A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery
The presence of sea ice leads in the sea ice cover represents a key feature in polar regions by controlling the heat exchange between the relatively warm ocean and cold atmosphere due to increased fluxes of turbulent sensible and latent heat. Sea ice leads contribute to the sea ice production and ar...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-06-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/12/1957 |
| _version_ | 1797564986028982272 |
|---|---|
| author | Fabian Reiser Sascha Willmes Günther Heinemann |
| author_facet | Fabian Reiser Sascha Willmes Günther Heinemann |
| author_sort | Fabian Reiser |
| collection | DOAJ |
| description | The presence of sea ice leads in the sea ice cover represents a key feature in polar regions by controlling the heat exchange between the relatively warm ocean and cold atmosphere due to increased fluxes of turbulent sensible and latent heat. Sea ice leads contribute to the sea ice production and are sources for the formation of dense water which affects the ocean circulation. Atmospheric and ocean models strongly rely on observational data to describe the respective state of the sea ice since numerical models are not able to produce sea ice leads explicitly. For the Arctic, some lead datasets are available, but for the Antarctic, no such data yet exist. Our study presents a new algorithm with which leads are automatically identified in satellite thermal infrared images. A variety of lead metrics is used to distinguish between true leads and detection artefacts with the use of fuzzy logic. We evaluate the outputs and provide pixel-wise uncertainties. Our data yield daily sea ice lead maps at a resolution of 1 km<sup>2</sup> for the winter months November– April 2002/03–2018/19 (Arctic) and April–September 2003–2019 (Antarctic), respectively. The long-term average of the lead frequency distributions show distinct features related to bathymetric structures in both hemispheres. |
| first_indexed | 2024-03-10T19:05:35Z |
| format | Article |
| id | doaj.art-e98cd67617374bd1ab3ce8b75625729c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T19:05:35Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e98cd67617374bd1ab3ce8b75625729c2023-11-20T04:10:17ZengMDPI AGRemote Sensing2072-42922020-06-011212195710.3390/rs12121957A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite ImageryFabian Reiser0Sascha Willmes1Günther Heinemann2Department of Environmental Meteorology, University of Trier, 54296 Trier, GermanyDepartment of Environmental Meteorology, University of Trier, 54296 Trier, GermanyDepartment of Environmental Meteorology, University of Trier, 54296 Trier, GermanyThe presence of sea ice leads in the sea ice cover represents a key feature in polar regions by controlling the heat exchange between the relatively warm ocean and cold atmosphere due to increased fluxes of turbulent sensible and latent heat. Sea ice leads contribute to the sea ice production and are sources for the formation of dense water which affects the ocean circulation. Atmospheric and ocean models strongly rely on observational data to describe the respective state of the sea ice since numerical models are not able to produce sea ice leads explicitly. For the Arctic, some lead datasets are available, but for the Antarctic, no such data yet exist. Our study presents a new algorithm with which leads are automatically identified in satellite thermal infrared images. A variety of lead metrics is used to distinguish between true leads and detection artefacts with the use of fuzzy logic. We evaluate the outputs and provide pixel-wise uncertainties. Our data yield daily sea ice lead maps at a resolution of 1 km<sup>2</sup> for the winter months November– April 2002/03–2018/19 (Arctic) and April–September 2003–2019 (Antarctic), respectively. The long-term average of the lead frequency distributions show distinct features related to bathymetric structures in both hemispheres.https://www.mdpi.com/2072-4292/12/12/1957sea iceleadsMODISArcticAntarcticpolar regions |
| spellingShingle | Fabian Reiser Sascha Willmes Günther Heinemann A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery Remote Sensing sea ice leads MODIS Arctic Antarctic polar regions |
| title | A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery |
| title_full | A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery |
| title_fullStr | A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery |
| title_full_unstemmed | A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery |
| title_short | A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery |
| title_sort | new algorithm for daily sea ice lead identification in the arctic and antarctic winter from thermal infrared satellite imagery |
| topic | sea ice leads MODIS Arctic Antarctic polar regions |
| url | https://www.mdpi.com/2072-4292/12/12/1957 |
| work_keys_str_mv | AT fabianreiser anewalgorithmfordailyseaiceleadidentificationinthearcticandantarcticwinterfromthermalinfraredsatelliteimagery AT saschawillmes anewalgorithmfordailyseaiceleadidentificationinthearcticandantarcticwinterfromthermalinfraredsatelliteimagery AT guntherheinemann anewalgorithmfordailyseaiceleadidentificationinthearcticandantarcticwinterfromthermalinfraredsatelliteimagery AT fabianreiser newalgorithmfordailyseaiceleadidentificationinthearcticandantarcticwinterfromthermalinfraredsatelliteimagery AT saschawillmes newalgorithmfordailyseaiceleadidentificationinthearcticandantarcticwinterfromthermalinfraredsatelliteimagery AT guntherheinemann newalgorithmfordailyseaiceleadidentificationinthearcticandantarcticwinterfromthermalinfraredsatelliteimagery |