Docstoc

Microwave Remote Sensing of Polar Regions

Document Sample
Microwave Remote Sensing of Polar Regions Powered By Docstoc
					Wideband Radars for Mapping of Near
 Surface Internal Layers to Estimate
         Accumulation Rate

   S. Gogineni, P. Kanagaratnam, R.
Parthasarathy, V. Ramasami & D. Braaten
      The University of Kansas

                          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




                                     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.
                                  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

                                 University of Kansas
 Introduction—GREENLAND ACCUMULATION MAP

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
                           Bales et al., 2001

                                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

                                University of Kansas
Surface-based system— FM-CW
  Transmit power        100 mW

  Bandwidth             1.5 GHz
  Frequency range       500 MHz – 2 GHz
  Resolution            10 cm
  Maximum beat          2 MHz
  frequency
  Sampling rate         5- 50 MHz
  Digitizer             12-bit A/D
  Spatial sample rate   Continuous
  Antenna               TEM horns or bow-tie
                        Array


                                     University of Kansas
Systems—Airborne Radar
• We used surface-       System specifications
  based measurements
  to determine optimum    Frequency              600 –900 MHz

  radar parameters        Sweep Time             100 ms

• Constraint              PRF                    2 kHz

                          Transmit Power         1W
  • No interference to    Number of Coherent     100
    navigation and           Integrations

    communication         Antennas               TEM Horns


    equipment
                          A/D Dynamic Range      12 bit, 74 dB

                          Sampling Rate          50 MHz




                                           University of Kansas
  System Description— Airborne Radar

       50 MHz
        TCXO




                                                                                              Transmit
                         Chirp
                       Synthesizer
                                     LPF       BPF                    Power Amp         BPF
                                       3 dB



                                                               3 dB
         1 GHz
          PLO



            C
            O
            M                                                  3 dB
            P
            U
Data System
            T                                             LO
   Clock                                      HPF
            E
            R
                                                     IF         RF
                 LPF                   LPF                             High-Isolation   BPF    Receive
                                                                           Amp




                                                                                                         University of Kansas
Installation of Radar System in Aircraft


  RF
                      Radar
  section             backend




                                University of Kansas
Results




          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.


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




                                         University of Kansas
Results— Accumulation rate
                                                                             Accumulation rate

                                                                                                 1990-92


• We computed
                                                                                                 1983-79
                                                                                                 1983-90
                                                         0.5
                                                                                                 Avg Accumulation Rate




  accumulation rate                                      0.4




                                     Accumulation Rate
  from radar data as
                                                         0.3



                                                         0.2



                                                         0.1

                        dR  layer
 Accumulation rate, A 
                        dt  water                        0
                                                               0   10   20          30
                                                                             distance in Kms
                                                                                                 40         50           60




                                                 Lowest accumulation
We found the water
                                                 rate during 1983-1990 =
equivalent accumulation
                                                 0.3045  0.017 m yr-1
rate to be 34.9±5.1
cm/yr.                                           Highest accumulation
                                                 rate 1979-1983=0.3904
Estimate from core                                0.027 m yr-1)
data is 34.57 cm/yr.

                                                                              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
                                University of Kansas

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:1
posted:10/22/2011
language:English
pages:16