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64 results for “radiative forcing”
Data used to create figures in the ACP Letters manuscipt "The value of remote marine aerosol measurements for constraining radiative forcing uncertainty" by Regayre et al. (2020)
<p>This dataset was created from perturbed parameter ensembles (PPEs) using the HadGEM-UKCA atmospheric composition climate model. All data needed to reproduce figures in the Regayre et al. (2020) ACP Letters article "The value of remote marine aerosol measurements for constraining radiative forcing uncertainty" are included. Other output from the PPEs can be obtained by contacting the lead author.</p> <p>The following data are included here:</p> <ul> <li>CCN measurement data degraded to match the model-measurement comparison resolution.</li> <li>Unconstrained and constrained CCN<sub>0.2</sub> output from the PPE used to make Figure 1. These compressed files contain 48 .dat files. Each .dat file contains the PPE mean, variance and 95% creidble interval data. Files are named consecutively, containing data from 90<sup>o</sup>S to 90<sup>o</sup>N at 0<sup>o</sup>E, then continuing Eastward. When combined, these files provide data for each latitude/longitude pair at the N48 spatial resolution.</li> <li>A zip file of an netcdf file containing 26-dimensional data for parameter values, used to create the sample of 1 million model variants from our statistical emulators of model output.</li> <li>A zip file containing a folder of files made of one million ones and zeros that indicate the retention/rejection criteria from applying our constraint methodology for various constraint combination scenarios, for each model variant. A value of 1 indicates the model variant was retained. Data in these files is in the same order as the unconstrained sample file of parameter values.</li> <li>Compressed files containing global, annual mean RF<sub>aci</sub> and ERF<sub>aci</sub> values for the unconstrained set of one million model variants. The compressed netcdf files contain RF (ERF), RF<sub>aci</sub> (ERF<sub>aci</sub>) and RF<sub>ari</sub> (ERF<sub>ari</sub>) values.</li> </ul>
Illustrative dataset for Ozone radiative forcing calculations using SOCRATES-RF
<p>This dataset provides to the reader/user with two netCDF files which illustrate the structure and properties of the input datasets (used directly by the software SOCRATES-RF) in support of the publication: "<strong>Historical tropospheric and stratospheric ozone radiative forcing using the CMIP6 database</strong>". It comprises two examples of January (pre-industrial decade, 1850s): one based on CMIP5 ozone concentrations and other based on the recently available CMIP6 ozone dataset. Both were created with the procedure described on the supplementary information of the publication "Historical tropospheric and stratospheric ozone radiative forcing using the CMIP6 database", Checa-Garcia, R et al.</p> <p>The sources of information for these datasets are the CMIP5 / CMIP6 ozone dataset, the ERA-Interim reanalysis dataset (2000-01 to 2009-12) and the solar irradiance from SORCE and TIM projects. Please see the references:</p> <ul> <li>Cionni, I., Eyring, V., Lamarque, J. F., Randel, W. J., Stevenson, D. S., Wu, F., Bodeker, G. E., Shepherd, T. G., Shindell, D. T., and Waugh, D. W.: Ozone database in support of CMIP5 simulations: results and corresponding radiative forcing, Atmos. Chem. Phys., 11, 11267-11292, https://doi.org/10.5194/acp-11-11267-2011, 2011.</li> <li>Hegglin, M. I., D. Kinnison, D. Plummer, R.Checa-Garcia et al., Historical and future ozone database (1850-2100) in support of CMIP6, GMD, in preparation.</li> <li>Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553–597. doi: 10.1002/qj.828</li> <li>Kopp G., Heuerman K., Lawrence G. (2005) The Total Irradiance Monitor (TIM): Instrument Calibration. In: Rottman G., Woods T., George V. (eds) The Solar Radiation and Climate Experiment (SORCE). Springer, New York, NY</li> </ul>
Data for the publication "The global aerosol-climate model ECHAM6.3-HAM2.3 – Part 2: Cloud evaluation, aerosol radiative forcing and climate sensitivity"
<p>This repository contains the data for the paper:</p> <p>"Neubauer, D., Ferrachat, S., Siegenthaler-Le Drian, C., Stier, P. Partridge, D. G., Tegen, I., Bey, I., Stanelle, T., Kokkola, H., and Lohmann, U.: The global aerosol-climate model ECHAM6.3-HAM2.3 – Part 2: Cloud evaluation, aerosol radiative forcing and climate sensitivity, Geosci. Mod. Dev., https://doi.org/10.5194/gmd-2018-307, 2019."</p> <p>Each tar-file contains the data (or instructions how to obtain the data) to reproduce a figure or table in our paper.</p> <p>Note that the scripts to plot this data are to be found in the accompanying package (http://dx.doi.org/10.5281/zenodo.2553891)</p> <p> </p>
Data for Figures 4, S2, S7-9 and emission data in the Publication "Enhanced Light Absorption and Radiative Forcing by Black Carbon Agglomerates"
