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Determination of optical and microphysical Properties of Water Clouds. Retrieved Parameters. Cloud optical thickness Cloud effective droplet radius Cloud top height Liquid water path Thermodynamic phase. Retrieved Parameters – Mathematical formulation.

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retrieved parameters
Retrieved Parameters
  • Cloud optical thickness
  • Cloud effective droplet radius
  • Cloud top height
  • Liquid water path
  • Thermodynamic phase
retrieved parameters mathematical formulation
Retrieved Parameters – Mathematical formulation
  • Effective cloud droplet radius Optical thickness
basic concept of optical retrievals
Basic concept of optical retrievals
  • reflectance / emission of a cloud
  • microphysical cloud parameters
reflection function
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
reflection function geometric dependence
Reflection Function – Geometric Dependence
  • Exact radiative transfer code (Mishchenko et al. 1999) using Gamma size distribution:

1

reflection function transmission
Reflection Function – Transmission
  • VIS: Reflection reduces due to transmission
  • = reflection function of a semi-infinite, non-abs. cloud
  • = global transmittance of a cloud
  • = asymmetry parameter
  • = escape functions
dependence of r vis on m 0 a ef t
Dependence of RVIS on m0,aef, t
  • Reflection function of clouds in VIS
    • depends strongly on optical thickness
    • depends weakly on aef

(Kokhanovsky et al. 2003)

reflection function nir
Reflection Function – NIR
  • NIR: Reflection reduces due to transmission and weak absorption
  • = reflection function of a semi-infinite cloud
  • = diffusion exponent
  • = escape functions
  •  Satellite signal is composed of a) solar component and b) thermal component
dependence of r nir on m 0 a ef t
Dependence of RNIR on m0,aef, t
  • Reflection function of clouds in NIR (weakly absorbing)
    • depends strongly on aef
    • depends moderately on optical thickness

(Kokhanovsky et al. 2003)

dependence of r nir a ef
Dependence of RNIRaef

Large droplets  Volume is dominant parameter  Absorption > Reflection

Small droplets  Cross-section is dominant parameter  Reflection > Absorption

dependence of radiance density on m 0 a ef t
Dependence of Radiance Density on m0,aef, t
  • Retrieval of cloud parameters is possible with VIS / NIR bands of satellite sensors
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)

Examples of suitable systems – Meteosat-8 SEVIRI
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)

Examples of suitable systems – Terra-/Aqua-MODIS
retrieval concepts
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)
example 1 gtr
Example 1 - GTR
  • Look-up table approach
  • GTR retrieval
  • T. Nakajima, T. Y. Nakajima, Kawamoto
gtr extraction of radiance density from signal
GTR – Extraction of Radiance Density from Signal

ground thermal component

cloud thermal component

ground reflection

  • VIS
  • NIR
gtr preparation of luts
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, Sc 0.300 g/m3As, Ac 0.250 g/m3Ci, Cs, Cc 0.014 g/m3Ns 0.300 g/m3Cb 0.393 g/m3St 1.540 g/m3

Pruppacher & Klett 1978, Heymsfield 1993

gtr preparation of additional datasets
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
gtr additional datasets
GTR – Additional datasets

Satellite dataVIS / NIR bandsCloud-free albedo maps (6S)Cloud-free ground BBT map

Radiative-Transfer-CalculationRadiance Density / BBT vs.microphysical Parameters

Actual Atmosphere ProfilesMM5Sounding data

IterationSatellite data - LUTs

gtr flow of analysis
GTR – Flow of Analysis

(Kawamoto et al. 2001)

gtr calculation of w d and z
GTR – Calculation of w, D and Z
  • Liquid water path
  • Geometrical thickness
  • Cloud-top height from vertical profile data
gtr input satellite data
GTR – Input Satellite Data

Radiance density 0.6µm Radiance density 3.9µm[W/m2/µm/sr] [W/m2/µm/sr]

gtr results
GTR - Results

11µmT[K]

t

Re[µm]

Terra-MODIS, 2002-08-05, 11:05 GMT

example 2 sacura
Example 2 - SACURA
  • Semianalytical approach
  • SACURA retrieval
  • A. A. Kokhanovsky
sacura retrieval of a ef t for 2 band algorithm 01
SACURA – Retrieval of aef & t for 2 band algorithm 01
  • VIS
  • NIR
  • can be calculated by simple approximation equations
sacura retrieval of a ef t for 2 band algorithm 02
SACURA – Retrieval of aef & t for 2 band algorithm 02
  • from VIS:
  • from scaled optical thickness:
  • from other simplifications:
  •  Substitution in R2 retrieves aef with a single transcendent equation
  •  t is retrieved subsequently with equation above
sacura results
SACURA - Results

