Data for "Background Conditions Influence the Estimated Cloud Radiative Effects of Anthropogenic Aerosol Emissions from Different Source Regions"

<b>Introduction</b>These data accompany the for the article by Grandey and Wang (2019), <b>Background Conditions Influence the Estimated Cloud Radiative Effects of Anthropogenic Aerosol Emissions from Different Source Regions</b>, <i>Journal of Geophysical Research: Atmospheres</i>, doi:10.1029/2018JD029644.<br>The files contain input data and output data associated with the CESM-CAM5 climate model simulations described in the manuscript.<br>Please also see https://github.com/grandey/draft2017a-region-rfp for details of the model configuration, data management, and analysis.<br><b>Input data (<i>input_p16a_F_2016-07-29_16-16.tar.gz</i>)</b><i>input_p16a_F_2016-07-29_16-16.tar.gz</i>, a tar archive, contains the modified emissions data files for the simulations. The tar archive unpacks to <i>p16a_F/.</i><br>The scripts used to generate these files can be viewed at https://github.com/grandey/draft2017a-region-rfp/tree/master/configuration_and_input.<br><b>Output data (<i>p1*.nc</i>)</b>The <i>p1*.nc</i> NetCDF files contain a subset of the output data from the simulations. These data have been converted to time-series format using PyReshaper, as described in https://github.com/grandey/draft2017a-region-rfp/blob/master/data_management.org.<br>The file naming convention is as follows:<i>[SIMULATION].cam.h0.[VARIABLE].nc</i>where1. <i>[SIMULATION]</i> refers to a simulation casename (e.g. "p16a_F_Hist_2000");3. <i>[VARIABLE] </i>refers to a specific variable code (e.g. "BURDENSO4" is sulfate burden).<br>For an example of how these data can be used, see <i>lib_draft2017a.py</i> and <i>figures_draft2017a.ipynb</i> in https://github.com/grandey/draft2017a-region-rfp.<br><b>NetCDF (.nc) file format</b>Most of the data files are in NetCDF format, a binary data format commonly used for climate model input and output data. These NetCDF files contain metadata which aid interpretation of the data. For example, the metadata contain a description of each output variable. The metadata and data can be explored using the free Panoply software tool (https://www.giss.nasa.gov/tools/panoply/ [accessed 16-Aug-2018]).<br><b>File size warning</b>Many of the NetCDF files are relatively large.<br><b>Contributors</b>B. S. Grandey and C. Wang have both contributed to this project, as described in the author contributions statement of <i>"Background Conditions Influence the Estimated Cloud Radiative Effects of Anthropogenic Aerosol Emissions from Different Source Regions"</i>.<br><b>Acknowledgements</b>This research is supported by the National Research Foundation of Singapore under its Campus for Research Excellence and Technological Enterprise programme. The Center for Environmental Sensing and Modeling is an interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology. This research is also supported by the U.S. National Science Foundation (AGS-1339264), by the U.S. Department of Energy, Office of Science (DE-FG02-94ER61937), and by L’Agence National de la Recherche (ANR) of France through the Make-Our-Planet-Great-Again Initiative, ANR-18-MPGA-003 EUROACE. The CESM project is supported by the National Science Foundation and the Office of Science (BER) of the U.S. Department of Energy. The computational work for this research was performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg).<br><br><b>Primary reference</b>B. S. Grandey and C. Wang (2019), <b>Background Conditions Influence the Estimated Cloud Radiative Effects of Anthropogenic Aerosol Emissions from Different Source Regions</b>, <i>Journal of Geophysical Research: Atmospheres</i>, doi:10.1029/2018JD029644. (A preprint is available via http://arxiv.org/abs/1808.05778.)