<p>This repository contains the data to produce Figure 4, S2, S7-9 and emission data for the paper:</p> <p>"Kelesidis, G. A., Neubauer, D., Fan, L.-S., Lohmann, U., & Pratsinis, S. E. (2022). Enhanced light absorption and radiative forcing by black carbon agglomerates. <em>Environmental Science and Technology</em>, 56(12), 8610– 8618. <a href="https://doi.org/10.1021/acs.est.2c00428">https://doi.org/10.1021/acs.est.2c00428</a> "</p> <p>Note that the scripts are to be found in the accompanying package (https://doi.org/10.5281/zenodo.8167401)</p>
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>
Supplementary data to "Radiative forcing and equivalent effective chlorine due to hydrochlorofluorocarbons peaked in 2021"
<p><span>README for Supplementary data to “</span><span>Radiative forcing and equivalent effective chlorine due to hydrochlorofluorocarbons peaked in 2021”</span></p> <p> </p> <p><span>This repository contains 4 folders:</span></p> <p><span>1) agage: contains the inputs to the 12-box model and the derived monthly and annual mole fractions (global and semi-hemispheric) using measurements from the AGAGE network.</span></p> <p><span>2) noaa: contains the inputs to the 12-box model and the derived monthly and annual mole fractions (global and semi-hemispheric) using measurements from the NOAA network.</span></p> <p><span>3) vollmer: contains the inputs to the 12-box model and the derived monthly and annual mole fractions (global and semi-hemispheric) using measurements from the measurements published in Vollmer et al. (2021).</span></p> <p><span>4) Projections: contains a csv file with the merged mole fractions (i.e., mean) from the various networks and the projected quantities.</span></p> <p> </p> <p><span>The 12-box model and the method used to quantify global mean mole fractions are available via GitHub (https://github.com/mrghg/py12box (last accessed 5 March 2024) and https://github.com/mrghg/py12box_invert (last accessed 5 March 2024)) and Zenodo (https://doi.org/10.5281/zenodo.6857447 and https://doi.org/10.5281/zenodo.6857794).</span></p> <p> </p> <p><span>AGAGE data are also available at http://agage.mit.edu/data/agage-data (last accessed 5 March 2024) and https://data.ess-dive.lbl.gov/ (current dataset <a href="https://doi.org/10.15485/1998580"><span>https://doi.org/10.15485/1998580</span></a>) and newer data can be made available upon request. The most recent NOAA atmospheric observations are available at https://gml.noaa.gov/aftp/data/hats/hcfcs/ (last accessed 5 March 2023). </span></p> <p> </p> <p><span>References:</span></p> <p><span>Vollmer, M. K. et al. Unexpected nascent atmospheric emissions of three ozone-depleting hydrochlorofluorocarbons. Proc Natl Acad Sci USA 118, e2010914118 (2021).</span></p>
Datasets for "Assessing satellite derived radiative forcing from snow impurities through inverse hydrologic modeling"
<p>This dataset contains observations and model output used in </p> <p>Matt, F. N., & Burkhart, J. F. (2018). Assessing satellite-derived radiative forcing from snow impurities through inverse hydrologic modeling. Geophysical Research Letters, 45. https://doi.org/10.1002/2018GL077133</p>
Additional radiative forcing (warming) under the different scenarios for ice melt
<p>This data set contains estimates of additional radiative forcing for 3 different sea-ice–albedo feedback (SIAF) scenarios, in addition to the baseline (no additional radiative forcing) scenario. The three scenarios are identical up to 2050, but vary significantly after this date.</p> <p> Full details of methods used to create the dataset are provided within the ReadMe file. </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>
Data for paper publication 'Important role of stratospheric injection height for the distribution and radiative forcing of smoke aerosol from the 2019/2020 Australian wildfires'
<p>This repository contains version 2.0 data from the aerosol-climate simulations performed with the ECHAM6.3-HAM2.3 model and aerosol lidar profiles, as presented in the paper publication by Heinold et al.: Important role of stratospheric injection height for the distribution and radiative forcing of smoke aerosol from the 2019/2020 Australian wildfires, submitted to Atmos. Chem. Phys. For details, please refer to the enclosed data description (README) file.</p>
Rapid decline of aerosol absorption coefficient and aerosol optical properties effects on radiative forcing in urban areas of Beijing from 2018 to 2021
<p>data for Rapid decline of aerosol absorption coefficient and aerosol optical properties effects on radiative forcing in urban areas of Beijing from 2018 to 2021</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>
Data from: Convolutional neural networks trained on internal variability predict forced response of TOA radiation by learning the pattern effect
Open the record for dataset details and reuse information.
