Current and projected climate data for North America (CMIP5 scenarios)

ClimateNA - Current and projected climate data for North America
The datasets on this page have been developed by AdaptWest, a project funded by the Wilburforce Foundation to develop information resources for climate adaptation planning. The data are based on the Parameter Regression of Independent Slopes Model (PRISM) interpolation method for current climate, and the Coupled Model Intercomparison Project phase 5 (CMIP5) database corresponding to the 5th IPCC Assessment Report for future projections. Ensemble projections are average projections from 15 CMIP5 models (CanESM2, ACCESS1.0, IPSL-CM5A-MR, MIROC5, MPI-ESM-LR, CCSM4, HadGEM2-ES, CNRM-CM5, CSIRO Mk 3.6, GFDL-CM3, INM-CM4, MRI-CGCM3, MIROC-ESM, CESM1-CAM5, GISS-E2R) that were chosen to represent all major clusters of similar AOGCMs (Knutti et al 2013, Geophys Res Let 40: 1–6, doi:10.1002/grl.50256). In addition to the ensemble projections, data are also provided from 8 individual AOGCMs which are representative of the larger ensemble and had high validation statistics in their CMIP3 equivalents.

Please cite the datasets below as:

AdaptWest Project. 2015. Gridded current and projected climate data for North America at 1km resolution, interpolated using the ClimateNA v5.10 software (T. Wang et al., 2015). Available at adaptwest.databasin.org.

For interpolated data produced using the older CMIP3 projections, see this link.

As an alternative to accessing interpolated climate data in gridded data formats from the table below, there is also a software solution (ClimateNA v5.10) to query climate data for a series of sample points of interest. Scroll to bottom of linked page to find software developed by Tongli Wang et al. which covers North America and includes climate normals and AR5/CMIP5 future scenarios. Download, unzip, and double click the executable file ClimateNA.exe. The programs should run on Windows 9x/NT/2000/XP/Vista/7/8 without an installation on most systems. If it doesn't work, you have to install these library files from Ascentive. The programs also runs on Linux, Unix and Mac systems with the free software Wine or MacPorts/Wine.

For further information and citation refer to:

Click on the thumbnails below to see high resolution images of mean annual temperature (MAT), mean winter temperature with inversions in northern mountain valleys (MWT), and mean annual preciptiation with leeward rainshadows (MAP).

MAT TaveDJF MAP


Data coverage and variables

The gridded climate layers downloadable below are in Lambert Conformal Conic projection, at 1km resolution, and covering North America. The database consists of 23 million grid cells and is designed to capture climate gradients, temperature inversions, and rain shadows in the landscape of North America.

There are two data formats available. ASCII (.asc) files can be transformed into ESRI grids, a native format of ArcGIS software, but are also compatible with many other GIS applications. NetCDF (.nc) files, a non-proprietary format, are compatible with most GIS applications.

Two sets of variables are available for download. One consists of 27 biologically relevant variables, including seasonal and annual means, extremes, growing and chilling degree days, snow fall, potential evapotranspiration, and a number of drought indices. The second dataset consists of 48 monthly temperature and precipitation variables.

All archives have been compressed with the 7-zip utilty. To extract the data, use the 7-zip software, which is freely available for Windows (link) as well as Mac and Linux systems (link). Use of 7-zip in place of the standard zip format allows better compression, lower storage costs, and shorter download times. 

(Please note that there is a typo (an extra hyphen) in the proj4string for the NetCDF files. The value "lon_0=--95.0" should be changed to "lon_0=-95.0").

Model selection

Selecting scenarios for climate change impact and adaptation research is a complex task. We selected eight individual models to represent all major clusters of similar AOGCMs (Knutti et al 2013) with high validation statistics. To further whittle the number of AOGCMs under consideration down, researchers often select "worst case", "best case", and "median" climate change projections. However, what constitutes a worst case or best case scenario, differs by region and by the climate variable of interest. The table below may help with scenario selection for states and provinces within western North America. We also provide ensemble scenarios for download above, but they may have unrealistic combinations of individual climate variables.

Mean annual temperature change for states and provinces of North America projected for the 2050s under the RCP4.5 scenario.

States and provinces are alphabetically sorted from left to right, AOGCMs are sorted by magnitude of projection for North America from top to bottom. MAT Selection

Mean annual precipitation change for states and provinces of North America projected for the 2050s under the RCP4.5 scenario.

