Modelling the Backscattering Properties of Anisotropic Rough Snow
Surfaces: Implications for the Evolution of Near Surface Features on the
Ice Sheets
Abstract
Understanding the near-surface roughness is paramount for the evolution
of surface features and its contribution to the ice sheet dynamics. In
regions experiencing the transition from dry snow to melt conditions,
the surface becomes rough which along with liquid water content
influences the radar backscatter. Such surfaces are driven by wind
resulting in the formation of features oriented at different azimuth
directions, ranging from ripples to dunes. Different scales of roughness
also induce depolarisation in the radar signal, thereby making it
difficult to infer the effective contribution of densification process
on total backscatter. Here, we present a physical understanding of a
wind-induced snow surface having anisotropic roughness from the modelled
radar backscatter. As part of the approach, we propose to model the
horizontal component of roughness (autocorrelation length) as a function
of azimuth direction in the surface scattering model, i.e. Integral
Equation Model. We performed our experiments for strongly anisotropic (a
< 0.2), weakly anisotropic (a > 0.7), and
isotropic (a = 1) surfaces, where a is the anisotropy, tuned for C-band
frequency. Also, the minima of backscatter intensity varied over entire
range of azimuth angles at a particular incidence angle is derived for
retrieving the most dominant wind direction. From our analysis,
significant azimuth modulation occurs in the radar backscatter at low
incidence angles. Moreover, we found that the most dominant wind
direction at 30-deg incidence angle changes from a strongly anisotropic
surface (i.e. 0-deg) to a weakly anisotropic surface (i.e. 90-deg),
however it remains unaltered for 45-deg and 60-deg incidence angles
(i.e. 90-deg). Our modelled results are in strong agreement with wind
scatterometer data of ice sheets and further show the potential of
30-deg incidence angle for tracking the changes in wind flow pattern
based on directionality of roughness. In this regard, we foresee the
importance of azimuth modulation for understanding the properties and
orientation of surface features in the ice sheets, with particular
application to wind flow. As a future scope, we plan to apply our model
on radar images for the retrieval of wind directions and compare the
directionality of roughness with the katabatic wind flow patterns and
AWS measurements.