DescriptionSnow extent and depth climatologies are presented for central North America in a region situated east of the Rocky Mountains from the Texas Panhandle to Southern Alberta. Daily surface observations from United States Cooperative Observer Program (COOP) and the Meteorological Service of Canada’s stations are used over the study period of 1966-2018. Using a quality-controlled gridded database, the spatial characteristics of extremes, season length, and snow depth are examined. Past studies have primarily focused on snow cover extent, with few including depth analyses. Adding depth to the more traditional examinations of extent allows for a more thorough evaluation of the region’s snow climatology and permits a better understanding of snow cover and associated relationships with hydrological, societal and other climatological variables.
Annual average maximum across the study area range between 2 cm to 68 cm, with peak depths varying from December 10th in the south to February 26th in the north. Average season length, defined as the longest run of snow depth of 7.6 cm or greater and at least seven days in length, varies between 10 to 135 days. A snow depth trend analysis for the 52-year period shows decreases in the coldest part of the year with the largest decreases being in the north. The downward trend is most pronounced at greater depths. In most months, depths have a larger percentage decrease than extent. Many analyses of depth are interested in understanding snow water equivalent over mountainous area, but few studies have focused in areas such as central North America, despite being of importance here too. Evaluating depth provides a more complete understanding of the impact of snow cover on the environment than simply looking at extent. This includes a better estimate of surface albedo, insulation of the underlying soil, and the snowpack water content. Thus, knowledge of snow depth contributes to a better understanding of ephemeral snow’s role in North America’s Plains and Prairies climate, as well as earth’s climate, atmospheric circulation, ecological systems, weather forecasting and flood prediction.