States and provinces are alphabetically sorted from left to right, AOGCMs are sorted by magnitude of projection for North America from top to bottom. MAP Selection


Download links for climate data (1km resolution)

Reference files: Elevation, ID
Meta data: Projection, Variables
netCDF ASCII Readme ESRI

Climate normals
27 Bioclimatic variables 48 Monthly variables
1961-1990 period
netCDF ASCII netCDF ASCII
1981-2010 period
netCDF ASCII netCDF ASCII





Projection
Emission scenario2
Future period3
27 Bioclimatic variables
48 Monthly variables
AOGCM ensemble projections



Ensemble of 15 CMIP5 AOGCMs1
RCP4.5
2020s netCDF ASCII netCDF ASCII

RCP4.5
2050s netCDF ASCII netCDF ASCII

RCP4.5
2080s netCDF ASCII netCDF ASCII

RCP8.5
2020s netCDF ASCII netCDF ASCII

RCP8.5
2050s netCDF ASCII netCDF ASCII

RCP8.5
2080s netCDF ASCII netCDF ASCII
Projections from individual AOGCMs



CCSM4
RCP4.5 2020s
netCDF ASCII netCDF ASCII

RCP4.5
2050s netCDF ASCII netCDF ASCII

RCP4.5 2080s netCDF ASCII netCDF ASCII

RCP8.5 2020s netCDF ASCII netCDF ASCII

RCP8.5 2050s netCDF ASCII netCDF ASCII

RCP8.5 2080s netCDF ASCII netCDF ASCII





CNRM-CM5
RCP4.5 2020s netCDF ASCII netCDF ASCII

RCP4.5 2050s netCDF ASCII netCDF ASCII

RCP4.5 2080s netCDF ASCII netCDF ASCII

RCP8.5 2020s netCDF ASCII netCDF ASCII

RCP8.5 2050s netCDF ASCII netCDF ASCII

RCP8.5 2080s netCDF ASCII netCDF ASCII





CanESM2
RCP4.5 2020s netCDF ASCII netCDF ASCII

RCP4.5 2050s netCDF ASCII netCDF ASCII

RCP4.5 2080s netCDF ASCII netCDF ASCII

RCP8.5 2020s netCDF ASCII netCDF ASCII

RCP8.5 2050s netCDF ASCII netCDF ASCII

RCP8.5 2080s netCDF ASCII netCDF ASCII





GFDL-CM3
RCP4.5 2020s netCDF ASCII netCDF ASCII

RCP4.5 2050s netCDF ASCII netCDF ASCII

RCP4.5 2080s netCDF ASCII netCDF ASCII

RCP8.5 2020s netCDF ASCII netCDF ASCII

RCP8.5 2050s netCDF ASCII netCDF ASCII

RCP8.5 2080s netCDF ASCII netCDF ASCII





HadGEM2-ES
RCP4.5 2020s netCDF ASCII netCDF ASCII

RCP4.5 2050s netCDF ASCII netCDF ASCII

RCP4.5 2080s netCDF ASCII netCDF ASCII

RCP8.5 2020s netCDF ASCII netCDF ASCII

RCP8.5 2050s netCDF ASCII netCDF ASCII

RCP8.5 2080s netCDF ASCII netCDF ASCII





INM-CM4
RCP4.5 2020s netCDF ASCII netCDF ASCII

RCP4.5 2050s netCDF ASCII netCDF ASCII

RCP4.5 2080s netCDF ASCII netCDF ASCII

RCP8.5 2020s netCDF ASCII netCDF ASCII

RCP8.5 2050s netCDF ASCII netCDF ASCII

RCP8.5 2080s netCDF ASCII netCDF ASCII





IPSL-CM5A-MR
RCP4.5 2020s netCDF ASCII netCDF ASCII

RCP4.5 2050s netCDF ASCII netCDF ASCII

RCP4.5 2080s netCDF ASCII netCDF ASCII

RCP8.5 2020s netCDF ASCII netCDF ASCII

RCP8.5 2050s netCDF ASCII netCDF ASCII

RCP8.5 2080s netCDF ASCII netCDF ASCII





MPI-ESM-LR
RCP4.5 2020s netCDF ASCII netCDF ASCII

RCP4.5 2050s netCDF ASCII netCDF ASCII

RCP4.5 2080s netCDF ASCII netCDF ASCII

RCP8.5 2020s netCDF ASCII netCDF ASCII

RCP8.5 2050s netCDF ASCII netCDF ASCII

RCP8.5 2080s netCDF ASCII netCDF ASCII

Footnotes:
1. The ensemble was composed of the following AOGCMs: ACCESS1-0,CCSM4,CESM1-CAM5,CNRM-CM5,CSIRO-Mk3-6-0,CanESM2,GFDL-CM3,GISS-E2R,HadGEM2-ES,INM-CM4,IPSL-CM5A-MR,MIROC-ESM,MIROC5,MPI-ESM-LR,MRI-CGCM3.
2. RCP4.5: low emissions scenario (
more info), RCP8.5: high emissions scenario (more info).
3. 2020s: average for years 2011-2040, 2050s: 2041-2070, 2080s: 2071-2100.