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Dataset results
14 results for “aerosol retrieval”
Dataset for "Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol-cloud interactions"
<p>This dataset in includes MODIS-CloudSat CFODD reference data, the updated Warm Rain Diagnostics implemented in COSPv2.0, RANSAC regression analysis, and figure production scripts associated with the manuscript “Droplet collection efficiencies estimated from satellite retrievals constrain effective radiative forcing of aerosol-cloud interactions”<br> Authors: Beall, Charlotte, M.; Ma, Po-Lun; Christensen, Matthew W.; Mülmenstädt, Johannes; Varble, Adam; Suzuki, Kentaroh; Michibata, Takuro<br> Journal: Atmospheric Chemistry & Physics (submitted, 2023)</p>
Data archive for the peer-reviewed journal article "Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data"
<p>Data archive accompanying the peer-reviewed journal article "Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data". This article was accepted for publication in the journal <em>Atmospheric Measurement Techniques</em> in 2022. The original contributions presented in the study are included in the article and its supplementary information. The GRASP-OPEN model was used to perform forward calculations: this model is publicly available on the official GRASP website (https://www.grasp-open.com/; last access: 14 September, 2022). The specific GRASP-OPEN model outputs that were used for the study are contained in this data archive. </p>
Planetary Boundary Layer Height Retrievals from the Cloud-Aerosol Transport System (CATS) around the US Southern Great Plains and the Eastern North Atlantic
<p>Planetary Boundary Layer Height (PBLH) retrievals in kilometers from the Cloud-Aerosol Transport System (CATS) around the DOE ARM US Southern Great Plains (SGP) and the Eastern North Atlantic (ENA), using a modified version of the Different Thermo-Dynamics Stability (DTDS) algorithm. Quality control Flags are included as follows:</p> <ul> <li>0 = 'Good Quality'</li> <li>1 = 'Mediate Quality'</li> <li>2 = 'Bad Quality'</li> </ul> <p>In addition, -999 values in the dataset represent no data. <br>The PBLH for daytime denoised CATS photon counts at SGP is named: "daytime-denoised-dtds-pblh-sgp.csv"<br>The PBLH for the original daytime and nighttime data at SGP and ENA, without denoising the data, are named: "original-cats-dtds-pblh-daytime-nighttime-sgp.csv" and "original-cats-dtds-pblh-daytime-nighttime-ena.csv"</p> <p>References: </p> <p>Roldán-Henao, N., Yorks, J., Su, T., Selmer, P., & Li, Z. (2024). Statistically Resolved Planetary Boundary Layer Height Diurnal Variability Using Spaceborne Lidar Data. <em>Remote Sensing. </em></p> <p>Su, T., Li, Z., & Kahn, R. (2020). A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions. <em>Remote Sensing of Environment</em>, <em>237</em>, 111519.</p>
Retrievals of aerosol optical, componential, and radiative properties from joint observations of sun photometer and Lidar using GRASP algorithm
<p>The site location is <span>114°21′E, 30°32′N (Central China). The time period is from 2021.07 to 2022.08.</span></p> <p><span>Data includes AOD (all sequences), SSA, ASY, ASD, CRI (only retrieved from sky irradiance), components (black carbon, brown carbon, dust, iron oxide, water-soluble inorganic salt and water), and vertical profiles of shapes of total extinction, fine-mode extinction, and coarse-mode extinction.</span></p>
MAGARA: A Multi-Angle Geostationary Aerosol Retrieval Algorithm
<p>MAGARA, NOAA bias-corrected, and AERONET datasets used for analysis of manuscipt titled "MAGARA: A Multi-Angle Geostationary Aerosol Retrieval Algorithm".</p>
Absorbing Aerosol Optical Central Height (AOCH) retrieved from TROPOMI with UIowa's AOCH-O2AB algorithm
<p>Absorbing Aerosol Optical Centroid Height (AOCH) retrieved from TROPOMI with UIowa’s AOCH-O<sub>2</sub>AB algorithm. Dataset for analyzing dust and smoke cases over Asia during 2021-2023.</p> <p>More information about this dataset can be found in: </p> <p>Chen, X., Wang, J., Xu, X. G., Zhou, M., Zhang, H. X., Garcia, L. C., Colarco, P. R., Janz, S. J., Yorks, J., McGill, M., Reid, J. S., de Graaf, M., and Kondragunta, S.: First retrieval of absorbing aerosol height over dark target using TROPOMI oxygen B band: Algorithm development and application for surface particulate matter estimates, Remote Sensing of Environment, 265, 18, <a href="https://doi.org/10.1016/j.rse.2021.112674">https://doi.org/10.1016/j.rse.2021.112674</a>, 2021.</p>
Video Supplement for Himes et al. (2024): "Using neural networks for near-real-time aerosol retrievals from OMPS Limb Profiler measurements"
<p>This archive contains the video supplement for</p> <p>Using neural networks for near-real-time aerosol retrievals from OMPS Limb Profiler measurements</p> <p>by Himes et al. (2024), submitted to Atmospheric Measurement Techniques. The file contains an animation of the V2.1 and NRT average retrieved extinction coefficient between 19.5--21.5 km at 997 nm for the 2024 Ruang eruptions.</p>
