D. Stralberg, S. M. Matsuoka, A. Hamann, E. M. Bayne, P. Sólymos, F. K. A. Schmiegelow, X. Wang, S. G. Cumming, and S. J. Song. 2015. Projecting boreal bird responses to climate change: the signal exceeds the noise. Ecological Applications 25:52–69. http://dx.doi.org/10.1890/13-2289.1


Supplement

Current and projected climate data for North America.
Ecological Archives A025-005-S1.

Copyright


Authors
File list (downloads)
Description


Author(s)

Diana Stralberg
University of Alberta
Department of Biological Sciences
CW 405, Biological Sciences Building
Edmonton, Alberta T6G 2E9 Canada
E-mail: stralber@ualberta.ca

Andreas Hamann
University of Alberta
Department of Renewable Resources
751 General Services Building
Edmonton, Alberta T6G 2H1 Canada
E-mail: andreas.hamann@ualberta.ca

Xianli Wang
University of Alberta
Department of Renewable Resources
751 General Services Building
Edmonton, Alberta T6G 2H1 Canada
E-mail: xianli@ualberta.ca


File list

ALL files at once:

NORM_6190_bioclimatic_ascii.zip (MD5: fe16a75825182e3dea1a2757e6a2baff)


bccr_bcm2_0_A2_2020s_bioclim_ascii.zip

bccr_bcm2_0_A2_2050s_bioclim_ascii.zip

bccr_bcm2_0_A2_2080s_bioclim_ascii.zip

cccma_cgcm3_1_A2_2020s_bioclim_ascii.zip

cccma_cgcm3_1_A2_2050s_bioclim_ascii.zip

cccma_cgcm3_1_A2_2080s_bioclim_ascii.zip

cnrm_cm3_A2_2020s_bioclim_ascii.zip

cnrm_cm3_A2_2050s_bioclim_ascii.zip

cnrm_cm3_A2_2080s_bioclim_ascii.zip

csiro_mk3_0_A2_2020s_bioclim_ascii.zip

csiro_mk3_0_A2_2050s_bioclim_ascii.zip

csiro_mk3_0_A2_2080s_bioclim_ascii.zip

csiro_mk3_5_A2_2020s_bioclim_ascii.zip

csiro_mk3_5_A2_2050s_bioclim_ascii.zip

csiro_mk3_5_A2_2080s_bioclim_ascii.zip

ENSEMBLE_A2_2020s_bioclim_ascii.zip

ENSEMBLE_A2_2050s_bioclim_ascii.zip

ENSEMBLE_A2_2080s_bioclim_ascii.zip

gfdl_cm2_0_A2_2020s_bioclim_ascii.zip

gfdl_cm2_0_A2_2050s_bioclim_ascii.zip

gfdl_cm2_0_A2_2080s_bioclim_ascii.zip

gfdl_cm2_1_A2_2020s_bioclim_ascii.zip

gfdl_cm2_1_A2_2050s_bioclim_ascii.zip

gfdl_cm2_1_A2_2080s_bioclim_ascii.zip

giss_model_e_r_A2_2020s_bioclim_ascii.zip

giss_model_e_r_A2_2050s_bioclim_ascii.zip

giss_model_e_r_A2_2080s_bioclim_ascii.zip

ingv_echam4_A2_2020s_bioclim_ascii.zip

ingv_echam4_A2_2050s_bioclim_ascii.zip

ingv_echam4_A2_2080s_bioclim_ascii.zip

inmcm3_0_A2_2020s_bioclim_ascii.zip

inmcm3_0_A2_2050s_bioclim_ascii.zip

inmcm3_0_A2_2080s_bioclim_ascii.zip

ipsl_cm4_A2_2020s_bioclim_ascii.zip

