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

ABSTRACT: This article introduces the Generalized Analog Regression Downscaling method Large Ensemble (GARD-LENS) dataset, 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 statistically 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. 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

SUBMITTER: Hartke SH 

PROVIDER: S-EPMC11655549 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature