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:English
Published: Geophysical Research Letters 2017
Subjects:
sea ice
melt ponds
microwave backscatter
Sentinel-1
seasonal forecast
Arctic
Canadian Arctic Archipelago
The Sentinel
Arctic Archipelago
Sea ice
Online Access:http://hdl.handle.net/1828/10645
https://doi.org/10.1002/2017GL075547
Description
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. Data collection and analysis were supported by funds from Natural Sciences and Engineering Research Council (NSERC) Discovery Grant (DG), Marine Environmental Observation, Prediction, and Response Network (MEOPAR), and the Changing Earth Science Network, part of the European Space Agency's Support To Science Element (STSE). The authors declare no financial conflicts of interests. Sentinel-1 data are available from the online database Copernicus Open Access Hub (https://scihub.copernicus.eu/). GeoEye-1 data are available at a cost from the DigitalGlobe database (https://browse.digitalglobe.com/). Supporting data are included as Data Set S1. Under certain terms and conditions, GeoEye-1 data may be available free of charge from the European Space Agency. Faculty Reviewed

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