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Dataset results
88 results for “Atmospheric aerosol”
Model simulation data used in "The global impact of the transport sectors on atmospheric aerosol in 2030 – Part 2: Aviation" (Righi et al., Atmos. Chem. Phys., 2016)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Atmos. Chem. Phys.</i>, 2016). For details see the README.md file.</p>
Model simulation data used in "The global impact of the transport sectors on atmospheric aerosol in 2030 – Part 1: Land transport and shipping" (Righi et al., Atmos. Chem. Phys., 2015)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Atmos. Chem. Phys.</i>, 2015). For details see the README.md file.</p>
Data supporting the study "An organic crystalline state in ageing atmospheric aerosol proxies: spatially resolved structural changes in levitated fatty acid particles" by Milsom et al. (2021))
<p>Data supporting the figures and findings presented in the study <strong>"An organic crystalline state in ageing atmospheric aerosol proxies: spatially resolved structural changes in levitated fatty acid particles" by Milsom et al. (2021), <em>Atmos. Chem. Phys..</em></strong></p>
Dataset associated with Banks et al.: "Dust aerosol from the Aralkum Desert influences the radiation budget and atmospheric dynamics of Central Asia"
<p>This dataset contains the COSMO-MUSCAT simulation output for the 'Dustbelt' (DUBLT) scenarios of Central Asian dust aerosol and associated radiative effects described by the paper "Radiative cooling and atmospheric perturbation effects of dust aerosol from the Aralkum Desert in Central Asia", written by Banks et al. and submitted to ACP in 2023. The paper was renamed "Dust aerosol from the Aralkum Desert influences the radiation budget and atmospheric dynamics of Central Asia" in 2024.</p>
Data archive for the peer-reviewed journal article "Links between atmospheric aerosols and sea state in the Arctic Ocean"
<p>This dataset accompanies the peer-reviewed journal article titled "Links between atmospheric aerosols and sea state in the Arctic Ocean" which was accepted for publication in the Journal of Atmospheric Environment in September 2024, https://doi.org/10.1016/j.atmosenv.2024.120844. </p> <p>This dataset contains information on sea surface properties, meteorology, and aerosol data from measurements conducted during the Arctic Century Expedition which was carried out in August and September of 2021 in the Russian Arctic region. The dataset contains the following information:</p> <p><br>1) aerosol_size_distributions.csv: The hourly averaged time-series of aerosol size distribution measurements from an aerodynamic particle sizer. Further information for this data file is provided in Meta_data_for_aerosol_size_distributions.txt.</p> <p><br>2) aerosol_composition_and_volume.csv: Time series of mass concentrations of Na+Mg (SSA proxy) and Al+Si+Ca (dust proxy) in aerosol particles collected on filters. The time-series also contains aerosol volume concentration information for the coarse and fine aerosol categories, i.e., samples with count median diameters larger than 0.99 µm and smaller than 0.99 µm, respectively. Further information for this data file is provided in Meta_data_for_aerosol_composition_and_volume.txt. </p> <p><br>3) sea_surface_elevation_time_series.pkl: a pickle file containing the sea surface elevation time-series. The sea surface elevation data was extracted from 3D-reconstructed sea surface data. The 3D reconstruction of the sea surface was achieved by processing stereoscopic images of the sea surface using the Waves Acquisition Stereo System (WASS) software (Bergamasco et al., 2017). Further information for this data file is provided in Metadata_for_sea_surface_elevation_time_series.txt.</p> <p><br>4) aerosol_meteo_wave_merged_data.csv: This file contains the time-series of merged hourly averages of aerosol number concentrations, meteorological data, environmental data, and sea surface properties. The dataset also contains the average coordinate of the research vessel and its distance to land masses throughout the expedition. The meteorological data were measured during the expedition and the original unmerged data are available in Thurnherr et al. (2024). Other environmental data, such as sea surface temperature, are obtained from the fifth generation ECMWF reanalysis for the global climate and weather (ERA5, Hersbach et al., 2023), and sea ice concentration was obtained from AMSR-2 daily satellite measurements (Copernicus Climate Change Service (C3S), 2020). Sea surface properties are extracted from time series of sea surface elevation. Further information for this data file is provided in Metadata_for_aerosol_meteo_wave_merged_data.txt.</p>
Polar atmospheric and aerosol river detection catalogs
<p>These detection catalogs of atmospheric and aerosol rivers were created for the publication <em>Lapere et al., "Polar aerosol atmospheric rivers: detection, characteristics and potential applications", Journal of Geophysical Research, Submitted</em>. The associated methodology is described in this publication.</p> <p>They provide binary detection of Atmospheric river (AR), Black carbon aerosol atmospheric river (BC_AER), Dust aerosol atmospheric river (DU_AER), Sea salt aerosol atmospheric river (SS_AER) and Organic carbon aerosol atmospheric river (OC_AER), in NetCDF format, for the period 1980-2022, with a 3-hour time resolution and 1x1° spatial resolution, for the regions 30°-90°N (indicated by the suffix "NH") and 30°-90°S (indicated by the suffix "SH").</p> <p>The code for pre-processing raw MERRA2 data, along with the detection algorithm are also provided here as Python Jupyter notebooks.</p>
Simulation dataset and plotting scripts used for journal article "Surface modulated dissociation of organic aerosol acids and bases in different atmospheric environments" by Sengupta and Prisle (2024)
<p>Simulation data underlying all figures presented in "Surface modulated dissociation of organic aerosol acids and bases in different atmospheric environments" by Sengupta and Prisle (2024) <a href="http://dx.doi.org/10.1080/02786826.2024.2323641" target="_blank" rel="noopener noreferrer">http://dx.doi.org/10.1080/02786826.2024.2323641</a>. </p> <p>The data for each figure and the plotting scripts are included in a zip file labelled by the figure number as presented in the paper and accompanying supplement.</p>
Data supporting the study "The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy" by Milsom et al.
