A physics-based Antarctic melt detection technique: Combining AMSR-2, radiative transfer modeling, and firn modeling

Abstract. Surface melt on ice shelves has been linked to hydrofracture and subsequent ice shelf breakup. Since the 1990s, scientists have been using microwave radiometers to detect melt on ice shelves and ice sheets by applying various statistically based thresholds to identify significant increases in brightness temperature that are associated with melt. We combine a statistical thresholding technique with Community Firn Model outputs, the Snow Microwave Radiative Transfer model, and AMSR-2 to create a hybrid method that accounts for the influence of variations in snow temperature and density on microwave brightness temperature. In the process, we also produce snow correlation lengths, and we run this algorithm on 13 sites over the Antarctic Ice Sheet and ice shelves. Compared to melt values from surface energy balance observations from automatic weather stations, this method is as accurate as previous statistically based thresholding techniques and is slightly more sensitive to melt events. Our correlation lengths from early 2014 correlate with surface grain size from the 2013–2014 Mosaic of Antarctica. We also find a significant relationship between correlation length and frequency of melt. In the future, this hybrid method can be further developed to quantify melt volume rather than to simply detect melt occurrence.