GARD-LENS: A downscaled large ensemble dataset for understanding the future climate and its uncertainties

The Generalized Analog Regression Downscaling method Large Ensemble (GARD-LENS) dataset is comprised of daily precipitation, mean temperature, and temperature range over the Contiguous U.S., Alaska, and Hawaii at 12 km, 4 km, and 1 km resolutions, respectively. GARD-LENS downscales three CMIP6 global climate model large ensembles, CESM2, CanESM5, and EC-Earth3, totaling 200 ensemble members. GARD-LENS is the first downscaled SMILE (single model initial-condition large ensemble), providing information about the role of internal climate variability at high resolutions. GARD LENS uses GMET as a training dataset for the period 1980-2014, although Hawaii GMET data is only available for 1990-2014. The total dataset consists of 200 ensemble member files per region per variable (e.g., 200 files for t_mean for CONUS), for a total of 1800 files and a total dataset size of roughly 12 TB.

The 150-year record of this large ensemble dataset provides ample data for assessing trends and extremes and allows users to robustly assess internal variability, forced climate signals, and time of emergence at high resolutions. As the need for high resolution, robust climate datasets continues to grow, GARD-LENS will be a valuable tool for scientists and practitioners who wish to account for internal variability in their future climate analyses and adaptation plans.

To Access Resource:

Questions? Email Resource Support Contact:

  • Joseph Gum
    jgum@ucar.edu
    UCAR/NCAR - Research Data Archive

Temporal Range

  • Begin:  1950
    End:  2100

Keywords

Resource Type dataset
Temporal Range Begin 1950
Temporal Range End 2100
Temporal Resolution N/A
Bounding Box North Lat N/A
Bounding Box South Lat N/A
Bounding Box West Long N/A
Bounding Box East Long N/A
Spatial Representation N/A
Spatial Resolution N/A
Related Links N/A
Additional Information N/A
Resource Format NetCDF (Binary)
Standardized Resource Format NetCDF
Asset Size 0.00 MB
Legal Constraints

Creative Commons Attribution 4.0 International License
Access Constraints None
Software Implementation Language N/A

Resource Support Name Joseph Gum
Resource Support Email jgum@ucar.edu
Resource Support Organization UCAR/NCAR - Research Data Archive
Distributor NCAR Research Data Archive
Metadata Contact Name N/A
Metadata Contact Email rdahelp@ucar.edu
Metadata Contact Organization NCAR Research Data Archive

Author Hartke, Samantha H.
Newman, Andrew J.
Gutmann, Ethan
McCrary, Rachel
Lybarger, Nicholas D.
Lehner, Flavio
Publisher Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
Publication Date 2024-07-12
Digital Object Identifier (DOI) https://doi.org/10.5065/5W7W-5224
Alternate Identifier d619000
Resource Version N/A
Topic Category climatologyMeteorologyAtmosphere
Progress completed
Metadata Date 2024-08-04T02:10:22Z
Metadata Record Identifier edu.ucar.rda::d619000
Metadata Language eng; USA
Suggested Citation Hartke, Samantha H., Newman, Andrew J., Gutmann, Ethan, McCrary, Rachel, Lybarger, Nicholas D., Lehner, Flavio. (2024). GARD-LENS: A downscaled large ensemble dataset for understanding the future climate and its uncertainties. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/5W7W-5224. Accessed 06 September 2024.

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