Velocity of climate change grids for North America

This dataset has been prepared f

The datasets on this page, representing velocity of climate change for North America, are based on Parameter Regression of Independent Slopes Model (PRISM) climate data from the historical normal period (see this page), and climate change projections of the Coupled Model Intercomparison Project phase 5 and 6 (CMIP5/CMIP6) database corresponding to the 5th and 6th IPCC Assessment Reports for future projections. The data has been prepared for AdaptWest, a project supported by the Wilburforce Foundation.

The velocity of climate change is an analytical concept that can be used to evaluate the exposure of organisms to climate change. As originally proposed, velocity is calculated by dividing the rate of climate change by the rate of spatial climate variability to obtain a speed at which species must migrate over the surface of the earth to maintain constant climate conditions. Here, we provide data from an improved algorithm that conforms to standard velocity calculations if climate equivalents are nearby. Otherwise, the algorithm extends the search for climate refugia globally. Below we provide velocity surfaces for a multivariate PCA implementation that searches for climate matches based on the first 2 axes derived from a PCA of 11 biologically relevant climate variables1.

The improved algorithm also distinguishes forward and backward velocities, allowing useful inferences about conservation of species (present-to-future velocities) and management of sites (future-to-present velocities). For the forward calculation we ask: what is the rate at which an organism in the current landscape has to migrate to maintain constant climate conditions? Conversely, in the backward calculation we ask: given the projected future climate habitat of a grid cell, what is the minimum rate of migration for an organism from equivalent climate conditions to colonize this climate habitat? 

Citations for the CMIP6-based velocity data are:

Carroll, C. (2023). Velocity of climate change for North America based on CMIP6 GCMs [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10631707

Carroll C, & Mahony CR. 2024. Sources of uncertainty in estimation of climate velocity and their implications for ecological and conservation applications. Preprint available at https://osf.io/q6ryk

For background information on the methodology and previous analyses see the two papers below. The R script used to produce the data on this page, along with other details concerning the data, can be found in the readme file provided here.

Hamann, A., Roberts, D.R., Barber, Q.E., Carroll, C. and Nielsen, S.E. 2014. Velocity of climate change algorithms for guiding conservation and management. Global Change Biology 21:997�1004, February 2015, DOI: 10.1111/gcb.12736.
Algorithms from Hamman et al. 2014 for generating velocity surfaces
Download
Sample data for algorithms below
ASCII: ASCII format
Univariate, complete search, simplest algorithm
Word: ASCII format
Univariate, complete search, faster algorithm
Word: ASCII format
Univariate, kNN search, xy coordinates, fastest algorithm *
Word: ASCII format
Univariate, kNN search, smoothed grids
Word: ASCII format
Multivariate, kNN search, xy coordinates, fastest algorithm
Word: ASCII format
Multivariate, kNN search, smoothed grids
Word: ASCII format


Carroll, C. Lawler, J.J, Roberts, D.R., and Hamann, A.. 2015. Biotic and climatic velocity identify contrasting areas of vulnerability to climate change. PLOS ONE 10(10): e0140486.


Download links for gridded data (1km resolution)

The gridded climate layers downloadable below are in Lambert Azimuthal Equal Area projection, at 1km resolution, and covering North America.

Velocity rasters based on CMIP6 GCM

CMIP6 ensemble data are based on mean projections from 8 CMIP6 models that were chosen to represent the very likely range of Earth's equilibrium climate sensitivity per the most recent IPCC assessment. Velocity rasters generated from these 8 individual GCMs are also provided below. Additionally, velocity rasters developed from the UKESM1-0-LL model (not used in the ensemble) are provided as a representative of high-sensitivity models characteristic of the long tail of uncertainty in the upper limit of climate sensitivity

Values represent climate velocity in km/yr from the histroical normal period (here 1961-1990) and the relevant future multi-decadal period (2041-2070 or 2071-2100). Areas of no-analog (backward velocity) and disappearing (forward velocity) climates are shown as NODATA in the velocity rasters. Values showing the proportion of runs in which a cell was characterized as no-analog or disappearing are given in additional rasters. Typically, the two related rasters (velocity and disappearing climates) would be viewed and analyzed together. Further information is contained in the readme file provided here.

The data is provided as GeoTiff formats that can be imported into ArcGIS or other GIS applications.

