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Increases in the intensity and frequency of extreme events in Western North America (WNA) can cause significant socioeconomic problems and threaten existing infrastructure. In this study we analyze the impacts of climate change on hydroclimatic extremes and assess the role of internal variability over WNA, which collectively drain an area of about 1 million km2. We used gridded observations and downscaled precipitation, maximum and minimum temperature from seven General Circulation Models (GCMs) that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and a large ensemble of CanESM2 model simulations (CanESM2-LE; 50 members) for this analysis. Spatial and temporal changes of eight climate extreme indices are assessed over the historical (1981-2010) and future (2060-2089) time periods. In addition, changes in extreme events with high return periods are analyzed based on the extreme value theory. To better understand the effects of internal climate variability on the hydroclimatology of WNA we assess the relations between 14 Low Frequency Variability Modes (LFVMs), with three different time lags, and the regional temperature and precipitation. The correlation between each LFVM and the principle component of temperature and precipitation over the spatial domain is computed using Maximum Covariance Analysis (MCA). Robustness of the results is further evaluated using composite analysis. Results show that the intensity and frequency of extreme precipitation and temperature are projected to increase over WNA. The uncertainties due to internal variability (represented by CanESM2-LE) are significant and comparable to those arising from GCM structures. El Nino Southern Oscillation, Trans-Polar Index (TPI), Southern Annular Mode (SAM), Eastern Pacific (EP) and West Pacific (WP) are found to be dominant LFVMs that can significantly influence WNA’s hydroclimatic variables.