Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss

Yurong Cui,Lingmei Jiang,Tongxi Hu,Dabin Ji,Chuan Xiong,Bin Peng,Jiancheng Shi,Juha Lemmetyinen,Tianjie Zhao,Huixuan Li

doi:10.3390/rs8060505

Abstract

Snow water equivalent (SWE) is a key parameter in the Earth’s energy budget and water cycle. It has been demonstrated that SWE can be retrieved using active microwave remote sensing from space. This necessitates the development of forward models that are capable of simulating the interactions of microwaves and the snow medium. Several proposed models have described snow as a collection of sphere- or ellipsoid-shaped ice particles embedded in air, while the microstructure of snow is, in reality, more complex. Natural snow usually forms a sintered structure following mechanical and thermal metamorphism processes. In this research, the bi-continuous vector radiative transfer (bi-continuous-VRT) model, which firstly constructs snow microstructure more similar to real snow and then simulates the snow backscattering signal, is used as the forward model for SWE estimation. Based on this forward model, a parameterization scheme of snow volume backscattering is proposed. A relationship between snow optical thickness and single scattering albedo at X and Ku bands is established by analyzing the database generated from the bi-continuous-VRT model. A cost function with constraints is used to solve effective albedo and optical thickness, while the absorption part of optical thickness is obtained from these two parameters. SWE is estimated after a correction for physical temperature. The estimated SWE is correlated with the measured SWE with an acceptable accuracy. Validation against two-year measurements, using the SnowScat instrument from the Nordic Snow Radar Experiment (NoSREx), shows that the estimated SWE using the presented algorithm has a root mean square error (RMSE) of 16.59 mm for the winter of 2009–2010 and 19.70 mm for the winter of 2010–2011.

Highlights

Snow cover can reflect a large part of incident solar radiation because of its high albedo and a large amount of water resources store in the snowpack, which are the primary source of water for river channel discharge in the middle-to-high latitude areas
This algorithm is based on a physical model in which the snow scattering is simulated by the bi-continuous-VRT model and the soil surface backscattering before snowfall is regarded as the ground backscattering under snow cover
To validate the accuracy of forward model, Advanced Integral Equation Model (AIEM) and Oh models were coupled to the bi-continuous-VRT under the measured soil surface parameters

Summary

Introduction

Snow cover can reflect a large part of incident solar radiation because of its high albedo and a large amount of water resources store in the snowpack, which are the primary source of water for river channel discharge in the middle-to-high latitude areas. Due to the inhomogeneous distribution of snow cover on the surface of the Earth, traditional in situ measurement techniques can hardly provide sufficient coverage of snow information. In the last few decades, remote sensing has proven to be an important technique for observing snow cover at large scales. Optical and near-infrared remote sensing have been successfully applied to snow cover mapping at relatively high spatial resolutions [6]. These observations are often affected by poor weather and insufficient lighting conditions. Microwave remote sensing can obtain snowpack information for all time and weather conditions because of its target-penetrating abilities [7]

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Conclusion