Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC

Abstract 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 t...

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Bibliographic Details
Published in:Scientific Data
Main Authors: Tim R. Sperzel, Evelyn Jäkel, Falk Pätzold, Astrid Lampert, Hannah Niehaus, Gunnar Spreen, Sophie Rosenburg, Gerit Birnbaum, Niklas Neckel, Manfred Wendisch
Format: Article in Journal/Newspaper
Language:English
Published: Nature Portfolio 2023
Subjects:
Q
Online Access:https://doi.org/10.1038/s41597-023-02492-6
https://doaj.org/article/30b81f5565bf4f9e8d71223e8e668b4c
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Summary:Abstract 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.