Articles | Volume 18, issue 2
https://doi.org/10.5194/tc-18-933-2024
https://doi.org/10.5194/tc-18-933-2024
Research article
 | 
29 Feb 2024
Research article |  | 29 Feb 2024

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

Hannah Niehaus, Larysa Istomina, Marcel Nicolaus, Ran Tao, Aleksey Malinka, Eleonora Zege, and Gunnar Spreen

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Cited articles

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Ding, Y., Cheng, X., Liu, J., Hui, F., Wang, Z., and Chen, S.: Retrieval of melt pond fraction over Arctic sea ice during 2000–2019 using an ensemble-based deep neural network, Remote Sens., 12, 2746, https://doi.org/10.3390/RS12172746, 2020. a, b, c, d
Dorn, W., Rinke, A., Köberle, C., Dethloff, K., and Gerdes, R.: HIRHAM–NAOSIM 2.0: The upgraded version of the coupled regional atmosphere-ocean-sea ice model for Arctic climate studies, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2018-278, 2018. a, b
Eicken, H., Grenfell, T. C., Perovich, D. K., Richter-Menge, J. A., and Frey, K.: Hydraulic controls of summer Arctic pack ice albedo, J. Geophys. Res.-Oceans, 109, C08007, https://doi.org/10.1029/2003JC001989, 2004. a, b
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Short summary
Melt ponds are puddles of meltwater which form on Arctic sea ice in the summer period. They are darker than the ice cover and lead to increased absorption of solar energy. Global climate models need information about the Earth's energy budget. Thus satellite observations are used to monitor the surface fractions of melt ponds, ocean, and sea ice in the entire Arctic. We present a new physically based algorithm that can separate these three surface types with uncertainty below 10 %.
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