Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1
Changing Arctic sea-ice extent and melt season duration, and increasing economic interest in the Arctic have prompted the need for enhanced marine ecosystem studies and improvements to dynamical and forecast models. Sea-ice melt pond fraction fp has been shown to be correlated with the September min...
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ftdoajarticles:oai:doaj.org/article:92a4dac683d64abb8878138ff1715f37 2023-05-15T13:11:29+02:00 Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1 RK Scharien R Segal JJ Yackel SEL Howell S Nasonova 2018-07-01T00:00:00Z https://doi.org/10.1017/aog.2017.43 https://doaj.org/article/92a4dac683d64abb8878138ff1715f37 EN eng Cambridge University Press https://www.cambridge.org/core/product/identifier/S026030551700043X/type/journal_article https://doaj.org/toc/0260-3055 https://doaj.org/toc/1727-5644 doi:10.1017/aog.2017.43 0260-3055 1727-5644 https://doaj.org/article/92a4dac683d64abb8878138ff1715f37 Annals of Glaciology, Vol 59, Pp 148-162 (2018) melt–surface remote sensing sea ice Meteorology. Climatology QC851-999 article 2018 ftdoajarticles https://doi.org/10.1017/aog.2017.43 2023-03-12T01:31:57Z Changing Arctic sea-ice extent and melt season duration, and increasing economic interest in the Arctic have prompted the need for enhanced marine ecosystem studies and improvements to dynamical and forecast models. Sea-ice melt pond fraction fp has been shown to be correlated with the September minimum ice extent due to its impact on ice albedo and heat uptake. Ice forecasts should benefit from knowledge of fp as melt ponds form several months in advance of ice retreat. This study goes further back by examining the potential to predict fp during winter using backscatter data from the commonly available Sentinel-1 synthetic aperture radar. An object-based image analysis links the winter and spring thermodynamic states of first-year and multiyear sea-ice types. Strong correlations between winter backscatter and spring fp, detected from high-resolution visible to near infrared imagery, are observed, and models for the retrieval of fp from Sentinel-1 data are provided (r2 ≥ 0.72). The models utilize HH polarization channel backscatter that is routinely acquired over the Arctic from the two-satellite Sentinel-1 constellation mission, as well as other past, current and future SAR missions operating in the same C-band frequency. Predicted fp is generally representative of major ice types first-year ice and multiyear ice during the stage in seasonal melt pond evolution where fp is closely related to spatial variations in ice topography. Article in Journal/Newspaper albedo Annals of Glaciology Arctic Sea ice Directory of Open Access Journals: DOAJ Articles Arctic Annals of Glaciology 59 76pt2 148 162 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
melt–surface remote sensing sea ice Meteorology. Climatology QC851-999 |
spellingShingle |
melt–surface remote sensing sea ice Meteorology. Climatology QC851-999 RK Scharien R Segal JJ Yackel SEL Howell S Nasonova Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1 |
topic_facet |
melt–surface remote sensing sea ice Meteorology. Climatology QC851-999 |
description |
Changing Arctic sea-ice extent and melt season duration, and increasing economic interest in the Arctic have prompted the need for enhanced marine ecosystem studies and improvements to dynamical and forecast models. Sea-ice melt pond fraction fp has been shown to be correlated with the September minimum ice extent due to its impact on ice albedo and heat uptake. Ice forecasts should benefit from knowledge of fp as melt ponds form several months in advance of ice retreat. This study goes further back by examining the potential to predict fp during winter using backscatter data from the commonly available Sentinel-1 synthetic aperture radar. An object-based image analysis links the winter and spring thermodynamic states of first-year and multiyear sea-ice types. Strong correlations between winter backscatter and spring fp, detected from high-resolution visible to near infrared imagery, are observed, and models for the retrieval of fp from Sentinel-1 data are provided (r2 ≥ 0.72). The models utilize HH polarization channel backscatter that is routinely acquired over the Arctic from the two-satellite Sentinel-1 constellation mission, as well as other past, current and future SAR missions operating in the same C-band frequency. Predicted fp is generally representative of major ice types first-year ice and multiyear ice during the stage in seasonal melt pond evolution where fp is closely related to spatial variations in ice topography. |
format |
Article in Journal/Newspaper |
author |
RK Scharien R Segal JJ Yackel SEL Howell S Nasonova |
author_facet |
RK Scharien R Segal JJ Yackel SEL Howell S Nasonova |
author_sort |
RK Scharien |
title |
Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1 |
title_short |
Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1 |
title_full |
Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1 |
title_fullStr |
Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1 |
title_full_unstemmed |
Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1 |
title_sort |
linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of sentinel-1 |
publisher |
Cambridge University Press |
publishDate |
2018 |
url |
https://doi.org/10.1017/aog.2017.43 https://doaj.org/article/92a4dac683d64abb8878138ff1715f37 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
albedo Annals of Glaciology Arctic Sea ice |
genre_facet |
albedo Annals of Glaciology Arctic Sea ice |
op_source |
Annals of Glaciology, Vol 59, Pp 148-162 (2018) |
op_relation |
https://www.cambridge.org/core/product/identifier/S026030551700043X/type/journal_article https://doaj.org/toc/0260-3055 https://doaj.org/toc/1727-5644 doi:10.1017/aog.2017.43 0260-3055 1727-5644 https://doaj.org/article/92a4dac683d64abb8878138ff1715f37 |
op_doi |
https://doi.org/10.1017/aog.2017.43 |
container_title |
Annals of Glaciology |
container_volume |
59 |
container_issue |
76pt2 |
container_start_page |
148 |
op_container_end_page |
162 |
_version_ |
1766247642123206656 |