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Linking snowfall and snow accumulation to generate spatial maps of SWE and snow depth
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Linking snowfall and snow accumulation to generate spatial maps of SWE and snow depth
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Journal Article
Linking snowfall and snow accumulation to generate spatial maps of SWE and snow depth
2016
Overview
It is critically important but challenging to estimate the amount of snow on the ground over large areas due to its strong spatial variability. Point snow data are used to generate or improve (i.e., blend with) gridded estimates of snow water equivalent (SWE) by using various forms of interpolation; however, the interpolation methodologies often overlook the physical mechanisms for the snow being there in the first place. Using data from the Snow Telemetry and Cooperative Observer networks in the western United States, we show that four methods for the spatial interpolation of peak of winter snow water equivalent (SWE) and snow depth based on distance and elevation can result in large errors. These errors are reduced substantially by our new method, i.e., the spatial interpolation of these quantities normalized by accumulated snowfall from the current or previous water years. Our method results in significant improvement in SWE estimates over interpolation techniques that do not consider snowfall, regardless of the number of stations used for the interpolation. Furthermore, it can be used along with gridded precipitation and temperature data to produce daily maps of SWE over the western United States that are comparable to existing estimates (which are based on the assimilation of much more data). Our results also show that not honoring the constraint between SWE and snowfall when blending in situ data with gridded data can lead to the development and propagation of unrealistic errors. Key Points Accumulated snowfall is a strong predictor of peak SWE and snow depth at SNOTEL and COOP sites For this data, spatial interpolation of SWE is improved by first normalizing by accumulated snowfall This interpolation produces maps of SWE comparable to existing maps that are based on much more data
Publisher
John Wiley & Sons, Inc
Subject
