Climate Scenarios for the conterminous United States at the county spatial scale using SRES scenarios A1B and A2 and PRISM climatology

Metadata:
Identification_Information:
Citation:
Citation_Information:
Originator: Coulson, David P.
Originator: Joyce, Linda A.
Originator: Price, David T.
Originator: McKenney, Daniel W.
Originator: Siltanen, R. Martin
Originator: Papadopol, Pia
Originator: Lawrence, Kevin
Publication_Date: 2010
Title:
Climate Scenarios for the conterminous United States at the county spatial scale using SRES scenarios A1B and A2 and PRISM climatology
Geospatial_Data_Presentation_Form: tabular digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: USDA Forest Service, Rocky Mountain Research Station
Online_Linkage: https://doi.org/10.2737/RDS-2010-0008
Description:
Abstract:
Monthly totals of precipitation in millimeters (mm), monthly means of daily maximum air temperature in degrees Celsius (C), and monthly means of daily minimum air temperature (C) were developed at the county level for the conterminous United States (US). Also, included are computed monthly mean of daily potential evapotranspiration (mm) and mean grid elevation in meters (m). These data were developed from climate scenarios used in the Fourth Assessment of the Intergovernmental Panel on Climate Change, specifically the A1B and the A2 SRES (Special Report on Emissions Scenarios) scenarios as modeled by these climate models: CGCM3.1MR, CSIRO-MK3.5, and MIROC3.2MR. The monthly change factors were developed from global model output and downscaled to the 5 arc minute spatial grid using ANUSPLIN. The 30 year mean climatology (1961-1990) was developed from PRISM (Parameter-elevation Regressions on Independent Slopes Model) data at the 2.5 arc minute scale and aggregated to the 5 arc minute grid scale. The change factors were imposed upon the 30-year period (1961-1990) to develop the projections for each climate scenario. The county means were computed using a weighted mean of the 5 arc minute grids within the county.
Purpose:
The USDA Forest Service (USFS) produces a periodic assessment of the condition and trends of the Nation's renewable resources as required by the Forest and Rangeland Renewable Resources Planning Act (RPA) of 1974. This RPA Assessment provides a snapshot of current US forest and rangeland conditions and trends on all ownerships, identifies drivers of change, and projects 50 years into the future (https://www.fs.usda.gov/research/inventory/rpaa). For 2010 RPA Assessment, an integrated modeling framework is being used in which the potential implications of climate change can be analyzed across some resource areas (Langner et al. 2012). The nature of the climate variables needed to address climate change impacts for these resource analyses in the 2010 RPA Assessment were determined to be monthly precipitation and temperature variables at the county level spatial scale, and for some resources, at the 5 arc minute grid scale.
Supplemental_Information:
Original metadata date was 08/03/2010. Metadata modified on 04/18/2011 to adjust citation to include the addition of a DOI (digital object identifier). Minor metadata updates on 02/19/2013. Metadata modified on 07/22/2015 to update cross-reference citations and other minor updates. Additional minor metadata updates on 12/13/2016, 02/08/2021, and 10/27/2022.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2001
Ending_Date: 2100
Currentness_Reference:
Observed
Status:
Progress: Complete
Maintenance_and_Update_Frequency: As needed
Spatial_Domain:
Description_of_Geographic_Extent:
All counties within the conterminous US as defined by ARC shape file fia_survey_unit obtained from Robert J. Huggett, Jr. (see Source Information for more details).
Bounding_Coordinates:
West_Bounding_Coordinate: -124.75
East_Bounding_Coordinate: -66.9167
North_Bounding_Coordinate: 49.5
South_Bounding_Coordinate: 25
Bounding_Altitudes:
Altitude_Minimum: 0
Altitude_Maximum: 3778.25
Altitude_Distance_Units: meters
Keywords:
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: RPA Assessment
Theme_Keyword: climate scenario
Theme_Keyword: temperature projections
Theme_Keyword: precipitation projections
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: climatologyMeteorologyAtmosphere
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Climate change
Theme_Keyword: Climatology
Theme_Keyword: Inventory, Monitoring, & Analysis
Theme_Keyword: Monitoring
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: conterminous United States
Place_Keyword: county level
Access_Constraints: None
Use_Constraints:
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the citation below when citing the data publication:

