About

The goal of ecoClimate is to provide an open database of processed climatic simulations in a suitable resolution and user-friendly format for macroecological and biogeographical studies. Our database includes all climate models currently available from CMIP5 and PMIP3 projects for past, present, and future periods.

 

Data availability

The dataset includes simulations for modern (1950-1999), historical (1900-1949), pre-industrial (~1760), Mid-Holocene (6ka), Last Glacial Maximum (21ka), Pliocene (3Ma) 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

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/ecoClimate.

References

  • TAYLOR KE, STOUFFER RJ and MEEHL GA (2009) A summary of the CMIP5 Experiment Design. Available in CMIP5.
  • TAYLOR KE, STOUFFER RJ and MEEHL GA (2012) An overview of CMIP5 and the Experiment Design. American Meteorological Society. 93: 485–498.
  • 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

Acknowledgements

We first acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling by the CMIP5 and PMIP3, and we thank the climate modeling groups for producing and making available model outputs. The U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We also thank Thiago F. Rangel (Universidade Federal de Goiás – Brazil) for help and invaluable suggestions. The feedback from users who used our previous climatic data sets was also valuable. Finally, we dedicate the ecoClimate to the memory of Mariana Rocha, who was enthusiastically interested in this project when integrating the early ecoClimate team. We acknowledge financial support from CNPq, CAPES, and FAPEG for supporting our work via multiple grants and fellowships, especially the research network GENPAC (Geographical Genetics and Regional Planning for Natural Resources in Brazilian Cerrado).