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The retrieval of the LWC in water clouds

The retrieval of the LWC in water clouds. O. A. Krasnov and H. W. J. Russchenberg International Research Centre for Telecommunications-transmission and Radar, Faculty of Information Technology and Systems, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands.

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The retrieval of the LWC in water clouds

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  1. The retrieval of the LWC in water clouds O. A. Krasnov and H. W. J. Russchenberg International Research Centre for Telecommunications-transmission and Radar, Faculty of Information Technology and Systems, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands. Ph. +31 15 2787544, Fax: +31 15 2784046 E-mail: o.krasnov@irctr.tudelft.nl, : h.w.j.russchenberg@irctr.tudelft.nl

  2. Radar reflectivity Liquid water content Dropsize distribution Very sensitive to tail of dsd Are power laws useful?

  3. drizzle “transition” drizzle A million droplets of 10 micron give the same radar reflection as one droplet of 100 micron! A million droplets of 10 micron contain a thousand times as much water as one one droplet of 100 micron... And so: one drizzle droplet changes the reflectivity significantly without changing the liquid water content non-drizzling

  4. Common opinion: No, there is too much scatter due to drizzle unless we can identify the drizzle droplets somehow...

  5. Techniques for identification • Radar reflection • Separation based on differences in reflectivity of drizzle • and non-drizzling clouds • High resolution Doppler radar • Separation based on differences in fall speeds • Radar – lidar combination • Separation based on differences in sensitivity of reflection • on droplet size

  6. Radar reflection Drizzling Non-drizzling Coarse classification

  7. Radar and lidar observables in relation to microphysical water cloud. Radar-lidar ratio vs effective radius Radar reflectivity vs liquid water content

  8. The Radar, Lidar, and Radiometer datasetfrom the Baltex Bridge Cloud (BBC) campaign August 1- September 30, 2001, Cabauw, NL • Radar Reflectivity from the 95 GHz Radar MIRACLE (GKSS) • Lidar Backscattering Coefficient from the CT75K Lidar Ceilometer (KNMI) • Liquid Water Path from the 22 channel MICCY (UBonn) All data were presented in equal time-height grid with time interval 30 sec and height interval 30 m.

  9. Case study: August 28, 2001, Cabauw, NL, 10.12-11.20 The profiles of measured variables

  10. Case study: August 28, 2001, Cabauw, NL, 10.12-11.20The profiles of Optical Extinction and Radar-Lidar Ratio

  11. Z1 = -20 dBZ, Z2 = -10 dBZ; thresholds for radar only

  12. + 0 dB

  13. + 5 dB

  14. + 10 dB

  15. 0 dB + 5 dB + 10 dB

  16. Frisch’s algorithm • log-normal drop size distribution • concentration and distribution width are equal to constant values From radiometer’s LWP and radar reflectivity profile:

  17. Case study: August 28, 2001, Cabauw, NL, 10.12-11.20Retrieval Results for Frisch’s algorithm

  18. Case study: August 28, 2001, Cabauw, NL, 10.12-11.20 Histogram of Differences in Retrieval Results for the Frisch’s and the Radar-Lidar algorithm

  19. Difference between LWC that retrieved using Frisch method and retrieved from radar-to-lidar ratio

  20. Case study: August 28, 2001, Cabauw, NL, 10.12-11.20Representation results on the Z-LWC plane Frisch’s fittings Log-Normal DSDN=1000 - 2000 cm-3, s = 0.8N=1000 - 2000 cm-3, s = 0.1

  21. Case: cloud without drizzle

  22. Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The profiles of measured variables

  23. Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The Resulting Classification Map (radar and lidar data)

  24. Atlas Z-LWC relationship

  25. Frisch’s fittings Log-Normal DSDN=1000 - 2000 cm-3, s = 0.8N=1000 - 2000 cm-3, s = 0.1 Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The results of Frisch’s algorithm application

  26. Z-LWC relationship based on aircraft data

  27. Comparison aircraft – radar data

  28. September 23, 2001, Z+13 dBZ Merlin flight Frisch Z-LWC relations after adding 13 dB to Z

  29. September 23, 2001, Z+13 dBZ Atlas equation

  30. September 23, 2001, Z+13 dBZ Frisch retrievals

  31. September 23, 2001, Z+13 dBZ Atlas - Baedi - Drizzle equations Frisch retrievals – Z/ retrieval

  32. Radar intercomparison; Miracle - KNMI In ice clouds also agreement with Tara

  33. Possible explanations for radar – aircraft difference Cloud inhomogeneity: temporal and spatial sampling? Clipping of Doppler spectrum?

  34. Conclusions • Given a proper calibration of the instruments, • Radar-lidar • Radar-microwave radiometer • Radar alone • produce similar LWC profiles of non-drizzling clouds. What’s going on with the radar data?

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