Coulson, David P.; Joyce, Linda A.; Price, David T.; McKenney, Daniel W.; Siltanen, R. Martin; Papadopol, Pia; Lawrence, Kevin. 2010. Climate Scenarios for the conterminous United States at the county spatial scale using SRES scenarios A1B and A2 and PRISM climatology. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. https://doi.org/10.2737/RDS-2010-0008
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Linda Joyce
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station, Human Dimensions Program
Contact_Position: Quantitative Ecologist
Contact_Address:
Address_Type: mailing and physical
Address: 240 West Prospect
City: Fort Collins
State_or_Province: CO
Postal_Code: 80526
Country: USA
Contact_Voice_Telephone: 970-498-2560
Data_Set_Credit:
We wish to acknowledge the support provided by the global climate modeling community, and their willingness to contribute and share data through web-based data archives, notably the Program for Climate Model Diagnosis and Intercomparison (PCMDI) Third Climate Model Intercomparison Project (CMIP3) data portal. Further, we greatly appreciate the availability of data provided by:
- The Canadian Centre for Climate Modelling and Analysis (CCCma)
- The Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO)
- In Japan, the Centre for Climate System Research (CCSR), together with the University of Tokyo, the National Institute for Environmental Studies (NIES) and the Frontier Research Center for Global Change.

The authors request that any users of the scenario data presented here, also provide appropriate acknowledgements to the respective GCM groups, as identified above

We also wish to acknowledge the use of the PRISM data (https://prism.oregonstate.edu/) to construct the 30-year normals. The PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate mapping system was developed by Christopher Daly, PRISM Group director.

We also acknowledge the support for this project from the USFS RPA Assessment staff.
Native_Data_Set_Environment:
The files are available as comma delimited ASCII text files (CSV).
Cross_Reference:
Citation_Information:
Originator: Joyce, Linda A.
Originator: Price, David T.
Originator: Coulson, David P.
Originator: McKenney, Daniel W.
Originator: Siltanen, R. Martin
Originator: Papadopol, Pia
Originator: Lawrence, Kevin
Publication_Date: 2014
Title:
Projecting climate change in the United States: A technical document supporting the Forest Service 2010 RPA Assessment
Geospatial_Data_Presentation_Form: document
Series_Information:
Series_Name: General Technical Report
Issue_Identification: RMRS-GTR-320
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station
Other_Citation_Details:
85 p.
Online_Linkage: https://doi.org/10.2737/RMRS-GTR-320
Cross_Reference:
Citation_Information:
Originator: Langner, Linda L.
Originator: Daniels, Amy E.
Originator: Joyce, Linda A.
Publication_Date: 2012
Title:
Future Scenarios: a technical document supporting the Forest Service 2010 RPA assessment
Geospatial_Data_Presentation_Form: document
Series_Information:
Series_Name: General Technical Report
Issue_Identification: RMRS-GTR-272
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station
Other_Citation_Details:
34 p.
Online_Linkage: https://doi.org/10.2737/RMRS-GTR-272
Cross_Reference:
Citation_Information:
Originator: Joyce, Linda A.
Originator: Price, David T.
Originator: McKenney, Daniel W.
Originator: Siltanen, R. Martin
Originator: Papadopol, Pia
Originator: Lawrence, Kevin
Originator: Coulson, David P.
Publication_Date: 2011
Title:
High resolution interpolation of climate scenarios for the conterminous United States and Alaska derived from general circulation model simulations
Geospatial_Data_Presentation_Form: document
Series_Information:
Series_Name: General Technical Report
Issue_Identification: RMRS-GTR-263
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station
Other_Citation_Details:
87 p.
Online_Linkage: https://doi.org/10.2737/RMRS-GTR-263
Cross_Reference:
Citation_Information:
Originator: Langner, Linda L.
Publication_Date: 2012
Title:
Future of America’s Forest and Rangelands: Forest Service 2010 Resources Planning Act Assessment
Geospatial_Data_Presentation_Form: document
Series_Information:
Series_Name: General Technical Report
Issue_Identification: WO-87
Publication_Information:
Publication_Place: Washington, DC
Publisher: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station
Other_Citation_Details:
198 p.
Online_Linkage: https://doi.org/10.2737/WO-GTR-87
Cross_Reference:
Citation_Information:
Originator: Coulson, David P.
Originator: Joyce, Linda A.
Originator: Price, David T.
Originator: McKenney, Daniel W.
Originator: Siltanen, R. Martin
Originator: Papadopol, Pia
Originator: Lawrence, Kevin
Publication_Date: 2010
Title:
Climate Scenarios for the conterminous United States at the 5 arc minute grid spatial scale using SRES scenarios A1B and A2 and PRISM climatology
Geospatial_Data_Presentation_Form: tabular digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: USDA Forest Service, Rocky Mountain Research Station
Online_Linkage: https://doi.org/10.2737/RDS-2010-0017
Back to Top
Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
The climate projection data have a history of several developers. Each developer documents the accuracy of the data at their step. The global data from the climate models was obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) Climate Model Intercomparison Project 3 (CMIP3). Model documentation is available at: https://pcmdi.llnl.gov/ipcc/model_documentation/ipcc_model_documentation.php. The attribute accuracy for the PRISM data is available for both the temperature and precipitation data as part of this data publication download (see: \Documents\Metadata_103yr_HiRes_TempData_for_US.pdf and \Documents\Metadata_103yr_HiRes_TempData_for_US.pdf). For the PRISM data, care should be taken in estimating temperature values or precipitation values at any single point on the map. Temperature or precipitation estimate for each grid cell (2.5 arc minutes) are an average over the entire area of that cell; thus, point temperature or precipitation can be estimated at a spatial precision no better than half the resolution of the cell. This application of PRISM aggregates the values across grid cells and does not violate this concern. Price and colleagues document the downscaling procedure and any problems with the climate data - no concerns were shared with temperature and precipitation (Joyce et al. 2014). For the final projection data, the quality assurance process initially focused on ensuring that the data has been downloaded without issue. Additional quality assurance tests are made in the development of the projection data where data from the change factor data sets and the 30-year means are manipulated at different spatial scales. This is documented in Joyce et al. (2014).
Completeness_Report:
The county level data includes projections for the conterminous United States where the United States and county boundaries are defined by the ARC shape file received from the United States Forest Service Forest Inventory and Analysis group (FIA). The data are available as comma-delimited files where each grid is identified by latitude and longitude. The data set contains 3111 counties with 3733200 lines of data, 12 months by 100 years by 3111 counties.
Lineage:
Methodology:
Methodology_Type: Lab
Methodolgy_Identifier:
Methodolgy_Keyword_Thesaurus:
None
Methodology_Keyword: high resolution, downscaling, ANUSPLIN
Methodology_Description:
The methodology to develop the county level projection dataset involved obtaining the climate scenario model data, downscaling the climate scenario data, deriving the 30 year historical means on which to build the scenario, and developing the projections. Each step is described here.

