Abstract

As the biggest economy in Canada, the Province of Ontario is now suffering many consequences caused by or associated with global warming, such as frequent and intense heat waves, floods, droughts, and wind gust. Planning of mitigation and adaptation strategies against the changing climate, which requires a better understanding of possible future climate outcomes over the Province in the context of global warming, is of great interest to local policy makers, stakeholders, and development practitioners. Therefore, in this study, high-resolution projections of near-surface air temperature outcomes including mean, maximum, and minimum daily temperature over Ontario are developed, aiming at investigating how the global warming would affect the local climatology of the major cities as well as the spatial patterns of air temperature over the entire Province. The PRECIS modeling system is employed to carry out regional climate ensemble simulations driven by the boundary conditions of a five-member HadCM3-based perturbed-physics ensemble (i.e., HadCM3Q0, Q3, Q10, Q13, and Q15). The ensemble simulations are then synthesized through a Bayesian hierarchical model to develop probabilistic projections of future temperature outcomes with consideration of some uncertain parameters involved in the regional climate modeling process. The results suggest that there would be a consistent increasing trend in the near-surface air temperature with time periods from 2030s to 2080s. The most likely mean temperature in next few decades (i.e., 2030s) would be [−2, 2] °C in northern Ontario, [2, 6] °C in the middle, and [6, 12] °C in the south, afterwards the mean temperature is likely to keep rising by ~ 2 °C per 30-years period. The continuous warming across the Province would drive the lowest mean temperature up to 2 °C in the north and the highest mean temperature up to 16 °C in the south. In addition, the spread of the most likely ranges of future outcomes shows a consistent widening trend from 2030s to 2080s, implying that long-term climate change is more difficult to predict than near-term change because many more uncertain or unknown factors may continue to emerge during the long-term simulation.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call