1. University of Kansas S. Gogineni, P. Kanagaratnam, R. Parthasarathy, V. Ramasami & D. Braaten The University of Kansas Wideband Radars for Mapping of Near Surface Internal Layers to Estimate Accumulation Rate

2. University of Kansas Outline Introduction Background Systems Description Results Conclusions

3. University of Kansas Introduction Sea level rose by about 15 cm over the last century. Thermal expansion of the ocean Melting of mountain glaciers Contribution from polar ice sheets There is a large uncertainty in polar ice sheets’ contribution. Accurate mass balance determination is essential to determining their contribution. Volumetric method Flux method

4. University of Kansas Introduction Volumetric method Measure change in surface elevation –Satellite radar and laser Altimeters –NASA ICESAT -- January 03. –ESA CRYOSAT -- 2003 or 2004. Interpretation of the data from these missions requires additional information. Spatial and temporal variation of accumulation rate.

5. University of Kansas Introduction Flux approach Measure net input and ouput –Snow accumulation –Ice loss –Melting –Calving Both methods need information on the accumulation rate. –Snow pits and ice cores –Limited coverage

6. University of Kansas Introduction —GREENLAND ACCUMULATION MAP Bales et al., 2001 Cores or pits on the Greenland ice sheet. Small variance where there are large numbers of cores or pits. Large variance in areas with significant change Difficult to operate in margins of the ice sheet

7. University of Kansas Introduction— Systems We developed two radar systems to map near-surface internal layers for estimating accumulation rate. Surface-based system –Center frequency = 1.25 GHz –10 cm resolution Airborne system –Center frequency = 750 MHz. –60 cm resolution

8. University of Kansas Surface-based system— FM-CW Transmit power100 mW Bandwidth1.5 GHz Frequency range500 MHz – 2 GHz Resolution10 cm Maximum beat frequency 2 MHz Sampling rate5- 50 MHz Digitizer12-bit A/D Spatial sample rateContinuous AntennaTEM horns or bow-tie Array

9. University of Kansas Systems—Airborne Radar We used surface- based measurements to determine optimum radar parameters Constraint No interference to navigation and communication equipment System specifications Frequency600 –900 MHz Sweep Time100 ms PRF2 kHz Transmit Power1 W Number of Coherent Integrations 100 AntennasTEM Horns A/D Dynamic Range12 bit, 74 dB Sampling Rate50 MHz

10. University of Kansas System Description— Airborne Radar

11. University of Kansas Installation of Radar System in Aircraft Radar backend RF section

12. University of Kansas Results

13. University of Kansas Results—Matching with core data We simulated idealized radar response using core data Matched layers qualitatively. Radar data were collected in 2002 and core data in 1995. We had to account for this difference. A source of error.

14. University of Kansas Results –Tracking layers Using the simulated response at the core site, we identified a few layers and tracked them

15. University of Kansas Results— Accumulation rate We computed accumulation rate from radar data as We found the water equivalent accumulation rate to be 34.9±5.1 cm/yr. Estimate from core data is 34.57 cm/yr. Lowest accumulation rate during 1983-1990 = 0.3045  0.017 m yr-1 Highest accumulation rate 1979-1983=0.3904  0.027 m yr-1 )

16. University of Kansas Conclusions We designed and developed two wideband radars for mapping near surface internal layers in glacial ice. We showed that we can estimate accumulation rate. Data will be distributed through the web in about six months. More accurate simulations System point spread function Incorporate volume and surface scattering— noise. Develop data inversion algorithms