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The retrieval of the LWC in water clouds: the comparison of Frisch and Radar-Lidar techniques

Third Progress Meeting 24-25 April 2003 , Reading. The retrieval of the LWC in water clouds: the comparison of Frisch and Radar-Lidar techniques. O. A. Krasnov and H. W. J. Russchenberg International Research Centre for Telecommunications-transmission and Radar,

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The retrieval of the LWC in water clouds: the comparison of Frisch and Radar-Lidar techniques

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  1. Third Progress Meeting24-25 April 2003, Reading The retrieval of the LWC in water clouds:the comparison of Frisch and Radar-Lidar techniques 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. 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.

  3. The relation between “in-situ” Effective Radius and Radar Reflectivity to Lidar Extinction Ratio for different field campaigns.

  4. Application of the relation for the identification of the Z-LWC relationship

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

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

  7. Case study: August 28, 2001, Cabauw, NL, 10.12-11.20The Resulting Classification Map (radar and lidar data)

  8. Case study: August 28, 2001, Cabauw, NL, 10.12-11.20Retrieval Results (classification using radar and lidar data)

  9. Frisch’s algorithm • log-normal drop size distribution • concentration and distribution width are constant in the cloud From radiometer’s LWP and radar reflectivity profile:

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

  11. 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

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

  13. 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

  14. Case: cloud without drizzle

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

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

  17. Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The profiles of optical extinction and Radar-Liadr Ratio

  18. Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The Classification Map (Radar-Lidar, threshold -35 and -25 dB)

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

  20. Atlas Z-LWC relationship

  21. 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

  22. Conclusions • The Frisch’s technique produce much more water • It does not recognize the presence of in-cloud drizzle • For the log-normal model Frisch’s fitting of Z-LWC relationships shows huge, non-realistic concentrations

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