The MERS research group has been actively involved in polar research in the southern hemisphere. As part of these studies Seasat scatterometer (SASS), ERS-1/2 scatterometer (Escat), NASA Scatterometer (NSCAT), and SeaWinds data have been processed with the Scatterometer Image Reconstruction (SIR) resolution enhancement algorithm.

While satellite microwave radar scatterometers were originally designed to measure winds over the ocean from space, they can also be useful in polar ice studies. Using the Scatterometer Image Reconstruction (SIR) resolution enhancement algorithm we have generated a time series of radar images of the Antarctic region. New methods for mapping the spatial extent and ice type have been developed for use with NASA Scatterometer (NSCAT) and SeaWinds data. The results enable study of the dynamics of the sea-ice sheet and permit multidecadal studies of change by comparison with previous scatterometers. The broad coverage, dual-pol measurements, and high resolution of NSCAT and SeaWinds yield very high quality images.

Microwave radar mitigates the need for optimal meteorological conditions and solar illumination which can hamper optical sensors. The radar scattering signal provides insight into characteristics of the ice which can not be inferred from optical images. In particular, the microwave images depend on both surface roughness and the electrical properties, which vary for different ice types, enabling the retrieval of ice characteristics from the radar data. Scatterometers observe the ice from a variety of incidence angles, further enhancing the utility of the radar data. Knowledge of the ice characteristics is of crucial import in modeling the interaction of the ocean and atmosphere in the polar regions and in evaluating the Earth's heat balance. Sea-ice cover also influences the production of Antarctic Bottom Water, a crucial factor in global ocean circulation.

SeaWinds Antarctic Studies

Unlike previous fan-beam instruments, SeaWinds makes sigma-0 measurements at only two discrete incidence angles, each with a different polarization. SeaWinds make measurements at a greater variety of azimuth angles than previous sensors. A variety of studies are underway. An operational automated algorithm for SeaWinds ice extent mapping has been generated

NSCAT Antarctic Studies

NSCAT makes measurements at both vertical and horizontal electrical polarization at a variety of azimuth angles. Sea-ice has a nearly isotropic response while the ocean exhibits a very directional response which is ordinarily used to determine the direction of the wind blowing over the surface. While the sea-ice evolves on time scales of days to weeks, winds over the ocean can change on hourly time scales. Using images of the vertical and horizontal radar response and the temporal variation in the radar response over a several day period, the spatial extent of the sea-ice can be mapped. The resulting ice edge compares favorably with passive microwave ice maps but has higher spatial resolution and precision (Remund and Long, 1999).

A Sample Time Series (95K gif) shows the seasonal recession and growth of the sea-ice around Antarctica. A sample 256x256 pixel NSCAT Movie (900K animated gif) was generated from the orignal 1940x1940 SIRF images. The images illustrated here show the incidence angle normalized radar backscatter (denoted `A'). The original Ku-band images have approximately 4.5 km resolution with images every three days. The images have been masked to show only sea-ice and the Antarctic continent. Masking was done using only NSCAT data and a newly developed algorithm. The ice edge corresponds closely with the SSM/I-derived NSIDC 30% ice concentration contour. Longer version of this movie are available as (animated gif 4.4 MB), (.avi 4.4 MB), (.mov [quiktime] 1.6 MB), or (.m1v [mpeg bitstream] 2.2 MB).

A&B Polar Images (290K gif) shows fine resoluione NSCAT A and B images of both the Arctic and Antarctic. Sea-ice edge masking for these particular images was done using SSM/I data though the NSCAT-only algorithm works well in both hemispheres.

In this sample time series and movie, the Antarctic continent is clearly visible in the center of the images and changes relatively little (except along the coast) while the sea-ice sheet dramatically moves. A large (100x60 km) white iceburg which broke of the Thwaites ice tongue is visible on image left. (It appears to vanish when the ice-sheet around it melts and the algorithm to remove the ocean part of the image also removes the iceburg--the massive burg is still there, however.) Movies of ice-masked enhanced resolution NSCAT Arctic images are available as (animated gif 8.8 MB), (.avi 4.3 MB), (.mov [quiktime] 1.0 MB), or (.m1v [mpeg bitstream] 1.1 MB).

Multisensor studies involving SSM/I, NSCAT, and ERS-1/2 scatterometer data suggest that the microwave response exhibits a wind-dependent signature which enables evaluation of the wind direction (Long and Drinkwater, 2000). A pdf version of this paper is available for download. Because of the small sized figure reproductions in the printed paper, full-size electronic versions of the figures are provided (these are copyrighted).

ERS-1/2 Antarctic Studies

While NSCAT has wider, more frequent coverage, better resolution, and dual-polarization capability, data from the ERS-1 and ERS-2 AMI scatterometers (EScat) is also use for ice sheet studies because of its long time history. We have made time series images of EScat data and done studies on azimuth modulation of C-band data over sea-ice.

Recent evidence for warming in the vicinity of the Antarctic Peninsula has raised concerns about the stability of the large ice shelves in that region. The recent past has seen calvings resulting in the disintegration of the King George and the Larsen Ice Shelves. Time series information provided by the EScat instrument shows the value for long-term monitoring of such delicate regions. An ERS-1 Antarctic Peninsula time series (152K) shows the inter-annual variability in melt, clearly visible as the brightness modulation. Melt is recognized as the lowest backscatter coefficients, and a distinct melt front is visible in 1992. In 1993 the entire Larsen ice shelf is melting, while the subsequent 1994 melt season has minimal melting. The following melt seasons in 1995 and 1996 show similar characteristics to 1992 and 1993, respectively. These data indicate that the summers of 1993 and 1995 were both extensive in time and space, perhaps contributing to the large iceberg calvings in those years. These images are being used to chart the regional distribution of seasonal melting on the ice shelves and the continental ice.

An early global ERS-1 Colorized time series (275K)

An early ERS-1 Weddell Sea Image (255K)

Glacial Ice

See the paper "Greenland Observed" below.

or Greenland Studies

The SIR Algorithm

The Scatterometer Image Reconstruction (SIR) algorithm was developed to generate enhanced resolution scatterometer imagry from raw sigma-0 measurements.

For fan-beam scatterometers SIR generates images of 'A' and 'B' which are related to the normalized radar cross section sigma-0 by

where theta is the incidence angle of the measurements. For SeaWinds only 'A' images are produced. SIR has also been applied to SSM/I data. The resolution of the resulting images is as fine as ~4-5 km for SASS and NSCAT, ~ 2-6 km for SeaWinds, and 25-30 km for ERS-1/2. Previous techniques were limited to the intrinsic resolution (typically 50 km) of the scatterometer.

Some Related Papers from the MERS Group

Azimuth Variation in Microwave Scatterometer and Radiometer Data Over Antarctica

D.G. Long and M.R. Drinkwater, IEEE Trans. Geosc. Remote Sens., Vol. 38, No. 4, pp. 1857-1870, Aug. 2000.

Sea Ice Extent Mapping Using Ku-Band Scatterometer Data

Q.P. Remund and D.G. Long, Journal of Geophysical Research, Vol. 104, No. C5, pp. 11515-11527, 2000.

Greenland Observed at High Resolution by the Seasat-A Scatterometer

D.G. Long and M.R. Drinkwater, Journal of Glaciology, Vol. 32, No. 2, pp. 213-220, 1994.

Resolution Enhancement of Spaceborne Scatterometer Data

D.G. Long, P. Hardin and P. Whiting, IEEE Trans. Geosc. Remote Sens., Vol. 31, No. 3, pp. 700-715, May 1993.

For a more extensive list see the MERS Bibliography