Estimating snow accumulation from InSAR correlation observations

Snow accumulation in remote regions such as Greenland and Antarctica is a key factor for estimating Earth's ice mass balance. In situ data are sparse, hence it is useful to derive snow accumulation from remote sensing observations, such as from microwave thermal emission and from radar brightness. These data are usually interpreted using electromagnetic models in which volume scattering is the dominant mechanism. The main limitation of this approach is that microwave brightness is not well-related to backscatter if the ice sheet is layered. Because larger grain size and thicker annual layers both increase radar image brightness, the first corresponding to lower accumulation rate and the second to higher accumulation rate, models of radar brightness alone cannot accurately reflect accumulation. Consideration of interferometric radar correlation measurements also can resolve this ambiguity. Here we introduce an ice scattering model that relates InSAR correlation and radar brightness to both ice grain size and hoar layer spacing in the dry snow zone of Greenland. We use this model and ERS satellite radar observations to derive several parameters related to snow accumulation rates in a small area in the dry snow zone. These parameters show agreement with four in situ core accumulation rate measurements in this area, while models using only radar brightness data do not match the observed variation in accumulation rates.; It is necessary to model both surface and volume scattering mechanism to predict the accumulation rate in the dry snow zone of Greenland accurately. In this work we process data covering several base stations in the dry snow zone of Greenland, acquired at two different incidence angles, in order to estimate the surface and volume scattering terms. The angle diversity is particularly helpful in characterizing the surface term. The detailed analysis of InSAR radar backscatter in Greenland better describes the physical surface conditions, so that we may better understand Earth's changing climate.