An Investigation of the Pineapple Express Phenomenon via Bivariate Extreme Value Theory

• Activity Number: 329
• Type: Topic Contributed
• Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Grant Brian Weller*+ and Daniel Cooley and Stephan Sain
• Companies: Colorado State University and Colorado State University and Geophysical Statistics Project
• Keywords: Extreme Precipitation ; Atmospheric Rivers ; Regional Climate Models ; Precipitation Generator ; Synoptic-scale Patterns

Abstract

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 reanalysis to develop a daily "PE index" for extreme precipitation which exhibits tail dependence with our observational quantity. Finally, we employ the fitted tail dependence model to conditionally 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.