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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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 |
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Open Polar |
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Copernicus Publications: E-Journals |
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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 |
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The Cryosphere |
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18 |
container_issue |
4 |
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1561 |
op_container_end_page |
1578 |
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1810479167305678848 |