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SNOTEL hourly and daily data are a strategic information about snowpack dynamics in western United States. Hourly data are highly noisy due to, e.g., non-physical temperature-based fluctuations of the signal or gauge under-catch. Noise may hinder, among other factors, the correct evaluation of precipitation events or the measurement of SWE, hence the reconstruction of accumulation and melt run-off timing. This makes hourly data practically useless without a denoising procedure. As this time resolution is widely used in hydrologic applications, here we test SNOTEL hourly data in modeling snowpack dynamics. A one-dimensional model of snow depth, snow water equivalent and bulk snow density has been adopted to this aim. We define an automated processing routine to denoise data-series of snow depth, snow water equivalent, bulk snow density, liquid and solid precipitation. Special attention is paid into …