Winter Sentinel-1 Backscatter as a Predictor of Spring Arctic Sea Ice Melt Pond Fraction

Spring melt pond fraction (fp) has been shown to influence September sea ice extent and, with a growing need to improve melt pond physics in climate and forecast models, observations at large spatial scales are needed. We present a novel technique for estimating fp on sea ice at high spatial resolut...

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Bibliographic Details
Published in:Geophysical Research Letters
Main Authors: Scharien, Randall K., Segal, Rebecca, Nasonova, Sasha, Nandan, Vishnu, Howell, Stephen E. L., Haas, Christian
Format: Article in Journal/Newspaper
Language:unknown
Published: 2017
Subjects:
Online Access:https://epic.awi.de/id/eprint/46087/
https://epic.awi.de/id/eprint/46087/1/Scharien_et_al-2017-Geophysical_Research_Letters.pdf
https://doi.org/10.1002/2017GL075547
https://hdl.handle.net/10013/epic.31fd6546-a3a1-4e8d-89f7-5a27a7205137
https://hdl.handle.net/
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Summary:Spring melt pond fraction (fp) has been shown to influence September sea ice extent and, with a growing need to improve melt pond physics in climate and forecast models, observations at large spatial scales are needed. We present a novel technique for estimating fp on sea ice at high spatial resolution from the Sentinel-1 satellite during the winter period leading up to spring melt. A strong correlation (r = -0.85) is found between winter radar backscatter and fp from first-year and multiyear sea ice data collected in the Canadian Arctic Archipelago (CAA) in 2015. Observations made in the CAA in 2016 are used to validate a fp retrieval algorithm, and a fp prediction for the CAA in 2017 is made. The method is effective using the horizontal transmit and receive polarization channel only and shows promise for providing seasonal, pan-Arctic, fp maps for improved understanding of melt pond distributions and forecast model skill.