California's spring snowpack provides a critical water resource that may be greatly reduced by greenhouse warming. However, warming over the past half century has had little effect on total summer water discharge. The region's snowpack may therefore be less sensitive to temperature change than predicted by numerical models. In this study, 53 years of 1 April snow course measurements of snow-water equivalent (SWE) from the Sierra Nevada are used in a spatially distributed covariance model of SWE sensitivity to temperature and precipitation. This model is applied at a 2.5 arc min resolution using a multivariate parameter-surface interpolation scheme and Parameter-elevation Regressions on Independent Slopes (PRISM) climate grids. Total modeled SWE volume has a greater covariance to precipitation than to temperature. Increasing precipitation and temperature from 1950 to 2002 has led to an increase in SWE at high elevations and a loss at low elevations, resulting in little or no overall change in SWE volume. The covariance model predicts a 6--10% decrease in total SWE volume per ¿C. However, sensitivity is both highly dependent on concurrent change in precipitation and spatially variable, with the lower-elevation watersheds in the north being the most sensitive to warming. Overall, climate sensitivity is much less than that predicted by numerical models. This difference may result from inadequate treatment of elevation and precipitation in climate models.