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: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) |
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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), 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 |
_version_ |
1772187835378434048 |