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  • 标题:Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD
  • 本地全文:下载
  • 作者:David J. Lorenz ; Diego Nieto-Lugilde ; Jessica L. Blois
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2016
  • 卷号:3
  • DOI:10.1038/sdata.2016.48
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.
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