biosphere Model (SiB4), Journal of Advances in Modeling Earth Systems, 11, 4423-4439, 10.1029/2018ms001540, 2019.</p> <p>Quaglia, I., Visioni, D., Pitari, G., and Kravitz, B.: An approach to sulfate geoengineering with surface emissions of carbonyl sulfide, Atmos. Chem. Phys., 22, 5757-5773, 10.5194/acp-22-5757-2022, 2022.</p> <p>Sellers, P. J., Mintz, Y., Sud, Y. C., and Salcher, A.: A Simple Biosphere Model (SiB) for Use within General Circulation Models, Journal of the Atmospheric Sciences, 43, 505-531, 1986.</p> <p>von Hobe, M., Brühl, C., Lennartz, S. T., Whelan, M. E., and Kaushik, A.: Comment on “An approach to sulfate geoengineering with surface emissions of carbonyl sulfide” by Quaglia et al. (2022) ,</p>
Spectropolarimetric observations of the solar atmosphere in the Hα 6563 Å line
<p>This dataset contains spectropolarimetric measurements obtained in the 6563A Halpha line near the solar limb with the Gregory Coudé Telescope at IRSOL in Locarno. The observations are discussed in the article:</p> <p>Jaume Bestard, J.; Trujillo Bueno, J.; Bianda, M.; Štěpán, J.; Ramelli, R.<br> "Spectropolarimetric observations of the solar atmosphere in the Hα 6563 Å line."<br> 2022A&A...659A.179J<br> DOI: 10.1051/0004-6361/202141834</p>
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.