GENERAL INFORMATION Title of Dataset: High-resolution Climate Simulations using the Model for Prediction Across Scales - Atmosphere (MPAS-A; version 5.1) Author/Principal Investigator Information Name: Allison C. Michaelis ORCID: 0000-0002-0793-5779 Institution: Department of Earth, Atmosphere, and Environment, Northern Illinois University Address: 218 Normal Rd, DeKalb, IL 60115 Email: amichaelis@niu.edu Author/Associate or Co-investigator Information Name: Roger Turnau ORCID: 0000-0001-7864-6299 Institution: Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University Address: 2800 Faucette Drive, Raleigh, NC 27695 Email: rwturnau@ncsu.edu Author/Associate or Co-investigator Information Name: Gary M. Lackmann ORCID: 0000-0001-9069-1228 Institution: Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University Address: 2800 Faucette Drive, Raleigh, NC 27695 Email: gary@ncsu.edu Author/Associate or Co-investigator Information Name: Walter A. Robinson ORCID: 0000-0002-6669-7408 Institution: Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University Address: 2800 Faucette Drive, Raleigh, NC 27695 Email: warobin3@ncsu.edu Date of data collection: Dataset simulated between 2018-05-01 and 2018-06-30 using MPAS-A 5.1 Geographic location of data collection: Full northern hemisphere at 0.15 degree horizontal grid spacing Information about funding sources that supported the collection of the data: NSF grants AGS-1546743 and AGS-1560844 SHARING/ACCESS INFORMATION Licenses/restrictions placed on the data: None Links to publications that cite or use the data: Michaelis et al. (2019): https://gmd.copernicus.org/articles/12/3725/2019/ Michaelis and Lackmann (2019): https://journals.ametsoc.org/view/journals/clim/32/24/jcli-d-19-0259.1.xml Michaelis and Lackmann (2021): https://journals.ametsoc.org/view/journals/clim/34/12/JCLI-D-20-0472.1.xml Lackmann et al. (2021): https://journals.ametsoc.org/view/journals/clim/34/13/JCLI-D-20-0465.1.xml Links to other publicly accessible locations of the data: None Links/relationships to ancillary data sets: None Was data derived from another source? Yes If yes, list source(s): MPAS-A model used to create dataset obtained from: https://mpas-dev.github.io/ MPAS-A initial conditions derived from the ECMWF ERA-Interim Reanalysis obtained from: https://rda.ucar.edu/datasets/ds627.0/ Daily-updated SST conditions derived from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) obtained from: https://resources.marine.copernicus.eu/product-detail/SST_GLO_SST_L4_NRT_OBSERVATIONS_010_001/INFORMATION Temperature deltas for future climate simulations derived from a subset of CMIP5 GCMs obtained from: https://pcmdi.llnl.gov/mips/cmip5/ Recommended citations for this dataset: Michaelis, A. C., R. Turnau, G. M. Lackmann, and W. A. Robinson, 2022: High-resolution Climate Simulations using the Model for Prediction Across Scales - Atmosphere (MPAS-A; version 5.1). Dryad, Dataset. https://doi.org/10.5061/dryad.8cz8w9gtp Michaelis, A. C., G. M. Lackmann, and W. A. Robinson, 2019: Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales–Atmosphere (MPAS-A) version 5.1. Geosci. Model Dev., 12, 3725–3743, https://doi.org/ 10.5194/gmd-12-3725-2019. DATA & FILE OVERVIEW File List: Current1988.nc, Current1992.nc, Current1994.nc, Current1997.nc, Current2001.nc, Current2005.nc, Current2010.nc, Current2011.nc, Current2013.nc, Current2015.nc, Future1988.nc, Future1992.nc, Future1994.nc, Future1997.nc, Future2001.nc, Future2005.nc, Future2010.nc, Future2011.nc, Future2013.nc, Future2015.nc Each of the twenty files is named using the format of [climate] + [year], in which climate references data modeled under current climate conditions or future climate conditions where future climate are adjusted using the difference between the 1980-1999 average temperature and the CMIP5 RCP8.5 projections set between 2080 and 2099 and have their carbon dioxide concentration set to 936ppm. Each year of simulation used observed conditions from the equivalent year as initial conditions and daily SST values as boundary conditions under a range of ENSO states (see Michaelis et. al. 2019 for details). The year from which the boundary conditions were taken (and then adjusted to a future climate for half the simulations) is noted in the title of the file. Each NetCDF4 file contains 2-meter temperature (in kelvin), cumulative rainfall (since simulation start, in millimeters), and 500-hPa heights (in meters) at 6-hour intervals split by month from May through September. These data were extracted from a much larger (~50TB) dataset of MPAS simulations on 6/30/2022 using a Python script to collect the relevant variables. These files were updated on 10/13/2022 to include April rainfall. METHODOLOGICAL INFORMATION Description of methods used for collection/generation of data: The complete technical description of these simulations is presented in Michaelis et al. (2019). Methods for processing the data: The simulations were run on the US National Center for Atmospheric Research (NCAR) supercomputer, Cheyenne. Variables were interpolated onto a lat/lon grid at set pressure levels, and a subset of the simulations extracted using a Python script to form this dataset. People involved with sample collection, processing, analysis and/or submission: Michaelis, Lackmann, and Robinson contributed equally to the model experimental design. Michaelis conducted the simulations. Turnau extracted the subset found here. DATA-SPECIFIC INFORMATION FOR EVERY FILE All files were created using a looping Python script so they have the exact same format and variables. Number of variables: 17 Variable List: Latitude: degrees north (starting at the equator and heading poleward) Longitude: degrees east (starting at the Prime Meridian and heading eastward) t2m-[May/June/July/Aug/Sept]: 2-meter temperature for the selected month with dimensions of time (180 for May, June, and September, or 184 for July and August), latitude (600), and longitude (2400). For example, t2m-May[0,0,0] is the data point at 0Z on May 1st at the Equator and Prime Meridian, assuming your programming language is zero indexed (MATLAB, for example, does not so it would be t2m-May[1,1,1]). Units are in Kelvin. rain-[May/June/July/Aug/Sept]: Accumulated grid-scale precipitation since simulation start (March 1) for the selected month with dimensions of time (180 for May, June, and September, or 184 for July and August), latitude (600), and longitude (2400). For example, rain-May[179,0,0] is the data point at 18Z on May 30th at the Equator and Prime Meridian, again assuming zero indexing. Units are in millimeters. To calculate the precipitation over some period of time simply subtract the value at the start of the period from that at the end of the period. Z500-[May/June/July/Aug/Sept]: 500hPa height for the selected month with dimensions of time (180 for May, June, and September, or 184 for July and August), latitude (600), and longitude (2400). For example, Z500-July[0,0,0] is the data point at 0Z on July 1st at the Equator and Prime Meridian, assuming zero indexing. Units are in meters. All variables are truncated to 6 significant figures for storage purposes. Missing data codes: 9.96920e+36