Determination of optical and microphysical Properties of Water Clouds

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# Determination of optical and microphysical Properties of Water Clouds - PowerPoint PPT Presentation

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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### Determination ofoptical and microphysical Properties of Water Clouds

Retrieved Parameters
• Cloud optical thickness
• Cloud top height
• Liquid water path
• Thermodynamic phase
Retrieved Parameters – Mathematical formulation
• Effective cloud droplet radius Optical thickness
Basic concept of optical retrievals
• reflectance / emission of a cloud
• microphysical cloud parameters
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
• Exact radiative transfer code (Mishchenko et al. 1999) using Gamma size distribution:

1

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 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
• 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 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 RNIRaef

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

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

Dependence of Radiance Density on m0,aef, t
• Retrieval of cloud parameters is possible with VIS / NIR bands of satellite sensors
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
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
• 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
• Look-up table approach
• GTR retrieval
• T. Nakajima, T. Y. Nakajima, Kawamoto
GTR – Extraction of Radiance Density from Signal

ground thermal component

cloud thermal component

ground reflection

• VIS
• NIR
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
• 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

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

Actual Atmosphere ProfilesMM5Sounding data

IterationSatellite data - LUTs

GTR – Flow of Analysis

(Kawamoto et al. 2001)

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

GTR - Results

11µmT[K]

t

Re[µm]

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

Example 2 - SACURA
• Semianalytical approach
• SACURA retrieval
• A. A. Kokhanovsky
SACURA – Retrieval of aef & t for 2 band algorithm 01
• VIS
• NIR
• can be calculated by simple approximation equations
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

11µmT[K]

t

Re[µm]

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

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

(Kokhanovsky et al. 2003)

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
• 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. MOD06

aef [µm]

GTR SACURA MOD06

t

GTR SACURA MOD06

Intercomparison SACURA vs. GTR vs. MOD06 - aef

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

Intercomparison SACURA vs. GTR vs. MOD06 - t

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

Intercomparison SACURA vs. GTR vs. MOD06 – Freq.

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

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
• 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
• Alexander A. Kokhanovsky
Thank you
• The End
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 - aef

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

Intercomparison SACURA vs. GTR vs. MOD06 - t

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

Intercomparison SACURA vs. GTR vs. MOD06 – Freq.

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

Intercomparison SACURA vs. GTR vs. MOD06 – Delta

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

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 - SACURA
• Error of retrieved parameters due to measurement errors and t

(Kokhanovsky et al. 2003)

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 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 – Delta

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