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Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC
Global climate change poses significant societal and political challenges. The rapid increase in the near-surface air temperatures and the drastic retreat of the Arctic sea ice during summer are not well represented by climate models. The data sets introduced here intend to help improving the curren...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482923/ https://www.ncbi.nlm.nih.gov/pubmed/37673937 http://dx.doi.org/10.1038/s41597-023-02492-6 |
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author | Sperzel, Tim R. Jäkel, Evelyn Pätzold, Falk Lampert, Astrid Niehaus, Hannah Spreen, Gunnar Rosenburg, Sophie Birnbaum, Gerit Neckel, Niklas Wendisch, Manfred |
author_facet | Sperzel, Tim R. Jäkel, Evelyn Pätzold, Falk Lampert, Astrid Niehaus, Hannah Spreen, Gunnar Rosenburg, Sophie Birnbaum, Gerit Neckel, Niklas Wendisch, Manfred |
author_sort | Sperzel, Tim R. |
collection | PubMed |
description | Global climate change poses significant societal and political challenges. The rapid increase in the near-surface air temperatures and the drastic retreat of the Arctic sea ice during summer are not well represented by climate models. The data sets introduced here intend to help improving the current understanding of the ongoing Arctic climate changes. In particular, this study considers observations from 24 helicopter flights (June–September 2020) and 5 flights with the helicopter-towed probe HELiPOD (May–July 2020) during MOSAiC. Distributions of various surface types (white ice/snow, bright melt ponds, dark melt ponds, open water, and bare ice) were determined using fisheye camera images. They were related to collocated broadband irradiance measurements to analyse the temporal and spatial changes of the surface albedo. Multiple linear regression was applied to assign the measured areal albedo to the corresponding surface-types. The resulting surface-type fractions, the albedo data and respective upward and downward broadband solar irradiances of several flights throughout the melting and refreezing season are provided. |
format | Online Article Text |
id | pubmed-10482923 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104829232023-09-08 Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC Sperzel, Tim R. Jäkel, Evelyn Pätzold, Falk Lampert, Astrid Niehaus, Hannah Spreen, Gunnar Rosenburg, Sophie Birnbaum, Gerit Neckel, Niklas Wendisch, Manfred Sci Data Data Descriptor Global climate change poses significant societal and political challenges. The rapid increase in the near-surface air temperatures and the drastic retreat of the Arctic sea ice during summer are not well represented by climate models. The data sets introduced here intend to help improving the current understanding of the ongoing Arctic climate changes. In particular, this study considers observations from 24 helicopter flights (June–September 2020) and 5 flights with the helicopter-towed probe HELiPOD (May–July 2020) during MOSAiC. Distributions of various surface types (white ice/snow, bright melt ponds, dark melt ponds, open water, and bare ice) were determined using fisheye camera images. They were related to collocated broadband irradiance measurements to analyse the temporal and spatial changes of the surface albedo. Multiple linear regression was applied to assign the measured areal albedo to the corresponding surface-types. The resulting surface-type fractions, the albedo data and respective upward and downward broadband solar irradiances of several flights throughout the melting and refreezing season are provided. Nature Publishing Group UK 2023-09-06 /pmc/articles/PMC10482923/ /pubmed/37673937 http://dx.doi.org/10.1038/s41597-023-02492-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Sperzel, Tim R. Jäkel, Evelyn Pätzold, Falk Lampert, Astrid Niehaus, Hannah Spreen, Gunnar Rosenburg, Sophie Birnbaum, Gerit Neckel, Niklas Wendisch, Manfred Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC |
title | Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC |
title_full | Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC |
title_fullStr | Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC |
title_full_unstemmed | Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC |
title_short | Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC |
title_sort | surface albedo measurements and surface type classification from helicopter-based observations during mosaic |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482923/ https://www.ncbi.nlm.nih.gov/pubmed/37673937 http://dx.doi.org/10.1038/s41597-023-02492-6 |
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