Melt Ponds on Arctic Summer Sea Ice from Optical Satellite Data

• Main Author: Niehaus, Hannah
• Other Authors: Spreen, Gunnar, Wendisch, Manfred
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: Universität Bremen 2024
• Subjects: Arctic; Sea Ice; Melt Ponds; Retrieval Algorithm; Remote Sensing; Satellite Observations; 530; 530 Physics; ddc:530; albedo; Sea ice
• Online Access: https://media.suub.uni-bremen.de/handle/elib/8044; https://doi.org/10.26092/elib/3078; https://nbn-resolving.org/urn:nbn:de:gbv:46-elib80445

The presence of melt ponds on Arctic summer sea ice strongly alters the absorption of solar radiation by the sea ice-ocean system and thereby the Arctic energy budget. Therefore, melt ponds are key to the positive sea ice-albedo feedback, which is one of the main drivers of the amplified Arctic warming observed in recent decades, and even affects the global climate. To analyze the mechanisms of melt pond evolution and their implications on the sea ice state, and to improve their representation in climate models, comprehensive observational data are needed. This dissertation presents a new approach to retrieve melt pond, sea ice and open ocean fractions at pan-Arctic scales from Sentinel-3 optical satellite data. The newly developed Melt Pond Detection 2 (MPD2) algorithm is the first fully physical retrieval that can distinguish these three surface types at the spatial resolution of 1.2 km. Because multiple combinations of surface type fractions result in similar observations at this coarse resolution, prior information are required for retrieval. As part of the development process, a reference data set of 33 local melt pond fraction maps with a spatial resolution of 10 m has been created from Sentinel-2 satellite data. Parts of these data were then used to calibrate an empirical pre-retrieval to provide preliminary estimates of surface type fractions. In addition, the correlation between sea ice optical properties and air temperature history has been investigated using measurement data from field campaigns. This correlation and the results of the pre-retrieval are used to initialize and constrain the physical retrieval. The results are validated against the full extent of the reference data set, leading to an uncertainty estimate of 7.8 % and 9 % for the melt pond and open ocean fractions, respectively. The MPD2 algorithm has been applied to seven years of Sentinel-3 observations from 2017 to 2023. This data set can be continued for future years and expanded by the application to previous satellite sensors. ...