3-dimensional surrogate cloud fields with measured structures victor venema clemens simmer...
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3-Dimensional surrogate cloud fields 3-Dimensional surrogate cloud fields with measured structureswith measured structures
Victor Venema Victor Venema Clemens SimmerClemens Simmer
University of Bonn, GermanyUniversity of Bonn, Germany
Cloud measurements: Cloud measurements: Susanne Crewell, Ulrich LöhnertSusanne Crewell, Ulrich Löhnert
Radiative transfer: Radiative transfer: Sebastián Gimeno García, Anke Kniffka, Steffen MeyerSebastián Gimeno García, Anke Kniffka, Steffen Meyer
LES Modelling:LES Modelling:Andreas Chlond, Frederick Chosson, Siegfried Raasch, Andreas Chlond, Frederick Chosson, Siegfried Raasch,
Michael SchroeterMichael Schroeter
BBC campaignsBBC campaigns Keywords: boundary layer water clouds, Keywords: boundary layer water clouds,
structure & radiation, climate structure & radiation, climate
AirplanesAirplanes Tethered balloonsTethered balloons SatellitesSatellites Regional network with lidar, Regional network with lidar,
ir-radiometersir-radiometers Ground based remote sensingGround based remote sensing
BBC campaignsBBC campaigns BBC1: August, September 2001BBC1: August, September 2001 BBC2: May 2003BBC2: May 2003 Chaotic skies, typically Dutch cloudscapesChaotic skies, typically Dutch cloudscapes
BBC campaignsBBC campaigns BBC1: August, September 2001BBC1: August, September 2001 BBC2: May 2003BBC2: May 2003 Chaotic skies, typically Dutch cloudscapesChaotic skies, typically Dutch cloudscapes
– High quality measurements for testingHigh quality measurements for testing
Open databaseOpen database– ftp://bbc.knmi.nlftp://bbc.knmi.nl
Beautiful measurements, Beautiful measurements, but modellers need 3D fieldsbut modellers need 3D fields
Dimensionally challengedDimensionally challenged
Time [hr] UTH
eigh
t [k
m]
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
Time [hr] UT
Hei
ght
[km
]
LWC template [kg/m3]
7 7.5
0.5
0.6
0.7
0.8
0.9
0
0.5
1
1.5
LWC Surrogate
0 5 100
5
10
0
5
10
0 5 10
Reff
Surrogate
0 5 100
5
10
0
5
10
0 5 10
Time [hr] UT
Hei
ght
[km
]
LWC template [kg/m3]
9 9.5
0.4
0.6
0.8
0
0.2
0.4
0.6
LWC Surrogate
0 5 100
5
10
0
5
10
0 5 100.40.60.8
Reff
Surrogate
0 5 100
5
10
0
5
10
0 5 100.40.60.8
MotivationMotivation Can not measure a full 3D cloud fieldCan not measure a full 3D cloud field Can measure many (statistical) cloud Can measure many (statistical) cloud
propertiesproperties
Generate cloud field based on Generate cloud field based on measurementsmeasurements
Emphasis on good structure for Emphasis on good structure for radiative transferradiative transfer
Structure & radiationStructure & radiation DistributionDistribution
– Amplitude (LWP, LWC, Amplitude (LWP, LWC, ) alone is already ) alone is already goodgood
– Success of Independent Pixel Success of Independent Pixel Approximation (IPA) at large scalesApproximation (IPA) at large scales
0 500 1000 1500 2000 2500 3000 35000
100
200
300
400
500
600
Number
LWP
(gr
/m2 )
MeasuredSurrogate
Structure & radiationStructure & radiation Power spectrumPower spectrum
– Spatial linear correlationsSpatial linear correlations
Full spectrumFull spectrum
Measured power spectrumMeasured power spectrum Scale breaksScale breaks WavesWaves Land sea mask Land sea mask ……
Satellite pictures: Eumetsat
Validation surrogate cloudsValidation surrogate clouds Is this statistical description good enough?Is this statistical description good enough?
