Climate data  |  Species range maps  |  Other data
Climate data for North America, Europe, Africa and South America

Following the links below, you can download grids of interpolated data 1km and 5km resolution for several continents, as well as software packages to query point locations. We provide historical climate normal periods, decadal averages, annual, seasonal and monthly data from 1901-present as well as multi-model CMIP6 climate projections for the 2020s, 2050s, 2080s on the pages below.

We also calculate a large number of derived variables of economic or biological relevance, such as drought indices, growing degree days, heating and cooling degree days, frost-free periods, etc. All together, more than 20,000 spatial coverages of climate variables can be downloaded and/or interactively queried for individual locations.

The methodological approaches used have shifted over time from thin-plate spines (Mexico & South America) to PRISM interpolations (North (America and Europe) to deep learning with neural networks (Africa). We are currently working on upgrading the South Amerca package to be based on interpolations with neural networks.

Climate data for North America

ClimateNA software & gridded data

Permanent link: http://tinyurl.com/ClimateNA
example

 Climate data for Europe

ClimateEU software & gridded data

Permanent link: http://tinyurl.com/ClimateEU
example
 Climate data for Africa

ClimateAF software & gridded data

Permanent link: http://tinyurl.com/ClimateAF
ClimateAF
Climate data for South America

ClimateSA software (under development)

Permanent link: http://tinyurl.com/ClimateSA
example		    


Depreciated datasets

Western North America     

ClimateWNA software and 1km resolution grids

Permanent link: http://tinyurl.com/ClimateWNA
example example

 Western North America - Velocity

Velocity of climate change grids at 1km resolution

Permanent link: http://tinyurl.com/VelocityWNA
example example

 Climate data for Alberta

ClimateAB software

Permanent link: http://tinyurl.com/ClimateAB
example

 
References
 

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Mahoney, C.R., Wang, T., Hamann, A., Cannon, A.J. 2022. A CMIP6 ensemble for downscaled monthly climate normals over North America. International Journal of Climatology 42: 5871-5891.
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Wang, T., Hamann, A. Spittlehouse, D.L. and Carroll, C. 2016. Locally downscaled and spatially customizable climate data for historical and future periods for North America. PLoS One 11: e0156720.
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Hamann, A. and Wang, T., Spittlehouse, D.L., and Murdock, T.Q. 2013. A comprehensive, high-resolution database of historical and projected climate surfaces for western North America. Bulletin of the American Meteorological Society 94: 1307–1309.
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Wang, T., Hamann, A., Spittlehouse, D.L. and Murdock, T.Q. 2012. ClimateWNA - High-resolution spatial climate data for western North America. Journal of Applied Meteorology and Climatology 51: 16-29.
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Mbogga, M. S., Hansen, C., Wang, T. and Hamann, A. 2010. A comprehensive set of interpolated climate data for Alberta. Government of Alberta, Publication Number: Ref. T/235. ISBN: 978-0-7785-9184-9 (on-line edition), 978-0-7785-9183-2 (print edition).
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Mbogga, M., Hamann, A. and T. L. Wang. 2009. Historical and projected climate data for natural resource management in western Canada. Agricultural and Forest Meteorology 149: 881-890.
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Wang, T., Hamann, A. Spittlehouse, D. L., and Aitken, S. N. 2006. Development of scale-free climate data for western Canada for use in resource management. International Journal of Climatology 26: 383-397. .
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Spittelhouse, D.L. 2006. ClimateBC: Your access to interpolated climate data for BC.Streamline Watershed Management Bulletin 9: 16-21.
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Hamann, A., and T. L. Wang. 2005. Models of climatic normals for genecology and climate change studies in British Columbia. Agricultural and Forest Meteorology 128: 211-221.
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Alberta Environment. 2005. Alberta Climate Model (ACM) to provide climate estimates (1961- 1990) for any location in Alberta from it geographic coordinates. Publ. No. T/749. Alberta Environment. 35 pp.

 
Software to query databases
 

The user can input latitude, longitude, and elevation (optional) to generate up to 50 monthly, seasonal, and annual climate variables, including various chilling and growing degree days, frost free period, snow fall, dryness indices, etc. In addition, the user can generate or query thousands of spatial data coverages for historical time periods and future predictions, through time scale and time period selection from hierarchical drop down lists. The multi-location processing function can be used to process spreadsheets of coordinates or digital elevation models.

interface

 
How it works
 

It is not practical to generate and distribute gridded climate data at very high resolution. A typical gridded GIS data set with 10,000 observations for British Columbia at the resolution of 10km would have 100 million observations at 100m resolution. Few users can handle such data sets, yet such accuracy is often needed for temperature related climate variables to determine, for example, the conditions of a sample site on a mountain slope in forestry research.

To solve this problem we use medium resolution climate data (2.5 arcmin or approximately 4km) and a software solution to build a local and temporary scale-free climate model on top. This model is mainly driven by the elevation difference between a location of interest and the elevation used to calculate the climate variables of the medium resolution data set at this point. GIS coverages of climate variables are generated from a high-resolution DEM in a two-step process: by elevation adjustments (left to middle) and by bilinear interpolation to remove tile artifacts (middle to right).

example