This AM4VR readme.txt file was generated on 2023-12-14 by Meiyun Lin GENERAL INFORMATION 1. Title of Dataset: Supporting Data for the GFDL Variable-Resolution Global Chemistry-Climate Model for Research at the Nexus of US Climate and Air Quality Extremes 2. Creators/Author list Information A. Principal Investigator Contact Information Name: Meiyun Lin Institution: NOAA GFDL Address: 201 Forrestal Road, Princeton, NJ External user inquiries need to be directed to: gfdl.climate.model.info@noaa.gov 3. Date of data collection (single date, range, approximate date) : 4. Geographic location of data collection : The Continuous US 5. Information about funding sources that supported the collection of the data: SHARING/ACCESS INFORMATION 1. Licenses/restrictions placed on the data: These data were produced by NOAA and are not subject to copyright protection in the United States. NOAA waives any potential copyright and related rights in these data worldwide through the Creative Commons Zero 1.0 Universal Public Domain Dedication (CC0-1.0). 2. Links to publications that cite or use the data: Meiyun Lin, Larry W. Horowitz, Ming Zhao, Lucas Harris, Paul Ginoux, John Dunne, Sergey Malyshev, Elena Shevliakova, Hamza Ahsan, Steve Garner, Fabien Paulot, Arman Pouyaei, Steven J. Smith, Yuanyu Xie, Niki Zadeh, Linjiong Zhou. The GFDL Variable-Resolution Global Chemistry-Climate Model for Research at the Nexus of US Climate and Air Quality Extremes. Journal of Advances in Modeling Earth Systems, https://doi.org/10.1029/2023MS003984 3. Links to other publicly accessible locations of the data: N/A 4. Links/relationships to ancillary data sets: The model source codes generating this dataset are available at https://zenodo.org/records/10257866 5. Was data derived from another source? No 6. Recommended citation for this dataset: Meiyun Lin, Larry W. Horowitz, Ming Zhao, Lucas Harris, Paul Ginoux, John Dunne, Sergey Malyshev, Elena Shevliakova, Hamza Ahsan, Steve Garner, Fabien Paulot, Arman Pouyaei, Steven J. Smith, Yuanyu Xie, Niki Zadeh, Linjiong Zhou. The GFDL Variable-Resolution Global Chemistry-Climate Model for Research at the Nexus of US Climate and Air Quality Extremes. Journal of Advances in Modeling Earth Systems, https://doi.org/10.1029/2023MS003984 DATA & FILE OVERVIEW 1. File List: Monthly mean gridded precipitation over the CONUS domain from 1988 to 2020: AM4VR/atmos/atmos_conus.1988-2020.precip.dp0.5.tar.gz Monthly mean gridded daily maximum temperature (2m) over the CONUS domain from 1988 to 2020: AM4VR/atmos/atmos_conus.1988-2020.t_ref_max.dp0.5.tar.gz Monthly mean climatology (2000-2014) of three-dimensional tracer fields over the CONUS domain: AM4VR/tracer/tracer_level_conus.2000-2014.tar.gz Atmospheric grid and vertical level information: AM4VR/atmos/atmos_conus.static.nc Land grid information: AM4VR/atmos/land_conus.static.nc 2. Relationship between files, if important: 3. Additional related data collected that was not included in the current data package: 4. Are there multiple versions of the dataset? NO METHODOLOGICAL INFORMATION 1. Description of methods/models used for collection/generation of data: The data were produced by the GFDL Variable-Resolution Global Chemistry-Climate Model (AM4VR) running in AMIP (Atmospheric Model Intercomparison Project) mode, driven by observed sea surface temperature (SST) and sea ice distributions, historical anthropogenic emissions, land use and atmospheric radiative forcing agents over 1988-2020. Please refer to Lin et al. (JAMES, 2023) for the details of the experiment design. Meiyun Lin, Larry W. Horowitz, Ming Zhao, Lucas Harris, Paul Ginoux, John Dunne, Sergey Malyshev, Elena Shevliakova, Hamza Ahsan, Steve Garner, Fabien Paulot, Arman Pouyaei, Steven J. Smith, Yuanyu Xie, Niki Zadeh, Linjiong Zhou. The GFDL Variable-Resolution Global Chemistry-Climate Model for Research at the Nexus of US Climate and Air Quality Extremes. Journal of Advances in Modeling Earth Systems, https://doi.org/10.1029/2023MS003984 2. Methods for processing the data: N/A 3. Instrument- or software-specific information needed to interpret the data: Software that can read NetCDF 4. Standards and calibration information, if appropriate: N/A 5. Environmental/experimental conditions: N/A 6. Describe any quality-assurance procedures performed on the data: The model has been carefully evaluated against a suite of measurements as described in Lin et al. (Journal of Advances in Modeling Earth Systems, 2023). 7. People involved with sample collection, processing, analysis and/or submission: N/A DATA-SPECIFIC INFORMATION FOR: 1. Number of variables: 92 2. Number of cases/rows: N/A 3. Variable List: Precipitation, see units with “ncdump -h atmos_conus.2020.precip.nc” Daily maximum temperature at 2m, see units with “ncdump -h atmos_conus.2020.t_ref_max.nc” 90 tracers. Please see the variable names, descriptions, and units with “ncdump -h tracer_level_conus.2000-2014.01.nc” 4. Missing data codes: N/A 5. Specialized formats or other abbreviations used: NetCDF