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1,574 results for “atmospheres”
1-km high resolution model outputs using the WRF and WRF-Hydro model Raw data from the manuscipt "Process-based Atmosphere-Hydrology-Malaria Modeling: Performance for Spatio-temporal Malaria Transmission Dynamics in Sub-Saharan Africa "
<p>Here we provide the model outputs from the numerical climate model WRF (Weather Research and Forecasting) and its hydrological coupled model WRF-Hydro for the Health and Demographic Surveillance Systems (HDSS) site regions of Nouna in Burkina Faso. Model results are used for investigating the influence of surface hydrology representation, environmental and climate-sensitive driver factors on malaria incidence.<br>The experiments use the following model configuration: 1km horizontal resolution with 200*200 grid points, WSM6 microphysics, ACM2 PBL, and RRTM & Dudhia radiation scheme. WRF uses the Noah LSM, and WRF-Hydro uses the Noah LSM with enhanced lateral hydrological description (https://ral.ucar.edu/projects/wrf_hydro/overview). These simulations were conducted in the Karlsruhe Steinbuch Centre for Computing (SCC) Horeka.</p> <p>Model outputs are provided in daily step (originally derived from the hourly output). Filename with "wrf-hydro_pr_2000-2020_d02-1km.nc" provides Precipitation,<br>n mm/day"wrf-hydro_tas_2000-2020_d02-1km.nc" provides mean temperature in Celsius, "wrf-hydro_tasmax_2000-2020_d02-1km.nc" provides maximum temperature in Celsius, "wrf-hydro_tasmin_2000-2020_d02-1km.nc" provides minmum temperature in Celsius, "wrf-hydro_dtr_2000-2020_d02-1km.nc" provides diurnal temperature ranges in Celius, "wrf-hydro_rh_2000-2020_d02-1km.nc" provides relative humudity in % and "wrf-hydro_sw_2000-2020_d02-1km.nc" provides the surface hydrology.</p>
Data for JGR-Atmospheres Paper: Stratospheric Hydration Processes in Tropopause-Overshooting Convection Revealed by Tracer-Tracer Correlations from the DCOTSS Field Campaign
<p>Airborne 1-second data merger of observations from the NASA Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign. This merger includes subjective feature identifications analyzed in the paper referenced in the title. </p>
High-resolution simulations of Mediterranean windstorm Adrian with the Meso-NH atmospheric model
<p>The dataset provides numerical simulations of Mediterranean windstorm Adrian of 29 October 2018 at two horizontal resolutions and using different representations of surface turbulent fluxes at the air-sea interface. The simulations are run with the Meso-NH non-hydrostatic mesoscale atmospheric model of the French research community, version 5.4, freely available under CeCILL-C license agreement: <a href="http://mesonh.aero.obs-mip.fr/" target="_blank" rel="noopener">http://mesonh.aero.obs-mip.fr/</a></p> <p>The data is formatted in Network Common Data Form (NetCDF) using the CF Metadata Conventions and standard Meso-NH names for physical variables. The data files are named as following: <strong>EXP.N.CONTENT.nc</strong></p> <ul> <li><strong>EXP</strong> describes the numerical experiment (name of the parameterization of surface turbulent fluxes or their absence) </li> <li><strong>N</strong> the horizontal resolution (1=1000m, mesoscale simulation; 2=200m, large-eddy simulation) </li> <li><strong>CONTENT</strong> the type of data (3D zoom over the windstorm center or vertical profiles in the same area at 1530 UTC, or 2D surface fields every 6 min from 12 to 18 UTC)</li> </ul>
Particulate atmospheric concentrations of trace metals and leachable nutrients in air at the Southeastern Mediterranean Sea (1994-1999)
<p><span>Table 1 dataset contains</span><span> aerosol concentrations of trace metals (Cd, Pb, Cu, Zn, Cr, Mn, Fe and Al)</span><span> </span><span>at the SE Mediterranean coast of Israel, </span><span>collected</span><span> between 1994 and </span><span>1999</span><span>. Total suspended particles (TSP) in air were collected</span><span> </span><span>on Whatman QM-A quartz micro</span><span>fi</span><span>bre </span><span>filters </span><span>and on Whatman 41 </span><span>fil</span><span>ters (both 20.3</span><span> cm x </span><span>25.4</span><span> </span><span>cm), by high-volume sampler</span><span> (HVS). </span><span><span> </span></span><span>The HVS was </span><span>located on the roof of the</span><span> </span><span>National Institute of Oceanography (NIO) at Tel-Shikmona</span><span>, Israel </span><span>(located on the shore, 22</span><span> </span><span>m above sea</span><span> </span><span>level) and at Maagan Michael</span><span>, Israel</span><span> (about 900m from shore, 13 m above sea level). Analyses were carried out after total digestion with HF following the procedure of ASTM (1983).