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  • 标题:Climate Data to Undertake Hygrothermal and Whole Building Simulations Under Projected Climate Change Influences for 11 Canadian Cities
  • 本地全文:下载
  • 作者:Abhishek Gaur ; Michael Lacasse ; Marianne Armstrong
  • 期刊名称:Data
  • 印刷版ISSN:2306-5729
  • 出版年度:2019
  • 卷号:4
  • 期号:2
  • 页码:72-88
  • DOI:10.3390/data4020072
  • 出版社:MDPI Publishing
  • 摘要:Buildings and homes in Canada will be exposed to unprecedented climatic conditions in the future as a consequence of global climate change. To improve the climate resiliency of existing and new buildings, it is important to evaluate their performance over current and projected future climates. Hygrothermal and whole building simulation models, which are important tools for assessing performance, require continuous climate records at high temporal frequencies of a wide range of climate variables for input into the kinds of models that relate to solar radiation, cloud-cover, wind, humidity, rainfall, temperature, and snow-cover. In this study, climate data that can be used to assess the performance of building envelopes under current and projected future climates, concurrent with 2 °C and 3.5 °C increases in global temperatures, are generated for 11 major Canadian cities. The datasets capture the internal variability of the climate as they are comprised of 15 realizations of the future climate generated by dynamically downscaling future projections from the CanESM2 global climate model and thereafter bias-corrected with reference to observations. An assessment of the bias-corrected projections suggests, as a consequence of global warming, future increases in the temperatures and precipitation, and decreases in the snow-cover and wind-speed for all cities.
  • 关键词:buildings; climate change; hygrothermal modelling; Canada; bias correction; climate model buildings ; climate change ; hygrothermal modelling ; Canada ; bias correction ; climate model
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