Remote sensing of Greenland ice sheet using multispectral near-infrared and visible radiances

We present the physical basis of and validate a new remote-sensing algorithm that utilizes reflected visible and near-infrared radiation to discriminate between dry and wet snow. When applied to the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, our discrimination algorithm has the potential to retrieve melting regions of the ice sheet at a spatial resolution of 0.25 km 2, over three orders of magnitude higher than the resolution of current microwave methods. The method should be useful for long-term monitoring of the melt area of the Greenland ice sheet, especially regions close to ice sheet margins and of the outflow glaciers. Our analysis of MODIS retrievals of the western portion of the Greenland ice sheet over the period 2000 to 2006 indicates significant interannual variability with a maximum melt extent in 2005. Collocated in situ meteorological data reveal a high correlation (0.80) between the MODIS melt-day area and the average summer temperature. Our analysis suggests that it is the magnitude of the summer temperature that dominates the melting (not the variability of the length of the melting season). Furthermore, we find that the melt-day area increases by about 3.8% for each 0.1 K increase in the average surface air summer temperature. We combine this empirical relationship with historic temperature data to infer that the melt-day area of the western part of the ice sheet doubled between the mid-1990s and mid-2000s and that the largest ice sheet surface melting probably occurred between 1920s and 1930s, concurrent with the warming in that period.