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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Main Authors: Pan, Jinmei, Durand, Michael, Lemmetyinen, Juha, Liu, Desheng, Shi, Jiancheng
Format: Text
Language:English
Published: 2023
Subjects:
Online Access:https://doi.org/10.5194/tc-2023-85
https://tc.copernicus.org/preprints/tc-2023-85/
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spelling ftcopernicus:oai:publications.copernicus.org:tcd112068 2023-07-23T04:21:45+02:00 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 2023-06-27 application/pdf https://doi.org/10.5194/tc-2023-85 https://tc.copernicus.org/preprints/tc-2023-85/ eng eng doi:10.5194/tc-2023-85 https://tc.copernicus.org/preprints/tc-2023-85/ eISSN: 1994-0424 Text 2023 ftcopernicus https://doi.org/10.5194/tc-2023-85 2023-07-03T16:24:18Z 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), VV polarization obtained at 50° incidence angle from the Nordic Snow Radar Experiment (NoSREx) in Sodankylä, Finland. We assume only an uninformative prior for snow microstructure, in contrast with an accurate prior required in previous studies. Starting from a biased SWE prior from land surface model simulation, two-layer snow state variables and single-layer soil variables are 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). Results show that BASE-AM achieved a RMSE of ~10 cm for snow depth (SD) and less than 30 mm for SWE, compared with the RMSE of ~20 cm SD 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 shows that providing a fully-unbiased snow microstructure prior is not the only promise to obtain accurate SWE retrievals. Text Sodankylä Copernicus Publications: E-Journals Sodankylä ENVELOPE(26.600,26.600,67.417,67.417)
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), VV polarization obtained at 50° incidence angle from the Nordic Snow Radar Experiment (NoSREx) in Sodankylä, Finland. We assume only an uninformative prior for snow microstructure, in contrast with an accurate prior required in previous studies. Starting from a biased SWE prior from land surface model simulation, two-layer snow state variables and single-layer soil variables are 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). Results show that BASE-AM achieved a RMSE of ~10 cm for snow depth (SD) and less than 30 mm for SWE, compared with the RMSE of ~20 cm SD 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 shows that providing a fully-unbiased snow microstructure prior is not the only promise to obtain accurate SWE retrievals.
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 2023
url https://doi.org/10.5194/tc-2023-85
https://tc.copernicus.org/preprints/tc-2023-85/
long_lat ENVELOPE(26.600,26.600,67.417,67.417)
geographic Sodankylä
geographic_facet Sodankylä
genre Sodankylä
genre_facet Sodankylä
op_source eISSN: 1994-0424
op_relation doi:10.5194/tc-2023-85
https://tc.copernicus.org/preprints/tc-2023-85/
op_doi https://doi.org/10.5194/tc-2023-85
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