Assessing the ability of Coupled Model Intercomparison Project Phase 5 (CMIP5) models to capture connections between Great Basin precipitation and Pacific Ocean modes of variability and applying the assessment into the future

Precipitation over the Wasatch Mountain Range of northern Utah, part of the Great Basin (GB) in the western United States, provides water for millions of people living along the Wasatch Front. Western US precipitation is known to be influenced by the El-Nino--Southern Oscillation (ENSO) as well as the Pacific Decadal Oscillation (PDO) in the North Pacific. Historical connectivity between GB precipitation and Pacific Ocean sea surface temperatures (SSTs) on interannual to multidecadal time scales is evaluated for 20 models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5). While the majority of the models had realistic ENSO and PDO spatial patterns in the SSTs, the simulated influence of these two modes on GB precipitation tended to be too strong for ENSO and too weak for PDO. Few models captured the connectivity at a quasi-decadal period influenced by the transition phase of the Pacific quasi-decadal oscillation (QDO; a recently identified climate mode that regulates GB precipitation). Some of the discrepancies appear to stem from models not capturing the observed tendency for the PDO to modulate the sign of the ENSO-GB precipitation teleconnection. Of all of the models, CCSM4 most consistently captured observed connections between Pacific SST variability and GB precipitation on all time scales, suggesting that in future applications, its output represents a higher confidence for the future climate of this region. The utility of the assessment is illustrated by a brief statistical analysis of future western US precipitation under a high emissions scenario.;Using the results from the assessment, the application portion of the study analyzes future precipitation data under a high emissions scenario (RCP 8.5) to determine what the future could potentially look like over the western US. The models are ranked based on their performance in capturing the connections between GB precipitation and Pacific Ocean modes of variability. The ranking then deter- mines which model would be appropriate to be applied to a stochastic framework and dynamical downscaling analyses. The results from the assessment were used to force a nonstationary, daily stochastic weather generator and produce precipitation occurrence output for a valley site and a mountain site located within the GB. With some considerations, the stochastic weather generator provides long-term data for any time period that statistically matches the input data.