We employ dynamical downscaling and pseudo global warming methodologies to evaluate climate change impact on the roles of temperature and precipitation in spring snowpack (S) variability across the western United States (U.S.). The negative correlation between S and temperature weakens linearly with elevation, whereas the correlation between S and precipitation increases asymptotically with elevation. The curvilinear relationship in the latter case was not visible in prior studies because of the observation networks' limited range. In our historical validation, there is a range of threshold elevations (1580–2181 m) across six mountainous regions, above which precipitation is the main driver of snowpack variability and below which temperature is the main driver. Under a moderate end‐of‐century climate change scenario, these thresholds increase by 191 to 432 m. These rising thresholds indicate increasing spatial and elevational vulnerability of western U.S. spring snowpack along with associated impacts to hydrologic and ecologic systems.

A 26 year high-resolution dynamical downscaling over the Wasatch Mountains of Utah, USA, was performed using the Weather Research and Forecasting model with initial and boundary conditions derived from Climate Forecast System Reanalysis. Precipitation validation was conducted on the inner (4 km resolution) domain with Snowpack Telemetry (SNOTEL) and Parameter-elevation Regressions on Independent Slopes Model data sets. Analysis of seasonal performance reveals the model's overall good skill at reproducing the spatial distribution of precipitation. Annual precipitation validates within ∼20% of SNOTEL. The largest monthly biases occurred in December-January (∼+30%) stemming from a small set of high-precipitation events. Composite analysis of cold season days with large positive or negative precipitation biases reveals two distinct synoptic regimes with significantly different moisture, temperature, and circulation patterns that respectively enhanced geopotential height and moisture biases consistent with the sign of their mean precipitation biases. The number of cold season days with large (>5 mm) positive precipitation bias was negatively correlated with El Niño (r = −0.55), indicating storm track-related effects on the sign of the bias consistent with the distinct synoptic regimes revealed by the above-noted composite analyses.