Obtaining the climate scenario model data:
Price and others obtained the climate model projection results (monthly means of daily temperature and monthly precipitation) from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) Climate Model Intercomparison Project 3 (CMIP3) data portal (originally available at URL: //esg.llnl.gov:8443/index.jsp, now available: https://www.data.gov/climate/portals/) as simulated by each of the following global climate models (GCMs)):
- CGCM3.1MR - Canadian Centre for Climate Modelling and Analysis (CCCma) Third Generation Coupled Global Climate Model Version 3.1, Medium Resolution (T47). https://www.ec.gc.ca/ccmac-cccma (original URL: //www.cccma.bc.ec.gc.ca/models/cgcm3.shtml)
- CSIRO-MK3.5 - Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mk3.5 Climate System Model (T63) https://www.cmar.csiro.au/e-print/open/gordon_2002a.pdf
https://pcmdi.llnl.gov/ipcc/model_documentation/CSIRO-Mk3.5.htm
- MIROC3.2MR - Japanese Centre for Climate System Research (CCSR), University of Tokyo; National Institute for Environmental Studies (NIES) and Frontier Research Center for Global Change (FRCGC) Model for Interdisciplinary Research on Climate (MIROC) Version 3.2 Medium Resolution (T42).

The use of these distinct and well-established GCMs ensured that the downscaled scenarios met the IPCC criteria for selecting and using scenarios for climate change impacts studies, including:
- Consistency of regional scenarios with global projections;
- Physically plausible and consistent, because multiple climate variables were to be interpolated for each GCM scenario separately and provided in each data set;
- Applicable for impacts assessment, because the downscaled scenario data were reported as change factors that can be referenced to locally observed climate data.

