Can convection-permitting modeling provide decent precipitation for offline high-resolution snowpack simulations over mountains?

We conduct and evaluate high-resolution (4-km) snowpack simulations over the western United States (WUS) mountains in Water Year 2013 using the Noah with multi-parameterization (Noah-MP) land surface model driven by precipitation forcing from convection-permitting (4-km) Weather Research and Forecasting (WRF) modeling and four widely used high-resolution datasets that are derived from statistical interpolation based on in situ measurements.

Substantial differences in the precipitation amount among these five datasets, particularly over the western and northern portions of WUS mountains, significantly affect simulated snow water equivalent (SWE) and snow depth (SD) but have relatively limited effects on snow cover fraction (SCF) and surface albedo. WRF generally captures observed precipitation patterns and results in an overall best-performed SWE and SD in the western and northern portions of WUS mountains, where the statistically interpolated datasets lead to underpredicted precipitation, SWE, and SD.