The pineapple express (PE) phenomenon is responsible for producing extreme winter precipitation events on the west coast of the US and Canada. We study regional climate models' ability to reproduce these events by defining a quantity which captures the spatial extent and intensity of PE events. We use bivariate extreme value theory to model the tail dependence of this quantity as seen in observational data and the Weather Research and Forecasting (WRF) regional climate model driven by reanalysis, and we find tail dependence between the two. To link to synoptic-scale processes, we use daily mean sea-level pressure (MSLP) fields from NCEP to develop a daily "PE index" for extreme precipitation which exhibits tail dependence with our observational quantity. Other models from the NARCCAP ensemble are used to estimate the future marginal distributions of NCEP-driven WRF output and observational precipitation. Finally, we employ the fitted tail dependence model to simulate observational precipitation measurements in the future, given output from a future run of WRF. We find evidence of a change in the tail behavior of precipitation from current to future climates, and examination of PE index values of simulated events suggests increases in frequency and intensity of PE precipitation in the future scenario.