past GCMs Sup material PLOS ONE

These are text files with the information about the climatic conditions predicted by 9 General Circulation Models for the Last Glacial Maximum. see more at http://ecoclimate.org/ Data availability: The dataset includes simulations for modern (simulations for 1950-1999), historical (1900-1949), pre-industrial (~1760), Mid-Holocene (6ka), Last Glacial Maximum (21ka), and future conditions (mean of simulations for 2080-2100), for nine coupled atmosphere-ocean global climate models (AOGCMs). Future simulations include four representative concentration pathways (RCPs): RCP2.6 (low emissions scenarios), RCP4.5 and RCP6.0 (intermediate emissions scenarios), and RCP 8.5 (high emissions scenario) (see details in Taylor et al. 2009, 2012).Data downscaling and interpolation: Monthly simulations of precipitation and mean, maximum and minimum temperature for all time periods and AOGCMs were downloaded in NetCDF format from CMIP5 and PMIP3, with spatial resolution originally ranging between 0.9o (e.g., CCSM4) to 2.8o (e.g., MIROC-ESM). All data were downscaled to 0.5o x 0.5o resolution, according to the standard change-factor approach (Wilby et al. 2004), namely: i) firstly we computed the change-factor (also called climate change trends or anomalies) between past/future and baseline climate for each raw variable at model-specific native spatial resolution, (ii) secondarily we downscaled the change-factor (instead of past/future climate values) and its respective baseline climate from each AOGCM to the standard 0.5o resolution, and (iii) thirdly applied the downscaled change-factor to the downscaled baseline climate to reconstitute values and obtain the downscaled layers for past and future climates. From downscaled data, we generated the 19 bioclimatic variables described in WorldClim. This procedure was done using a script developed by Matheus Lima-Ribeiro in https://github.com/macroecology/LGM_GCMs.References: TAYLOR, KE; STOUFFER, RJ and MEEHL, GA (2012) An overview of CMIP5 and the Experiment Design. American Meteorological Society. 93: 485–498.TAYLOR, KE; STOUFFER, RJ and MEEHL, GA (2009) A summary of the CMIP5 Experiment Design. Available in CMIP5. WILBY, RL; CHARLES, SP: ZORITA, E: TIMBAL, B, WHETTON, P, MEARNS ,LO (2004) Guidelines for use of climate scenarios developed from statistical downscaling methods. IPCC Task Group on Data and Scenario Support for Impact and Climate Analysis. http://www.ipcc data.org/guidelines/dgm_no2_v1_09_2004.pd People: Matheus Lima-Ribeiro ProfessorLaboratory of MacroecologyUniversidade Federal de GoiásRegional Jataí, Brazil Levi Carina Terribile ProfessorLaboratory of MacroecologyUniversidade Federal de GoiásRegional Jataí, Brazil Sara Varela Postdoctoral researcherDepartment of EcologyCharles UniversityPrague, Czech Republic Javier González-Hernández Software engineerBerlin, Germany Guilherme de Oliveira ProfessorLaboratory of Conservation BiogeographyUniversidade Federal do Recôncavo da BahiaBahia, Brazil José Alexandre Felizola Diniz-Filho ProfessorDepartment of EcologyUniversidade Federal de GoiásGoiás, Brazil Acknowledgements Financial support for data processing and downscaling was provided by the Brazilian National Council for Scientific and Technological Development (CNPq) and Brazilian Federal Agency for the Support and Evaluation of Graduate Education (CAPES), through the Research Network GENPAC (Geographical Genetics and Regional Planning for Natural Resources in Brazilian Cerrado, project no 563727/2010-1). We thank the World Climate Research Programme (WCRP) and Working Group on Coupled Modelling (WGCM) by the CMIP5 and the PMIP3, from which climatic simulations were derived. We also thank Thiago Fernando Rangel (UFG) for help and suggestions. We dedicate the EcoClimate to Mariana Rocha (in memorian), who was enthusiastically interested in this project when integrating the early EcoClimate team.