Developing Extreme Climate Indices for Building Code Calculation in Ontario from the IPCC AR5 Multi-model Ensemble
The urban environment and its infrastructure will be impacted significantly by climate change and are identified as specific sectors needing “priority planning” for adaptation (Heather et al., 2010). As a northern region, the province Ontario of Canada could experience significant changes in both mean and extreme climatic conditions.The design values could very likely be altered under the future projected climate change. There is clearly a need for more comprehensive research on potential impacts of climate change on infrastructure design. However, very few studies have examined the likely effects of climate change on these design values due to it is a very challenging issue. Most of the design values are defined with hourly or minute data. The climatic design values are usually thresholds of long return period events (for example 5-year, 10-year or 50-year extreme events) or 1, 2.5 percentiles. Some recent studies have provided a framework to deal with this issue. For example the general extreme theory (GEV, Castillo 1988; De Haan & Ferreira 2007; Castillo 2012; Hong 2014) provided a framework for the threshold issue and some recently proposed temporal downscaling methodologies has been used for hourly rainfall, wind speed and temperature (Ephrath et al 1996; Hosmer & Lemeshow 2004; Vrac et al. 2012; Maraun, 2013; Shrestha et al. 2015).
To meet the needs for the built environment and its infrastructure sectors in Ontario to adapt to the changing climate, this study applied the GEV and spatial-temporal downscaling approaches to produce probabilistic projections for 2050s and 2080s of some climatic design values at the 228 sites listed in table 1 of the MMAH Supplementary Standard SB-1 Climatic and Seismic Data. The projected climatic design values can provide valuable information to fill in the knowledge gaps of climate building code and to increase the safety or uncertainty factors used for current and future design. To achieve this goal, different temporal downscaling models were developed and used to a spatially downscaled IPCC AR5 RCP6.0 GCM ensemble. The impact of climate change on climatic design values is an extreme challenging issue. Results from this projects should be used with caution and under guidance from building code development professionals.
Deng, Z., Liu, J., Qiu, X., Zhou, X., & Zhu, H. (2018). Downscaling RCP8. 5 daily temperatures and precipitation in Ontario using localized ensemble optimal interpolation (EnOI) and bias correction. Climate Dynamics, 51(1-2), 411-431.
Deng, Z., Qiu, X., Liu, J., Madras, N., Wang, X., & Zhu, H. (2016). Trend in frequency of extreme precipitation events over Ontario from ensembles of multiple GCMs. Climate dynamics, 46(9-10), 2909-2921.
Deng Z., Liu, J., Qiu, X., Zhou, X., Babazadeh, H., Zhu, H. (2018). Projection of Temperature and Precipitation Related Climatic Design Data Using CMIP5 Multi-Model Ensemble. Journal of Buildings and Sustainability, 1(1), 39-54.