Do downscaled general circulation models reliably simulate historical climatic conditions?

This dataset includes nine files (in comma-separated value format [.csv]) which contain metrics that are described in the Bock and others 2018 Earth Interactions article “Do downscaled general circulation models reliably simulate historical climatic conditions?” Three files contain p-values from the two-sided Kolmogorov-Smirnov Test (that compared distributions of three variables (precipitation [CONUS_KS_PPT.csv], temperature [CONUS_KS_TAVE.csv], and runoff [CONUS_KS_RUN.csv]) derived from statistically-downscaled general circulation models (SD GCM) with distributions of the three variables derived from gridded station data (GSD) for historical conditions (1950 through 2005). Three files contain the x-axis value (Dx) at which the largest vertical difference occurs between the distributions of SD GCMs and GSD for the three variables (DX_PPT/TAVE/RUN.csv). Three files describe if the relative value of the SD GCM variable is greater or less than the GSD at the Dx value. See Bock and others (2018) for full description of the three metrics (DB_PPT/TAVE/RUN.csv). The metrics are calculated from variables previously summarized across the conterminous United States for hydrologic response units of the Geospatial Fabric for National Hydrologic Modeling (Viger and Bock, 2014). Runoff was previously derived using a monthly water balance model (Bock and others, 2016; 2017). Names, sources, and references of the climate inputs (SD GCMS and GSD) are described in Bock and others (2017).

                                            [
  "010:12"
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                                            {
  "fn": "Andy Bock",
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                                            [
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                                            [
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  "air temperature",
  "inlandWaters",
  "precipitation (atmospheric)",
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                                            {
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                                            [
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