Abstract
This study evaluates the rainfall patterns and assesses the impact of precipitation on the climate of Sherbrooke, Canada. The research examines rainfall data from 1960 to 2010 to identify patterns, variations, and anomalies in frequency. Due to its mid-latitude location and proximity to the Appalachian Mountains, Sherbrooke experiences a unique climate with significant seasonal precipitation changes. The study employs probabilistic approaches, such as the Normal, Log-Normal, Inverse Gaussian, and Gamma distributions, to calculate rainfall for various return periods. Additionally, climate modeling using statistical downscaling is incorporated to predict future precipitation variations from 2051 to 2080. The results are then compared to find the similarity between the trends of future precipitation using climate modelling and probability methods. The results indicate that average annual precipitation may increase by 10%, highlighting the potential impact of climate change on future precipitation patterns. These insights are valuable for agriculturists, urban planners, engineers, and water resource managers in creating sustainable cities, ensuring stable agriculture, and optimizing water resource usage to mitigate the effects of fluctuating rainfall patterns. Understanding these interactions is essential for adapting to and preparing for the broader implications of climate change on both regional and global scales.
Details
Presentation Type
Theme
KEYWORDS
Climate model, Precipitation, Probabilistic method
