University of Kansas

S. Gogineni, P. Kanagaratnam, R. Parthasarathy, V. Ramasami & D.

BraatenThe University of Kansas

Wideband Radars for Mapping of Near Surface

Internal Layers to Estimate Accumulation Rate

University of Kansas

Outline •Introduction•Background•Systems Description•Results•Conclusions

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

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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.

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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

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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

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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

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Surface-based system— FM-CW

Transmit power 100 mW

Bandwidth 1.5 GHz

Frequency range 500 MHz – 2 GHz

Resolution 10 cm

Maximum beat frequency

2 MHz

Sampling rate 5- 50 MHz

Digitizer 12-bit A/D

Spatial sample rate Continuous

Antenna TEM horns or bow-tie Array

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Systems—Airborne Radar

• We used surface-based measurements to determine optimum radar parameters

• Constraint• No interference

to navigation and communication equipment

System specifications

Frequency 600 –900 MHz

Sweep Time 100 ms

PRF 2 kHz

Transmit Power 1 W

Number of Coherent Integrations

100

Antennas TEM Horns

A/D Dynamic Range 12 bit, 74 dB

Sampling Rate 50 MHz

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System Description— Airborne Radar

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Installation of Radar System in Aircraft

Radar

backend

RF section

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Results

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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.

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Results –Tracking layers• Using the simulated response at the core site, we

identified a few layers and tracked them

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Results— Accumulation rate

• We computed accumulation rate from radar data as

water

layer

dt

dRArateonAccumulati

,

We found the water equivalent accumulation rate to be 34.9±5.1 cm/yr.

Estimate from core data is 34.57 cm/yr.

0 10 20 30 40 50 600

0.1

0.2

0.3

0.4

0.5

Ac

cu

mu

lati

on

Ra

te

distance in Kms

Accumulation rate

1990-921983-791983-90Avg Accumulation Rate

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)

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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