Antarctic ice-sheet near-surface snowmelt detection based on the synergy of SSM/I data and QuikSCAT data

Abstract

Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the ice-sheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve the Antarctic ice-sheet near-surface snowmelt detection accuracy, a new Antarctic ice-sheet near-surface snowmelt synergistic detection method was proposed based on the principle of complementary advantages of SSM/I data (high reliability) and QuikSCAT data (high sensitivity) by the use of edge detection model to automatically extract the edge information to get the distribution of Antarctic snowmelt onset date, snowmelt duration and snowmelt end date. The verification result shows that the proposed snowmelt synergistic detection method improves the detection accuracy from about 75% to 86% based on AWS (Automatic Weather Stations) Butler Island and Larsen Ice Shelf. The algorithm can also be applied to other regions, which provides methodological support and supplement for the global snowmelt detection. Keywords: Snowmelt detection, SSM/I data, QuikSCAT data, Synergy, Edge detection model