New image analysis technologies for fast and accurate retrieval of sea ice floe size distribution (FSD) from satellite SAR imagery

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Arctic sea ice is changing rapidly. The most profound example is during the summer of 2012, in which the lowest ice extent was recorded since satellite sensors began to monitor sea ice in 1979. Within just one week, as a violent storm passed the Arctic in August of 2012, sea ice area equivalent to nearly twice the size of UK (0.4 million square kilometres) disappeared, leaving ice-free water up to 80 N by mid-August in western Arctic. One of the key processes that cause such rapid sea ice decline is sea-ice floe breakup during the winter-to-summer transition. During this transition the edge of sea ice retreats to the north, exposing larger open water fetch to generate waves, propagating into the ice pack, allowing larger sea-ice floes to break into smaller ones. As the floes become smaller, they melt faster and become more dynamic. At the same time more solar radiation is absorbed through exposed open water areas, which makes the upper ocean layer warmer and in turn promotes faster ice melting. This chain reaction can accelerate the sea ice retreat and thus impact the minimum ice extent. This important floe breakup and associated effects are poorly implemented in sea-ice/climate models. This is partly due to lack of understanding and verification of our current knowledge on the processes as well as due to complexity of the processes that makes it difficult to effectively implement them into "simple" representations in the models. Producing effective parameterisations requires accurate data on in-situ floe size distribution (FSD) that can be used to verify and refine the known parameterisations as well as to formulate new ones. Satellite Synthetic Aperture Radar (SAR) provides observations of sea ice unhindered by either darkness or cloud, thus provide ideal raw data from which FSD can be retrieved from dark winter to cloudy summer in the Arctic. There is an increasing number of satellite SAR images being acquired in the Arctic, and often at spatial resolutions in the images as good as 1-20 m. More importantly satellite SAR images are being acquired over autonomous buoy systems and in conjunction with field campaigns. This provides the ideal framework to measure the full range of ocean, sea-ice and atmosphere parameters to investigate complex floe breakup process. However the challenge we have is a lack of proven-quality algorithms that can derive FSD from satellite SAR images fast and accurately. Thresholding algorithms previously applied to the problem are not adequate for quantitative analysis and the performance has not been precisely assessed. In this project we, for the first time, combine sea ice physics with edge-cutting image processing techniques to develop FSD algorithms at a completely different level. We leverage the latest image processing technologies which include a) wavelet algorithms to reduce the speckle noise while increasing the contrast of the boundary between ice and water, b) local-statistics based algorithm to extract ice floe features from the background open water, c) and a combination of edge-preserving watershed and split-and-merge algorithms to effectively split up the touching boundary of the floes. We expect this set of new algorithms will produce much more accurate FSD from satellite SAR images, and lay a foundation develop universal algorithm that can be used to build a long-term sea-ice FSD database.