Downscaling methodology:
The downscaling methodology followed Price et al. (2000, 2004) and McKenney et al. (2006). The ANUSPLIN software was developed at the Australian National University by Hutchinson and coworkers (e.g., Hutchinson 2015) for interpolating climate station observations (see also https://fennerschool.anu.edu.au/research/products/anusplin-vrsn-44). It has been applied to climatological data sets around the world, including Australia, New Zealand, China and parts of southeast Asia, South America, Africa, and Europe and more recently to Canada (Price et al. 2000; McKenney et al. 2006). Thin plate splines can be described as a generalized multivariate linear regression model in which the parametric model is replaced by a smooth nonparametric function. For climate data interpolation, the target climate variable is considered dependent upon spatial dimensions (latitude, longitude and elevation). The general method is to fit the spline function to the values of a single climate variable observed at irregularly distributed locations in the region of interest for a specified period (a single day, or month or a long-term average, such as a 30-year monthly normal). This study used ANUSPLIN 4.3; a newer version (4.4) is now up on the web (Hutchinson 2015).

The simulated climate variables to be interpolated were monthly means of daily surface temperature (minimum and maximum), and the monthly precipitation. The monthly values from the climate scenario datasets were converted to the monthly change factors, using the means of the simulated monthly values for the 30-year period 1961-1990 as the baseline. In the case of temperature variables (monthly mean daily minimum and maximum air temperature), the change factor was computed as the arithmetic difference between the monthly value and the corresponding 30-year mean of the same temperature variable for that month. For monthly precipitation, the change factor was the ratio of the monthly value to the 1961-1990 mean for that month.

The change factors were then interpolated using ANUSPLIN to create time series for the period over which the GCM simulations were carried out. ANUSPLIN produced a fitted spline "surface" equation for each monthly variable, which was then used to create gridded data for that monthly variable covering North America at the spatial resolution of 5 arc minutes.

Coulson and Joyce obtained the downscaled data as UNIX tar files of gzipped ASCII grids from David Price's team. The North American 5 arc-minute (1/12 degree) ASCII grid file names also include the year, month, and region number in the file name e.g. "cgcm2_a2_prec_anom1990_1_r1.grd" would be the grid name for the CGCM2, SRES-A2, precipitation anomalies, 1990, January, Region 1 grid. Each grid has a header suitable for import into Arc/Info or similar GIS, e.g.:
ncols 462
nrows 234
xllcorner -168
yllcorner 52.5
cellsize 0.0833
NODATA_value -9999
Grids are referenced by the southwesterly point corner (lower left-hand corner).

Variable names and short forms used in file names from Price and colleagues are:
prec - monthly precipitation (change factor is a ratio, units are mm absolutes),
tmin - mean daily minimum temperature (change factor is a difference, units are degrees C absolutes),
tmax - mean daily maximum temperature (change factor is a difference, units are degrees C absolutes).

Development of the Historical Climate Normals for the 1961-1990 period:
The PRISM data (https://prism.oregonstate.edu/) were selected to build the 1961-1990 historical baseline from which the future climate scenarios were constructed using change factors developed by Price and others. The PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate mapping system, developed by Christopher Daly, PRISM Group director, is a knowledge-based system that uses point measurements of precipitation, temperature, and other climatic factors to produce continuous, digital grid estimates of monthly, yearly, and event-based climatic parameters (Daly et al. 2002, Gibson et al. 2002). Continuously updated, this unique analytical tool incorporates point data, a digital elevation model, and expert knowledge of complex climatic extremes, including rain shadows, coastal effects, and temperature inversions. We obtained historical climate data (monthly means of daily maximum air temperature, monthly means of daily minimum temperature, and monthly values of precipitation) via download (above site). Data are provided in raster files, where each file contains 1405 columns (longitude) and 621 lines (latitude), resulting in 872,505 grids covering the conterminous United States. Each file represents the month and year of a single climate variable. PRISM grids are 2.5 arc minutes square (1/24 arc degrees) referenced by the southwesterly point corner (lower left-hand corner) at longitude -125.02083 and latitude 25.0625. All longitude/latitude values represent the southwest corner of the grid.

Development of the Projections at the Grid Level:
Because the climate scenario change factors were developed at the 5 arc minute (1/12 arc degree) scale and PRISM data are at the 2.5 arc minute scale, we aggregated the historical climate data to the 5 arc minute spatial scale so that these normals can be used to construct future climate scenarios using the downscaled change factors.

