1. Determination of optical and microphysical Properties of Water Clouds

2.  LCRS 2004 Retrieved Parameters  Cloud optical thickness  Cloud effective droplet radius  Cloud top height  Liquid water path  Thermodynamic phase

3.  LCRS 2004 Retrieved Parameters – Mathematical formulation  Effective cloud droplet radiusOptical thickness

4.  LCRS 2004 Basic concept of optical retrievals  reflectance / emission of a cloud  microphysical cloud parameters

5.  LCRS 2004 Reflection Function  = ratio of reflected light intensity of a cloud to that of an ideal Lambertian white reflector  for Lambertian ideally white reflector  Clouds are not a Lambertian reflector   geometric dependence of R   transmission of incident radiation

6.  LCRS 2004 Reflection Function – Geometric Dependence  Exact radiative transfer code (Mishchenko et al. 1999) using Gamma size distribution: 1

7.  LCRS 2004 Reflection Function – Transmission  = reflection function of a semi-infinite, non-abs. cloud  = global transmittance of a cloud  = asymmetry parameter  = escape functions  VIS: Reflection reduces due to transmission

8.  LCRS 2004 Dependence of R VIS on    a ef   Reflection function of clouds in VIS  depends strongly on optical thickness  depends weakly on a ef (Kokhanovsky et al. 2003)

9.  LCRS 2004 Reflection Function – NIR  NIR: Reflection reduces due to transmission and weak absorption   Satellite signal is composed of a) solar component and b) thermal component  = reflection function of a semi-infinite cloud  = diffusion exponent  = escape functions

10.  LCRS 2004 Dependence of R NIR on    a ef   Reflection function of clouds in NIR (weakly absorbing)  depends strongly on a ef  depends moderately on optical thickness (Kokhanovsky et al. 2003)

11.  LCRS 2004 Dependence of R NIR a ef Large droplets  Volume is dominant parameter  Absorption > Reflection Small droplets  Cross-section is dominant parameter  Reflection > Absorption

12.  LCRS 2004 Dependence of R on    a ef  for VIS and NIR Sensor Signal Parameter VISNIR  very strongmoderate a ef weakvery strong

13.  LCRS 2004 Dependence of Radiance Density on    a ef   Retrieval of cloud parameters is possible with VIS / NIR bands of satellite sensors

14.  LCRS 2004 Examples of suitable systems – Meteosat-8 SEVIRI  Meteosat-8  Eumetsat  geostationary orbit (0°)  launch: 28.08.2002  operational since 4/2004  available at least up to 2012  SEVIRI Sensor  repetition: 15 minutes  12 bands:  2 VIS (3km)  2 NIR (3km)  7 WV/IR (3km)  1 HRV (1km)

15.  LCRS 2004 Examples of suitable systems – Terra-/Aqua-MODIS  Terra & Aqua  NASA (EOS)  sun-synchronous orbit  Terra  launch 1999-12-18  EOS-AM (10:30 south)  Aqua  launch 2002-05-04  EOS-PM (13:30 north)  MODIS Sensor  36 bands (0,62 – 14,39 µm)  resolution 1km  2 VIS (250m)  5 VIS/NIR (500m)

16.  LCRS 2004 Retrieval Concepts  Look-up table approach  = satellite signal is iteratively lined with pre-calculated look-up tables connecting cloud microphysical parameters with measured radiance density in VIS/NIR bands.  GTR (T. Nakajima, T. Y. Nakajima, Kawamoto)  NASA MOD06 (Platnick, King, Ackerman, Menzel, Baum, Riédi, Frey)  Semianalytical approach  = satellite signal is used for the solution of a simplified, single semi- analytical equation which is derived from exact radiative transfer equations.  SACURA (Kokhanovsky)

17.  LCRS 2004 Example 1 - GTR  Look-up table approach  GTR retrieval  T. Nakajima, T. Y. Nakajima, Kawamoto

18.  LCRS 2004 GTR – Extraction of Radiance Density from Signal  VIS  NIR ground reflection cloud thermal componentground thermal component

19.  LCRS 2004 GTR - Preparation of LUTs  Grid system of LUTs  1.,2.,4.,6.,9.,14.,20.,30.,50.,70. 2.,4.,6.,9.,12.,15.,20.,25.,30.,35.,40. 0.,5.,10.,20.,30.,35.,40.,45.,50.,55.,60. 0.,5.,10.,20.,30.,35.,40.,45.,50.,55.,60.,65.,70. 0.,10.,20.,30.,40.,50.,60.,70.,80.,90.,100.,110.,120.,130.,140.,150.,160.,170.,180.  Liquid water content for several classified cloud types  Cu, Sc0.300 g/m 3 As, Ac0.250 g/m 3 Ci, Cs, Cc0.014 g/m 3 Ns0.300 g/m 3 Cb0.393 g/m 3 St1.540 g/m 3 Pruppacher & Klett 1978, Heymsfield 1993

20.  LCRS 2004 GTR - Preparation of additional datasets  Cloud-free albedo maps (monthly mean – minimum map)  VIS and NIR (solar radiation only) band  6S code (Tanré 1990)  Cloud-free background BTT map (actual scene)  Multiple regression function  Latitude  Longitude  Height above sea level (DGM)  Temperature  Vertical profiles (actual scene)  MM5, Sounding data, etc.  Temperature  Humidity  Pressure

21.  LCRS 2004 GTR – Additional datasets Satellite data VIS / NIR bands Cloud-free albedo maps (6S) Cloud-free ground BBT map Radiative-Transfer-Calculation Radiance Density / BBT vs. microphysical Parameters Iteration Satellite data - LUTs Actual Atmosphere Profiles MM5 Sounding data

