Evaluation of Sea Ice Concentration Data Using Dual-Polarized Ratio Algorithm in Comparison With Other Satellite Passive Microwave Sea Ice Concentration Data Sets and Ship-Based Visual Observations
The dual-polarized ratio (DPR) algorithm is a new algorithm that enable calculation of Arctic sea ice concentration from the 36.5-GHz channel of the sensor Advanced Microwave Scanning Radiometer for EOS/Advanced Microwave Scanning Radiometer 2 (AMSR-E/AMSR2). In this paper, we demonstrate results th...
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ftdoajarticles:oai:doaj.org/article:a6d46039a5404f1a865c3f33522df47c 2023-05-15T14:55:22+02:00 Evaluation of Sea Ice Concentration Data Using Dual-Polarized Ratio Algorithm in Comparison With Other Satellite Passive Microwave Sea Ice Concentration Data Sets and Ship-Based Visual Observations Fangyi Zong Shugang Zhang Ping Chen Lipeng Yang Qiuli Shao Jinping Zhao Lai Wei 2022-04-01T00:00:00Z https://doi.org/10.3389/fenvs.2022.856289 https://doaj.org/article/a6d46039a5404f1a865c3f33522df47c EN eng Frontiers Media S.A. https://www.frontiersin.org/articles/10.3389/fenvs.2022.856289/full https://doaj.org/toc/2296-665X 2296-665X doi:10.3389/fenvs.2022.856289 https://doaj.org/article/a6d46039a5404f1a865c3f33522df47c Frontiers in Environmental Science, Vol 10 (2022) Arctic sea ice concentraiton brightness temperature remote sensing products passive microwave Environmental sciences GE1-350 article 2022 ftdoajarticles https://doi.org/10.3389/fenvs.2022.856289 2022-12-31T11:41:53Z The dual-polarized ratio (DPR) algorithm is a new algorithm that enable calculation of Arctic sea ice concentration from the 36.5-GHz channel of the sensor Advanced Microwave Scanning Radiometer for EOS/Advanced Microwave Scanning Radiometer 2 (AMSR-E/AMSR2). In this paper, we demonstrate results that the sea ice concentration data using DPR algorithm (DPR-AMSR) are evaluated and compared with other eight Arctic sea ice concentration data products with respect to differences in sea ice concentration, sea ice area, and sea ice extent. On a pan-Arctic scale, the evaluation results are mostly very similar between DPR-AMSR and the bootstrap algorithm from AMSR-E/AMSR2 (BT-AMSR), the bootstrap algorithm from SSM/I or SSMIS (BT-SSMI), the ARTIST Sea Ice algorithm from AMSR-E/AMSR2 (ASI-AMSR), and the enhanced NASA Team algorithm from AMSR-E/AMSR2 (NT2-AMSR). Among of these products, the differences in sea ice concentration agree within ±5%. However, European Space Agency Climate Change Initiative algorithm from AMSR-E/AMSR2 (SICCI-AMSR), the European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility from SSM/I or SSMIS (OSI-SSMI), the ARTIST Sea Ice algorithm from SSM/I or SSMIS (ASI-SSMI), and the NASA Team algorithm from SSM/I or SSMIS (NT1-SSMI) are all lower than DPR-AMSR at sea ice edge. And NT1-SSMI had the largest negative difference, which was lower than -15% or even 20%.The difference of sea ice area was consistently within ±0.5 million km2 between DPR-AMSR and BT-AMSR, BT-SSMI, ASI-AMSR, and NT2-AMSR in all years. The smallest difference was with BT-SSMI (less than 0.1 million km2), whereas the largest difference was with NT1-SSMI (up to 1.5 million km2). In comparisons of sea ice extent, BT-AMSR, NT1-SSMI, and NT2-AMSR estimates were consistent with that of DPR-AMSR and were within ±0.5 million km2. However, differences exceeded 0.5 million km2 between DPR-AMSR and the other data sets. When ship-based visual observation (OBS) values ranged from ... Article in Journal/Newspaper Arctic Climate change Sea ice Directory of Open Access Journals: DOAJ Articles Arctic Frontiers in Environmental Science 10 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic sea ice concentraiton brightness temperature remote sensing products passive microwave Environmental sciences GE1-350 |
spellingShingle |
Arctic sea ice concentraiton brightness temperature remote sensing products passive microwave Environmental sciences GE1-350 Fangyi Zong Shugang Zhang Ping Chen Lipeng Yang Qiuli Shao Jinping Zhao Lai Wei Evaluation of Sea Ice Concentration Data Using Dual-Polarized Ratio Algorithm in Comparison With Other Satellite Passive Microwave Sea Ice Concentration Data Sets and Ship-Based Visual Observations |
topic_facet |
