## 3 Results
### Temperature and Precipitation
Additionally, when these AST magnitudes are placed side by side, it becomes evident that CanESM5 projects an 8.45% increase in maximum AST compared to its CanESM2 counterpart. As per the depictions in the historical and projected AST maps, it is discernible that the highest AST is situated in the southern regions of the study area and the southwestern vicinity of Quebec City. Advancing towards the northern regions, a consistent decline in temperature is evident, as substantiated by both historical and projected datasets. Specifically, for Quebec City, the historical AST figure stands at 8.52 \({}^{\circ}\)C, whereas CanESM2 and CanESM5 envision this variable to reach 13.11 \({}^{\circ}\)C and 14.41 \({}^{\circ}\)C, respectively, in their projections. In conclusion, as per the historical and projected data analysis concerning the average season  
Figure 2: Distribution of the total precipitation (**A**) and average temperature (**B**) during the golf season in the province of Quebec (May to November) across historical data (yellow) and projected climate change models (CanESM2 (light orange) and CanESM5 (cyan)). temperature (AST), it becomes evident that a significant surge in temperature (50.08% and 74.87% for CanESM2 and CanESM5, respectively) is anticipated across all sections of the study area. This temperature increase is poised to yield noteworthy ramifications for disease and insect pressure on golf courses within this region, thus affecting pesticide use. Figure 2 presents the distribution of total precipitation and AST during the golf season in the province of Quebec (May to November). This presentation encompasses a range of climate change models and scenarios. The boxplots were applied to visually summarize the central tendency, spread, and skewness of the total precipitation and AST and identify potential outliers. A comparison between two different climate change models, CanESM2 and CanESM5, reveals significant differences. CanESM2 assesses future climate change impacts based on various greenhouse gas emission trajectories, while CanESM5 considers both emissions and a broader set of socioeconomic factors. This comparison indicates that total precipitation projections from CanESM2 are considerably lower than those projected by CanESM5, resulting in relative errors of 7.46% for the minimum and 5.4% for the maximum projected total precipitation. The interquartile section of the boxplot, which represents the middle 50% of all samples, clearly demonstrates that historical total precipitation significantly exceeds the projections made by climate change models, particularly CanESM2 (Figure 2A). To illustrate this difference, attention can be drawn to the first quartile (Q1) in the provided box plot for historical total precipitation, which is higher than the third quartile (Q3) for CanESM2. This means that over 75% of recorded historical total precipitation values surpass the 25% mark of total precipitation projected by CanESM2. These observations indicate that, due to climatic effects, total precipitation in the coming years is anticipated to decrease when compared to the historical values recorded in the study area. Specifically, upon comparing the projected total precipitation values by CanESM2 to the historical records, it becomes evident that there is a decrease in the range of 11-14% for the minimum, Q1, mean, Q3, and maximum values of total precipitation. The values for the various components of these boxplots are provided in Table 1. A comparison of the distribution of historical total precipitation with the projections made by CanESM5 indicates that all the presented characteristics, including minimum, Q1, average, Q3, maximum, and interquartile range, are higher for historical total precipitation, with relative errors of 8%, 4.9%, 6.66%, 7.27%, 8.42%, and 23.23%, respectively. Indeed, based on the CanESM5 projections, the average total precipitation is expected to decrease by 6.66%.