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Cloud liquid water path and drizzle from attenuation of CloudSat ocean return ( s 0 )

Cloud liquid water path and drizzle from attenuation of CloudSat ocean return ( s 0 ). Lee Smith Anthony Illingworth. Surface echo attenuation method. Two - way attenuation at 94 GHz:. Oxygen: 0.35-0.4 dB Water: Ice particles: negligble Liquid water: ~ 1dB per 120 gm -2

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Cloud liquid water path and drizzle from attenuation of CloudSat ocean return ( s 0 )

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  1. Cloud liquid water path and drizzle from attenuation of CloudSat ocean return (s0) Lee Smith Anthony Illingworth

  2. Surface echo attenuation method

  3. Two - way attenuation at 94 GHz: • Oxygen: 0.35-0.4 dB • Water: • Ice particles: negligble • Liquid water: ~ 1dB per 120 gm-2 • Water vapour: ~ 1dB per 10 000 gm-2 • Factor of ~100 greater attenuation for liquid water  liquid water drops dominate attenuation in cloudy conditions • Use of CALIPSO lidar allows discrimination between clear sky and cloudy areas

  4. Corrections to surface echo (1) Temperature dependent vapour attenuation, using AMSR-E vapour path, model temperatures and Liebe attenuation model (2) Correct for poor vertical sampling of surface echo (3) Derive combined Wind/SST correction table for variability in surface echo derived from clear sky data Surface echo well characterized

  5. Statistics of corrected clear sky so: Standard deviation of s0 generally < 0.5 dB 50 gm-2even over 200 km

  6. Case study: Measure attenuation • Identify clear sky using LIDAR and set reference s0 (blue line) 20 km

  7. Case study: Liquid water path: • Multiply attenuation by temperature dependent coefficient LWP • Compare with MODIS, AMSR-E and Z-R relationship

  8. Case study: Drizzle 0.16 0.033 0.007 0.0012 Drizzle rate mm hr-1 • Simulate adiabatic LWC from LWP and LIDAR cloud top

  9. Advantages: • LWP at 1km resolution coincident with cloud profiles during both local day and night • Possibility that lack of shadowing effects may give advantage over MODIS in horizontally small cumulus • Simple discrimination between drizzling and non-drizzling clouds by comparison of simulated Z from cloud water content and observed Z (dominated by drizzle) • Method can be applied to boundary layer clouds beneath ice cloud

  10. Next steps: • Currently refining quality flags • Statistics of LWP and drizzle occurrence • Model comparisons

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