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Groundbased and Spacebased Radar Precipitation Imaging

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Backscattered signal in weather radars is from distributed target ... Horizontal resolution at nadir : 4.3 km. ( 5 km. postboost) - Range resolution : 250 m. ... – PowerPoint PPT presentation

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Title: Groundbased and Spacebased Radar Precipitation Imaging


1
Ground-based and Space-based Radar Precipitation
Imaging V.Chandrasekar Colorado state
University January 28, 2008
2
  • Introduction
  • CSU-CHILL radar
  • - PPI (Plan Position Indicator) scan
  • - RHI (Range Height Indicator) scan
  • Tropical Rainfall Measurement Mission (TRMM)
  • - Precipitation Radar (PR)

3
CSU-CHILL radar New antenna installation
4
Example of PPI scan
5
Example of RHI scan
6
The received signal corresponds to resolution
volume determined by the transmit pulse width
beam width
  • Backscattered signal in weather radars is from
    distributed target
  • Cross range resolution is dependent on the
    antenna beam width and range

7
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9
Waveform Coding at CSU-CHILL radar
  • Intrinsic backscattering properties of
    hydrometeor in a linear polarization basis
    enables the measurements such as size, shape and
    spatial orientation
  • Intrinsic backscattering properties of
    hydrometeor is described by the backscattering
    covariance matrix

10
Waveform Coding at CSU-CHILL radar
Backscattered signal from horizontal polarization
Backscattered signal from vertical polarization
  • Backscattering covariance matrix is given by

11
Waveform Coding at CSU-CHILL radar
  • The received signal in the two polarization
    channels can be written as
  • The covariance matrix of the received signal is
    given by

12
Waveform Coding at CSU-CHILL radar
Reflectivity from (a) Alternate mode (203400
UTC) (b) Walsh coded simultaneous mode (202851
UTC). Data collected by CSU-CHILL on May 29, 2007
LDR estimated from (a) Alternate mode (203400
UTC) (b) Walsh coded simultaneous mode (202851
UTC). Data collected by CSU-CHILL on May 29, 2007
13
Networked System Processing
KSAO
KCYR
KRSP
KLWE
14
Networked System Processing
Tornadic circulation feature wind speeds greater
than 40 m/s (90 mph)
UNFILTERED
FILTERED
15
Networked System Processing
Measurement at each radar node
Networked retrieval
16
Reflectivity retrieval in a networked radar
environment Demonstration from IP-1 radar network
17
Before
After
KTLX
May 7, 2007 CSE
18
Before
After
KTLX
May 8, 2007 CSE
19
TRMM-PR orbital and observatory characteristics
  • TRMM Tropical Rainfall
  • Measurement Mission
  • - Joint mission between NASA and JAXA
  • - Observing precipitation over tropical
    regions
  • between 37oS and 37oN
  • - Satellite was lunched in 1997
  • PR Precipitation Radar (installed on TRMM)
  • - 13.8 GHz Ku-band radar
  • - Horizontal resolution at nadir
    4.3 km.

  • ( 5 km. postboost)
  • - Range resolution 250 m.
  • - Swath width 215 km. ( 245 km
    postboost)
  • - Altitude 350 km. ( 402.5 km
    postboost)
  • Note TRMM was boosted in altitude in
    August 2001

A hurricane in TRMM-PR track
215 km.
(Adopted from TRMM data user handbook, 2001)
20
Ground and Space-based radar volume matching
  • Performance and system cross validation

21
Geometry of pulse volume and resolution
degradation effect of space-based radar
measurement.
Effective vertical resolution xr xb

hcos? r ?B sin ?
Effective horizontal resolution hr hb

hsin? r ?B cos ?
to surface
22
Geometric distortion in the space-base radar
image caused by platform motion
23
Difference in resolution between space and
ground-based radar images
  • A couple example from simultaneous observations
    between NEXRAD and TRMM

TRMM-PR
NEXRAD KAMX Miami, FL
24
TRMM-PR
NEXRAD KEVX , Red Bay/Eglin, FL
25
3-D volume matching and shifting based on GR and
SR resolution volumes
26
Matched and Aligned images between SR and GR
GR
SR
27
Matched images of a tropical storm in Bay of
Bengal
GR (SHAR, India)
SR (TRMM-PR)
28
Summary
  • The Radar research group works on a variety of
    problems all the way from
  • Design and development of imaging sensors
  • Analysis of images for interpretation and
  • Cross validation of images from multiple
    platforms
  • Developing hardware, theory algorithms and and
    novel applications
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