22.  LCRS 2004 GTR – Flow of Analysis (Kawamoto et al. 2001)

23.  LCRS 2004 GTR – Calculation of w, D and Z  Liquid water path  Geometrical thickness  Cloud-top height from vertical profile data

24.  LCRS 2004 GTR – Input Satellite Data Radiance density 0.6µm Radiance density 3.9µm [W/m 2 /µm/sr] [W/m 2 /µm/sr]

25.  LCRS 2004 GTR - Results Terra-MODIS, 2002-08-05, 11:05 GMT Re[µm]  11µm T[K]

26.  LCRS 2004 Example 2 - SACURA  Semianalytical approach  SACURA retrieval  A. A. Kokhanovsky

27.  LCRS 2004 SACURA – Retrieval of a ef &  for 2 band algorithm 01  VIS  NIR  can be calculated by simple approximation equations

28.  LCRS 2004 SACURA – Retrieval of a ef &  for 2 band algorithm 02  from VIS:  from scaled optical thickness:  from other simplifications:     Substitution in R 2 retrieves a ef with a single transcendent equation    is retrieved subsequently with equation above

29.  LCRS 2004 SACURA - Results Terra-MODIS, 2002-08-05, 11:05 GMT Re[µm]  11µm T[K]

30.  LCRS 2004 Error Estimation  Theoretical Errors

31.  LCRS 2004 Error Estimation - SACURA  Error of R due to simplification of semi-analytical equations (Kokhanovsky et al. 2003)

32.  LCRS 2004 Error Estimation - GTR  Error of retrieved parameters when applied to simulated satellite signals using  [5;10;15] at a ef 10µm and a ef [6;10;16µm] at  = 10. (Kawamoto et al. 2001)

33.  LCRS 2004 Intercomparison  Intercomparison  SACURA vs. GTR. vs MOD06

34.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 Terra-MODIS, 2001-07-18, 15:30 GMT  a ef [µm] GTR SACURA MOD06

35.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06  a ef [µm] GTR SACURA MOD06

36.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 - a ef Terra-MODIS, 2001-07-18, 15:30 GMT

37.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 -  Terra-MODIS, 2001-07-18, 15:30 GMT

38.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 – Freq. Terra-MODIS, 2001-07-18, 15:30 GMT

39.  LCRS 2004 Conclusion  Retrieval of a ef and  from satellite data is possible  Retrieval is one realization of the reality  LUT and asymptotic theory approaches have errors due to  Inhomogeneous clouds  Errors in additional datasets, partly cloud covered pixels etc.  Errors of asymptotic approach are negligible for optically thick clouds  Asymptotic equations can be simplified with negligible errors for  > 5

40.  LCRS 2004 Outlook  We will join efforts to implement a new version combining both approaches   > 10  semi-analytical equations   < 5  LUT approach  5 <  < 10  one of both but we will see….   Optimized algorithm with regard of  minimization of computer time and  minimization of errors

41.  LCRS 2004 Acknowledgments  Alexander A. Kokhanovsky

42.  LCRS 2004 Thank you  The End

43.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 Terra-MODIS, 2002-08-10, 09:45 GMT a ef [µm]  GTR SACURA MOD06

44.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 - a ef Terra-MODIS, 2002-08-10, 09:45 GMT

45.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 -  Terra-MODIS, 2002-08-10, 09:45 GMT

46.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 – Freq. Terra-MODIS, 2002-08-10, 09:45 GMT

47.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 – Delta Terra-MODIS, 2002-08-10, 09:45 GMT

48.  LCRS 2004 SACURA – Lambert surface reflection  VIS  Large optical thickness  direct solar light term can be neglected  NIR  can be calculated by simple approximation equations

49.  LCRS 2004 Error Estimation - SACURA  Error of retrieved parameters due to measurement errors and  (Kokhanovsky et al. 2003)

50.  LCRS 2004 Geometry

51.  LCRS 2004 Compatibility SEVIRI – MODIS SEVIRIMODIS VIS 0,6Kanal 1 VIS 0,8Kanal 15 NIR 1,6Kanal 6 NIR 3,9Kanal 21 WV 6,2Kanal 27 WV 7,3Kanal 28 IR 8,7Kanal 29 IR 9,7Kanal 30 IR 10,8Kanal 31 IR 12,0Kanal 32 IR 13,4Kanal 33 / 34 HRV

52.  LCRS 2004 GTR - Preparation of LUTs  Grid system of LUTs  1.,2.,4.,6.,9.,14.,20.,30.,50.,70. 2.,4.,6.,9.,12.,15.,20.,25.,30.,35.,40. 0.,5.,10.,20.,30.,35.,40.,45.,50.,55.,60. 0.,5.,10.,20.,30.,35.,40.,45.,50.,55.,60.,65.,70. 0.,10.,20.,30.,40.,50.,60.,70.,80.,90.,100.,110.,120.,130.,140.,150.,160.,170.,180.  Liquid water content for several classified cloud types  Cu, Sc0.300 g/m 3 As, Ac0.250 g/m 3 Ci, Cs, Cc0.014 g/m 3 Ns0.300 g/m 3 Cb0.393 g/m 3 St1.540 g/m 3 ISCCP, Rossow et al. 1996 Pruppacher & Klett 1978, Heymsfield 1993

53.  LCRS 2004 Retrieved Parameters  Cloud optical thickness [1... 70] resp. [5...150]  Cloud effective droplet radius[1...40 µm] resp. [1...140µm]  Cloud top height [0.1...10 km]  Liquid water path […50...200…g/m 2 ]  Thermodynamic phase (ice, water, mixed clouds)

54.  LCRS 2004 Intercomparison SACURA vs. GTR vs. MOD06 – Delta Terra-MODIS, 2001-07-18, 15:30 GMT