Comparison of the change factor (5.0 arc minute grids) grids with PRISM (2.5 arc minute) grids:
Listed below: 5.0 arc minute, 2.5 arc minute
Number of columns (ncols) = 702, 1405
Number of rows (nrows) = 294, 621
X corner (xllcorner) = -125, -125.02083
Y corner (yllcorner) = 25, 25.0625
Cell size equivalence = 1/12 degree, 1/24 degree
No data value = -9999, -9999
Longitude grid coverage bound: West = -125, -125.02083
Longitude grid coverage bound: East = -66.41666667, -66.43749667
Latitude grid coverage bound: North = 49.58333333, 50.97916667
Latitude grid coverage bound: South =25, 25.0625

The PRISM grid scale is one half that of the change factor grids, 2.5 versus 5 arc minutes, as a result there are four PRISM grids per change factor grid. PRISM grids starting point (southwest corner) is offset by 3.75 degrees north and 1.25 degrees east from the change factor grids. This has the effect of lining up the longitude/latitude center of one out of four of the PRISM grids with each change factor grid.

We create a set of normals by averaging all years from 1961 to 1990 for each month for each climate metric: precipitation, maximum temperature and minimum temperature for each PRISM grid.

We then calculate a weighted mean value for each change factor grid using the following formula of the PRISM grids overlapping the change factor grid where one PRISM grid (p5 in formula) overlaps with the center of the change factor grid, and portions of 8 other grids are added to the estimate.

Mean grid value = (0.25*p1+0.5*p2+0.25*p3+0.5*p4+p5+0.5*p6+0.25*p7+0.5*p8+0.25*p9)/4, where p1 is overlapping PRISM grid number 1(northwest corner), p2 - north center, p3 - northeast corner, p4 - west center, p5 - center, p6 - east center, p7 - southwest corner, p8 - south center, and p9 - southeast corner. In the event an overlapping PRISM grid has missing data the average is a weighted average of those grids with data.

We obtained the change factor data from Price and co-workers. The tar files were unzipped and imported into SAS 9.2. The change factors were then applied to the normals to develop the resultant grid level climate projections.

Computation of Potential Evapotranspiration:
Potential evapotranspiration (PET) for vegetation was calculated using a modification of Penman's work by Linacre (1977), where PET=[500Tm/(100-A)+15(T-Td)]/(80-T)mm day-1.
T is the mean monthly temperature in units of degrees Celsius, Tm is the mean monthly temperature adjusted for elevation, h is the elevation in units of meters, Td is the mean monthly dew point temperature in units of degrees Celsius, and A is the latitude in degrees.

Tm = T + 0.0006h, where h is the elevation. Linacre provides an alternate for estimating (T-Td) when dew point data are not available. (T-Td) = 0.0023h+0.37T+0.53R+0.35Rann-10.9 degrees C. Rann is the difference between the means of the hottest and coldest months. R is mean daily range of temperature.

Rann is calculated from the projected data by the formula Max(T1-T12)-Min(T1-T12). Ti is the mean monthly temperature of the month, where T1= Jan, T2=Feb, ..., T12=Dec.

Mean R is estimated from PRISM data using mean monthly of maximum air temperature and the minimum air temperature from 1940-2006. This value is used as a surrogate for any given year in the future. The R is calculated for each PRISM grid and then a weighted average calculated for the 5 arc minute grids as describe above.

Note that R = sum of {(Dmax - Dmin)/n}, where R is the monthly average, Dmax is the daily maximum temperature, Dmin is the daily minimum temperature, n is the number of day in the month.

An elevation is obtained from PRISM data which is available at the 2.5 minute grids (1/24 degree) and a weighted mean calculated for the 5 arc minute grid.

This methodology provides an estimate of future PET, using only the temperature and latitude values from the climate projections, elevation, and average mean daily temperature range from PRISM data.

Development of County Level Climate Scenarios:
An overlay file between the 5 arc minute grid and the County boundaries was developed in ArcGIS 9.2. This ultimately resulted in 120,680 grids with climate normal data within the continental US. This resulting database file was imported into SAS, merged with the projected climate data.

