Influence of snow spatial variability on cosmic ray neutron snow water equivalent (SWE): case study in a northern prairie
Year: 2025
Type: article
Abstract: . Monitoring prairie snow has been difficult due to its extreme spatial variability from windy conditions, gentle topography, and low tree cover. Previous work has shown that a noninvasive (or aboveground) Cosmic Ray Neutron Sensor (CRNS) placed at the Central Agricultural Research Center (CARC; 47.07° N, 109.95° W), an agricultural research site within a semi-arid prairie environment managed by Montana State University, was sensitive to both the low snow amounts and spatial variability of prairie snow. In this study, we build upon previous work to understand how different snow distributions would have influenced CRNS measurements at the CARC. Specifically, we compared the changes in neutron counts and snow water equivalent (SWE) after relocating our CRNS probe at the CARC using the Ultra Rapid Neutron-Only Simulation (URANOS) and comparing them to uniform snow distributions. For shallow, heterogeneous snowpacks like the ones observed at the CARC, the magnitude and distance of the snow drifts from the CRNS has the greatest effect on neutron counts. Therefore, the best place to site a CRNS is within areas of low snow accumulation that are nearby areas of high snow accumulation to obtain a reasonable spatial estimate. Despite this, a naive CRNS placement was 2 to 5 times more likely to yield better SWE estimates compared to snow scales or currently available gridded products. CRNS provides valuable information about shallow, heterogeneous snowpacks in prairie and other environments and can benefit future missions from UAV and satellite platforms.
Source: The cryosphere
Authors: Haejo Kim, Eric Sproles, Samuel E. Tuttle
Institutions: Syracuse University, Montana State University
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,574
OpenAlex ID: W4413437034