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

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 mic...

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Main Authors: Yurong Cui, Chuan Xiong, Juha Lemmetyinen, Jiancheng Shi, Lingmei Jiang, Bin Peng, Huixuan Li, Tianjie Zhao, Dabin Ji, Tongxi Hu
Format: Article
Language:English
Published: MDPI AG 2016-06-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/8/6/505
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spelling doaj-2539e2709d5e467f9c292dcfade628d22020-11-24T23:55:57ZengMDPI AGRemote Sensing2072-42922016-06-018650510.3390/rs8060505rs8060505Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption LossYurong Cui0Chuan Xiong1Juha Lemmetyinen2Jiancheng Shi3Lingmei Jiang4Bin Peng5Huixuan Li6Tianjie Zhao7Dabin Ji8Tongxi Hu9State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaFinnish Meteorological Institute, P.O. Box 503, Helsinki Fin-00101, FinlandState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaDepartment of Geography, University of South Carolina, Callcott Building 709 Bull Street, Columbia, SC 29208, USAState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaSnow 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.http://www.mdpi.com/2072-4292/8/6/505snow water equivalentactive microwave remote sensingbi-continuousX and Ku
collection DOAJ
language English
format Article
sources DOAJ
author Yurong Cui
Chuan Xiong
Juha Lemmetyinen
Jiancheng Shi
Lingmei Jiang
Bin Peng
Huixuan Li
Tianjie Zhao
Dabin Ji
Tongxi Hu
spellingShingle Yurong Cui
Chuan Xiong
Juha Lemmetyinen
Jiancheng Shi
Lingmei Jiang
Bin Peng
Huixuan Li
Tianjie Zhao
Dabin Ji
Tongxi Hu
Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss
Remote Sensing
snow water equivalent
active microwave remote sensing
bi-continuous
X and Ku
author_facet Yurong Cui
Chuan Xiong
Juha Lemmetyinen
Jiancheng Shi
Lingmei Jiang
Bin Peng
Huixuan Li
Tianjie Zhao
Dabin Ji
Tongxi Hu
author_sort Yurong Cui
title Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss
title_short Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss
title_full Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss
title_fullStr Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss
title_full_unstemmed Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss
title_sort estimating snow water equivalent with backscattering at x and ku band based on absorption loss
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2016-06-01
description 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.
topic snow water equivalent
active microwave remote sensing
bi-continuous
X and Ku
url http://www.mdpi.com/2072-4292/8/6/505
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