11µmT[K]

t

Re[µm]

Terra-MODIS, 2002-08-05, 11:05 GMT

error estimation
Error Estimation
  • Theoretical Errors
error estimation sacura
Error Estimation - SACURA
  • Error of R due to simplification of semi-analytical equations

(Kokhanovsky et al. 2003)

error estimation gtr
Error Estimation - GTR
  • Error of retrieved parameters when applied to simulated satellite signals using t [5;10;15] at aef 10µm and aef [6;10;16µm] at t = 10.

(Kawamoto et al. 2001)

intercomparison
Intercomparison
  • Intercomparison
  • SACURA vs. GTR. vs MOD06
intercomparison sacura vs gtr vs mod06
Intercomparison SACURA vs. GTR vs. MOD06

aef [µm]

GTR SACURA MOD06

Terra-MODIS, 2001-07-18, 15:30 GMT

t

GTR SACURA MOD06

intercomparison sacura vs gtr vs mod061
Intercomparison SACURA vs. GTR vs. MOD06

aef [µm]

GTR SACURA MOD06

t

GTR SACURA MOD06

intercomparison sacura vs gtr vs mod06 a ef
Intercomparison SACURA vs. GTR vs. MOD06 - aef

Terra-MODIS, 2001-07-18, 15:30 GMT

intercomparison sacura vs gtr vs mod06 t
Intercomparison SACURA vs. GTR vs. MOD06 - t

Terra-MODIS, 2001-07-18, 15:30 GMT

intercomparison sacura vs gtr vs mod06 freq
Intercomparison SACURA vs. GTR vs. MOD06 – Freq.

Terra-MODIS, 2001-07-18, 15:30 GMT

conclusion
Conclusion
  • Retrieval of aef and t 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 t > 5
outlook
Outlook
  • We will join efforts to implement a new version combining both approaches
    • t > 10  semi-analytical equations
    • t < 5  LUT approach
    • 5 < t < 10  one of both but we will see….
  •  Optimized algorithm with regard of
    • minimization of computer time and
    • minimization of errors
acknowledgments
Acknowledgments
  • Alexander A. Kokhanovsky
thank you
Thank you
  • The End
intercomparison sacura vs gtr vs mod062
Intercomparison SACURA vs. GTR vs. MOD06

aef [µm]

GTR SACURA MOD06

Terra-MODIS, 2002-08-10, 09:45 GMT

t

GTR SACURA MOD06

intercomparison sacura vs gtr vs mod06 a ef1
Intercomparison SACURA vs. GTR vs. MOD06 - aef

Terra-MODIS, 2002-08-10, 09:45 GMT

intercomparison sacura vs gtr vs mod06 t1
Intercomparison SACURA vs. GTR vs. MOD06 - t

Terra-MODIS, 2002-08-10, 09:45 GMT

intercomparison sacura vs gtr vs mod06 freq1
Intercomparison SACURA vs. GTR vs. MOD06 – Freq.

Terra-MODIS, 2002-08-10, 09:45 GMT

intercomparison sacura vs gtr vs mod06 delta
Intercomparison SACURA vs. GTR vs. MOD06 – Delta

Terra-MODIS, 2002-08-10, 09:45 GMT

sacura lambert surface reflection
SACURA – Lambert surface reflection
  • VIS
  • Large optical thickness  direct solar light term can be neglected
  • NIR
  • can be calculated by simple approximation equations
error estimation sacura1
Error Estimation - SACURA
  • Error of retrieved parameters due to measurement errors and t

(Kokhanovsky et al. 2003)

gtr preparation of luts1
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, Sc 0.300 g/m3As, Ac 0.250 g/m3Ci, Cs, Cc 0.014 g/m3Ns 0.300 g/m3Cb 0.393 g/m3St 1.540 g/m3

Pruppacher & Klett 1978, Heymsfield 1993

ISCCP, Rossow et al. 1996

retrieved parameters1
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/m2]
  • Thermodynamic phase (ice, water, mixed clouds)
intercomparison sacura vs gtr vs mod06 delta1
Intercomparison SACURA vs. GTR vs. MOD06 – Delta

Terra-MODIS, 2001-07-18, 15:30 GMT

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