Abstract
Snowpack seasonality in the conterminous United States (U.S.) is examined using a recently-released daily, 4 km spatial resolution gridded snow water equivalent and snow depth product developed by assimilating station-based observations and gridded temperature and precipitation estimates from PRISM. Seasonal snowpacks for the period spanning water years 1982–2017 were calculated using two established methods: (1) the classic Sturm approach that requires 60 days of snow cover with a peak depth >50 cm and (2) the snow seasonality metric (SSM) that only requires 60 days of continuous snow cover to define seasonal snow. The latter approach yields continuous values from −1 to +1, where −1 (+1) indicates an ephemeral (seasonal) snowpack. The SSM approach is novel in its ability to identify both seasonal and ephemeral snowpacks. Both approaches identify seasonal snowpacks in western U.S. mountains and the northern central and eastern U.S. The SSM approach identifies greater areas of seasonal snowpacks compared to the Sturm method, particularly in the Upper Midwest, New England, and the Intermountain West. This is a result of the relaxed depth constraint compared to the Sturm approach. Ephemeral snowpacks exist throughout lower elevation regions of the western U.S. and across a broad longitudinal swath centered near 35° N spanning the lee of the Rocky Mountains to the Atlantic coast. Because it lacks a depth constraint, the SSM approach may inform the location of shallow but long-duration snowpacks at risk of transitioning to ephemeral snowpacks with climatic change. A case study in Oregon during an extreme snow drought year (2014/2015) highlights seasonal to ephemeral snowpack transitions. Aggregating seasonal and ephemeral snowpacks to the HUC-8 watershed level in the western U.S. demonstrates the majority of watersheds are at risk of losing seasonal snow.
Highlights
Snowfall occurs over a wide range of landscapes worldwide [1,2,3], providing essential services to ecosystems and human society [4,5,6]
Seasonal snowpacks identified by the seasonality metric (SSM) but absent from the Sturm approach included the High Plains, much of the Upper Midwest, and areas of New York and Pennsylvania
By including a locally-relevant depth constraint, the SSM could offer a metric to identify and assess transitions from seasonal snow to ephemeral snow that builds on the well-established Sturm method
Summary
Snowfall occurs over a wide range of landscapes worldwide [1,2,3], providing essential services to ecosystems and human society [4,5,6]. Vegetation and topographic characteristics, such as canopy cover, slope, aspect, and elevation determine the behavior of snow cover [10,11,12]. Interactions between the topoclimate, meteorology, and land surface conditions determine the physical character of snow cover during and following snow deposition [7,8,13,14]. Classifying snow cover in terms of its seasonal and physical characteristics has long been a focus of cryospheric and hydrologic science [13] with the earliest classification systems developed in the early 1900s [15,16]. Prior to the advent of remote sensing and numerical modeling, snow classifications were primarily qualitative [16] and based upon field observations, though more quantitative characteristics were later incorporated [17]. The approach developed by [13]
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