ipsl_cm4_A2_2050s_bioclim_ascii.zip

ipsl_cm4_A2_2080s_bioclim_ascii.zip

miroc3_2_medres_A2_2020s_bioclim_ascii.zip

miroc3_2_medres_A2_2050s_bioclim_ascii.zip

miroc3_2_medres_A2_2080s_bioclim_ascii.zip

miub_echo_g_A2_2020s_bioclim_ascii.zip

miub_echo_g_A2_2050s_bioclim_ascii.zip

miub_echo_g_A2_2080s_bioclim_ascii.zip

mpi_echam5_A2_2020s_bioclim_ascii.zip

mpi_echam5_A2_2050s_bioclim_ascii.zip

mpi_echam5_A2_2080s_bioclim_ascii.zip

mri_cgcm2_3_2a_A2_2020s_bioclim_ascii.zip

mri_cgcm2_3_2a_A2_2050s_bioclim_ascii.zip

mri_cgcm2_3_2a_A2_2080s_bioclim_ascii.zip

ncar_ccsm3_0_A2_2020s_bioclim_ascii.zip

ncar_ccsm3_0_A2_2050s_bioclim_ascii.zip

ncar_ccsm3_0_A2_2080s_bioclim_ascii.zip

ncar_pcm1_A2_2020s_bioclim_ascii.zip

ncar_pcm1_A2_2050s_bioclim_ascii.zip

ncar_pcm1_A2_2080s_bioclim_ascii.zip

ukmo_hadcm3_A2_2020s_bioclim_ascii.zip

ukmo_hadcm3_A2_2050s_bioclim_ascii.zip

ukmo_hadcm3_A2_2080s_bioclim_ascii.zip

ukmo_hadgem1_A2_2020s_bioclim_ascii.zip

ukmo_hadgem1_A2_2050s_bioclim_ascii.zip

ukmo_hadgem1_A2_2080s_bioclim_ascii.zip 

bccr_bcm2_0_A1B_2020s_bioclim_ascii.zip

bccr_bcm2_0_A1B_2050s_bioclim_ascii.zip

bccr_bcm2_0_A1B_2080s_bioclim_ascii.zip

cccma_cgcm3_1_A1B_2020s_bioclim_ascii.zip

cccma_cgcm3_1_A1B_2050s_bioclim_ascii.zip

cccma_cgcm3_1_A1B_2080s_bioclim_ascii.zip

cccma_cgcm3_1_t63_A1B_2020s_bioclim_ascii.zip

cccma_cgcm3_1_t63_A1B_2050s_bioclim_ascii.zip

cccma_cgcm3_1_t63_A1B_2080s_bioclim_ascii.zip

cnrm_cm3_A1B_2020s_bioclim_ascii.zip

cnrm_cm3_A1B_2050s_bioclim_ascii.zip

cnrm_cm3_A1B_2080s_bioclim_ascii.zip

csiro_mk3_0_A1B_2020s_bioclim_ascii.zip

csiro_mk3_0_A1B_2050s_bioclim_ascii.zip

csiro_mk3_0_A1B_2080s_bioclim_ascii.zip

csiro_mk3_5_A1B_2020s_bioclim_ascii.zip

csiro_mk3_5_A1B_2050s_bioclim_ascii.zip

csiro_mk3_5_A1B_2080s_bioclim_ascii.zip

ENSEMBLE_A1B_2020s_bioclim_ascii.zip

ENSEMBLE_A1B_2050s_bioclim_ascii.zip

ENSEMBLE_A1B_2080s_bioclim_ascii.zip

gfdl_cm2_0_A1B_2020s_bioclim_ascii.zip

gfdl_cm2_0_A1B_2050s_bioclim_ascii.zip

gfdl_cm2_0_A1B_2080s_bioclim_ascii.zip

gfdl_cm2_1_A1B_2020s_bioclim_ascii.zip

gfdl_cm2_1_A1B_2050s_bioclim_ascii.zip

gfdl_cm2_1_A1B_2080s_bioclim_ascii.zip

giss_aom_A1B_2020s_bioclim_ascii.zip

giss_aom_A1B_2050s_bioclim_ascii.zip

giss_aom_A1B_2080s_bioclim_ascii.zip

giss_model_e_h_A1B_2020s_bioclim_ascii.zip

giss_model_e_h_A1B_2050s_bioclim_ascii.zip

