In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications

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 constr...

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Autores principales:	Ryan W. Webb, Adrian Marziliano, Daniel McGrath, Randall Bonnell, Tate G. Meehan, Carrie Vuyovich, Hans-Peter Marshall
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	snow permittivity liquid water content radar Science Q
Acceso en línea:	https://doaj.org/article/5f8967649d3940878b65e87536c78d79
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spelling	oai:doaj.org-article:5f8967649d3940878b65e87536c78d792021-11-25T18:54:46ZIn Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications10.3390/rs132246172072-4292https://doaj.org/article/5f8967649d3940878b65e87536c78d792021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4617https://doaj.org/toc/2072-4292Extensive 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 (<i>k</i>) 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 <i>k</i> 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 <i>k</i>, 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 r<sup>2</sup> 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) <i>k</i> 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.Ryan W. WebbAdrian MarzilianoDaniel McGrathRandall BonnellTate G. MeehanCarrie VuyovichHans-Peter MarshallMDPI AGarticlesnow permittivityliquid water contentradarScienceQENRemote Sensing, Vol 13, Iss 4617, p 4617 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	snow permittivity liquid water content radar Science Q
spellingShingle	snow permittivity liquid water content radar Science Q Ryan W. Webb Adrian Marziliano Daniel McGrath Randall Bonnell Tate G. Meehan Carrie Vuyovich Hans-Peter Marshall In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications
description	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 (<i>k</i>) 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 <i>k</i> 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 <i>k</i>, 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 r<sup>2</sup> 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) <i>k</i> 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.
format	article
author	Ryan W. Webb Adrian Marziliano Daniel McGrath Randall Bonnell Tate G. Meehan Carrie Vuyovich Hans-Peter Marshall
author_facet	Ryan W. Webb Adrian Marziliano Daniel McGrath Randall Bonnell Tate G. Meehan Carrie Vuyovich Hans-Peter Marshall
author_sort	Ryan W. Webb
title	In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications
title_short	In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications
title_full	In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications
title_fullStr	In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications
title_full_unstemmed	In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications
title_sort	in situ determination of dry and wet snow permittivity: improving equations for low frequency radar applications
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/5f8967649d3940878b65e87536c78d79
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In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications

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