Outdoor skating is a valued and culturally important winter activity in Canada that is vulnerable to warming winter temperatures resulting from anthropogenic climate change. Changes to the outdoor skating season (OSS) due to climate change have been estimated from historical weather records using the occurrence of daily temperatures below a particular temperature threshold as a proxy for rink availability. However, research on the actual weather conditions needed for outdoor rinks to be maintained in reasonable condition is limited. In this study, we used historical weather data and daily reports on outdoor rinks in Montréal to identify which daily or multi-day temperature variable can best act as an indicator of outdoor ice rink availability. We evaluated a series of temperature variables using a logistic regression to predict the likelihood of open rinks during each day of the season. Using AIC scores to select the best model, we found that the mean of the preceding six-day maximum temperature was the best predictor of skating availability. Using this temperature predictor, we then projected changes in the duration of the future OSS in Montréal based on global climate model data, downscaled to the island of Montréal using the MarkSim Weather Generator. Our results showed that the mean OSS duration in Montréal would range from a 15% to a >75% decline by 2090 depending on which future emissions scenario we follow. In a scenario that limits global temperature rise to below 2.0°C (RCP 2.6), we projected a 41 day mean OSS duration at the end of this century. By contrast, under a business-as-usual emissions pathway (RCP 8.5), the average length of the OSS in Montréal could decline to only 11 days per year. Our results suggest that very ambitious climate change mitigation will be required to preserve outdoor skating in Montréal in the face of ongoing global climate change.

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Abstract. Fire is an integral part of the Earth system, interacting in complex ways with humans, vegetation and climate. Global fire activity is an important element of the carbon cycle, and understanding its role in the context of climate change is crucial. In order to represent the transient fire-climate-vegetation interactions and to integrate these in the long term climate projections of climate models, coupling these three components is necessary. Global fire models have been coupled to climate-vegetation models with complex atmosphere modules but these models are computationally intensive. In this research, we use the University of Victoria Earth System Climate Model (UVic ESCM), an ESCM of intermediate complexity to which we couple a process based global fire model, in order to develop a computationally efficient means of studying long term fire-climate-vegetation interactions. The fire model used simulates burned area based primarily on relative humidity, soil moisture and biomass density. The UViC ESCM’s simulated relative humidity is improved by parameterizing it according to the simulated precipitation, and observational variability is added to the simulated climatology to improve the variability of simulated burned area. The best parameterization achieves a moderate spatial agreement of simulated burned area with observational data. Tropical rainforests in South America and Africa, however, display very high burned fractions, due to the poorly simulated relative humidity input; indeed, when we used observed relative humidity to simulate fire activity, the pattern of burned area in the tropics improved substantially. This research demonstrates the importance of variability and regional patterns of climatology for global wildfire activity and the corresponding limitations of ESCMs that simplify atmospheric circulation. This suggests that using pattern scaling of climate variables as an input to fire models could provide such ESCMs of intermediate complexity with the ability to integrate global fire activity.