2 research outputs found
A Facet-Based Numerical Model for Simulating SAR Altimeter Echoes From Heterogeneous Sea Ice Surfaces
Cryosat-2 has provided measurements of pan-Arctic
sea ice thickness since 2010 with unprecedented spatial coverage
and frequency. However, it remains uncertain how the Ku-band
radar interacts with the vast range of scatterers that can be present
within the satellite footprint, including sea ice with varying
physical properties and multi-scale roughness, snow cover, and
leads. Here, we present a numerical model designed to simulate
delay-Doppler SAR (Synthetic Aperture Radar) altimeter echoes
from snow-covered sea ice, such as those detected by Cryosat-2.
Backscattered echoes are simulated directly from triangular facetbased models of actual sea ice topography generated from
Operation IceBridge Airborne Topographic Mapper (ATM) data,
as well as virtual statistical models simulated artificially. We use
these waveform simulations to investigate the sensitivity of SAR
altimeter echoes to variations in satellite parameters (height, pitch,
roll) and sea ice properties (physical properties, roughness,
presence of water). We show that the conventional Gaussian
assumption for sea ice surface roughness may be introducing
significant error into the Cryosat-2 waveform retracking process.
Compared to a more representative lognormal surface, an echo
simulated from a Gaussian surface with rms roughness height of
0.2 m underestimates the ice freeboard by 5 cm – potentially
underestimating sea ice thickness by around 50 cm. We present a
set of ‘ideal’ waveform shape parameters simulated for sea ice and
leads to inform existing waveform classification techniques. This
model will ultimately be used to improve retrievals of key sea ice
properties, including freeboard, surface roughness and snow
depth, from SAR altimeter observations
A Facet-Based Numerical Model for Simulating SAR Altimeter Echoes from Heterogeneous Sea Ice Surfaces
Cryosat-2 has provided measurements of pan-Arctic
sea ice thickness since 2010 with unprecedented spatial coverage
and frequency. However, it remains uncertain how the Ku-band
radar interacts with the vast range of scatterers that can be present
within the satellite footprint, including sea ice with varying
physical properties and multi-scale roughness, snow cover, and
leads. Here, we present a numerical model designed to simulate
delay-Doppler SAR (Synthetic Aperture Radar) altimeter echoes
from snow-covered sea ice, such as those detected by Cryosat-2.
Backscattered echoes are simulated directly from triangular facetbased models of actual sea ice topography generated from
Operation IceBridge Airborne Topographic Mapper (ATM) data,
as well as virtual statistical models simulated artificially. We use
these waveform simulations to investigate the sensitivity of SAR
altimeter echoes to variations in satellite parameters (height, pitch,
roll) and sea ice properties (physical properties, roughness,
presence of water). We show that the conventional Gaussian
assumption for sea ice surface roughness may be introducing
significant error into the Cryosat-2 waveform retracking process.
Compared to a more representative lognormal surface, an echo
simulated from a Gaussian surface with rms roughness height of
0.2 m underestimates the ice freeboard by 5 cm – potentially
underestimating sea ice thickness by around 50 cm. We present a
set of ‘ideal’ waveform shape parameters simulated for sea ice and
leads to inform existing waveform classification techniques. This
model will ultimately be used to improve retrievals of key sea ice
properties, including freeboard, surface roughness and snow
depth, from SAR altimeter observations