giss_model_e_h_A1B_2080s_bioclim_ascii.zip

giss_model_e_r_A1B_2020s_bioclim_ascii.zip

giss_model_e_r_A1B_2050s_bioclim_ascii.zip

giss_model_e_r_A1B_2080s_bioclim_ascii.zip

iap_fgoals1_0_g_A1B_2020s_bioclim_ascii.zip

iap_fgoals1_0_g_A1B_2050s_bioclim_ascii.zip

iap_fgoals1_0_g_A1B_2080s_bioclim_ascii.zip

ingv_echam4_A1B_2020s_bioclim_ascii.zip

ingv_echam4_A1B_2050s_bioclim_ascii.zip

ingv_echam4_A1B_2080s_bioclim_ascii.zip

inmcm3_0_A1B_2020s_bioclim_ascii.zip

inmcm3_0_A1B_2050s_bioclim_ascii.zip

inmcm3_0_A1B_2080s_bioclim_ascii.zip

ipsl_cm4_A1B_2020s_bioclim_ascii.zip

ipsl_cm4_A1B_2050s_bioclim_ascii.zip

ipsl_cm4_A1B_2080s_bioclim_ascii.zip

miroc3_2_hires_A1B_2020s_bioclim_ascii.zip

miroc3_2_hires_A1B_2050s_bioclim_ascii.zip

miroc3_2_hires_A1B_2080s_bioclim_ascii.zip

miroc3_2_medres_A1B_2020s_bioclim_ascii.zip

miroc3_2_medres_A1B_2050s_bioclim_ascii.zip

miroc3_2_medres_A1B_2080s_bioclim_ascii.zip

miub_echo_g_A1B_2020s_bioclim_ascii.zip

miub_echo_g_A1B_2050s_bioclim_ascii.zip

miub_echo_g_A1B_2080s_bioclim_ascii.zip

mpi_echam5_A1B_2020s_bioclim_ascii.zip

mpi_echam5_A1B_2050s_bioclim_ascii.zip

mpi_echam5_A1B_2080s_bioclim_ascii.zip

mri_cgcm2_3_2a_A1B_2020s_bioclim_ascii.zip

mri_cgcm2_3_2a_A1B_2050s_bioclim_ascii.zip

mri_cgcm2_3_2a_A1B_2080s_bioclim_ascii.zip

ncar_ccsm3_0_A1B_2020s_bioclim_ascii.zip

ncar_ccsm3_0_A1B_2050s_bioclim_ascii.zip

ncar_ccsm3_0_A1B_2080s_bioclim_ascii.zip

ncar_pcm1_A1B_2020s_bioclim_ascii.zip

ncar_pcm1_A1B_2050s_bioclim_ascii.zip

ncar_pcm1_A1B_2080s_bioclim_ascii.zip

ukmo_hadcm3_A1B_2020s_bioclim_ascii.zip

ukmo_hadcm3_A1B_2050s_bioclim_ascii.zip

ukmo_hadcm3_A1B_2080s_bioclim_ascii.zip

ukmo_hadgem1_A1B_2020s_bioclim_ascii.zip

ukmo_hadgem1_A1B_2050s_bioclim_ascii.zip

ukmo_hadgem1_A1B_2080s_bioclim_ascii.zip

bccr_bcm2_0_B1_2020s_bioclim_ascii.zip

bccr_bcm2_0_B1_2050s_bioclim_ascii.zip

bccr_bcm2_0_B1_2080s_bioclim_ascii.zip

cccma_cgcm3_1_B1_2020s_bioclim_ascii.zip

cccma_cgcm3_1_B1_2050s_bioclim_ascii.zip

cccma_cgcm3_1_B1_2080s_bioclim_ascii.zip

cccma_cgcm3_1_t63_B1_2020s_bioclim_ascii.zip

cccma_cgcm3_1_t63_B1_2050s_bioclim_ascii.zip

cccma_cgcm3_1_t63_B1_2080s_bioclim_ascii.zip

cnrm_cm3_B1_2020s_bioclim_ascii.zip

cnrm_cm3_B1_2050s_bioclim_ascii.zip

cnrm_cm3_B1_2080s_bioclim_ascii.zip

csiro_mk3_5_B1_2020s_bioclim_ascii.zip

csiro_mk3_5_B1_2050s_bioclim_ascii.zip

csiro_mk3_5_B1_2080s_bioclim_ascii.zip