Please cite the CMIP6 data below as:
AdaptWest Project. 2023. Gridded CMIP6-based climatic velocity data for North America at 1km resolution. Available at adaptwest.databasin.org.

Velocity rasters based on CMIP5 GCM

CMIP5 ensemble data are velocities based on mean 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). Projections from 8 of these 15 GCMs were also used to generate velocities based on individual GCM projections.

Values represent climate velocity in km/yr from the histroical normal period (here 1981-2010) and the relevant future multi-decadal period (2041-2070 or 2071-2100). Areas of no-analog (backward velocity) and disappearing (forward velocity) climates are shown as NODATA in the velocity rasters. Values showing the proportion of runs in which a cell was characterized as no-analog or disappearing are given in additional rasters. Typically, the two related rasters (velocity and disappearing climates) would be viewed and analyzed together. Further information is contained in the readme file provided here.

The data is provided in several formats: 1) for ensemble-based velocites only, via a link to the DataBasin page from which an ArcGis layer file can be downloaded, and 2) for all velocities, via a link to a zipfile containing either ASCII (.asc) or TIFF (.tif) format files that can be imported into ArcGIS or other GIS applications. The DataBasin link also allows one to open the associated dataset in a map window on DataBasin.

CMIP5 velocity 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 cite the CMIP5 data below as:
AdaptWest Project. 2015. Gridded climatic velocity data for North America at 1km resolution. Available at adaptwest.databasin.org.

For gridded velocity data for western North America based on CMIP3 projections, see this page .

Velocity based on CMIP6 GCM
Archive of GeoTIFF files
Readme ASCII format
Ensemble of 8 GCM based on Mahony et al. (2022)
ASCII format
ACCESS-ESM1-5
ASCII format
CNRM-ESM2-1
ASCII format
EC-Earth3
ASCII format
GFDL-ESM4
ASCII format
GISS-E2-1-G
ASCII format
MIROC6
ASCII format
MPI-ESM1-2-HR ASCII format
MRI-ESM2-0 ASCII format
UKESM1-0-LL ASCII format


Velocity based on CMIP5 15-GCM ensemble (listed by type of velocity of climate change calculation)
Emission scenario2
Future period3
DataBasin Record
Zipped ASCII files
Zipped TIFF files
Multivariate, Forward (present to future)
RCP4.5 2050s ASCII format ASCII format ASCII format
Multivariate, Forward (present to future)
RCP4.5 2080s ASCII format ASCII format ASCII format
Multivariate, Forward (present to future)
RCP8.5 2050s ASCII format ASCII format ASCII format
Multivariate, Forward (present to future)
RCP8.5 2080s ASCII format ASCII format ASCII format
Multivariate, Backward (future to present)
RCP4.5 2050s ASCII format ASCII format ASCII format
Multivariate, Backward (future to present)
RCP4.5 2080s ASCII format ASCII format ASCII format
Multivariate, Backward (future to present)
RCP8.5 2050s ASCII format ASCII format ASCII format
Multivariate, Backward (future to present)
RCP8.5 2080s ASCII format ASCII format ASCII format
All ensemble-based rasters ASCII format ASCII format

Velocity based on individual CMIP5 GCM
Zipped ASCII files
Zipped TIFF files
CanESM2
ASCII format ASCII format
CCSM4
ASCII format ASCII format
CNRM-CM5
ASCII format ASCII format
GFDL-CM3
ASCII format ASCII format
INM-CM4
ASCII format ASCII format
IPSL-CM5A-MR
ASCII format ASCII format
MPI-ESM-LR ASCII format ASCII format


1) Bioclimatic variables used in PCA:

MAT: mean annual temperature (C)
MWMT: mean temperature of the warmest month (C)
MCMT: mean temperature of the coldest month (C)
TD: difference between MCMT and MWMT, as a measure of continentality (C)
MAP: mean annual precipitation (mm)
MSP: mean summer (May to Sep) precipitation (mm)
MWP: mean winter (Oct to Apr) precipitation (mm)
DD5: degree-days above 5C (growing degree days)
NFFD: the number of frost-free days
Eref: Hargreave's reference evaporation
CMD: Hargreave's climatic moisture index.

2) RCP4.5: moderate emission scenario, RCP8.5: high emission scenario.

3) 2050s: 2041-2070, 2080s: 2071-2100.