3D LWC fields from LES modelling3D LWC fields from LES modelling Make surrogates from their statisticsMake surrogates from their statistics Calculate radiative propertiesCalculate radiative properties
– Radiances Radiances (remote sensing; Steffen Meyer)(remote sensing; Steffen Meyer)
– Irradiances Irradiances (radiative budget; (radiative budget; Sebastián Gimeno GarcíaSebastián Gimeno García))
– Actinic fluxesActinic fluxes (chemistry; Anke Kniffka)(chemistry; Anke Kniffka)
Compare themCompare them
LES Surrogates - LWCLES Surrogates - LWCLES originalsLES originals SurrogatesSurrogates
LES
: A
ndre
as C
hlon
dLE
S:
And
reas
Chl
ond
Validation resultsValidation results IrradiancesIrradiances
– RMSE mean: < 0.03 % of the radiative RMSE mean: < 0.03 % of the radiative budgetbudget
– Monte Carlo error, statistically not Monte Carlo error, statistically not significantsignificant
RadiancesRadiances– RMSE mean: < 0.3 % RMSE mean: < 0.3 % – Monte Carlo error, statistically not Monte Carlo error, statistically not
significantsignificant Actinic fluxActinic flux
– RMSE mean: < 1.4 %RMSE mean: < 1.4 %– No error estimate (SHDOM)No error estimate (SHDOM)
Validation resultsValidation results Fields with only one statistic Fields with only one statistic
(i.e. PDF (i.e. PDF oror Fourier) Fourier) – clearly worse clearly worse – statistically significantstatistically significant
The statistical description is probably The statistical description is probably good enoughgood enough– LES stratocumulus and within 1 %LES stratocumulus and within 1 %– Limitation is likely the amount of dataLimitation is likely the amount of data
Validation cumulusValidation cumulus Developed a more Developed a more
accurate Stochastic accurate Stochastic IAAFT algorithmIAAFT algorithm
Surrogates are Surrogates are copies of templatescopies of templates
In practise the bias In practise the bias is likely still there as is likely still there as you cannot measure you cannot measure the power spectrum the power spectrum that accuratelythat accurately
Validation cumulusValidation cumulus
LES originalLES original SurrogateSurrogate
Validation broken cloudsValidation broken cloudsLES originalsLES originals SurrogatesSurrogates
LES
: F
rede
rick
Cho
sson
LES
: F
rede
rick
Cho
sson
Time series
Iterative algorithm Iterative algorithm (Schreiber and Schmitz, 1996)(Schreiber and Schmitz, 1996)
DistributionFlow diagram Time series
Iterative algorithmIterative algorithm Original problemOriginal problem
– Generate a cloud similar to measurementsGenerate a cloud similar to measurements
New problemNew problem– Based on limited data estimate:Based on limited data estimate:
distributiondistribution power spectrumpower spectrum
fx (Hz)
f y (H
z)
Log 10
pow
er
(a)
0 0.1 0.2 0.3 0.4 0.50
0.1
0.2
0.3
0.4
0.5
5
10
15
20
Estimate spectrum – method 1Estimate spectrum – method 1 Add a dimensionAdd a dimension Assume isotropyAssume isotropy Rotate and scale Rotate and scale
power spectrumpower spectrumTime (s)
Tim
e (s
)
2000 4000 6000 8000
1000
2000
3000
4000
5000
6000
7000
8000 0
100
200
300
400
500
1000 2000 3000 4000 5000 6000 7000 80000
100
200
300
400
500
Time (s)
LWP
(gr
/m2 )
Pow
er
Frequency (Hz)
1D power spectrumLWP Measurement 2D power spectrum
Time (s)
LWP
Fre
quen
cy (
Hz)
Frequency (Hz)10
-310
-210
-1
10-5
100
105
k (Hz)
Pow
er
MeasuredSurrogate
Pow
er
Estimate spectrum – method 2Estimate spectrum – method 2 Scanning measurementScanning measurement Estimate 2D-autocorrelation functionEstimate 2D-autocorrelation function 2D anisotropic power spectrum2D anisotropic power spectrum
Estimate distribution - zenithEstimate distribution - zenith Option: PDF field is measured PDFOption: PDF field is measured PDF However!However!
