Skip to main content
Article
In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications
Remote Sensing
  • Ryan Webb, University of New Mexico
  • Adrian Marziliano, University of New Mexico
  • Daniel McGrath, Colorado State University
  • Randall Bonnell, Colorado State University
  • Tate G. Meehan, Boise State University
  • Carrie Vuyovich, NASA-Goddard Space Flight Center
  • Hans-Peter Marshall, Boise State University
Document Type
Article
Publication Date
11-1-2021
Abstract

Extensive efforts have been made to observe the accumulation and melting of seasonal snow. However, making accurate observations of snow water equivalent (SWE) at global scales is challenging. Active radar systems show promise, provided the dielectric properties of the snowpack are accurately constrained. The dielectric constant (k) determines the velocity of a radar wave through snow, which is a critical component of time-of-flight radar techniques such as ground penetrating radar and interferometric synthetic aperture radar (InSAR). However, equations used to estimate k have been validated only for specific conditions with limited in situ validation for seasonal snow applications. The goal of this work was to further understand the dielectric permittivity of seasonal snow under both dry and wet conditions. We utilized extensive direct field observations of k, along with corresponding snow density and liquid water content (LWC) measurements. Data were collected in the Jemez Mountains, NM; Sandia Mountains, NM; Grand Mesa, CO; and Cameron Pass, CO from February 2020 to May 2021. We present empirical relationships based on 146 snow pits for dry snow conditions and 92 independent LWC observations in naturally melting snowpacks. Regression results had r2 values of 0.57 and 0.37 for dry and wet snow conditions, respectively. Our results in dry snow showed large differences between our in situ observations and commonly applied equations. We attribute these differences to assumptions in the shape of the snow grains that may not hold true for seasonal snow applications. Different assumptions, and thus different equations, may be necessary for varying snowpack conditions in different climates, suggesting that further testing is necessary. When considering wet snow, large differences were found between commonly applied equations and our in situ measurements. Many previous equations assume a background (dry snow) k that we found to be inaccurate, as previously stated, and is the primary driver of resulting uncertainty. Our results suggest large errors in SWE (10–15%) or LWC (0.05–0.07 volumetric LWC) estimates based on current equations. The work presented here could prove useful for making accurate observations of changes in SWE using future InSAR opportunities such as NISAR and ROSE-L.

Comments

Erratum in: Remote Sensing, 2022 September, 14(17), 4407.Significant correction made to original publication including correction to figure 4 and multiple text corrections to Equation 5 and Section 3.2 paragraph 1. See erratum publication for details at https://doi.org/10.3390/rs14174407

Creative Commons License
Creative Commons Attribution 4.0 International
Citation Information
Ryan Webb, Adrian Marziliano, Daniel McGrath, Randall Bonnell, et al.. "In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications" Remote Sensing (2021)
Available at: http://works.bepress.com/hanspeter_marshall/65/