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Remote sensing of Stratocumulus using radar/lidar synergy

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

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Remote sensing of Stratocumulus using radar/lidar synergy

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

  2. 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

  3. 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

  4. Algorithm • Assume gamma distribution of the form • Radar reflectivity, Z • Lidar backscatter  extinction coefficient (  ) • Ratio of Z to  gives first guess of D0

  5. 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

  6. Observations Lidar backscatter Radar reflectivity

  7. Observations Doppler velocity Doppler spectral width

  8. Observations Radar Reflectivity Lidar backscatter

  9. Derived Parameters Median Diameter Shape parameter

  10. Derived Parameters Liquid Water Content Liquid Water Flux

  11. Derived Parameters Air velocity Droplet fall velocity

  12. Cellular Structure

  13. Observations Lidar backscatter Radar reflectivity

  14. Observations Doppler velocity Doppler spectral width

  15. Derived Parameters Median Diameter Shape parameter

  16. Derived Parameters Liquid Water Content Liquid Water Flux

  17. Derived Parameters Air velocity Droplet fall velocity

  18. 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

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

  20. Doppler spectra • Drizzle droplets have significant terminal velocities (>1 m s-1) • Much higher reflectivity since Z = ND6

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

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

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

  24. 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

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

  26. Observations

  27. Observations

  28. Derived Parameters

  29. Derived Parameters

  30. Derived Parameters

  31. 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)

  32. 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)

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