</span><span> <span>Further details in Herut et al., 2001.</span></span></p> <p><span>Table 2 dataset contains leachable</span><span> inorganic</span><span> </span><span>nitrogen (NO</span><sub><span>3</span></sub><span> </span><span>+ NO<sub>2</sub></span><span>, NH</span><sub><span>4</span></sub><span>) and phosphorus (PO<sub>4</sub>)</span><span> concentrations in</span><span> aerosol</span><span> <span>(</span></span><span>total suspended particles </span><span>in air</span><span>)</span><span> </span><span>samples collected on Whatman 41 filters between</span><span> </span><span>April 1996 and January 1999</span><span>. </span><span>The atmospheric</span><span> </span><span>sampling was performed</span><span> </span><span>on the roof of the National Institute of Oceanography</span><span> </span><span>(NIO) at Tel-Shikmona (TS)</span><span>, Israel</span><span> (located on the shore and inside</span><span> </span><span>the sea, 22 m above sea level). Leaching experiments were performed to evaluate the amount of seawater leachable nitrate, ammonium, and phosphate from the TSP</span><span> using </span><span>SE</span><span> </span><span>Mediterranean </span><span>low nutrient low chlorophyll </span><span>surface seawater</span><span>. Further details in Herut et al., 2002.</span></p> <p><span>Herut, B., Nimmo<span>, M., Medway, A., Chester, R., & Krom, M. D. (2001). Dry atmospheric inputs of trace metals at the Mediterranean coast of Israel (SE Mediterranean): sources and fluxes. <em>Atmospheric Environment</em>, <em>35</em>(4), 803-813.</span><span><span>‏</span></span></span></p> <p><span>Herut, B., Collier, R., & Krom, M. D. (2002). The role of dust in supplying nitrogen and phosphorus to the Southeast Mediterranean. <em>Limnology and Oceanography</em>, <em>47</em>(3), 870-878.</span><span><span>‏</span></span></p> <p><span>Herut, B., Krom, M. D., Pan, G., & Mortimer, R. (1999). Atmospheric input of nitrogen and phosphorus to the Southeast Mediterranean: Sources, fluxes, and possible impact. <em>Limnology and Oceanography</em>, <em>44</em>(7), 1683-1692.</span><span><span>‏</span></span></p>
Output from ICON v2.6.2.2 cloud locking simulations: 3D radiative fluxes and additional atmospheric variables
<p>Simulation output from a cloud locking experiment carried out by A. Voigt with ICON version 2.6.2.2, originally for use in M. Huber’s PhD thesis (<a href="https://utheses.univie.ac.at/detail/63548/">https://utheses.univie.ac.at/detail/63548/</a>) and described therein. This subset was processed by E.K. Van de Koot for use in a study by McGraw et al (submitted 2024). Vertically-resolved radiative flux output is in the ‘phy_3d’ files, while ‘atm_2d’ and ‘atm_3d’ include additional atmospheric quantities, such as temperatures, specific humidity, and 2D radiative fluxes at the top-of-atmosphere and surface. Each file name is prefaced with the name of the relevant simulation (e.g. ‘amip_T1C1W1’), which follows nomenclature described in the Huber thesis.</p> <p>*Updated Dec 4, 2024 to fix a very small issue on vertical levels in the 'phy' files.</p>
Output of simulations for "Atmosphere Response to an Oceanic Sub-mesoscale SST Front: A Coherent Structure Analysis": Part 1
<p>This dataset contains the output of the simulations for the paper "Atmosphere Response to an Oceanic Sub-mesoscale SST Front: A Coherent Structure Analysis" doi: [TO BE COMPLETED]. This is part 1. It contains data for the S1 simulation.</p>
Output of simulations for "Atmosphere Response to an Oceanic Sub-mesoscale SST Front: A Coherent Structure Analysis": Part 2
<p>This dataset contains the output of the simulations for the paper "Atmosphere Response to an Oceanic Sub-mesoscale SST Front: A Coherent Structure Analysis" doi: [TO BE COMPLETED]. This is part 2. It contains the remaining of data for the S1 simulation, the data of the reference simulations RefC and RefW, and the data for the sensitivity analysis of the supplementary material.</p>