ENSEMBLE_B1_2020s_bioclim_ascii.zip

ENSEMBLE_B1_2050s_bioclim_ascii.zip

ENSEMBLE_B1_2080s_bioclim_ascii.zip

gfdl_cm2_0_B1_2020s_bioclim_ascii.zip

gfdl_cm2_0_B1_2050s_bioclim_ascii.zip

gfdl_cm2_0_B1_2080s_bioclim_ascii.zip

gfdl_cm2_1_B1_2020s_bioclim_ascii.zip

gfdl_cm2_1_B1_2050s_bioclim_ascii.zip

gfdl_cm2_1_B1_2080s_bioclim_ascii.zip

giss_aom_B1_2020s_bioclim_ascii.zip

giss_aom_B1_2050s_bioclim_ascii.zip

giss_aom_B1_2080s_bioclim_ascii.zip

giss_model_e_r_B1_2020s_bioclim_ascii.zip

giss_model_e_r_B1_2050s_bioclim_ascii.zip

giss_model_e_r_B1_2080s_bioclim_ascii.zip

iap_fgoals1_0_g_B1_2020s_bioclim_ascii.zip

iap_fgoals1_0_g_B1_2050s_bioclim_ascii.zip

iap_fgoals1_0_g_B1_2080s_bioclim_ascii.zip

inmcm3_0_B1_2020s_bioclim_ascii.zip

inmcm3_0_B1_2050s_bioclim_ascii.zip

inmcm3_0_B1_2080s_bioclim_ascii.zip

ipsl_cm4_B1_2020s_bioclim_ascii.zip

ipsl_cm4_B1_2050s_bioclim_ascii.zip

ipsl_cm4_B1_2080s_bioclim_ascii.zip

miroc3_2_hires_B1_2020s_bioclim_ascii.zip

miroc3_2_hires_B1_2050s_bioclim_ascii.zip

miroc3_2_hires_B1_2080s_bioclim_ascii.zip

miroc3_2_medres_B1_2020s_bioclim_ascii.zip

miroc3_2_medres_B1_2050s_bioclim_ascii.zip

miroc3_2_medres_B1_2080s_bioclim_ascii.zip

miub_echo_g_B1_2020s_bioclim_ascii.zip

miub_echo_g_B1_2050s_bioclim_ascii.zip

miub_echo_g_B1_2080s_bioclim_ascii.zip

mpi_echam5_B1_2020s_bioclim_ascii.zip

mpi_echam5_B1_2050s_bioclim_ascii.zip

mpi_echam5_B1_2080s_bioclim_ascii.zip

mri_cgcm2_3_2a_B1_2020s_bioclim_ascii.zip

mri_cgcm2_3_2a_B1_2050s_bioclim_ascii.zip

mri_cgcm2_3_2a_B1_2080s_bioclim_ascii.zip

ncar_ccsm3_0_B1_2020s_bioclim_ascii.zip

ncar_ccsm3_0_B1_2050s_bioclim_ascii.zip

ncar_ccsm3_0_B1_2080s_bioclim_ascii.zip

ncar_pcm1_B1_2020s_bioclim_ascii.zip

ncar_pcm1_B1_2050s_bioclim_ascii.zip

ncar_pcm1_B1_2080s_bioclim_ascii.zip

ukmo_hadcm3_B1_2020s_bioclim_ascii.zip

ukmo_hadcm3_B1_2050s_bioclim_ascii.zip

ukmo_hadcm3_B1_2080s_bioclim_ascii.zip

Description

Gridded climate layers are in Lambert Conformal Conic projection, covering all of North America. The database is based on a 1-km digital elevation model, but sub-sampled at 4 km vertical and horizontal intervals for a manageable database size. This preserves the full range of climate values (as opposed to a 4-km average), and captures elevationalgradients, temperature inversions, and rain shadows in the mountainous landscape of western North America.

