Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model ...

The presence of melt ponds on Arctic summer sea ice significantly alters its albedo and thereby the surface energy budget and mass balance. Large-scale observations of melt pond coverage and sea ice albedo are crucial to investigate the role of sea ice for Arctic amplification and its representation...

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Main Authors: Niehaus, Hannah, Istomina, Larysa, Nicolaus, Marcel, Tao, Ran, Malinka, Aleksey, Zege, Eleonora, Spreen, Gunnar
Format: Article in Journal/Newspaper
Language:English
Published: Universität Bremen 2024
Subjects:
Online Access:https://dx.doi.org/10.26092/elib/2847
https://media.suub.uni-bremen.de/handle/elib/7765
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author Niehaus, Hannah
Istomina, Larysa
Nicolaus, Marcel
Tao, Ran
Malinka, Aleksey
Zege, Eleonora
Spreen, Gunnar
author_facet Niehaus, Hannah
Istomina, Larysa
Nicolaus, Marcel
Tao, Ran
Malinka, Aleksey
Zege, Eleonora
Spreen, Gunnar
author_sort Niehaus, Hannah
collection DataCite
description The presence of melt ponds on Arctic summer sea ice significantly alters its albedo and thereby the surface energy budget and mass balance. Large-scale observations of melt pond coverage and sea ice albedo are crucial to investigate the role of sea ice for Arctic amplification and its representation in global climate models. We present the new Melt Pond Detection 2 (MPD2) algorithm, which retrieves melt pond, sea ice, and open-ocean fractions as well as surface albedo from Sentinel-3 visible and near-infrared reflectances. In contrast to most other algorithms, our method uses neither fixed values for the spectral albedo of the surface constituents nor an artificial neural network. Instead, it aims for a fully physical representation of the reflective properties of the surface constituents based on their optical characteristics. The state vector X, containing the optical properties of melt ponds and sea ice along with the area fractions of melt ponds and open ocean, is optimized in an iterative procedure to ...
format Article in Journal/Newspaper
genre albedo
Arctic
Sea ice
genre_facet albedo
Arctic
Sea ice
geographic Arctic
geographic_facet Arctic
id ftdatacite:10.26092/elib/2847
institution Open Polar
language English
op_collection_id ftdatacite
op_doi https://doi.org/10.26092/elib/2847
op_rights Creative Commons Attribution 4.0 International
CC BY 4.0 (Attribution)
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
publishDate 2024
publisher Universität Bremen
record_format openpolar
spelling ftdatacite:10.26092/elib/2847 2025-01-16T18:42:10+00:00 Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model ... Niehaus, Hannah Istomina, Larysa Nicolaus, Marcel Tao, Ran Malinka, Aleksey Zege, Eleonora Spreen, Gunnar 2024 https://dx.doi.org/10.26092/elib/2847 https://media.suub.uni-bremen.de/handle/elib/7765 en eng Universität Bremen Creative Commons Attribution 4.0 International CC BY 4.0 (Attribution) https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 sea ice Arctic Albedo satellite remote sensing melt ponds 550 article Artikel/Aufsatz Other CreativeWork 2024 ftdatacite https://doi.org/10.26092/elib/2847 2024-04-02T10:30:01Z The presence of melt ponds on Arctic summer sea ice significantly alters its albedo and thereby the surface energy budget and mass balance. Large-scale observations of melt pond coverage and sea ice albedo are crucial to investigate the role of sea ice for Arctic amplification and its representation in global climate models. We present the new Melt Pond Detection 2 (MPD2) algorithm, which retrieves melt pond, sea ice, and open-ocean fractions as well as surface albedo from Sentinel-3 visible and near-infrared reflectances. In contrast to most other algorithms, our method uses neither fixed values for the spectral albedo of the surface constituents nor an artificial neural network. Instead, it aims for a fully physical representation of the reflective properties of the surface constituents based on their optical characteristics. The state vector X, containing the optical properties of melt ponds and sea ice along with the area fractions of melt ponds and open ocean, is optimized in an iterative procedure to ... Article in Journal/Newspaper albedo Arctic Sea ice DataCite Arctic
spellingShingle sea ice
Arctic
Albedo
satellite remote sensing
melt ponds
550
Niehaus, Hannah
Istomina, Larysa
Nicolaus, Marcel
Tao, Ran
Malinka, Aleksey
Zege, Eleonora
Spreen, Gunnar
Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model ...
title Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model ...
title_full Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model ...
title_fullStr Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model ...
title_full_unstemmed Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model ...
title_short Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model ...
title_sort melt pond fractions on arctic summer sea ice retrieved from sentinel-3 satellite data with a constrained physical forward model ...
topic sea ice
Arctic
Albedo
satellite remote sensing
melt ponds
550
topic_facet sea ice
Arctic
Albedo
satellite remote sensing
melt ponds
550
url https://dx.doi.org/10.26092/elib/2847
https://media.suub.uni-bremen.de/handle/elib/7765