The Influence of Cloudiness, Temperature, and Precipitation Variabilities on Snowmelt Variations in the Western U.S

We investigate the influence of cloudiness variability on spring snowmelt and streamflow variations in the
mountains of western U.S., and how it compares to that of precipitation (P), daily maximum and minimum
temperature (Tmax and Tmin). We derive daily cloud albedo (αcloud) from GOES visible albedo product to represent
cloudiness. Daily snowmelt (ΔSWE) is obtained from 235 SNOTEL and CDEC snow water equivalent records.
Daily streamflow fluctuations (ΔQ) are derived from 79 USGS/HCDN stream discharge records. Multivariate
regression models are developed for five different sets: where αcloud, P, Tmax and Tmin surface are predictors, and
successively, where each one of the predictors is removed. αcloud, Tmax, Tmin and P altogether account for 3%-62% of
ΔSWE variance over Feb-Jul, averaging ~23%. The results further show the dominance of αcloud influence, with
increasing αcloud role and decreasing Tmax, Tmin and P roles in warmer months and in drier years. Greater αcloud
contribution in dry years suggests the diminished importance of other hydrological factors in dry years, such as
heavy precipitation events and fluctuations associated with higher snowpack. ΔQ responses to αcloud, Tmax, Tmin and P
exhibit similar patterns, but with lower explained variances.