Unveiling Energy Conversions of the Venus Atmosphere by the Bred Vectors
<p>This is the data for the paper: Unveiling Energy Conversions of the Venus Atmosphere by the Bred Vectors</p> <p><a href="../api/records/13790212/draft/files/BV-energy-equation.ipynb/content" target="_blank" rel="noopener noreferrer">BV-energy-equation.ipynb</a>: script for plotting</p> <p><span><a href="../api/records/13790212/draft/files/solar-position.csv/content" target="_blank" rel="noopener noreferrer">solar-position.csv</a></span>: solar positions</p> <p>control-run.tar.gz: control run data</p> <p>perturbed-run.tar.gz: perturbed run data</p>
Spatial and temporal variability of the freezing level in Patagonia's atmosphere
<h3>Short Summary:</h3> <p>This repository houses the Python preprocessing scripts utilized in generating the metadata for García-Lee et al., (2024) dataset. With these files and scripts, you gain access to the algorithm and examples for generating gridded products in netCDF format, specifically featuring the 0°C isotherm field.</p> <h3>Dependencies:</h3> <ul> <li>numpy (tested with 1.24.4 in py3)</li> <li>pandas (tested with 2.0.3 in py3)</li> <li>netCDF4 (tested with 1.6.0 in py3)</li> <li>re (tested with 2.2.1 in py3)</li> <li>glob</li> <li>OS: Tested in Windows.</li> </ul> <h3>Technical Info:</h3> <table> <tbody> <tr> <td> <p>File</p> </td> <td> <p>Type</p> </td> <td> <p>Description</p> </td> </tr> <tr> <td> <p><a href="../records/10523940/files/1_H0_Detect.py?download=1">1_H0_Detect.py</a></p> </td> <td> <p>Python script</p> </td> <td> <p>0°C Isotherm Detection Algorithm.</p> </td> </tr> <tr> <td> <p><a href="../records/10523940/files/2_Daily_Mean_H0.py?download=1">2_H0_Daily_Mean.py</a></p> </td> <td> <p>Python script</p> </td> <td> <p>Calculation of Daily Mean.</p> </td> </tr> <tr> <td> <p><a href="../records/10523940/files/ISO0_1959_2021_GRID.nc?download=1">ISO0_1959_2021_GRID.rar</a></p> </td> <td> <p>netCDF</p> </td> <td> <p>0°C Isotherm Data at 6-Hour Intervals (1959-2021) in meters above sea level (m a.s.l.).</p> </td> </tr> <tr> <td> <p><a href="../records/10523940/files/ERA5_PATAGONIA_6H_T_GPH_1959.rar?download=1">ERA5_PATAGONIA_6H_T_GPH_1959.rar</a></p> </td> <td> <p>netCDF</p> </td> <td> <p>Raw ERA5 data example for 1959: Temperature (°K) and Geopotential (m**2 s**-2).</p> </td> </tr> </tbody> </table> <h3>Extra:</h3> <p>The file 'Observations and Charts.pdf' shows averages, standard deviations, bias, and trends of the 0°C isotherm for Puerto Montt, Río Gallegos, Comodoro Rivadavia, and Punta Arenas. These values were estimated using both observations and reanalysis ERA5 data.</p> <h3>Reference:</h3> <p>García-Lee, N., Bravo, C., Gónzalez-Reyes, Á., and Mardones, P.: Spatial and temporal variability of the freezing level in Patagonia's atmosphere, Weather Clim. Dynam., 5, 1137–1151, https://doi.org/10.5194/wcd-5-1137-2024, 2024.</p>
WP2: Photochemical model of planetary atmospheres driven by high-energy stellar irradiation
<p>Modeling results of irradiated planetary atmospheres (Locci et al. 2021, <em>Extreme Ultraviolet and X-ray Driven Photochemistry of Gaseous Exoplanets</em>, PSJ, submitted). See <em>Introduction</em> and <em>Readme_Reference_model</em> for more details.</p>
Planetary Atmosphere-Interior Model Outputs from Time-Evolution Movie
<p>This array contains the outputs from the movie version of Fig. 2 in Krissansen-Totton et al. (2021, Nature Astronomy). The numpy array can be loaded as follows</p> <p>Outputs = np.load("Output_arrays.npy",allow_pickle=True)</p> <p>The array has format Outputs[i][k][j]</p> <p>where i = 0, ... 5 (total_time, pO2, pCO2, pH2O, Tsurf, and AU)</p> <p>k = 0 , ..., 1437 is the iteration number</p> <p>j = 0 , ... , 2000 is the time index</p> <p>(AU is just a scalar providing orbital separation of that iteration)</p>
Phanerozoic global climatic fields simulated using the FOAM ocean-atmosphere general circulation model
