Implementation of refractivity retrieval from ground clutter using the Sband KOUN radar

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Implementation of refractivity retrieval from
ground clutter using the S-band KOUN radar

• Michael James1, Robert Palmer1, Tian-You Yu2,
  Sebastian Torres3,4, Richard Doviak4, Dusan
  Zrnic4
• 1. University of Oklahoma, School of Meteorology
• 2. University of Oklahoma, Electrical and
  Computer Engineering
• 3. Cooperative Institute for Mesoscale
  Meteorological Studies
• 4. National Severe Storms Laboratory
• Norman, OK

Funded by
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Project Relationship with CASA CLEAR

• CASA COLLABORATIVE ADAPTIVE SENSING OF THE
  ATMOSPHERE
• ERC program featuring UMass, OU, CSU and the
  University of Puerto Rico
• Vision To revolutionize our ability to observe
  the lower troposphere through Distributed
  Collaborative Adaptive Sensing, improving our
  ability to detect, understand, and predict severe
  weather.
• CLEAR
• Look-ahead research targeting non-precipitating
  atmosphere when obvious radar scatterers are
  absent
• Improve small-scale atmospheric predictability

CASA Radar Test Bed(Spring 2006)
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Refractivity Retrieval Overview

• Clutter echo phase returns will change with
  atmospheric conditions moisture / temperature /
  atmospheric pressure (Bean and Dutton 1968 and
  references therein)
• PROCEDURE (Fabry et al. 1997, Fabry 2004)
• 1) Calibration - Determine clutter echo quality
  index
• 2) Use clutter returns to estimate phase
  difference
• 3) Use radial derivative of phase difference to
  estimate refractivity

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Retrieval Method

• CALIBRATION
• Define a reference phase can use a multi-scan
  average
• Determine a reference index of refraction use
  Oklahoma Mesonet surface observations
• Determine clutter point reliability
• - Spectral moment information
• - Temporal coherence of phase

Oklahoma Mesonet Stations
Spencer
El Reno
Shawnee
Minco
Norman
Chickasha
Washington
Ninnekah
Byars
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Classifying Clutter

• High SNR
• Narrow spectrum width
• Near-zero Doppler velocity
• High temporal phase coherence

Clutter point reliability was determined from
KOUN 114-scan temporal coherence of phase
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Classifying Clutter
Phase coherence defined as the ratio of lag-1
to lag-0 autocorrelation function of target phase
over a 114 scan dataset - roughly 90
minutes Coherence threshold is determined from
the phase coherence distribution division
between reliable clutter and noisy targets
clear air can be easily seen
Phase Coherence Threshold 0.65
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Example April 24, 2005
(scan 114)
(scan 114)
(scans 1-10 avg)
Clutter mask
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Example April 24, 2005
Smoothed in the complex signal domain, with a
two-dimensional Gaussian filter encompassing a 4
km x 4 km area. Then the radial derivative of
phase difference is computed
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Example April 24, 2005
A
B
C
N calculated from Oklahoma Mesonet surface
observations
A
B
C
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Waiting for Interesting WeatherSimulations

• A moisture bubble was simulated, and the
  resulting phase difference was projected onto the
  actual clutter map

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Waiting for Interesting WeatherSimulations

• A moisture bubble was simulated, and the
  resulting phase difference was projected onto the
  actual clutter map

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• Conclusions Further Research
• Refractivity retrieval (Fabry technique) has been
  implemented with the KOUN radar
• Spring 2006 CASA radar test-bed will be
  installed, and more convectively active weather
  will be available for data collection frontal
  passages, moisture convergence preceding
  thunderstorm initiation and more.
• Some Concerns
• Phase wrapping for 3 cm CASA radars will be more
  rapid than for 10 cm KOUN
• We are investigating phase wrapping mitigation
  using multi-frequency techniques
• Because reference phase map is cumbersome and may
  change with season, we would like to investigate
  ways to eliminate reference maps altogether

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• REFERENCES
• Fabry, F., C. Frush, I. Zawadzki, and A. Kilambi,
  1997 On the extraction of near-surface index of
  refraction using radar phase measurements from
  ground targets. J. Atmos. Oceanic Technol., 14,
  978-987.
• Fabry, F., 2004 Meteorological value of ground
  target measurements by radar. J. Atmos. Oceanic
  Technol., 21, 560-573.
• Bean, B. R., and E. J. Dutton, 1968 Radio
  Meteorology. National Bureau of Standards
  Monogr., No. 92, National Bureau of Standards,
  435 pp.