Once merged, the county means for monthly totals of precipitation, monthly means of daily maximum air temperature, monthly means for daily minimum air temperature and mean daily potential evapotranspiration were calculated using a weighted mean value of the underlying grids within the county.
Methodology_Citation:
Citation_Information:
Originator: Daly, Christopher
Originator: Gibson, Wayne P.
Originator: Taylor, George H.
Originator: Johnson, Gregory L.
Originator: Pasteris, Phillip
Publication_Date: 2002
Title:
A knowledge-based approach to the statistical mapping of climate
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Climate Research
Issue_Identification: 22: 99-113
Online_Linkage: https://doi.org/10.3354/cr022099
Methodology_Citation:
Citation_Information:
Originator: Hutchinson, Michael F.
Publication_Date: 2015
Title:
ANUSPLIN Software Version 4.4
Geospatial_Data_Presentation_Form: website including manual and software information
Other_Citation_Details:
Website last accessed July 15, 2015
Online_Linkage: https://fennerschool.anu.edu.au/research/products/anusplin-vrsn-44
Methodology_Citation:
Citation_Information:
Originator: Linacre, Edward T.
Publication_Date: 1977
Title:
A simple formula for estimating evaporation rates in various climates using temperature data alone
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Agricultural Meteorology
Issue_Identification: 18: 409-424
Online_Linkage: https://doi.org/10.1016/0002-1571(77)90007-3
Methodology_Citation:
Citation_Information:
Originator: McKenney, Daniel W.
Originator: Price, David T.
Originator: Papadapol, Pia
Originator: Siltanen, R. Martin
Originator: Lawrence, Kevin
Publication_Date: 2006
Title:
Customized spatial climate models for Canada
Geospatial_Data_Presentation_Form: document
Series_Information:
Series_Name: Frontline Technical Note
Issue_Identification: 107
Publication_Information:
Publication_Place: Canadian Forestry Service
Publisher: Great Lakes Forestry Centre, Sault Ste. Marie, ON
Online_Linkage: https://cfs.nrcan.gc.ca/publications?id=27373
Methodology_Citation:
Citation_Information:
Originator: Price, David T.
Originator: McKenney, Daniel W.
Originator: Papadopol, Pia
Originator: Logan, T.
Originator: Hutchinson, Michael F.
Publication_Date: 2004
Title:
High resolution future scenario climate data for North America
Geospatial_Data_Presentation_Form: conference proceedings
Series_Information:
Series_Name: American Meteorological Society Annual Meetings
Issue_Identification: August 2004
Publication_Information:
Publication_Place: Vancouver
Online_Linkage: https://ams.confex.com/ams/AFAPURBBIO/techprogram/paper_78202.htm
Methodology_Citation:
Citation_Information:
Originator: Gibson, Wayne
Originator: Daly, Christopher
Originator: Kittel, Tim
Originator: Nychka, Doug
Originator: Johns, Craig
Originator: Rosenbloom, Nan
Originator: McNab, Alan
Originator: Taylor, George
Publication_Date: 2002
Title:
Development of a 103-year high-resolution climate data set of the conterminous United States
Geospatial_Data_Presentation_Form: conference proceedings
Series_Information:
Series_Name: Proc., 13th AMS Conf. on Applied Climatology, Amer. Meteorological Soc., Portland, OR, May 13-16
Issue_Identification: 181-183
Other_Citation_Details:
Proceedings of the American Meteorological Society
Online_Linkage: https://ams.confex.com/ams/13ac10av/techprogram/programexpanded_99.htm
Methodology_Citation:
Citation_Information:
Originator: Price, David T.
Originator: McKenney, Daniel W.
Originator: Nalder, Ian A.
Originator: Hutchinson, Michael F.
Originator: Kestevan, Jennifer L.
Publication_Date: 2000
Title:
A comparison of statistical and thin-plate spline methods for spatial interpolation of Canadian monthly mean climate data
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Agricultural and Forest Meteorology
Issue_Identification: 101: 81-94
Online_Linkage: https://doi.org/10.1016/S0168-1923(99)00169-0
Source_Information:
Source_Citation:
Citation_Information:
Originator: Christopher Daly (PRISM Group director)
Publication_Date: Unpublished material
Title:
Parameter-elevation Regressions on Independent Slopes Model climate mapping system
Geospatial_Data_Presentation_Form: tabular digital data
Online_Linkage: https://prism.oregonstate.edu/
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1961
Ending_Date: 1990
Source_Currentness_Reference:
observed
Source_Citation_Abbreviation:
PRISM
Source_Contribution:
Originally, files were obtained from: //prism.oregonstate.edu/docs/meta/ppt_103yr.htm and https://prism.oregonstate.edu/docs/meta/temp_103yr.htm. However, these URLs are no longer valid.

