Output of a Multi-Model Ensemble for the simulation of temperature variability over Ontario, Canada

Multi-model ensembles for climate modeling, which have generally proven to have a superior performance compared to individual models, are assessed for Ontario, Canada. Specifically, the performance of seven Global Climate Model (GCM) and Regional Climate Model (RCM) combinations are evaluated on twelve stations across Ontario, as well as for the entire domain. Two multi-model ensembles were produced, one using the mean of seven GCM and RCM combinations and the other using the median of the same seven GCM and RCM combinations. Three temperature variables (average surface temperature, maximum surface temperature, and minimum surface temperature) were used to evaluate the performance of the models, as well as twelve stations chosen within the domain. Data obtained from the North American Coordinated Regional Downscaling Experiment were compared with gridded data based on observations from the Climactic Research Unit's TS v4.00 dataset, as well as observed station data from the Digital Archive of Canadian Climatological Data provided by Environment and Climate Change Canada. For all three climate variables, at each station, and over the whole domain of Ontario, the multi ensemble based on the mean generally outperformed the ensemble based on median and each of the individual models. Future predictions of the multi-model ensemble under the Representative Concentration Pathway 4.5 (RCP4.5) scenario are generated to provide bases for the climate change mitigation and adaptation in Ontario. The multi-model ensembles predict a 2.89 increase in annual mean temperature between 1951-2005 and 2040-2069.

针对加拿大安大略省，研究对经证实普遍优于单一气候模型的气候建模用多模型集合（Multi-model Ensembles）展开了评估。具体而言，研究针对安大略省境内12个气象站点及全省全域，采用地表平均气温、地表最高气温及地表最低气温这3类温度变量，对7组全球气候模型（Global Climate Model, GCM）与区域气候模型（Regional Climate Model, RCM）组合方案的表现进行评估。本次研究构建了两类多模型集合：其一基于7组GCM与RCM组合的平均值，其二则基于同一7组组合的中位数。研究将北美区域降尺度协调试验（North American Coordinated Regional Downscaling Experiment）获取的数据，与基于气候研究单位（Climatic Research Unit）TS v4.00数据集的格点观测数据，以及加拿大环境与气候变化部提供的加拿大气候数据数字档案馆的实测站点数据进行对比。针对3类气候变量、每个气象站点及安大略省全域，基于平均值构建的多模型集合整体表现均优于基于中位数构建的多模型集合及所有单一模型。研究针对典型浓度路径4.5（Representative Concentration Pathway 4.5, RCP4.5）情景下的多模型集合未来预测结果进行构建，旨在为安大略省的气候变化减缓与适应工作提供科学依据。多模型集合预测显示，1951-2005年至2040-2069年间，安大略省年平均气温将上升2.89℃。