Arctic sea ice concentraiton brightness temperature remote sensing products passive microwave Environmental sciences GE1-350 |
description |
The dual-polarized ratio (DPR) algorithm is a new algorithm that enable calculation of Arctic sea ice concentration from the 36.5-GHz channel of the sensor Advanced Microwave Scanning Radiometer for EOS/Advanced Microwave Scanning Radiometer 2 (AMSR-E/AMSR2). In this paper, we demonstrate results that the sea ice concentration data using DPR algorithm (DPR-AMSR) are evaluated and compared with other eight Arctic sea ice concentration data products with respect to differences in sea ice concentration, sea ice area, and sea ice extent. On a pan-Arctic scale, the evaluation results are mostly very similar between DPR-AMSR and the bootstrap algorithm from AMSR-E/AMSR2 (BT-AMSR), the bootstrap algorithm from SSM/I or SSMIS (BT-SSMI), the ARTIST Sea Ice algorithm from AMSR-E/AMSR2 (ASI-AMSR), and the enhanced NASA Team algorithm from AMSR-E/AMSR2 (NT2-AMSR). Among of these products, the differences in sea ice concentration agree within ±5%. However, European Space Agency Climate Change Initiative algorithm from AMSR-E/AMSR2 (SICCI-AMSR), the European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility from SSM/I or SSMIS (OSI-SSMI), the ARTIST Sea Ice algorithm from SSM/I or SSMIS (ASI-SSMI), and the NASA Team algorithm from SSM/I or SSMIS (NT1-SSMI) are all lower than DPR-AMSR at sea ice edge. And NT1-SSMI had the largest negative difference, which was lower than -15% or even 20%.The difference of sea ice area was consistently within ±0.5 million km2 between DPR-AMSR and BT-AMSR, BT-SSMI, ASI-AMSR, and NT2-AMSR in all years. The smallest difference was with BT-SSMI (less than 0.1 million km2), whereas the largest difference was with NT1-SSMI (up to 1.5 million km2). In comparisons of sea ice extent, BT-AMSR, NT1-SSMI, and NT2-AMSR estimates were consistent with that of DPR-AMSR and were within ±0.5 million km2. However, differences exceeded 0.5 million km2 between DPR-AMSR and the other data sets. When ship-based visual observation (OBS) values ranged from ... |
format |
Article in Journal/Newspaper |
author |
Fangyi Zong Shugang Zhang Ping Chen Lipeng Yang Qiuli Shao Jinping Zhao Lai Wei |
author_facet |
Fangyi Zong Shugang Zhang Ping Chen Lipeng Yang Qiuli Shao Jinping Zhao Lai Wei |
author_sort |
Fangyi Zong |
title |
Evaluation of Sea Ice Concentration Data Using Dual-Polarized Ratio Algorithm in Comparison With Other Satellite Passive Microwave Sea Ice Concentration Data Sets and Ship-Based Visual Observations |
title_short |
Evaluation of Sea Ice Concentration Data Using Dual-Polarized Ratio Algorithm in Comparison With Other Satellite Passive Microwave Sea Ice Concentration Data Sets and Ship-Based Visual Observations |
title_full |
Evaluation of Sea Ice Concentration Data Using Dual-Polarized Ratio Algorithm in Comparison With Other Satellite Passive Microwave Sea Ice Concentration Data Sets and Ship-Based Visual Observations |
title_fullStr |
Evaluation of Sea Ice Concentration Data Using Dual-Polarized Ratio Algorithm in Comparison With Other Satellite Passive Microwave Sea Ice Concentration Data Sets and Ship-Based Visual Observations |
title_full_unstemmed |
Evaluation of Sea Ice Concentration Data Using Dual-Polarized Ratio Algorithm in Comparison With Other Satellite Passive Microwave Sea Ice Concentration Data Sets and Ship-Based Visual Observations |
title_sort |
evaluation of sea ice concentration data using dual-polarized ratio algorithm in comparison with other satellite passive microwave sea ice concentration data sets and ship-based visual observations |
publisher |
Frontiers Media S.A. |
publishDate |
2022 |
url |
https://doi.org/10.3389/fenvs.2022.856289 https://doaj.org/article/a6d46039a5404f1a865c3f33522df47c |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change Sea ice |
genre_facet |
Arctic Climate change Sea ice |
op_source |
Frontiers in Environmental Science, Vol 10 (2022) |
op_relation |
https://www.frontiersin.org/articles/10.3389/fenvs.2022.856289/full https://doaj.org/toc/2296-665X 2296-665X doi:10.3389/fenvs.2022.856289 https://doaj.org/article/a6d46039a5404f1a865c3f33522df47c |
op_doi |
https://doi.org/10.3389/fenvs.2022.856289 |
container_title |
Frontiers in Environmental Science |
container_volume |
10 |
_version_ |
1766327159835590656 |