Data and code for: Nature-based climate solutions can help mitigate the radiative forcing that follows deforestation
Open the record for dataset details and reuse information.
Radiative Forcing of Nitrate Aerosols from 1975 to 2010 as Simulated by MOSAIC Module in CESM2-MAM4
<p>Netcdf outputs from CESM2 simulations for publication: Radiative Forcing of Nitrate Aerosols from 1975 to 2010 as Simulated by MOSAIC Module in CESM2-MAM4</p>
Impact of host climate model on contrail cirrus effective radiative forcing estimates
<p>Data to reproduce the figures in the article 'Impact of host climate model on contrail cirrus effective radiative forcing estimates'.</p>
Senator Beck Basin Radiative Forcing at MODIS overpass (2005-2023 WY)
<p>Data used in: </p> <p>Naple, P., Skiles, S. M., Lang, O. I., Rittger, K., Lenard, S. J. P., Burgess, A., Painter, T. H. (2023). Dust 774 on snow radiative forcing and contribution to melt in the Colorado River Basin over the MODIS record. 775 ESS Open Archive. https://doi.org/10.22541/essoar.172987451.11953219/v1</p> <p>This is qa/qc'd radiative forcing validation data from two snow energy balance instrumentation towers in Senator Beck Basin Study Area, San Juan Mountains, CO. Measurements are from nearest hour to MODIS overpass</p> <p>All data originates from the Center for Snow and Avalanche Studies, and if used they should be recognized, please see their data policy: <a href="https://snowstudies.org/csas-archival-data/">https://snowstudies.org/csas-archival-data/</a> </p> <p>Radiative forcing is calculated using Equation 1 from Painter et al. 2007</p> <p> </p> <p>Painter, T. H., Barrett, A. P., Landry, C. C., Neff, J. C., Cassidy, M. P., Lawrence, C. R., ... & Farmer, G. L. (2007). Impact of disturbed desert soils on duration of mountain snow cover. <em>Geophysical Research Letters</em>, <em>34</em>(12).</p>
Effective radiative forcing of anthropogenic aerosols in E3SMv1
<p>This archive contains processed E3SMv1 simulation data documented the following manuscript: </p> <p>Zhang et al. (2021): Effective radiative forcing of anthropogenic aerosols in E3SMv1: historical changes, causality, decomposition, and parameterization sensitivities. In submission to Atmospheric Chemistry and Physics. </p> <p>The E3SM maint-1.0 code (E3SM github hash 849d9ee, https://github.com/E3SM-Project/E3SM/tree/849d9ee1a4996e7bea9a6dcc53784259d8272ab8) used for nudged simulations was obtained from the E3SM project sponsored by the U.S.Department of Energy, Office of Science, Office of Biological and Environmental Research.</p>
Addressing Observational Gaps in Aerosol Parameters using Machine Learning: Implications to Aerosol Radiative Forcing
<p>This dataset represents Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA), and Absorption Parameter (AP) data over Kanpur, India, sourced from AERONET with initial data gaps of approximately 37%, 62%, and 58% respectively. To reduce these gaps, XGBoost, a machine learning model trained with reanalysis and satellite datasets, was employed with optimized hyperparameter tuning. Using AERONET data for training, XGBoost effectively addressed gaps, improving AOD by 10%, SSA by 23%, and AP by 21%.</p>
Data and Code for "Informative risk analyses of radiative forcing geoengineering require proper counterfactuals"
<p>This repository contains data and code necessary to generate the figures presented in the maunscript "Data and Code for “Informative risk analyses of radiative forcing geoengineering require proper counterfactuals”, submitted for publication to the Nature journal <em>Communications Earth & Environment</em>.</p>
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International Brain Laboratory public data
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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.