Abstract
ABSTRACTMicrowave scatterometer measurements have been used in monitoring the snowmelt characteristics of the Greenland ice sheet. The melt signals and the appropriate threshold scheme are critical to the detection of ice-sheet snowmelt. We propose a scatterometer ice-sheet snowmelt detecting method based on diurnal variation and polarization ratio (DVPR) time series. We implement the algorithm to detect the snowmelt of the Greenland ice sheet using Quick Scatterometer (QuikSCAT) data. Moreover, the detection results of the DVPR method are compared with two other scatterometer snowmelts and validated by the automatic weather station (AWS) data in Greenland. The results show that the method based on the DVPR time series has better detection accuracy and this method is more precise for detecting the melt onset and melt end of ice sheets.
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