Remote sensing of Stratocumulus using radarlidar synergy

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Remote sensing of Stratocumulus using radar/lidar
synergy

• Ewan OConnor, Anthony Illingworth Robin Hogan
• University of Reading

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Importance of Stratocumulus

• Most common cloud type globally
• Global coverage 26
• Ocean 34
• Land 18
• Average net radiative effect is about 65 W m-2
• Cooling effect on climate

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Role of drizzle

• Ubiquitous in clouds deeper than 300m
• Determines cloud lifetime and evolution
• Alters droplet spectra
• Implications for the processing of aerosol
  particles
• Feedback on BL dynamics through evaporative
  cooling

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Algorithm

• Assume gamma distribution of the form
• Radar reflectivity, Z
• Lidar backscatter ? extinction coefficient (? ?
  ?)
• Ratio of Z to ? gives first guess of D0

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Algorithm

• Doppler spectral width, ?v ? ? and improved D0
• D0 and ?v ? VT, Z-weighted terminal fall
  velocity
• Air velocity, w (ve upwards)
• LWC and LWF

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Observations
Lidar backscatter
Radar reflectivity
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Observations
Doppler velocity
Doppler spectral width
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Observations
Radar Reflectivity
Lidar backscatter
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Derived Parameters
Median Diameter
Shape parameter
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Derived Parameters
Liquid Water Content
Liquid Water Flux
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Derived Parameters
Air velocity
Droplet fall velocity
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Cellular Structure
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Observations
Lidar backscatter
Radar reflectivity
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Observations
Doppler velocity
Doppler spectral width
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Derived Parameters
Median Diameter
Shape parameter
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Derived Parameters
Liquid Water Content
Liquid Water Flux
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Derived Parameters
Air velocity
Droplet fall velocity
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Technique 3 Doppler spectra

• Can use Doppler spectra to infer vertical air
  velocity, w, since small cloud droplets act as
  tracers (4 cm s-1)
• Shows cellular nature of updrafts and downdrafts

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Technique 3 Doppler spectra

• Identify cloud mode and drizzle mode - determine
  w
• Infer Z of drizzle mode and cloud mode

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Doppler spectra

• Drizzle droplets have significant terminal
  velocities (gt1 m s-1)
• Much higher reflectivity since Z ND6

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Doppler spectra

• Can use spectral and drizzle techniques to obtain
  w in cloud and below cloud in drizzle

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Doppler spectra

• Can use spectral and drizzle techniques to obtain
  w in cloud and below cloud in drizzle

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Doppler spectra

• Can use spectral and drizzle techniques to obtain
  w in cloud and below cloud in drizzle

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Conclusion

• Can infer droplet number concentration in Sc
• Drizzle drop spectra and liquid water
  content/fluxes
• Dynamic motions/overturning in Sc
• Consistency shown between w derived in drizzle
  and obtained from Doppler spectra
• CloudNet 3 years, 3 sites with radar and lidar

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Chilbolton observations

• Sc present 26 of the time
• 50 of Sc seen by radar contains drizzle droplets

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Observations
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Observations
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Derived Parameters
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Derived Parameters
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Derived Parameters
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Drizzle flux versus radar reflectivity calculated
from ASTEX spectra
calculated from FSSP and 2DC size spectra
measured by the Met Office C-130 during the
Atlantic Stratocumulus Transition Experiment
(ASTEX)
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Spaceborne radar

• Global values of liquid water flux from a Z/LWF
  relationship suitable for 94GHz radar
• LWF (g m-2 s-1) 0.0093 Z 0.69 (mm-6 m-3)