Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling

Melt ponds play a crucial role in the melting of Arctic sea ice. Studying the evolution of melt ponds is essential for understanding changes in Arctic sea ice. In this study, we used a revised sea ice model to simulate the evolution of melt ponds along the MOSAiC drift at a resolution of 10 m. A nov...

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Main Authors: Mingfeng Wang, Felix Linhardt, Victor Lion, Natascha Oppelt
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/16/19/3748
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author Mingfeng Wang
Felix Linhardt
Victor Lion
Natascha Oppelt
author_facet Mingfeng Wang
Felix Linhardt
Victor Lion
Natascha Oppelt
author_sort Mingfeng Wang
collection DOAJ
description Melt ponds play a crucial role in the melting of Arctic sea ice. Studying the evolution of melt ponds is essential for understanding changes in Arctic sea ice. In this study, we used a revised sea ice model to simulate the evolution of melt ponds along the MOSAiC drift at a resolution of 10 m. A novel melt pond parameterization scheme simulates the movement of meltwater under the influence of gravity over a realistic sea ice topography. We evaluated different melt pond parameterization schemes based on remote sensing observations. The absolute deviation of the maximum pond coverage simulated by the new scheme is within 3%, while differences among parameterization schemes exceed 50%. Errors were found to be primarily due to the calculation of macroscopic meltwater loss, which is related to sea ice surface topography. Previous studies have indicated that sea ice with a lower surface roughness has a larger catchment area, resulting in larger pond coverage during the melt season. This study has identified an opposing mechanism: sea ice with lower surface roughness has a larger catchment area connected to the macroscopic flaws of the sea ice surface, which leads to more macroscopic drainage into the ocean and thereby a decrease in melt pond coverage. Experimental simulations showed that sea ice with 46% higher surface roughness, resulting in 12% less macroscopic drainage, exhibited a 38% higher maximum pond fraction. The presence of macroscopic flaws is related to the fragmentation of sea ice cover. As Arctic sea ice cover becomes increasingly fragmented and mobile, this mechanism will become more significant.
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spelling doaj-art-9290973caa8841eda0591e06ae2ac41f2025-08-20T01:47:37ZengMDPI AGRemote Sensing2072-42922024-10-011619374810.3390/rs16193748Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and ModelingMingfeng Wang0Felix Linhardt1Victor Lion2Natascha Oppelt3Earth Observation and Modelling, Department of Geography, Kiel University, Ludewig-Meyn-Str. 8, 24098 Kiel, GermanyEarth Observation and Modelling, Department of Geography, Kiel University, Ludewig-Meyn-Str. 8, 24098 Kiel, GermanyEarth Observation and Modelling, Department of Geography, Kiel University, Ludewig-Meyn-Str. 8, 24098 Kiel, GermanyEarth Observation and Modelling, Department of Geography, Kiel University, Ludewig-Meyn-Str. 8, 24098 Kiel, GermanyMelt ponds play a crucial role in the melting of Arctic sea ice. Studying the evolution of melt ponds is essential for understanding changes in Arctic sea ice. In this study, we used a revised sea ice model to simulate the evolution of melt ponds along the MOSAiC drift at a resolution of 10 m. A novel melt pond parameterization scheme simulates the movement of meltwater under the influence of gravity over a realistic sea ice topography. We evaluated different melt pond parameterization schemes based on remote sensing observations. The absolute deviation of the maximum pond coverage simulated by the new scheme is within 3%, while differences among parameterization schemes exceed 50%. Errors were found to be primarily due to the calculation of macroscopic meltwater loss, which is related to sea ice surface topography. Previous studies have indicated that sea ice with a lower surface roughness has a larger catchment area, resulting in larger pond coverage during the melt season. This study has identified an opposing mechanism: sea ice with lower surface roughness has a larger catchment area connected to the macroscopic flaws of the sea ice surface, which leads to more macroscopic drainage into the ocean and thereby a decrease in melt pond coverage. Experimental simulations showed that sea ice with 46% higher surface roughness, resulting in 12% less macroscopic drainage, exhibited a 38% higher maximum pond fraction. The presence of macroscopic flaws is related to the fragmentation of sea ice cover. As Arctic sea ice cover becomes increasingly fragmented and mobile, this mechanism will become more significant.https://www.mdpi.com/2072-4292/16/19/3748sea icemelt pondremote sensingmodeling
spellingShingle Mingfeng Wang
Felix Linhardt
Victor Lion
Natascha Oppelt
Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling
Remote Sensing
sea ice
melt pond
remote sensing
modeling
title Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling
title_full Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling
title_fullStr Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling
title_full_unstemmed Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling
title_short Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling
title_sort melt pond evolution along the mosaic drift insights from remote sensing and modeling
topic sea ice
melt pond
remote sensing
modeling
url https://www.mdpi.com/2072-4292/16/19/3748
work_keys_str_mv AT mingfengwang meltpondevolutionalongthemosaicdriftinsightsfromremotesensingandmodeling
AT felixlinhardt meltpondevolutionalongthemosaicdriftinsightsfromremotesensingandmodeling
AT victorlion meltpondevolutionalongthemosaicdriftinsightsfromremotesensingandmodeling
AT nataschaoppelt meltpondevolutionalongthemosaicdriftinsightsfromremotesensingandmodeling