The measurements of snowfall and snow depth are important for various disciplines including: transportation networks, river forecasting, climate change research and numerous others. In the 1990's the National Weather Service transitioned from human observers to automated surface observing systems. When these systems were initially deployed snowfall and snow depth measurements ceased at many stations due to the lack of a reliable sensor. To date, much work has been done testing ultrasonic snow depth sensors to reinstate these important climatological elements at observing stations.

For the 2006-07 snow season, 17 sites across the U.S. including Alaska uniformly installed three SR-50 sensors to evaluate if these sensors can be transitioned to an operational status. The test showed promising results in a variety of climates and weather conditions; however wind scour and redistribution proved to be a challenge at some locations. In order to transition to an operational status, both signal processing to smooth the data as well as algorithm development to derive snowfall from the continuous measurement of total snow on ground provided by these sensors is needed. This presentation will provide up-to-date results from comparisons of automated snow depth and derived snowfall to the traditional manual observations of these climatological elements.