Three different CMIP6-LOCA2 based climate projection data sets are spatially averaged for the contiguous United States counties to provide time series for analysis. The primary data set is the statistically downscaled CMIP6-LOCA2 (Localized Constructed Analogs, v2022051 version, Pierce et al. 2023), which includes temperature and precipitation projections from the Climate Model Intercomparison Program Phase 6 (CMIP6) for 27 models under the ssp245, ssp370, and ssp585 scenarios. The “unsplit Livneh” (Pierce et al. (2021) is used as the training data set for LOCA2, where county spatial summaries are also included here for convenience. The second data set analyzes the daily LOCA2 to produce 36 annual and 4 monthly threshold and extreme event metrics (CMIP6-LOCA2 Thresholds). Many of the threshold exceedance variables stem from the Climdex project (https://www.climdex.org), which predominately uses metric units. Additional English-based thresholds were included to support Department of Interior research. The third data set applies a monthly water-balance model to the LOCA2 projections to simulate the hydrological cycle of runoff, snow, soil moisture, and evapotranspiration (CMIP6-LOCA2 MWBM). Users interested in 6 km grids are referred to the home pages of each of the respective sources. Each of these three data sets are spatially average using the 2023 United States Census Bureau TIGER/Line Shapefiles (https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html). The NetCDF time series files herein can be linked to the shapefile geometry using the “GEOID field”. The “feature_area” variable can be used to create weighted averages for multiple counties, such creating a weighted state average from the enclosing counties. The 27 included CMIP6 GCMs are: ACCESS-CM2, ACCESS-ESM1-5, AWI-CM-1-1-MR, BCC-CSM2-MR, CESM2-LENS, CNRM-CM6-1, CNRM-CM6-1-HR, CNRM-ESM2-1, CanESM5, EC-Earth3, EC-Earth3-Veg, FGOALS-g3, GFDL-CM4, GFDL-ESM4, HadGEM3-GC31-LL, HadGEM3-GC31-MM, INM-CM4-8, INM-CM5-0, IPSL-CM6A-LR, KACE-1-0-G, MIROC6, MPI-ESM1-2-HR, MPI-ESM1-2-LR, MRI-ESM2-0, NorESM2-LM, NorESM2-MM, TaiESM1