<p>These files contain the output of Phanerozoic global climate simulations conducted using the coupled ocean-atmosphere FOAM general circulation model. They are available every 20 Myrs between 540 Ma and 0 Ma, both included. All simulations have been conducted using identical boundary conditions; pCO2: 2240 ppm, solar luminosity: 1368 W m-2, vegetation: rocky desert, orbital configuration: null eccentricity and minimum obliquity. Only the continental configuration was varied from one time slice to the other (sensitivity test to the continental configuration), using the reconstructions of Scotese and Wright (https://www.earthbyte.org/paleodem-resource-scotese-and-wright-2018/).</p> <p>The reader is referred to the associated paper for a full description of the model and boundary conditions.</p> <p>All file names use the following pattern: "[age]rd_1368W_EccN_[model_component]_2240ppm.nc", with [age], the age expressed in million years ago, and [model_component] being 'atmos', 'ocean' or 'coupl' (atmospheric and oceanic components, plus coupler).</p>
Climate model output for "The Unexpected Oceanic Peak in Energy Input to the Atmosphere and its Consequences for Monsoon Rainfall"
<p>Climate model output associated with the manuscript "The Unexpected Oceanic Peak in Energy Input to the Atmosphere and its Consequences for Monsoon Rainfall"</p>
Computational results for the publication "Evolution of water structures in metal-organic frameworks for improved atmospheric water harvesting"
<p>This upload contains the computationally obtained atomic coordinates for MOF-303 and MOF-333 at different water loadings.</p>
Varied oxygen simulations with WACCM6 (Proterozoic to pre-industrial atmosphere)
<p>The history of molecular oxygen (O<sub>2</sub>) in Earth's atmosphere is still debated; however, geological evidence supports at least two major episodes where O<sub>2</sub> increased by an order of magnitude or more: the Great Oxidation Event (GOE) and the Neoproterozoic Oxidation Event. O<sub>2 </sub>concentrations have likely fluctuated (between 10<sup>−3</sup> and 1.5 times the present atmospheric level) since the GOE ∼ 2.4 Gyr ago, resulting in a time-varying ozone (O<sub>3</sub>) layer. Using a three-dimensional (3D) chemistry climate model, we simulate changes in O<sub>3</sub> in Earth's atmosphere since the GOE and consider the implications for surface habitability, and glaciation during the Mesoproterozoic. We find lower O<sub>3</sub> columns (reduced by up to 4.68 times for a given O<sub>2</sub> level) compared to previous work; hence, higher fluxes of biologically harmful UV radiation would have reached the surface. Reduced O<sub>3</sub> leads to enhanced tropospheric production of the hydroxyl radical (OH) which then substantially reduces the lifetime of methane (CH<sub>4</sub>). We show that a CH<sub>4</sub> supported greenhouse effect during the Mesoproterozoic is highly unlikely. The reduced O<sub>3</sub> columns we simulate have important implications for astrobiological and terrestrial habitability, demonstrating the relevance of 3D chemistry-climate simulations when assessing paleoclimates and the habitability of faraway worlds.</p>
ExoCAM: A 3D Climate Model for Exoplanet Atmospheres :: Model data and supplementary figures and analysis
<p>This repository contains 3D GCM model output data from the paper, "ExoCAM: A 3D Climate Model for Exoplanet Atmospheres", which is published in the Planetary Science Journal: Trapppist Habitable Atmospheres Intercomparison Special Issue. The model data includes mean climate states for the standard THAI simulations of TRAPPIST-1e, simulations using an upgraded radiative transfer, along with a large variety sensitivity experiments considering common tuning parameters of sub-grid scale cloud and convection physics. In total 43 simulations are included. Also included here are a variety of multi-panel contour plots showing basic results from all simulations as supplemental figures.</p> <p>https://iopscience.iop.org/article/10.3847/PSJ/ac3f3d</p>
Experimental and model data for "Nitrogen oxide production in laser-induced breakdown simulating impacts on the Hadean atmosphere"
