This data release includes climatic variables and associated descriptive material created for the purpose of assessing uncertainties associated with climatic estimates based on vegetation assemblages (Thompson and others, 2021). The data are from the interior of the western United States, including all of Arizona, and portions of California, Colorado, Nevada, New Mexico, Texas, and Utah. The data are observed, interpolated, and estimated values for the mean temperature of the coldest month (MTCO, degrees C), mean temperature of the warmest month (MTWA, degrees C), and mean annual total precipitation (MAP, mm).

On the continental scale, climate is an important determinant of the distributions of plant taxa and ecoregions. To quantify and depict the relations between specific climate variables and these distributions, we placed modern climate and plant taxa distribution data on an approximately 25-kilometer (km) equal-area grid with 27,984 points that cover Canada and the continental United States (Thompson and others, 2015). The gridded climatic data include annual and monthly temperature and precipitation, as well as bioclimatic variables (growing degree days, mean temperatures of the coldest and warmest months, and a moisture index) based on 1961-1990 30-year mean values from the University of East Anglia (UK) Climatic Research Unit (CRU) CL 2.0 dataset (New and others, 2002), and absolute minimum and maximum temperatures for 1951-1980 interpolated from climate-station data (WeatherDisc Associates, 1989). As described below, these data were used to produce portions of the "Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America" (hereafter referred to as "the Atlas"; Thompson and others, 1999a, 1999b, 2000, 2006, 2007, 2012a, 2015). Evolution of the Atlas Over the 16 Years Between Volumes A & B and G: The Atlas evolved through time as technology improved and our knowledge expanded. The climate data employed in the first five Atlas volumes were replaced by more standard and better documented data in the last two volumes (Volumes F and G; Thompson and others, 2012a, 2015). Similarly, the plant distribution data used in Volumes A through D (Thompson and others, 1999a, 1999b, 2000, 2006) were improved for the latter volumes. However, the digitized ecoregion boundaries used in Volume E (Thompson and others, 2007) remain unchanged. Also, as we and others used the data in Atlas Volumes A through E, we came to realize that the plant distribution and climate data for areas south of the US-Mexico border were not of sufficient quality or resolution for our needs and these data are not included in this data release. The data in this data release are provided in comma-separated values (.csv) files. We also provide netCDF (.nc) files containing the climate and bioclimatic data, grouped taxa and species presence-absence data, and ecoregion assignment data for each grid point (but not the country, state, province, and county assignment data for each grid point, which are available in the .csv files). The netCDF files contain updated Albers conical equal-area projection details and more precise grid-point locations. When the original approximately 25-km equal-area grid was created (ca. 1990), it was designed to be registered with existing data sets, and only 3 decimal places were recorded for the grid-point latitude and longitude values (these original 3-decimal place latitude and longitude values are in the .csv files). In addition, the Albers conical equal-area projection used for the grid was modified to match projection irregularities of the U.S. Forest Service atlases (e.g., Little, 1971, 1976, 1977) from which plant taxa distribution data were digitized. For the netCDF files, we have updated the Albers conical equal-area projection parameters and recalculated the grid-point latitudes and longitudes to 6 decimal places. The additional precision in the location data produces maximum differences between the 6-decimal place and the original 3-decimal place values of up to 0.00266 degrees longitude (approximately 143.8 m along the projection x-axis of the grid) and up to 0.00123 degrees latitude (approximately 84.2 m along the projection y-axis of the grid). The maximum straight-line distance between a three-decimal-point and six-decimal-point grid-point location is 144.2 m. Note that we have not regridded the elevation, climate, grouped taxa and species presence-absence data, or ecoregion data to the locations defined by the new 6-decimal place latitude and longitude data. For example, the

This dataset provides estimates of the uncertainty in components of the carbon cycle including: soil carbon stock, autotrophic respiration (Ra), heterotrophic respiration (Rh), net ecosystem exchange (NEE), net primary production (NPP), and gross primary productivity (GPP) across the entire ABoVE Study Domain at 0.5-degree resolution for the reference year 2003. The uncertainties were calculated from the multi-model (n = 20) disagreement, i.e. standard deviation, from the Trends in Net Land Atmosphere Carbon Exchanges program (TRENDY) and the North American Carbon Program (NACP) regional synthesis model outputs averaged to annual means. This total uncertainty integrates both structural uncertainty of land-surface physics among models as well as inherent parametric uncertainty introduced within models, and uncertainty from forcing data.

Projected current and future distributions of Abies amabilis (Pacific silver fir), Abies grandis (Grand fir), Abies procera (Noble fir), Acer macophylla (Big leaf maple), Larix lyallii (Subalpine larch), Larix occidentalis (Western larch), Pinus albicaulis (Whitebark pine), Quercus garryana (Garry oak), Taxus brevifolia (Pacific yew), Thuja plicata (Western red cedar) based on empirical bioclimatic models. Tree distributions models were built using 42 climate and bioclimatic variables from Climate Western North America climate dataset (www.climatevulnerability.org). I used random forest to project USGS range maps (http://esp.cr.usgs.gov/data/little/) for historical (1961-1990) and five general circulation models (GCMs) for the SRES A2 emissions scenario. GCMs included: BCCR BCM2.0 (2070-2099), CCCMA CGCM3 (2070-2099), CSIRO MK 3.0 (2070-2099), INMCM 3.0 (2070-2099), and MIROC3.2 MEDRES (2070-2099).

Projected current and future distributions of Abies amabilis (Pacific silver fir), Abies grandis (Grand fir), Abies procera (Noble fir), Acer macophylla (Big leaf maple), Larix lyallii (Subalpine larch), Larix occidentalis (Western larch), Pinus albicaulis (Whitebark pine), Quercus garryana (Garry oak), Taxus brevifolia (Pacific yew), Thuja plicata (Western red cedar) based on empirical bioclimatic models. Tree distributions models were built using 42 climate and bioclimatic variables from Climate Western North America climate dataset (www.climatevulnerability.org). I used random forest to project USGS range maps (http://esp.cr.usgs.gov/data/little/) for historical (1961-1990) and five general circulation models (GCMs) for the SRES A2 emissions scenario. GCMs included: BCCR BCM2.0 (2070-2099), CCCMA CGCM3 (2070-2099), CSIRO MK 3.0 (2070-2099), INMCM 3.0 (2070-2099), and MIROC3.2 MEDRES (2070-2099).

Projected current and future distributions of Abies amabilis (Pacific silver fir), Abies grandis (Grand fir), Abies procera (Noble fir), Acer macophylla (Big leaf maple), Larix lyallii (Subalpine larch), Larix occidentalis (Western larch), Pinus albicaulis (Whitebark pine), Quercus garryana (Garry oak), Taxus brevifolia (Pacific yew), Thuja plicata (Western red cedar) based on empirical bioclimatic models. Tree distributions models were built using 42 climate and bioclimatic variables from Climate Western North America climate dataset (www.climatevulnerability.org). I used random forest to project USGS range maps (http://esp.cr.usgs.gov/data/little/) for historical (1961-1990) and five general circulation models (GCMs) for the SRES A2 emissions scenario. GCMs included: BCCR BCM2.0 (2070-2099), CCCMA CGCM3 (2070-2099), CSIRO MK 3.0 (2070-2099), INMCM 3.0 (2070-2099), and MIROC3.2 MEDRES (2070-2099).

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of New Hampshire, United States Of America. The time period coverage is from 168 to -62 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Indiana, United States Of America. The time period coverage is from 96 to -63 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Minnesota, United States Of America. The time period coverage is from 99 to -70 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Minnesota, United States Of America. The time period coverage is from 130 to -33 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.