Estimating Ground Snow Loads Using Local Climatological Data

Ground snow loads have traditionally been estimated from data, in the form of accumulated water-equivalent snow depth (density), collected by the National Weather Service (NWS) and the Soil Conservation Service (SCS), at so-called first-order weather stations. Extensive data related to snow depth, with the exception of water equivalents, are available from other weather stations (other NWS stations, cooperative state and local agencies' stations, etc.). In this paper, we present a method, using first-order station data, to relate water-equivalent depth to snow depth and daily temperature. A locality with a similar weather pattern as the first-order station that maintains an appropriate weather database (i.e., snow depth and daily temperature) was identified. Using the developed relationship between water equivalents, snow depth, and daily temperature, we convert snow depth to density (i.e., water equivalents) for the local data source. This procedure allows us to significantly expand our ground snow load database, better determine the proper statistical distribution for annual maximum events, and more accurately estimate design ground snow loads. We illustrate the method using climatological data from a NWS first-order station (including water equivalents), and a nearby cooperative state weather station.