1. Sea Ice Melt Pond Fraction Derived From Sentinel‐2 Data: Along the MOSAiC Drift and Arctic‐Wide
- Author
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Niehaus, Hannah, Spreen, Gunnar, Birnbaum, Gerit, Istomina, Larysa, Jäkel, Evelyn, Linhardt, Felix, Neckel, Niklas, Fuchs, Niels, Nicolaus, Marcel, Sperzel, Tim, Tao, Ran, Webster, Melinda, and Wright, Nicholas
- Abstract
Melt ponds forming on Arctic sea ice in summer significantly reduce the surface albedo and impact the heat and mass balance of the sea ice. Therefore, their areal coverage, which can undergo rapid change, is crucial to monitor. We present a revised method to extract melt pond fraction (MPF) from Sentinel‐2 satellite imagery, which is evaluated by MPF products from higher‐resolution satellite and helicopter‐borne imagery. The analysis of melt pond evolution during the MOSAiC campaign in summer 2020, shows a split of the Central Observatory (CO) into a level ice and a highly deformed ice part, the latter of which exhibits exceptional early melt pond formation compared to the vicinity. Average CO MPFs are 17% before and 23% after the major drainage. Arctic‐wide analysis of MPF for years 2017–2021 shows a consistent seasonal cycle in all regions and years. In the Arctic summer, puddles of surface melt water, called melt ponds, form on the sea ice. These melt ponds reduce the ability of the surface to reflect the sunlight. Instead, they absorb more solar energy and pave the way into the ocean beneath where the energy is also absorbed. Thus, it is important to know where these melt ponds develop and what fraction of the surface they cover. To investigate this, we present a classification algorithm that is used to extract the areal fraction of melt ponds from satellite measurements. The special focus of this study is the MOSAiC campaign in summer 2020, where the research vessel Polarstern drifted with an ice floe for 1 year. We can see a separation of this floe into two parts. One of them shows melt pond formation much earlier than the other. This is because of different ice age and surface properties. Additionally, we use the classification algorithm to analyze the differences of melt pond fraction between different dates and regions in the Arctic. Algorithm to extract melt pond and open water areas from Sentinel‐2 imagery with maximum uncertainty of 6%Exceptional early melt pond formation on MOSAiC Central Observatory, summer 2020, compared to broader vicinityHigh spatial and temporal variability of melt pond fraction on local and regional scales Algorithm to extract melt pond and open water areas from Sentinel‐2 imagery with maximum uncertainty of 6% Exceptional early melt pond formation on MOSAiC Central Observatory, summer 2020, compared to broader vicinity High spatial and temporal variability of melt pond fraction on local and regional scales
- Published
- 2023
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