Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method

Radar at high frequency is a promising technique for fine-resolution snow water equivalent (SWE) mapping. In this paper, we extend the Bayesian-based Algorithm for SWE Estimation (BASE) from passive to active microwave (AM) application and test it using ground-based backscattering measurements at th...

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Published in:The Cryosphere
Main Authors: Pan, Jinmei, Durand, Michael, Lemmetyinen, Juha, Liu, Desheng, Shi, Jiancheng
Format: Text
Language:English
Published: 2024
Subjects:
Online Access:https://doi.org/10.5194/tc-18-1561-2024
https://tc.copernicus.org/articles/18/1561/2024/
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spelling ftcopernicus:oai:publications.copernicus.org:tc112068 2024-09-15T18:35:58+00:00 Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method Pan, Jinmei Durand, Michael Lemmetyinen, Juha Liu, Desheng Shi, Jiancheng 2024-04-05 application/pdf https://doi.org/10.5194/tc-18-1561-2024 https://tc.copernicus.org/articles/18/1561/2024/ eng eng doi:10.5194/tc-18-1561-2024 https://tc.copernicus.org/articles/18/1561/2024/ eISSN: 1994-0424 Text 2024 ftcopernicus https://doi.org/10.5194/tc-18-1561-2024 2024-08-28T05:24:15Z Radar at high frequency is a promising technique for fine-resolution snow water equivalent (SWE) mapping. In this paper, we extend the Bayesian-based Algorithm for SWE Estimation (BASE) from passive to active microwave (AM) application and test it using ground-based backscattering measurements at three frequencies (X and dual Ku bands; 10.2, 13.3, and 16.7 GHz), with VV polarization obtained at a 50° incidence angle from the Nordic Snow Radar Experiment (NoSREx) in Sodankylä, Finland. We assumed only an uninformative prior for snow microstructure, in contrast with an accurate prior required in previous studies. Starting from a biased monthly SWE prior from land surface model simulation, two-layer snow state variables and single-layer soil variables were iterated until their posterior distribution could stably reproduce the observed microwave signals. The observation model is the Microwave Emission Model of Layered Snowpacks 3 and Active (MEMLS3&a) based on the improved Born approximation. Results show that BASE-AM achieved an RMSE of ∼ 10 cm for snow depth and less than 30 mm for SWE, compared with the RMSE of ∼ 20 cm snow depth and ∼ 50 mm SWE from priors. Retrieval errors are significantly larger when BASE-AM is run using a single snow layer. The results support the potential of X- and Ku-band radar for SWE retrieval and show that the role of a precise snow microstructure prior in SWE retrieval may be substituted by an SWE prior from exterior sources. Text Sodankylä Copernicus Publications: E-Journals The Cryosphere 18 4 1561 1578
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description Radar at high frequency is a promising technique for fine-resolution snow water equivalent (SWE) mapping. In this paper, we extend the Bayesian-based Algorithm for SWE Estimation (BASE) from passive to active microwave (AM) application and test it using ground-based backscattering measurements at three frequencies (X and dual Ku bands; 10.2, 13.3, and 16.7 GHz), with VV polarization obtained at a 50° incidence angle from the Nordic Snow Radar Experiment (NoSREx) in Sodankylä, Finland. We assumed only an uninformative prior for snow microstructure, in contrast with an accurate prior required in previous studies. Starting from a biased monthly SWE prior from land surface model simulation, two-layer snow state variables and single-layer soil variables were iterated until their posterior distribution could stably reproduce the observed microwave signals. The observation model is the Microwave Emission Model of Layered Snowpacks 3 and Active (MEMLS3&a) based on the improved Born approximation. Results show that BASE-AM achieved an RMSE of ∼ 10 cm for snow depth and less than 30 mm for SWE, compared with the RMSE of ∼ 20 cm snow depth and ∼ 50 mm SWE from priors. Retrieval errors are significantly larger when BASE-AM is run using a single snow layer. The results support the potential of X- and Ku-band radar for SWE retrieval and show that the role of a precise snow microstructure prior in SWE retrieval may be substituted by an SWE prior from exterior sources.
format Text
author Pan, Jinmei
Durand, Michael
Lemmetyinen, Juha
Liu, Desheng
Shi, Jiancheng
spellingShingle Pan, Jinmei
Durand, Michael
Lemmetyinen, Juha
Liu, Desheng
Shi, Jiancheng
Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
author_facet Pan, Jinmei
Durand, Michael
Lemmetyinen, Juha
Liu, Desheng
Shi, Jiancheng
author_sort Pan, Jinmei
title Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
title_short Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
title_full Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
title_fullStr Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
title_full_unstemmed Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
title_sort snow water equivalent retrieved from x- and dual ku-band scatterometer measurements at sodankylä using the markov chain monte carlo method
publishDate 2024
url https://doi.org/10.5194/tc-18-1561-2024
https://tc.copernicus.org/articles/18/1561/2024/
genre Sodankylä
genre_facet Sodankylä
op_source eISSN: 1994-0424
op_relation doi:10.5194/tc-18-1561-2024
https://tc.copernicus.org/articles/18/1561/2024/
op_doi https://doi.org/10.5194/tc-18-1561-2024
container_title The Cryosphere
container_volume 18
container_issue 4
container_start_page 1561
op_container_end_page 1578
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