General circulation model (GCM) projections were obtained from the Intergovernmental Panel on Climate Change 4th Assessment Report as part of the World Climate Research Programme's Coupled Model Intercomparison Project phase 3 multi-model data set. Future projections were taken from three emissions scenarios--SRESA2 (high), SRESA1B (intermediate), and SRESB2 (low)--run from 2000 or 2001 through at least 2099 or 2100. Monthly temperature (mean + minimum and maximum if available) and total precipitation projections were averaged across multiple model runs (if available) for the following thirty year periods: 1961–1990 (baseline), 2011–2040, 2041–2070, and 2071–2100. A total of 24 GCM simulations were used, 17 of which were run for all three future scenarios. Grid cell resolution ranged from 1.125° to 5°. Temperature values were converted to degrees Celsius and precipitation values were converted to mm/day. Future climate normals (30-year averages) were compared with GCM-projected baseline normals to generate anomalies for each future time period and emissions scenario. Precipitation anomalies were capped at 500%. Anomalies were then clipped to North America and downscaled to a 0.5-degree resolution using a thin-plate spline interpolation. Downscaled anomalies were added to 4-km baseline data for North America based on the Parameter-elevation Regressions on Independent Slopes Model (PRISM) for the 1961–1990 normal period. For the majority of GCMs that did not have future projections for minimum and maximum temperature (17 of 24), average temperature anomalies were used in place of minimum/maximum temperature anomalies to calculate future minimum/maximum temperature projections. Mean monthly projections for each time period where then converted to a set of 20 derived bioclimatic variables, defined below.

Variable definitions:

MAT: mean annual temperature (°C)
MCMT: mean temperature of the coldest month (°C)
MWMT: mean temperature of the warmest 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)
DD0: degree-days below 0°C (chilling degree days)
DD5: degree-days above 5°C (growing degree days)
NFFD: the number of frost-free days
FFP: length of the frost-free period
PAS: precipitation as snow (mm)
EMT: extreme minimum temperature over 30 years
PETpm: Potential Evapotranspiration (Hogg 1997 modified Penmnan-Monteith method)
CMDpm: Climatic moisture deficit (Hogg 1997 modified Penmnan-Monteith method)
CMIpm: Climatic moisture index (Hogg 1997 modified Penmnan-Monteith method)
CMIJJApm: Summer (Jun to Aug) climate moisture index(Hogg 1997 modified Penmnan-Monteith method)
Tave_wt: winter (Dec to Feb) mean temperature (°C)
Tave_sm: summer (Jun to Aug) mean temperature (°C)
PPT_wt: winter (Dec to Feb) precipitation (mm)
PPT_sm: summer (Jun to Aug) precipitation (mm)

List of GCMs:

INGV-ECHAM4, Italy/Germany

CCSM3, USA

ECHAM5/MPI-OM, Germany

UKMO-HadGEM1, UK

CSIRO-Mk3.5, Australia

UKMO-HadCM3, UK

ECHO-G, Germany/Korea

MIROC3.2(hires), Japan

GFDL-CM2.1, USA

CSIRO-Mk3.0, Australia

GFDL-CM2.0, USA

MIROC3.2(medres), Japan

CGCM3.1(T47), Canada

CGCM3.1(T63), Canada

MRI-CGCM2.3.2, Japan

CNRM-CM3, France

PCM, USA

IPSL-CM4, France

INM-CM3.0, Russia

FGOALS-g1.0, China

BCCR-BCM2.0, Norway

GISS-ER, USA

GISS-EH, USA

GISS-AOM, USA