Data for "Effective radiative forcing in the aerosol-climate model CAM5.3-MARC-ARG"

These data accompany the manuscript by B. S. Grandey, D. Rothenberg, A. Avramov, Q. Jin, H.-H. Lee, X. Liu, Z. Lu, S. Albani, and C. Wang (2018), Effective radiative forcing in the aerosol-climate model CAM5.3-MARC-ARG, Atmospheric Chemistry and Physics, https://doi.org/10.5194/acp-18-15783-2018.

The files contain input data and output data associated with the CESM-CAM5 climate model simulations described in the manuscript.

Please also see https://github.com/grandey/p17c-marc-comparison/ for details of the experimental design, model configuration, data management, and analysis.

input_data_p17c.tar.gz, a tar archive, contains the input data files for the CAM5-MARC-ARG simulations. The tar archive also contains the scripts used to generate the emissions input data files and a readme file. The scripts and readme file can also be viewed via https://github.com/grandey/p17c-marc-comparison/tree/master/input_data_p17c/.

emis_NH3_1850_p17c.nc contains ammonia emissions for the year-1850 MAM7 simulation.

output_timing.tar.gz contains timing data files from the timing simulations. For an example of how these data can be used, see https://github.com/grandey/p17c-marc-comparison/blob/master/analysis_draft2017b/timing_table_draft2017b.ipynb

The p17c_*.nc NetCDF files contain a subset of the output data from the comparison simulations. These data have been converted to time-series format using PyReshaper, as described in https://github.com/grandey/p17c-marc-comparison/blob/master/manage_data/data_management.org

The file naming convention is as follows:

where

1. [SIMULATION] refers to a comparison simulation casename (e.g. "p17c_marc_2000"; see https://github.com/grandey/p17c-marc-comparison/blob/master/experimental_design.org);

2. [HISTORY_FILE_TYPE] is either "cam.h0" (monthly atmosphere data), "clm2.h0" (monthly land data), or "cice.h" (monthly sea-ice data); and

3. [VARIABLE] refers to a specific variable code (e.g. "AEROD_v" is aerosol optical depth).

For an example of how these data can be used, see analysis_cdo_nco_draft2017b.ipynb and figures_draft2017b.ipynb in https://github.com/grandey/p17c-marc-comparison/tree/master/analysis_draft2017b/.

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 metadeta contain a description of each output variable. The metadata and data can be explored using the free Panoply software tool (http://www.giss.nasa.gov/tools/panoply/ [accessed 11-Dec-2017]).

B. S. Grandey, D. Rothenberg, A. Avramov, Q. Jin, H.-H. Lee, X. Liu, Z. Lu, S. Albani, and C. Wang have all contributed to this project, as described in the author contribution statement of "Effective radiative forcing in the aerosol-climate model CAM5.3-MARC-ARG".

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) and the U.S. Department of Energy, Office of Science (DE-FG02-94ER61937). The CESM project is supported by the National Science Foundation and the Office of Science (BER) of the U.S. Department of Energy. We acknowledge high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. We thank Natalie Mahowald for contributing dust model code, optical tables, a soil erodibility map, and advice, all of which have aided the development of CAM5.3-MARC-ARG.

Grandey, Rothenberg, Avramov, Jin, Lee, Liu, Lu, Albani, and Wang (2018), Effective radiative forcing in the aerosol-climate model CAM5.3-MARC-ARG, Atmospheric Chemistry and Physics, https://doi.org/10.5194/acp-18-15783-2018.