victor venema, sebastián gimeno garcía, steffen meyer,
DESCRIPTION
3D cloud fields with measured power spectra and LWC height distributions for radiative transfer calculations. Victor Venema, Sebastián Gimeno García, Steffen Meyer, Clemens Simmer, Susanne Crewell, Ulrich Löhnert, Thomas Trautmann, Andreas Macke. - PowerPoint PPT PresentationTRANSCRIPT
3D cloud fields with 3D cloud fields with measured power spectra and measured power spectra and LWC height distributions for LWC height distributions for
radiative transfer calculationsradiative transfer calculations
Victor Venema, Sebastián Gimeno García, Steffen Meyer, Victor Venema, Sebastián Gimeno García, Steffen Meyer, Clemens Simmer, Susanne Crewell, Ulrich Löhnert, Clemens Simmer, Susanne Crewell, Ulrich Löhnert,
Thomas Trautmann, Andreas MackeThomas Trautmann, Andreas Macke
3D cloud fields with 3D cloud fields with measured power spectra and measured power spectra and LWC height distributions for LWC height distributions for
radiative transfer calculationsradiative transfer calculationsVictor Venema, Clemens Simmer, Susanne Crewell, Ulrich LöhnertVictor Venema, Clemens Simmer, Susanne Crewell, Ulrich Löhnert
University of BonnUniversity of Bonn
Sebastián Gimeno García, Thomas TrautmannSebastián Gimeno García, Thomas TrautmannUniversity of Leipzig / DLRUniversity of Leipzig / DLR
Steffen Meyer, Andreas MackeSteffen Meyer, Andreas MackeUniversity of KielUniversity of Kiel
3D surrogate clouds3D surrogate clouds
Time [hr] UT
Hei
ght
[km
]
LWC template [kg/m3]
10.5 11
1.4
1.6
1.8
2
2.2
0
0.1
0.2
0.3
0.4
0.5
LWC Surrogate
0 2 4 60
2
4
6
0
2
4
6
0 2 4 61.5
2
3D LWC field2D Measurement
ProblemProblem Radiative transfer through cloudsRadiative transfer through clouds
– Radiative transfer modelsRadiative transfer models– Realistic cloud fieldsRealistic cloud fields
Dynamical cloud modelsDynamical cloud models Fractal cloudsFractal clouds Empirical surrogate cloudsEmpirical surrogate clouds
– Stay closer to the measurementStay closer to the measurement
Empirical surrogate cloudsEmpirical surrogate clouds Surrogate clouds have (statistical) Surrogate clouds have (statistical)
properties of measured cloudsproperties of measured clouds
Retrievals & parameterisationsRetrievals & parameterisations– Empirical alternativeEmpirical alternative
Validation, closure experimentsValidation, closure experiments– Close to the measured cloud fieldClose to the measured cloud field
Power spectrumPower spectrum Fourier transform, square the Fourier transform, square the
coefficientscoefficients Describes the linear spatial correlations Describes the linear spatial correlations
in the fieldin the field Signal is a super positioning of sinusesSignal is a super positioning of sinuses Equivalent to an spatial autocorrelation Equivalent to an spatial autocorrelation
functionfunction Gaussian PDFGaussian PDF
Amplitude distributionAmplitude distribution Amplitude (LWP, LWC, Amplitude (LWP, LWC, ) alone is ) alone is
already good: See Independent Pixel already good: See Independent Pixel Approximation (IPA)Approximation (IPA)
Especially very important are the cloud Especially very important are the cloud free portionsfree portions
Together with power spectrum it also Together with power spectrum it also ‘defines’ the structure‘defines’ the structure
Iterative algorithm Iterative algorithm (Schreiber and Schmitz)(Schreiber and Schmitz)
