Ground snow loads have traditionally been estimated from data, in the
form of accumulated water-equivalent snow depth (density), collected b
y the National Weather Service (NWS) and the Soil Conservation Service
(SCS), at so-called first-order weather stations. Extensive data rela
ted to snow depth, with the exception of water equivalents, are availa
ble from other weather stations (other NWS stations, cooperative state
and local agencies' stations, etc.). In this paper, we present a meth
od, using first-order station data, to relate water-equivalent depth t
o snow depth and daily temperature. A locality with a similar weather
pattern as the first-order station that maintains an appropriate weath
er database (i.e., snow depth and daily temperature) was identified. U
sing 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 si
gnificantly expand our ground snow load database, better determine the
proper statistical distribution for annual maximum events, and more a
ccurately estimate design ground snow loads. We illustrate the method
using climatological data from a NWS first-order station (including wa
ter equivalents), and a nearby cooperative state weather station.