Present addresses: IMEP, Université Aix-Marseille 3, Europôle méditerranéen de l’Arbois, BP 80, 13545 Aix-en-Provence Cedex 04, France.
CliMond: global high-resolution historical and future scenario climate surfaces for bioclimatic modelling
Article first published online: 19 JUL 2011
© 2011 The Authors. Methods in Ecology and Evolution © 2011 British Ecological Society
Methods in Ecology and Evolution
Volume 3, Issue 1, pages 53–64, February 2012
How to Cite
Kriticos, D. J., Webber, B. L., Leriche, A., Ota, N., Macadam, I., Bathols, J. and Scott, J. K. (2012), CliMond: global high-resolution historical and future scenario climate surfaces for bioclimatic modelling. Methods in Ecology and Evolution, 3: 53–64. doi: 10.1111/j.2041-210X.2011.00134.x
Correspondence site: http://www.respond2articles.com/MEE/
- Issue published online: 1 FEB 2012
- Article first published online: 19 JUL 2011
- Received 20 February 2011; accepted 9 May 2011 Handling Editor: Andrew Tatem
- climate change;
- conservation biology;
- invasion ecology;
- niche model;
- pest risk assessment;
- species distribution model;
1. Gridded climatologies have become an indispensable component of bioclimatic modelling, with a range of applications spanning conservation and pest management. Such globally conformal data sets of historical and future scenario climate surfaces are required to model species potential ranges under current and future climate scenarios.
2. We developed a set of interpolated climate surfaces at 10′ and 30′ resolution for global land areas excluding Antarctica. Input data for the baseline climatology were gathered from the WorldClim and CRU CL1·0 and CL2·0 data sets. A set of future climate scenarios were generated at 10′ resolution. For each of the historical and future scenario data sets, the full set of 35 Bioclim variables was generated. Climate variables (including relative humidity at 0900 and 1500 hours) were also generated in CLIMEX format. The Köppen–Geiger climate classification scheme was applied to the 10′ hybrid climatology as a tool for visualizing climatic patterns and as an aid for specifying absence or background data for correlative modelling applications.
3. We tested the data set using a correlative model (MaxEnt) addressing conservation biology concerns for a rare Australian shrub, and a mechanistic niche model (CLIMEX) to map climate suitability for two invasive species. In all cases, the underlying climatology appeared to behave in a robust manner.
4. This global climate data set has the advantage over the WorldClim data set of including humidity data and an additional 16 Bioclim variables. Compared with the CRU CL2·0 data set, the hybrid 10′ data set includes improved precipitation estimates as well as projected climate for two global climate models running relevant greenhouse gas emission scenarios.
5. For many bioclimatic modelling purposes, there is an operational attraction to having a globally conformal historical climatology and future climate scenarios for the assessments of potential climate change impacts. Our data set is known as ‘CliMond’ and is available for free download from http://www.climond.org.