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Gerd-Jan van Zadelhoff & Dave Donovan

Comparing ice-cloud microphysical properties using Cloudnet & ARM data. Gerd-Jan van Zadelhoff & Dave Donovan. GOAL : Compare and evaluate microphysical cloud properties at 3 sites.

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Gerd-Jan van Zadelhoff & Dave Donovan

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  1. Comparing ice-cloud microphysical properties using Cloudnet & ARM data. Gerd-Jan van Zadelhoff & Dave Donovan

  2. GOAL : Compare and evaluate microphysical cloud properties at 3 sites 2 sites: coastal Europe, 1 site: Southern great plains; USA Site Instrument Period 1. Cabauw: • 35 GHz Radar Oct 2001 – June 2003 • 905 nm CT-75 Ceilometer • ECMWF data (T & P) Oct 2001 – March 2002 2. Chilbolton: • 94 GHz Radar (Galileo) • 905 nm CT-75 Ceilometer Due to problems with Galileo only Z> -20 dB is used • ECMWF data (T & P) 3. ARM: • 35 GHz Radar Nov/Dec 1996 June 1997 Jan & July 2000 • 532 nm Micro Pulse Lidar (MPL) • Sonde data (T & P)

  3. Selection of cloud typed • T < -2 oC • Radar and Lidar top of • cloud are roughly the same. • Ice-clouds are optically thin. • Ice clouds • Visible in both Lidar and Radar Both Radar and Lidar Only Radar 11-03-2002 24-05-2002 Particle sizes (R’eff) Only Lidar

  4. Selection of cloud typed • T < -2 oC • Radar and Lidar top of • cloud are roughly the same. • Ice-clouds are optically thin. • Ice clouds • Visible in both Lidar and Radar INCLUDED EXCLUDED Particle sizes (R’eff)

  5. High Cloud Statistics: Frequency of cumulated IR transmissive clouds above 4 km. (11 year mean of the month June, HIRS data NOAA) Wylie & Menzel (1998)

  6. Comparing vertical cloud statistics at the three sites. Observed low t clouds ARM Cabauw Chilbolton Shown is the normalized cloud height distribution FOR EACH cloud pixel detected

  7. Example for an ice-cloud measured at Cabauw. Radar Reflectivity (KNMI 35 GHz) Effective radius of the particles (Reff) Relative Backscatter (KNMI CT-75)

  8. How to deal with the observed clouds Define the regions wherein 10, 30, 60, 90 and 99 % of all observed values reside Plot for every cloud pixel the appropriate values (T vs R’eff) Calculate the mean in each x-bin (DT) and the s of the distribution

  9. R’eff vs. T Doppler velocity vs. R’eff ARM vs CABAUW a vs. Z IWC’ vs Z

  10. Height vs. particle size Reff vs T (complex poly-crystals) Height vs. Size ARM vs CABAUW Depth from top of cloud vs. Size IWC’ distribution

  11. Dependence of the retrieved particle sizes on Z. Particle size versus Temperature (with lower limit to used Z data) Height dist. of the probed clouds (with lower limit to used Z data) Need to use data with Z > -20 dBz for comparison with The GALILEO radar in the 2001-2002 period.

  12. R’eff vs. T IWC vs. Z (complex poly-crystals) -ARM -Cabauw -Chilbolton Depth from top of cloud vs. Size Height vs. particle size Z > -20 dB

  13. Seasonal influences on the low optical depth ice clouds Top row: Cabauw WINTER SPRING SUMMER AUTUMN HEIGHT R’eff Log10(IWC’) HEIGHT Bottom row: ARM R’eff Log10(IWC’)

  14. CONCLUSIONS • Cabauw & Chilbolton show very similar results • (for Z > -20 dBz) • Derived parameter relations depend strongly on the lowest • value of Z for Z > -30 dBz 3. The ARM site has higher and thicker ice-clouds the latter results in a larger particle size distribution. 4. The cabauw site shows no seasonal dependence for the low optical depth ice-clouds studied here. The ARM site shows a small dependence.

  15. THE END ! THANKS DAVE !!! For questions or comments: ask Dave or contact me: zadelhof@knmi.nl

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