Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation
The Arctic sea ice deforms constantly due to stresses imposed by winds, ocean currents and interaction with coastlines. The most dominant features produced by this deformation in the ice cover are leads and pressure ridges that are often referred to as Linear Kinematic Features (LKFs). With increasi...
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ftawi:oai:epic.awi.de:45782 2023-05-15T15:09:37+02:00 Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation Hutter, Nils Zampieri, Lorenzo Losch, Martin 2017-10-25 application/pdf https://epic.awi.de/id/eprint/45782/ https://epic.awi.de/id/eprint/45782/1/A24-Hutter-Developing_a_dataset_of_Linear_Kinematic_Features.pdf https://hdl.handle.net/10013/epic.51903 https://hdl.handle.net/10013/epic.51903.d001 unknown https://epic.awi.de/id/eprint/45782/1/A24-Hutter-Developing_a_dataset_of_Linear_Kinematic_Features.pdf https://hdl.handle.net/10013/epic.51903.d001 Hutter, N. orcid:0000-0003-3450-9422 , Zampieri, L. orcid:0000-0003-1703-4162 and Losch, M. orcid:0000-0002-3824-5244 (2017) Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation , FAMOS Workshop, Woods Hole, USA, 24 October 2017 - 27 October 2017 . hdl:10013/epic.51903 EPIC3FAMOS Workshop, Woods Hole, USA, 2017-10-24-2017-10-27 Conference notRev 2017 ftawi 2021-12-24T15:43:23Z The Arctic sea ice deforms constantly due to stresses imposed by winds, ocean currents and interaction with coastlines. The most dominant features produced by this deformation in the ice cover are leads and pressure ridges that are often referred to as Linear Kinematic Features (LKFs). With increasing resolution of classical (viscous-plastic) sea ice models, or using new rheological frameworks (e.g. Maxwell elasto-brittle), sea-ice models start to resolve this small-scale deformation. So far, scaling properties of sea-ice deformation are commonly used to evaluate the modelled LKFs, besides other measures like lead area density. These metrics evade the problem of detecting individual LKFs by taking statistics over continuous fields like sea ice deformation or concentration. This way, they can provide specific information, but lack a comprehensive description of LKFs. We detect individual LKFs in sea ice deformation fields from satellite observations with an object detection algorithm. Combining this information with the sea ice drift fields used to derive the deformation fields, the LKFs are tracked in time. In doing so, the spatial characteristics (density, length, orientation, intersection angle, curvature) as well as the temporal evolution can be extracted from the same data-set. This algorithm can be applied to modelled sea-ice deformation and drift to enable a consistent comparison and thorough evaluation of simulated sea-ice deformation. We present preliminary results of LKFs detected in the RGPS data set and give examples of possible applications. Conference Object Arctic Sea ice Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Arctic |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
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ftawi |
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description |
The Arctic sea ice deforms constantly due to stresses imposed by winds, ocean currents and interaction with coastlines. The most dominant features produced by this deformation in the ice cover are leads and pressure ridges that are often referred to as Linear Kinematic Features (LKFs). With increasing resolution of classical (viscous-plastic) sea ice models, or using new rheological frameworks (e.g. Maxwell elasto-brittle), sea-ice models start to resolve this small-scale deformation. So far, scaling properties of sea-ice deformation are commonly used to evaluate the modelled LKFs, besides other measures like lead area density. These metrics evade the problem of detecting individual LKFs by taking statistics over continuous fields like sea ice deformation or concentration. This way, they can provide specific information, but lack a comprehensive description of LKFs. We detect individual LKFs in sea ice deformation fields from satellite observations with an object detection algorithm. Combining this information with the sea ice drift fields used to derive the deformation fields, the LKFs are tracked in time. In doing so, the spatial characteristics (density, length, orientation, intersection angle, curvature) as well as the temporal evolution can be extracted from the same data-set. This algorithm can be applied to modelled sea-ice deformation and drift to enable a consistent comparison and thorough evaluation of simulated sea-ice deformation. We present preliminary results of LKFs detected in the RGPS data set and give examples of possible applications. |
format |
Conference Object |
author |
Hutter, Nils Zampieri, Lorenzo Losch, Martin |
spellingShingle |
Hutter, Nils Zampieri, Lorenzo Losch, Martin Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation |
author_facet |
Hutter, Nils Zampieri, Lorenzo Losch, Martin |
author_sort |
Hutter, Nils |
title |
Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation |
title_short |
Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation |
title_full |
Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation |
title_fullStr |
Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation |
title_full_unstemmed |
Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation |
title_sort |
developing a dataset of linear kinematic features (lkfs) for the evaluation of small-scale sea ice deformation |
publishDate |
2017 |
url |
https://epic.awi.de/id/eprint/45782/ https://epic.awi.de/id/eprint/45782/1/A24-Hutter-Developing_a_dataset_of_Linear_Kinematic_Features.pdf https://hdl.handle.net/10013/epic.51903 https://hdl.handle.net/10013/epic.51903.d001 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
EPIC3FAMOS Workshop, Woods Hole, USA, 2017-10-24-2017-10-27 |
op_relation |
https://epic.awi.de/id/eprint/45782/1/A24-Hutter-Developing_a_dataset_of_Linear_Kinematic_Features.pdf https://hdl.handle.net/10013/epic.51903.d001 Hutter, N. orcid:0000-0003-3450-9422 , Zampieri, L. orcid:0000-0003-1703-4162 and Losch, M. orcid:0000-0002-3824-5244 (2017) Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation , FAMOS Workshop, Woods Hole, USA, 24 October 2017 - 27 October 2017 . hdl:10013/epic.51903 |
_version_ |
1766340770175909888 |