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Multiwavelength aerosol lidar and vertical-wind lidar observations during COPS

Multiwavelength aerosol lidar and vertical-wind lidar observations during COPS Dietrich Althausen, Detlef Müller, Ronny Engelmann, Matthias Tesche, Patric Seifert, Julia Fruntke, Christina Herold, Luise Hentschel, (Albert Ansmann)

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Multiwavelength aerosol lidar and vertical-wind lidar observations during COPS

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  1. Multiwavelength aerosol lidar and vertical-wind lidar observations during COPS Dietrich Althausen, Detlef Müller, Ronny Engelmann, Matthias Tesche, Patric Seifert, Julia Fruntke, Christina Herold, Luise Hentschel, (Albert Ansmann) Leibniz Institute for Tropospheric Research, Leipzig, Germany

  2. Aerosol and vertical–velocity profiling and cloud glaciation observations during COPS Applicant: Albert Ansmann Contribution to ACM and SPP 1167 (2 year period) • Aerosol characterization • Obtaining geometrical, optical, and microphysical properties of aerosols and clouds • Derivation of microphysical properties such as aerosol number concentration • Vertical Wind in the upper PBL (at cloud base) • Studies of heterogeneous ice formation • Investigating the effect of aerosol particles and meteorological conditions on cloud glaciation • Many Saharan dust cases and forest fire cases observed DFG proposal

  3. Backscatter Extinction lidar-Ratio Temperature Humditiy profiling Apparatus Wind Lidar 3 months of data, 400-500 hours

  4. 6 x beta2xsigma INDOEX, Maldives 1999-2000 SAMUM I, Morocco, May-Jun 2006 COPS, Black F., Jun-Aug 2007 SAMUM II, Cape Verde, Jan/Feb+May/Jun 2008

  5. Inversion algorithm • Input: • 6 backscatter coefficients • 2 extinction coefficients • Output: • volume size distribution • effective radius • total volume concentration • total surface-area concentration • mean complex refractive index • single-scattering albedo COPS: β(532nm) ~ n (particle number conc.)

  6. VALIDATION OF INVERSION RESULTS WITH AIRBORNE IN-SITU MEASUREMENTS DLR Falcon COPS: we may only get the order of magnitude of the particle number conc. (100 cm-3, 1000 cm-3, 10000 cm-3)

  7. Aerosol type: finger prints Aerosol type Lidar ratio (sr) Depol. ratio (%) Maritime S355=S532(low) <5% (low) UrbanS355>=S532 (high) <5% (low) Forest fire smokeS355<S532(high) <10-15% (med) Desert DustS355>=S532(high) 25-35% (high) 355 nm versus532 nm

  8. COPS: Some measurement examples

  9. PBL+CU Vertical wind

  10. P B L d e v e l o p m e n t in terms of vertical wind profile of horiz. wind speed and direction

  11. Spectacular event Deep cumulus tower

  12. Heterogenous ice formation melting layer uncalibrated depol. ratio (710nm)

  13. Bertha + Wili AC CI ICE terminal velocities

  14. Topic 2 Topic 1 heterog. ice form. PBL

  15. Our work on heterogenous ice formation Published February 2008 SAMUM II: 15 Jan – 14 Feb 2008, Praia, Cabo Verde (15oN, 23.5oW) …upcoming Influence of Saharan dust and biomass burning smoke on cloud glaciation over the northern tropical Atlantic Ocean (Cape Verde) during SAMUM II

  16. Next future (beginning in March 2008): Diploma student working on WiLi data (wind fields) Diploma student working on Raman lidar data (water vapor and temperature)

  17. BERTHA, Heselbach, 532nm backscatter signal PBL, sunny daydust

  18. BERTHA, water vapor Raman lidar, Heselbach 532 nm backscatter signal SONDE LIDAR LIDAR g/kg LIDAR, 20 min, 60m smoothing LIDAR, 1 min, 240 m smoothing

  19. COPS: Bertha (Raman lidar) water vapor nighttime, 1 min res., 60 m height res.

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