Remote sensing of Stratocumulus using radar/lidar synergy Ewan O’Connor, Anthony Illingworth & Robin Hogan University of Reading.

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Presentation transcript:

Remote sensing of Stratocumulus using radar/lidar synergy Ewan O’Connor, Anthony Illingworth & Robin Hogan University of Reading

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

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

Algorithm Assume gamma distribution of the form Radar reflectivity, Z Lidar backscatter  extinction coefficient (    ) Ratio of Z to  gives first guess of D 0

Algorithm Doppler spectral width,  v   and improved D 0 D 0 and  v  V T, Z-weighted terminal fall velocity Air velocity, w (+ve upwards) LWC and LWF

Observations Lidar backscatter Radar reflectivity

Observations Doppler spectral width Doppler velocity

Observations Lidar backscatter Radar Reflectivity

Derived Parameters Median Diameter Shape parameter

Derived Parameters Liquid Water Flux Liquid Water Content

Derived Parameters Droplet fall velocity Air velocity

Cellular Structure

Observations Lidar backscatter Radar reflectivity

Observations Doppler spectral width Doppler velocity

Derived Parameters Median Diameter Shape parameter

Derived Parameters Liquid Water Flux Liquid Water Content

Derived Parameters Droplet fall velocity Air velocity

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

Technique 3: Doppler spectra Identify cloud mode and drizzle mode - determine w Infer Z of drizzle mode and cloud mode w from cloud mode

Doppler spectra Drizzle droplets have significant terminal velocities (>1 m s -1 ) Much higher reflectivity since Z = ND 6

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

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

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

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

Chilbolton observations Sc present 26% of the time 50% of Sc seen by radar contains drizzle droplets

Observations

Derived Parameters

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)

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