Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing
Authors: Tsang Leung , Durand Michael , Derksen Chris , Barros Ana P. , Kang Do-Hyuk , Lievens Hans , Marshall Hans-Peter , Zhu Jiyue , Johnson Joel , King Joshua , Lemmetyinen Juha , Sandells Melody , Rutter Nick , Siqueira Paul , Nolin Anne , Osmanoglu Batu , Vuyovich Carrie , Kim Edward , Taylor Drew , Merkouriadi Ioanna , Brucker Ludovic , Navari Mahdi , Dumont Marie , Kelly Richard , Kim Rhae Sung , Liao Tien-Hao , Borah Firoz , Xu Xiaolan 
Published: September 2022

Abstract. Seasonal snow cover is the largest single component of
the cryosphere in areal extent, covering an average of 46 × 106 km2
of Earth's surface (31 % of the land area) each year, and is thus an
important expression and driver of the Earth's climate. In recent
years, Northern Hemisphere spring snow cover has been declining at about the
same rate (∼ −13 % per decade) as Arctic summer sea ice. More
than one-sixth of the world's population relies on seasonal snowpack and
glaciers for a water supply that is likely to decrease this century. Snow is
also a critical component of Earth's cold regions' ecosystems, in which
wildlife, vegetation, and snow are strongly interconnected. Snow water
equivalent (SWE) describes the quantity of water stored as snow on the land
surface and is of fundamental importance to water, energy, and geochemical
cycles. Quality global SWE estimates are lacking. Given the vast seasonal
extent combined with the spatially variable nature of snow distribution at
regional and local scales, surface observations are not able to provide
sufficient SWE information. Satellite observations presently cannot provide
SWE information at the spatial and temporal resolutions required to address
science and high-socio-economic-value applications such as water resource
management and streamflow forecasting. In this paper, we review the
potential contribution of X- and Ku-band synthetic aperture radar (SAR) for
global monitoring of SWE. SAR can image the surface during both day and
night regardless of cloud cover, allowing high-frequency revisit at high
spatial resolution as demonstrated by missions such as Sentinel-1. The
physical basis for estimating SWE from X- and Ku-band radar measurements at
local scales is volume scattering by millimeter-scale snow grains. Inference
of global snow properties from SAR requires an interdisciplinary approach
based on field observations of snow microstructure, physical snow modeling,
electromagnetic theory, and retrieval strategies over a range of scales. New
field measurement capabilities have enabled significant advances in
understanding snow microstructure such as grain size, density, and layering.
We describe radar interactions with snow-covered landscapes, the small but
rapidly growing number of field datasets used to evaluate retrieval
algorithms, the characterization of snowpack properties using radar
measurements, and the refinement of retrieval algorithms via synergy with
other microwave remote sensing approaches. This review serves to inform the
broader snow research, monitoring, and application communities on progress
made in recent decades and sets the stage for a new era in SWE
remote sensing from SAR measurements.