Both of these files were printed to PDF on 6/9/2010 and included in this data publication as: \Documents\Metadata_103yr_HiRes_PPTData_for_US.pdf and \Documents\Metadata_103yr_HiRes_TempData_for_US.pdf.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Robert J. Huggett, Jr.
Publication_Date: Unpublished material
Title:
Conterminous US as defined by ARC shape file fia_survey_unit
Geospatial_Data_Presentation_Form: Shapefile Feature Class
Publication_Information:
Publication_Place: PO Box 12254 (mail), 3041 Cornwallis Road (deliveries), Research Triangle Park, NC 27709
Publisher: USFS FIA
Other_Citation_Details:
Tel.: 919-549-4025, Fax: 919-549-4047, e-mail: rhuggett@fs.fed.us
Type_of_Source_Media: DVD
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: Unknown
Ending_Date: Unknown
Source_Currentness_Reference:
observed
Source_Citation_Abbreviation:
Huggett
Source_Contribution:
Data Type: Shapefile Feature Class
Shapefile: fia_survey_unit.shp
Geometry Type: Polygon

Projected Coordinate System: North_America_Albers_Equal_Area_Conic
Projection: Albers
False_Easting: 0.00000000
False_Northing: 0.00000000
Central_Meridian: -96.00000000
Standard_Parallel_1: 20.00000000
Standard_Parallel_2: 60.00000000
Latitude_Of_Origin: 40.00000000
Linear Unit: Meter

Geographic Coordinate System: GCS_North_American_1983
Datum: D_North_American_1983
Prime Meridian: Greenwich
Angular Unit: Degree

Left -178,217598 degrees
Top 71.406235
Right: -66.969271
Bottom: 18.929271
Process_Step:
Process_Description:
No process steps have been described for this data set
Process_Date: Unknown
Back to Top
Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:
Each comma-delimited ASCII text file contains the following variables:

FIPS = State-County Federal Identification Code (https://www.census.gov/geo/reference/codes/cou.html)

year = 2001 to 2100

month = values from 1 through 12 represent January through December respectively

ppt_mm = Total monthly precipitation (millimeters)

tmin_C = Monthly averages of daily minimum temperature (degrees Celsius)

tmax_C = Monthly averages of daily maximum temperature (degrees Celsius)

avg_elev_m = Average elevation (meters)

pet_veg_mm = Monthly averages of daily potential evapotranspiration (PET) (millimeters)
Entity_and_Attribute_Detail_Citation:
none provided
Back to Top
Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Research and Development
Contact_Position: Research Data Archivist
Contact_Address:
Address_Type: mailing and physical
Address: 240 West Prospect Road
City: Fort Collins
State_or_Province: CO
Postal_Code: 80526
Country: USA
Contact_Voice_Telephone: See Contact Information
Contact Instructions: This contact information was current as of October 2022. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Resource_Description: RDS-2010-0008
Distribution_Liability:
Metadata documents have been reviewed for accuracy and completeness. Unless otherwise stated, all data and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. However, neither the author, the Archive, nor any part of the federal government can assure the reliability or suitability of these data for a particular purpose. The act of distribution shall not constitute any such warranty, and no responsibility is assumed for a user's application of these data or related materials.

The metadata, data, or related materials may be updated without notification. If a user believes errors are present in the metadata, data or related materials, please use the information in (1) Identification Information: Point of Contact, (2) Metadata Reference: Metadata Contact, or (3) Distribution Information: Distributor to notify the author or the Archive of the issues.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: ASCII
Format_Version_Number: See Format Specification
Format_Specification:
Comma-delimited ASCII text file (CSV)
File_Decompression_Technique: Files were zipped using 7-Zip 19.0.
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2010-0008
Fees: none
Technical_Prerequisites:
Files are large and not all software packages can view these files. WordPad, which is typically available on a Windows PC, can be used to view these files.
Back to Top
Metadata_Reference_Information:
Metadata_Date: 20221027
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Linda Joyce
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station, Human Dimensions Program
Contact_Position: Quantitative Ecologist
Contact_Address:
Address_Type: mailing and physical
Address: 240 West Prospect
City: Fort Collins
State_or_Province: Colorado
Postal_Code: 80526
Contact_Voice_Telephone: 970-498-2560
Metadata_Standard_Name: FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001.1-1999
Back to Top