<p>This is raw data and supporting figures associated with the publication: Heays, A. N., Kaiserová, T., Rimmer, P. B., Knížek, A., Petera, L., Civiš, S., et al. (2022). Nitrogen oxide production in laser-induced breakdown simulating impacts on the Hadean atmosphere. <em>Journal of Geophysical Research: Planets</em>, 127, e2021JE006842. <a href="https://doi.org/10.1029/2021JE006842">https://doi.org/10.1029/2021JE006842</a></p> <p>Two data files contain model output of the ARGO atmospheric photochemistry code that was used to generate figures for Sec. 3 of the paper:</p> <ul> <li>ARGO_model_data_neutral_case.txt</li> <li>ARGO_model_data_reducing_case.txt</li> </ul> <p>The following data files contain a tabulation of laboratory-measured and modelled photoabsorption spectra as described in Sec. 2 of the paper. The A-G letter-encoding of these files follows Table 1 of the paper, and the spectral ranges correspond to the strongest bands of NO, N2O, and NO2. </p> <ul> <li>laboratory_spectrum_experiment_A_species_N2O.txt</li> <li>laboratory_spectrum_experiment_A_species_NO2.txt</li> <li>laboratory_spectrum_experiment_A_species_NO.txt</li> <li>laboratory_spectrum_experiment_B_species_N2O.txt</li> <li>laboratory_spectrum_experiment_B_species_NO2.txt</li> <li>laboratory_spectrum_experiment_B_species_NO.txt</li> <li>laboratory_spectrum_experiment_C_species_N2O.txt</li> <li>laboratory_spectrum_experiment_C_species_NO2.txt</li> <li>laboratory_spectrum_experiment_C_species_NO.txt</li> <li>laboratory_spectrum_experiment_D_species_N2O.txt</li> <li>laboratory_spectrum_experiment_D_species_NO2.txt</li> <li>laboratory_spectrum_experiment_D_species_NO.txt</li> <li>laboratory_spectrum_experiment_E_species_N2O.txt</li> <li>laboratory_spectrum_experiment_E_species_NO2.txt</li> <li>laboratory_spectrum_experiment_E_species_NO.txt</li> <li>laboratory_spectrum_experiment_F_species_N2O.txt</li> <li>laboratory_spectrum_experiment_F_species_NO2.txt</li> <li>laboratory_spectrum_experiment_F_species_NO.txt</li> <li>laboratory_spectrum_experiment_G_species_N2O.txt</li> <li>laboratory_spectrum_experiment_G_species_NO2.txt</li> <li>laboratory_spectrum_experiment_G_species_NO.txt</li> </ul> <p>The following file contains a tabulation of the full-spectral-range laboratory-measured photoabsorption spectrum of experiment A, along with a modelled spectrum.</p> <ul> <li><a href="https://zenodo.org/api/files/49f05962-9a34-4bbc-855c-1a0976f62531/laboratory_spectrum_experiment_A_full_spectrum.txt?versionId=79a70ade-63d1-4fd7-b423-176e27f8dc37">laboratory_spectrum_experiment_A_full_spectrum.txt </a></li> </ul> <p>The following file contains plots of the experimental spectra for all NxOy species in all measurements as well as the residual error of models fit to these spectra. Additional residual errors of model neglecting NxOy species indicates their contribution to the spectra.</p> <ul> <li>laboratory_spectrum_figures.pdf</li> </ul> <p> </p>
Supplementary Information: Investigating the detectability of hydrocarbons in exoplanet atmospheres with JWST
<p>Supplementary information containing additional figures of the journal article 'Investigating the detectability of hydrocarbons in exoplanet atmospheres with JWST' by D. Gasman, M. Min, and K. L. Chubb, published in Astronomy & Astrophysics (2022).</p>
Data related to "Emissions of atmospherically reactive gases nitrous acid and nitric oxide from arctic permafrost peatlands"
<p>The data file contains the individual (each replicate) values of the soil variables and gas fluxes obtained from the study. It contains data shown in the both main text and supplementary files. </p>
Simulation Files for Organic Contaminants and Atmospheric Nitrogen at the Graphene–Water Interface
<p>This data set provides files needed to run the simulations described in the manuscript entitled "Organic contaminants and atmospheric nitrogen at the graphene–water interface: A simulation study" using the molecular dynamics software NAMD and LAMMPS. The output of the simulations, as well as scripts used to analyze this output, are also included. The files are organized into directories corresponding to the figures of the main text and supplementary information. They include molecular model structure files (NAMD psf), force field parameter files (in CHARMM format), initial atomic coordinates (pdb format), NAMD or LAMMPS configuration files, Colvars configuration files, NAMD log files, and NAMD output including restart files (in binary NAMD format) and some trajectories in dcd format (downsampled). Analysis is controlled by shell scripts (Bash-compatible) that call VMD Tcl scripts. A modified LAMMPS C++ source file is also included.</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.