Data from: Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

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.

越来越多的生态建模研究者将古数据（paleodata）与未来气候预测相结合，以解析从过去直至本世纪由气候驱动的生物多样性动态变化过程。地球系统模型（earth system models）生成的气候模拟结果是该研究工作的必要支撑，但在应用于生态模型之前，必须对其完成偏差校正（debiased）与降尺度（downscaled）处理。不同研究者所采用的降尺度方法与观测基准存在差异，这会导致经降尺度处理的气候模拟结果间产生混杂偏差（confounding biases）。本研究提供一套统一数据集，涵盖北美地区自21 ka BP至2100年的经偏差校正与降尺度处理的气候模拟结果，空间分辨率为0.5°。其时间分辨率设置如下：1950年以前采用逐月数据的十年平均值，1950–2005年采用年均气候态数据，2010–2100年则同时提供逐月数据与十年平均值两种形式。本次降尺度处理涵盖两项瞬态古气候模拟结果，以及适配政府间气候变化专门委员会第五次评估报告（IPCC AR5）下耦合模型比较计划第五阶段（CMIP5）历史情景（1850–2005年）、典型浓度路径（Representative Concentration Pathways，RCP）4.5与典型浓度路径（RCP）8.5等21世纪情景的12个气候模型结果。气候变量涵盖基础气候变量与衍生生物气候变量（derived bioclimatic variables）。本数据集提供了一套统一的气候模拟结果集，可用于无缝建模过去与未来气候变化对物种分布及生物多样性的影响。