Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation

Sea ice models have become essential components of weather, climate and ocean models. The reliability of process studies, environmental forecasts and climate projections alike depend on a realistic representation of sea ice. Developing and evaluating sea ice models requires methods for both large sc...

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Main Authors: Mohammadi Aragh, Mahdi, Losch, Martin, Goessling, Helge
Format: Conference Object
Language:unknown
Published: 2020
Subjects:
Online Access:https://epic.awi.de/id/eprint/51863/
https://epic.awi.de/id/eprint/51863/1/EGU2020_MMA.pdf
https://meetingorganizer.copernicus.org/EGU2020/EGU2020-18293.html
https://hdl.handle.net/10013/epic.1ac8cc90-bb80-4f88-9691-083dc140f01f
https://hdl.handle.net/
id ftawi:oai:epic.awi.de:51863
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spelling ftawi:oai:epic.awi.de:51863 2023-05-15T14:27:17+02:00 Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation Mohammadi Aragh, Mahdi Losch, Martin Goessling, Helge 2020-05-08 application/pdf https://epic.awi.de/id/eprint/51863/ https://epic.awi.de/id/eprint/51863/1/EGU2020_MMA.pdf https://meetingorganizer.copernicus.org/EGU2020/EGU2020-18293.html https://hdl.handle.net/10013/epic.1ac8cc90-bb80-4f88-9691-083dc140f01f https://hdl.handle.net/ unknown https://epic.awi.de/id/eprint/51863/1/EGU2020_MMA.pdf https://hdl.handle.net/ Mohammadi Aragh, M. , Losch, M. orcid:0000-0002-3824-5244 and Goessling, H. orcid:0000-0001-9018-1383 (2020) Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation , EGU General Assembly, Virtual Vienna, 4 May 2020 - 8 May 2020 . hdl:10013/epic.1ac8cc90-bb80-4f88-9691-083dc140f01f EPIC3EGU General Assembly, Virtual Vienna, 2020-05-04-2020-05-08 Conference notRev 2020 ftawi 2021-12-24T15:45:30Z Sea ice models have become essential components of weather, climate and ocean models. The reliability of process studies, environmental forecasts and climate projections alike depend on a realistic representation of sea ice. Developing and evaluating sea ice models requires methods for both large scales and fine-scale geomorphological structures such as linear kinematic features (LKF). We introduce a Multiscale Directional Analysis (MDA) method that diagnoses distributions of LKF orientation and intersection angles. The MDA method is different from previous methods in that it (a) takes into account the width of LKFs instead of estimating the orientation of centerlines; (b) separates curve-like features from point-like features providing the opportunity to reach a unified definition of LKF in both numerical and observational fields; (c) estimates scale-dependent intersection angles. Conference Object Arctic Arctic Sea ice Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Arctic
institution Open Polar
collection Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center)
op_collection_id ftawi
language unknown
description Sea ice models have become essential components of weather, climate and ocean models. The reliability of process studies, environmental forecasts and climate projections alike depend on a realistic representation of sea ice. Developing and evaluating sea ice models requires methods for both large scales and fine-scale geomorphological structures such as linear kinematic features (LKF). We introduce a Multiscale Directional Analysis (MDA) method that diagnoses distributions of LKF orientation and intersection angles. The MDA method is different from previous methods in that it (a) takes into account the width of LKFs instead of estimating the orientation of centerlines; (b) separates curve-like features from point-like features providing the opportunity to reach a unified definition of LKF in both numerical and observational fields; (c) estimates scale-dependent intersection angles.
format Conference Object
author Mohammadi Aragh, Mahdi
Losch, Martin
Goessling, Helge
spellingShingle Mohammadi Aragh, Mahdi
Losch, Martin
Goessling, Helge
Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation
author_facet Mohammadi Aragh, Mahdi
Losch, Martin
Goessling, Helge
author_sort Mohammadi Aragh, Mahdi
title Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation
title_short Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation
title_full Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation
title_fullStr Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation
title_full_unstemmed Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation
title_sort comparing arctic sea ice model simulations to satellite observations by multiscale directional analysis of sea ice deformation
publishDate 2020
url https://epic.awi.de/id/eprint/51863/
https://epic.awi.de/id/eprint/51863/1/EGU2020_MMA.pdf
https://meetingorganizer.copernicus.org/EGU2020/EGU2020-18293.html
https://hdl.handle.net/10013/epic.1ac8cc90-bb80-4f88-9691-083dc140f01f
https://hdl.handle.net/
geographic Arctic
geographic_facet Arctic
genre Arctic
Arctic
Sea ice
genre_facet Arctic
Arctic
Sea ice
op_source EPIC3EGU General Assembly, Virtual Vienna, 2020-05-04-2020-05-08
op_relation https://epic.awi.de/id/eprint/51863/1/EGU2020_MMA.pdf
https://hdl.handle.net/
Mohammadi Aragh, M. , Losch, M. orcid:0000-0002-3824-5244 and Goessling, H. orcid:0000-0001-9018-1383 (2020) Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation , EGU General Assembly, Virtual Vienna, 4 May 2020 - 8 May 2020 . hdl:10013/epic.1ac8cc90-bb80-4f88-9691-083dc140f01f
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