– Inhomogeneous (non-stationary) fieldInhomogeneous (non-stationary) field– Underestimate the width distributionUnderestimate the width distribution
Time (s)
Tim
e (s
)
2000 4000 6000 8000
1000
2000
3000
4000
5000
6000
7000
8000 0
100
200
300
400
500
0 5 10 150
1
2
3
4
5
Reduction in variance (%)
Num
ber
Histogram cumulus
0 10 20 30 400
1
2
3
4Histogram stratocumulus
Reduction in variance (%)
Num
ber
Relative reduction in variance Relative reduction in variance Zenith measurement Zenith measurement Simulated on LES cloudsSimulated on LES clouds
Estimate distribution - zenithEstimate distribution - zenith
Estimate distribution - scanEstimate distribution - scan CorrectingCorrecting
– Frank EvansFrank Evans
More dataMore data SpreadSpreadScanningScanning
Estimate distribution - scanEstimate distribution - scan
-80 -60 -40 -20 0 20 400
1
2
3
4
5Scanning measurement - Sc
Reduction in variance (%)
Num
ber
-600 -400 -200 0 2000
2
4
6
8Scanning measurement - Cu
Reduction in variance (%)
Num
ber
Estimate distribution - heightEstimate distribution - height Distribution Distribution
as a function as a function of heightof height
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
Time [hr] UT
Hei
ght
[km
]
LWC template [kg/m3]
7 7.5
0.5
0.6
0.7
0.8
0.9
0
0.5
1
1.5
LWC Surrogate
0 5 100
5
10
0
5
10
0 5 10
Reff
Surrogate
0 5 100
5
10
0
5
10
0 5 10
Time [hr] UT
Hei
ght
[km
]
LWC template [kg/m3]
9 9.5
0.4
0.6
0.8
0
0.2
0.4
0.6
LWC Surrogate
0 5 100
5
10
0
5
10
0 5 100.40.60.8
Reff
Surrogate
0 5 100
5
10
0
5
10
0 5 100.40.60.8
Added: Local valuesAdded: Local values Input from scanning Input from scanning
measurementmeasurement– Amplitude distribution Amplitude distribution – 2D power spectrum2D power spectrum– The measured The measured
values on the spiralvalues on the spiral
Added: Local constraint & maskAdded: Local constraint & mask
Surrogate with cloud mask
Added: Coarse meansAdded: Coarse means
Coarse fractionCoarse means
SurrogateOriginal
Added: Coarse means & maskAdded: Coarse means & mask
Coarse fractionCoarse means
SurrogateOriginal
ApplicationsApplications Closure studiesClosure studies
– Bring micro-physics and radiation togetherBring micro-physics and radiation together– Poster: 3D surrogates from in situ Poster: 3D surrogates from in situ
measurements (Sebastian Schmidt, measurements (Sebastian Schmidt, Ronald Scheirer, Francesca Di Giuseppe)Ronald Scheirer, Francesca Di Giuseppe)
Structure studiesStructure studies Fractal generatorFractal generator
o GeophysicsGeophysics
ApplicationsApplications Closure studiesClosure studies Structure studiesStructure studies
– How good is the fractal approximation?How good is the fractal approximation?– How accurate do you need to know the How accurate do you need to know the
PDF?PDF?
