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Anthony Illingworth, Robin Hogan , Ewan O

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CloudNET: retrieving turbulence parameters from cloud radar. Anthony Illingworth, Robin Hogan , Ewan O Connor, U of Reading, UK Dominique Bouniol, CETP, France – PowerPoint PPT presentation

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Title: Anthony Illingworth, Robin Hogan , Ewan O


1
CloudNET retrieving turbulence parameters from
cloud radar.
  • Anthony Illingworth, Robin Hogan , Ewan OConnor,
    U of Reading, UK
  • Dominique Bouniol, CETP, France

2
New method of estimating turbulence
Previous methods used Doppler spectral width
(for ground based radar) ? but also
contributions from shear and terminal velocity
Spectral analysis of w (from airborne and ground
observations) ? only gives e at a given level
time noisy for low w.
3
Turbulence measurements
  • Changes in 1-s mean Doppler velocity dominated by
    changes in vertical wind, not terminal fall-speed
  • We calculate new parameter 30-s standard
    deviation of 1-s mean Doppler velocity, sv
  • Can use this to estimate turbulent kinetic energy
    dissipation rate
  • Important for vertical mixing, warm rain
    initiation in cumulus etc.

Spectral width sv contaminated by variations in
particle fall speed
4
Measurements of sigma-v-bar
  • 26 Jan 2004

Stable layer sv3 mm/s
Frontal shear layer sv3 cm/s
Unstable evaporating layer sv30 cm/s
5
TKE dissipation rate ?
  • Part of TKE spectrum can be interpreted in terms
    of the variance of the mean Doppler velocity
  • k1 is min horizontal wavenumber sampled in 30 s
    (use model winds)
  • k2 is max horizontal wavenumber due to beamwidth
    of radar
  • In the inertial sub-range (Kolmogorov)
  • Hence by integration

6
Calculation of ?
1. Use model winds to find the value of k1.
- this may fail in the tropics unpredictable
winds. ideally have a co-located wind
profiler. 2. Remove any linear trends in the one
second value of v this could be due
to gravity waves. 3. Check that changes in v not
due to gradients in Z leading to changes in
terminal velocity, by computing ?Z/Z(av).
Reject data if this is too high.
7
Dissipation rate in different clouds
  • Z
  • ?

8
1 year of CloudNet data
  • PDF of dissipation rate for different types of
    cloud
  • Note that aircraft measurements have lower limit
    of detectability of 106 due to aircraft
    vibrations

?0.02 to trigger Coalescence in Cu? Khain and
Pinsky, 1997
Previous range for cirrus found from aircraft
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