<p>Model and experimental data from the study "The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy" to be published in Atmospheric Chemistry and Physics. </p>
Atmospheric aerosol chemical characterization and organic aerosol source apportionment by HR-TOF-AMS in the Po Valley during RHAPS (2021)
<p><span>Time series of non-refractory submicrometric aerosol (PM1) chemical components (sulfate, nitrate, ammonium, chloride, and organic aerosol, OA) from RHAPS campaigns (winter and summer 2021) at Bologna (BO) and San Pietro Capofiume (SPC), Po Valley, Italy.<br></span></p> <p><span>Time series and profiles of OA source factors derived from PMF.</span></p>
MAJA look-up tables for Sentinel-2 A&B sensors, for Copernicus Atmosphere Monitoring Service aerosol types
<p>The archive contains the Look-up tables used by MAJA atmospheric correction software, used to process Sentinel-2 A&B sensors. These look-up tables correspond to the aerosol types used by Copernicus Atmosphere Monitoring Service (CAMS). However, the default continental model is also provided.</p> <p>Version 1.1 has new LUT for water vapour estimates, which corrects for a bias observed for large water vapour contents (above 2.5 g/cm2)</p> <p>Version 1.2 just changed the Folder name for a better integration with Start_maja.</p> <p>Version 1.3 added the Header files</p>
Comparison of radiative transfer schemes for the calculation of aerosol radiative forcing in Mars' atmosphere
<p>Output datasets for Figures (fig. 1 to 10) for the intercomparison of radiative transfer algorithms for the calculation of aerosol radiative forcing in the Martian atmosphere.</p>
Resources for publication "Meteorologically normalised long-term trends of atmospheric ammonia (NH3) in Switzerland/Liechtenstein and the explanatory role of gas-aerosol partitioning"
<p>Resources for publication "Meteorologically normalised long-term trends of atmospheric ammonia (NH3) in Switzerland/Liechtenstein and the explanatory role of gas-aerosol partitioning".</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>
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>
Model simulation data used in "The global impact of the transport sectors on the atmospheric aerosol and the resulting climate effects under the Shared Socioeconomic Pathways (SSPs)" (Righi et al., Earth Syst. Dynam., 2023)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Earth Syst. Dynam.</i>, 2023). For details see the README.md file.</p>
Dataset for combined influences of sources and atmospheric bleaching on light absorption of water-soluble brown carbon aerosols
<p>This dataset provides the mass-absorption cross section at 365 nm and the corresponding absorption Ångström exponent, carbon isotope (13C and 14C) signature of water-soluble organic carbon, and OC, EC and WS-BrC concentration for aerosol samples collected in East Asia. The PM2.5 samples were collected simultaneously during the winter period (January 2014) from the representative hotspot regions of BrC emissions in E. Asia, including in the Beijing-Tianjin-Hebei (BTH) area, Yangtze River Delta (YRD), Pearl River Delta (PRD), Sichuan (SC) province and SE Yellow Sea regional receptor site — the Korea Climate Observatory at Gosan (KCOG). The earlier published data in E. and S. Asia, such as KCOG, urban city Delhi, Bangladesh Climate Observatory at Bhola Island (BCOB) in the outflow region of the Indo-Gangetic Plain and Maldives Climate Observatory at Hanimaadhoo Island (MCOH) in the Indian Ocean are from corresponding references (see the annotation in each sheet).</p> <p>Please cite Wenzheng Fang, August Andersson, Meehye Lee, Mei Zheng, Ke Du, Sang-Woo Kim, Henry Holmstrand and Örjan Gustafsson (2023): Combined influences of sources and atmospheric bleaching on light absorption of water-soluble brown carbon aerosols. npj Climate and Atmospheric Science. </p>
Data of the paper: Atmospheric energy budget response to idealized aerosol perturbation in tropical cloud systems
<p>Here you can find the data presented in the paper: <strong>Atmospheric energy budget response to idealized aerosol perturbation in tropical cloud systems</strong></p> <p>The data include all variables included in the paper for the shallow-cloud and the deep-cloud dominated cases.</p> <p>The variable names are as in the paper (beside T_tot which is the 2m temperature). The numbers in the names of the variables represent the CDNC case.</p> <p>The time series variables are as a function of t. The vertical profiles are as a function of the pressure p. The maps are as a function of latitude and longitude. </p>
Data for "Aerosol invigoration of atmospheric convection through increases in humidity"
<p>Codes, simulation input files, and simulation output data supporting “Aerosol invigoration of atmospheric convection through increases in humidity”. Enclosed README files provide detailed descriptions of the archive contents.</p>
Oxidation of thin films at the air-water interface of atmospheric aerosol
<p>X-ray reflectivity data (reflectivity vs Q) for the oxidation of insoluble organic material at the air-water interface. The organic material was extracted from atmospheric aerosol and sea water samples. The organic material was reacted with gas-phase ozone and aqueous phase hydroxyl radicals. The reflectivity data was collected at the Diamond Light source on I07 in May 2013 (SI8744) and April 2014 (SI9632) funded by STFC and NERC. The data supports a publication in Atmospheric Environment entitled “Are organic films from atmospheric aerosol and sea water inert to oxidation by ozone at the air-water interface?"</p>
dataset for: Carbonate content and stable isotopic composition of atmospheric aerosol carbon in the Canadian High Arctic
<p>Dataset related to publication of the same title in <a href="https://www.atmospheric-chemistry-and-physics.net/">Atmospheric Chemistry and Physics</a></p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.
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.