Cloud radar spectral polarimetry for atmospheric research · Case study, 9 June 2018, 21:20 UTC...
Transcript of Cloud radar spectral polarimetry for atmospheric research · Case study, 9 June 2018, 21:20 UTC...
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Alexander Myagkov and Thomas Rose
Radiometer Physics GmbH, Germany
Cloud radar spectral polarimetry
for atmospheric research
Alexander Myagkov , [email protected], ISTP 2019, 20 - 24 May 2019, Toulouse, France
Acknowledgements:
Stefan Kneifel (Uni Cologne, Germany)
Dmitri Moisseev (Uni Helsinki, Finland)
Alessandro Battaglia (Uni Leicester, GB)
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Weather radar (cm-wavelength) polarimetry
Concentration
Shape
Size
Orientation
Phase
Density
Absolute
calibration Attenuation Radar Reflectivity Ze How much power scattered back
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Weather radar (cm-wavelength) polarimetry
Concentration
Shape
Size
Orientation
Phase
Density
Absolute
calibration Attenuation Radar Reflectivity Ze
Differential reflectivity ZDR
Backscattering diff. phase δ
How much power scattered back
Scattering is more efficient at one
polarization
Scattering ‘center’ is closer at one
polarization
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Weather radar (cm-wavelength) polarimetry
Concentration
Shape
Size
Orientation
Phase
Density
Absolute
calibration Attenuation Radar Reflectivity Ze
Differential attenuation DA
Propagation diff. phase shift KDP
Differential reflectivity ZDR
Backscattering diff. phase δ
How much power scattered back
One polarization is attenuated more
One polarization propagates faster
Scattering is more efficient at one
polarization
Scattering ‘center’ is closer at one
polarization
Variables sensitive to
different properties
A set used for classification
and quantitative estimates
See Kumjian 2013, J. Operational Meteor. For more details 2
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• 94 GHz scanning radar
• STSR mode (Myagkov et al 2016, AMT)
• Rain event with intensity up to 15 mm/hr
• Backscattering signatures in melting layer
• ZDR in rain <0.2 dB
• PHI in rain up to 3 deg
• KDP signatures in ice area
Observations at
30˚ elevation
Plankton
Melting layer
Liquid precipitation
Ice Strong attenuation
Cloud radar (mm-wavelength) polarimetry
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Rain
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Precipitation
Ice
Melting layer
Cloud radar (mm-wavelength) polarimetry
Observations at
30˚ elevation
No signatures in
integrated polarimetric
variables in rain
Are polarimetric
observations at 94 GHz
in rain useless?
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Water particle cross-section
at millimeter wavelength
Mie oscillations
(resonance
effect, scatter
comparable to
wavelength)
Size
No
rmal
ized
bac
ksca
tter
ing
Rayleigh scattering
(scatter smaller
than wavelength)
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Water particle cross-section
at millimeter wavelength
Size
No
rmal
ized
bac
ksca
tter
ing
V-pol
H-pol
ZDR ~ 1
De = 0.2 mm
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Water particle cross-section
at millimeter wavelength
Size
No
rmal
ized
bac
ksca
tter
ing
H-pol
V-pol
ZDR > 1
De = 1 mm
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Water particle cross-section
at millimeter wavelength
Size
No
rmal
ized
bac
ksca
tter
ing
H-pol
V-pol
ZDR < 1
De = 1.8 mm
Polarimetric “oscillations”
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Polarimetric oscillations for a water spheroid
Can we observe this oscillatory behavior in drop scattering?
Known size-terminal velocity relations
Spectral polarimetry
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Case study, 9 June 2018, 21:20 UTC
Spectral reflectivity [dBZ]
Observations at
30˚ elevation
Strong
attenuation
Slower drops
on the right Faster drops
on the left
Towards the radar Away from the
radar
• Observations at low
elevation angles are
strongly influenced by
air motions
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Case study, 9 June 2018, 21:20 UTC
Rough mitigation of wind effects
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Observations at
30˚ elevation
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Case study, 9 June 2018, 21:20 UTC
Rough mitigation of wind effects
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Observations at
30˚ elevation
Polarimetric oscillations!
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Comparison of model and observations
Model Obs.
Good agreement
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Data processing: Separation of backscattering and propagation effects Absolute radar calibration (manuscript in preparation with S. Kneifel) Microphysics: DSD profiling (at relatively low elevations) Rain microphysical processes (similar to F. Tridon and C. Williams)
Applications
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Ice
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Single particle type cannot explain the observations
KDP signatures in ice area
Observations at
30˚ elevation
Mo
del
Ob
serv
ati
on
s
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Spectral observations
Spectral polarimetry resolves different types of particles in a volume 16
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Applications of spectral polarimetry Data processing:
• Separation of backscattering and propagation effects
• Absolute radar calibration (manuscript in preparation with S. Kneifel)
Rain:
• DSD profiling (at relatively low elevations)
• Rain microphysical processes (similar to F. Tridon and C. Williams)
Ice:
• Detection of secondary ice production
• Detailed quantitative characterization of ‘pristine’ ice particles (incl. shape, size, concentration)
For more details contact [email protected] 17
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Supplementary slides
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