Winter Sentinel‐1 Backscatter as a Predictor of Spring Arctic Sea Ice Melt Pond Fraction. Issue 24 (18th December 2017) - Scharien, Randall K.; Segal, Rebecca; Nasonova, Sasha; Nandan, Vishnu; Howell, Stephen E. L.; Haas, Christian
Abstract: Spring melt pond fraction ( f p ) 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 f p 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 f p 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 f p retrieval algorithm, and a f p 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, f p maps for improved understanding of melt pond distributions and forecast model skill. Plain Language Summary: Recent and well‐documented changes in Arctic sea ice have introduced the need for timely and accurate seasonal forecasts of ice conditions. Seasonal forecasts of ice conditions will reduce the risks to humans and help preserve the fragile Arctic ecosystem by preventing accidents and spills. Recent studies have shown a link between the amount of surface meltwater flooding that occurs on sea ice in the spring, termed melt pond fraction, and the extent of sea ice that remains at the end of summer. This link is due to the ability of surface meltwater to absorb more sunlight compared to bare ice and snow. This study provides a new way to estimate the amount of surface meltwater flooding expected to occur on the sea ice in spring, using satellite data collected during the winter period. The results presented here provide a key link between winter and late summer sea ice conditions that will enhance the ability of forecasters to make accurate seasonal predictions several months in advance of the active summer period. Key Points: A novel approach to estimate spring melt pond fraction from winter Sentinel‐1 backscatter is developed The correlation between backscatter and melt pond fraction is strong at r  = −0.85 Large‐scale maps of predicted spring melt pond fraction months in advance are possible