Add an dimensionAdd an dimension Assume isotropyAssume isotropy Rotate and scale power spectrumRotate and scale power spectrum
1000 2000 3000 4000 5000 6000 7000 80000
100
200
300
400
500
Time (s)
LWP
(gr
/m2 )
Time (s)
Tim
e (s
)
2000 4000 6000 8000
1000
2000
3000
4000
5000
6000
7000
8000 0
100
200
300
400
500
TemplateTemplate SurrogateSurrogate
LWC profilesLWC profiles
8 8.2 8.4 8.6 8.8 9 9.2 9.4
300
400
500
600
700
800
900
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
3.6 29.5 55.1 80.7 107 132 158 184
He
igh
t (m
)
Distance (km)
Time (h)
8 8.2 8.4 8.6 8.8 9 9.2 9.4
300
400
500
600
700
800
900
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
3.6 29.5 55.1 80.7 107 132 158 184
He
igh
t (m
)
Distance (km)
Time (h)
3D surrogate clouds3D surrogate clouds
Time [hr] UT
Hei
ght [
km]
LWC template [kg/m3]
10.5 11
1.4
1.6
1.8
2
2.2
0
0.1
0.2
0.3
0.4
0.5
LWC Surrogate
0 2 4 60
2
4
6
0
2
4
6
0 2 4 61.5
2
Reff Surrogate
0 2 4 60
2
4
6
0
2
4
6
0 2 4 61.5
2
Time [hr] UT
Hei
ght [
km]
LWC template [kg/m3]
13.2 13.41
1.5
2
0
0.5
1
1.5
LWC Surrogate
0 2 4 6 80
2
4
6
8
0
2
4
6
8
0 2 4 6 81
1.52
Reff Surrogate
0 2 4 6 80
2
4
6
8
0
2
4
6
8
0 2 4 6 81
1.52
Validation surrogate cloudsValidation surrogate clouds Which statistical parameters are Which statistical parameters are
needed to describe cloud structure?needed to describe cloud structure? Does the distribution and spectrum Does the distribution and spectrum
suffice?suffice?
MethodMethod– Modelled 3D LWC fields (template)Modelled 3D LWC fields (template)– Make surrogates from their statisticsMake surrogates from their statistics– Calculate radiative propertiesCalculate radiative properties– Compare themCompare them
Surrogate stratocumulus Surrogate stratocumulus ((Duynkerke et al., FIREDuynkerke et al., FIRE))
TemplatesTemplates SurrogatesSurrogates
Surrogate stratocumulusSurrogate stratocumulus
0.3 0.4 0.5 0.6 0.7
0.3
0.4
0.5
0.6
0.7re
flect
ance
sur
roga
te
reflectance template
(a)
Rel. bias: 2 10-4,
Rel. RMS: 2 10-4
Rel. bias: < 7 10-4,
Rel. RMS: 6 10-3
0.02 0.04 0.06 0.08 0.1
0.02
0.04
0.06
0.08
0.1
radi
ance
sur
roga
te
radiance template
(b)
Surrogate cumulus Surrogate cumulus ((Brown et al., ARMBrown et al., ARM))
TemplatesTemplates SurrogatesSurrogates
Surrogate cumulusSurrogate cumulus
Rel. bias: < 1 10-2
Rel. RMS: 1 10-2
Rel. bias: < 2.3 10-2
Rel. RMS: < 4 10-2
0.05 0.1 0.15
0.02
0.04
0.06
0.08
0.1
0.12
0.14re
flect
ance
sur
roga
te
reflectance template cumulus
0.005 0.01 0.015 0.02
0.005
0.01
0.015
0.02
radiance template cumulus [W m-2 sr-1]
radi
ance
sur
roga
te [W
m-2
sr-1
]
Conclusions and outlookConclusions and outlook Validation LES: description is goodValidation LES: description is good More validation cases available?More validation cases available?
– stratocumulus with holes, dense cumulusstratocumulus with holes, dense cumulus– Raining clouds, more cloud top structure Raining clouds, more cloud top structure
Scanning measurementScanning measurement– More samplesMore samples– Better decorrelationBetter decorrelation– Anisotropic power Anisotropic power
spectrumspectrum
More information - WebpageMore information - Webpage Algorithms (Matlab)Algorithms (Matlab) ExamplesExamples
– MeasurementsMeasurements– Theoretical conditionsTheoretical conditions
Articles in PDFArticles in PDF
http://www.meteo.uni-bonn.de/ http://www.meteo.uni-bonn.de/ victor/themes/surrogates/victor/themes/surrogates/
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