Research Compendium for Himes et al. (2024): "Using neural networks for near-real-time aerosol retrievals from OMPS Limb Profiler measurements"
<p>This archive is the Reproducible Research Compendium for</p> <p>Using neural networks for near-real-time aerosol retrievals from OMPS Limb Profiler measurements</p> <p>by Himes et al. (2024), submitted to Atmospheric Measurement Techniques.</p> <p>This compendium includes all files related to MARGE associated with the manuscript.</p> <p>NN model files are split into smaller files for convenience, given their sizes. To recombine the files, do, e.g., <br> cat cnn_weights_NH-LW.h5* > cnn_weights_NH-LW.h5</p> <p>User interested in running MARGE will need to clone the GitHub repo (https://github.com/exosports/MARGE), apply the patch file to checksum fc95b3c, organize the relevant files into directories as listed in the configuration files (Zenodo does not support organizing files into directory structures) and calculate the number of training, validation, and test cases to be stored in the relevant input file specified in the configuration file. MARGE is under the Reproducible Research Software License (https://planets.ucf.edu/resources/reproducible-research/software-license/). For more details on MARGE, see the User Manual on GitHub.</p>
Towards improving short-term predictions of fine particulate matter over the United States via assimilation of satellite aerosol optical depth retrievals
<p>This dataset contains paired modeled and observed values of different trace gases and aerosol species over the CONUS for the period of 15 July to 14 August 2014 for the three different data assimilation experiments (BKG, MET_BE and MET+EMIS_BE) described in the paper. </p>
Lidar size retrieval of soot aerosol
<p>The original data of figures shown in the paper: "Size retrieval errors of soot particles observed using triple-wavelength lidar and the effects on recalculated optical parameters: A numerical investigation on fractal models".</p>
The field measured size-dependent volatility of ambient fine particles at different heating temperatures and the retrieval of aerosol chemical composition
<p>This is the data used in the paper of “Qiao, X, R., Chen, L., Ren, J, Y., et al. The field measured size-dependent volatility of ambient fine particles at different heating temperatures and the retrieval of aerosol chemical composition. Journal of Geophysical Research - Atmospheres”.</p>
Dataset 2 "Aerosol optical properties within the atmospheric boundary layer predicted from ground-based observations compared to Raman lidar retrievals during RITA-2021"
<p>This dataset provides additional profiles for the manuscript titled "Aerosol optical properties within the atmospheric boundary layer predicted from ground-based observations compared to Raman lidar retrievals during RITA-2021". It is available for those who are interested.</p>
JWST-JupiterSPR-MIRI benzene and Aerosol retrieval
<p>In this dataset you can find the benzene abundance for the three MIRI/JWST tiles, noted as obsX, where x is the number of the tile. In each directory, wou will find three folders noted as 'c6h6...' indicating the peak altitude for the c6h6 profile. In obs2 you will also find the results for the optical depth of the aerosols in the 'hazes...' directories.</p>
Datasets of Aerosol properties retrieved from AOD time series at selected GAWPFR stations
<p>The datasets of aerosol properties retrieved from Aerosol Optical Depth (AOD) measurements from Precision Filter Radiometers (PFR) using the model Generalized Retrieval of Atmosphere and Surface Properties-Aerosol Optical Depth (GRASP-AOD). They correspond to 3 stations of the GAW-PFR network (Davos, Izana and Hohenpeissenberg) and one associated (Lindenberg).</p> <p>Each file corresponds to a station (identifier DAV for Davos, HPB for Hohenpeissenberg and IZO for Izaña). The file names include the identifier for each station, the starting and ending year of the measurements. The first 4 lines of the file include information about the station and the 5th about the columns of the file. The following columns are included in every text file: date(1-3), time UTC (4-6), air mass (7), PFR AOD at 368, 412, 500 and 862 nm (8-11), retrieved PFR AOD from GRASP at 368, 412, 500 and 862 nm (12-15), Angström Exponent (16), Fine mode aerosol optical depth (17), Coarse mode aerosol optical depth (18), Total volume concentration (19), Fine mode volume concentration (20), Coarse mode volume concentration (21), Effective radius (22), Fine mode volume median radius (23), Coarse mode volume median radius (24), Fine mode geometric standard deviation (25), Coarse mode geometric standard deviation (26), Inversion absolute error (27), Inversion relative error (28).</p> <p>The dataset includes the full time series days per station. At stations there was a CIMEL sun photometer from AERONET measuring in parallel, which we used for the validation of the aerosol properties.</p> <p>We also include a report describing the work in more detail, including the validation process and results.</p>
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