The Natural Resources Conservation Service measures high elevation snowpack manually at snow courses across the western US. In addition to supporting the production of seasonal snowmelt-driven streamflow forecasts, this long-term dataset is widely used throughout the research community to study historical climatic change impacts. Therefore it is critical to understand what factors may affect the quality of the measurements, especially if those non-climatic factors possess long-term trends. For example, the snowpack measurement dates are nominally the first and fifteenth of the month although they actually average approximately 2 days earlier. This study found that the variability of measurement dates are determined by, 1) the epoch of the measurement, 2) the day of the week of the nominal measurement date, 3) the presence or absence of snow at the site and 4) if the measurement is for the first or the fifteenth of the month. The measurement date is less variable if snow is absent from the site. Mid-month data are collected closer to the nominal measurement date, and first of month data have a greater early bias. Since 1957, there has been a stronger aversion to collecting data on Fridays and weekends. Measurements are taken today on average 1.35 days earlier than they were before 1957. The effect on measurement bias depended on the time of year and was generally less than 5 % of the measurement. Therefore, changes in measurement date only slightly mask one’s ability to accurately detect long-term climatic trends.