Fractal generatorFractal generator
o GeophysicsGeophysics
Structure studiesStructure studies 2D tdMAP clouds2D tdMAP clouds IAAFT surrogatesIAAFT surrogates
– Full structureFull structure– Only correlations at small scalesOnly correlations at small scales
Compare radiative propertiesCompare radiative properties
y
Optical depth -2.5 -2.5 0.0033333
50 100 150 200 250
50
100
150
200
250
0
5
10
15
20
25
30
y
Optical depth 0 -2.5 0.0033333
50 100 150 200 250
50
100
150
200
250
0
5
10
15
20
25
30
2D & 3D reflectance2D & 3D reflectance
RT
: S
ebas
tián
Gim
eno
Gar
cía
RT
: S
ebas
tián
Gim
eno
Gar
cía
ApplicationsApplications Closure studiesClosure studies Structure studiesStructure studies Fractal generatorFractal generator
– Sensitivity studiesSensitivity studies Retrievals and parameterisationsRetrievals and parameterisations
– Spectrum and PDF varied independentlySpectrum and PDF varied independently– Broad-band radiometer EarthCARE Broad-band radiometer EarthCARE
Jaime F. Gimeno (University of Valencia) & Jaime F. Gimeno (University of Valencia) & Howard BarkerHoward Barker
o GeophysicsGeophysics
ApplicationsApplications Closure studiesClosure studies Structure studiesStructure studies Fractal generatorFractal generator
o Soil temperature fields LES Soil temperature fields LES o Rain fields Rain fields
o Downscaling low resolution atmospheric models Downscaling low resolution atmospheric models to high resolution hydrological modelsto high resolution hydrological models
o Surrogate run-offSurrogate run-offo Wind stress fieldso Soil propertieso …
Comparison cloud generatorsComparison cloud generators3,2: 3D, 2D; S: Structure; P: PDF; 3,2: 3D, 2D; S: Structure; P: PDF; L: Local values; M: MaskL: Local values; M: Mask
IAAFT methodIAAFT method Cumulus fields (Evans; structure of a binary mask)Cumulus fields (Evans; structure of a binary mask)
CLABAUTAIR (Scheirer and Schmidt)CLABAUTAIR (Scheirer and Schmidt) Shift cloud (Schmidt; Los and Duynkerke)Shift cloud (Schmidt; Los and Duynkerke) 2D-2D Ice cloud (Liou et al.)2D-2D Ice cloud (Liou et al.)
tdMAP (tdMAP (A. Benassi, F. Szczap, et al.)A. Benassi, F. Szczap, et al.) Multi-fractal cloudsMulti-fractal clouds Bounded Cascade and other fractal cloudsBounded Cascade and other fractal clouds Fourier methodFourier method
– SITCOM (F. di Giuseppe; 2D structure)SITCOM (F. di Giuseppe; 2D structure)– Ice clouds (R. Hogan, S. Kew; 2.5D structure)Ice clouds (R. Hogan, S. Kew; 2.5D structure)
3SPLM3SPLM33SSP__P__
33SSPL_PL_2__L_2__L_2__L_2__L_
2S2SPP____2S2SPP____2S___2S___2S___2S___
ConclusionsConclusions Developed/extended an algorithmDeveloped/extended an algorithm
– Full 3D structureFull 3D structure– LWC height profileLWC height profile– Local measured constraints (fine or coarse)Local measured constraints (fine or coarse)– Cloud maskCloud mask
AdvantagesAdvantages– FlexibleFlexible– DimensionsDimensions– InstrumentsInstruments– Vary the statistics easily and independentlyVary the statistics easily and independently
More informationMore information HomepageHomepage
– Papers, Matlab-programs, examplesPapers, Matlab-programs, examples
http://www.meteo.uni-bonn.de/ http://www.meteo.uni-bonn.de/ venema/themes/surrogates/venema/themes/surrogates/
Google: surrogate cloudsGoogle: surrogate clouds
BBC campaign surrogatesBBC campaign surrogates– ftp://bbc.knmi.nl/bbc1/model/ftp://bbc.knmi.nl/bbc1/model/
[email protected]@uni-bonn.de
Constrained surrogatesConstrained surrogates Arbitrary constraintsArbitrary constraints Evolutionary search algorithmEvolutionary search algorithm
Better convergenceBetter convergence Try new statisticsTry new statistics Fractal geometry for cloud boundariesFractal geometry for cloud boundaries
Evolutionary search algorithmEvolutionary search algorithm
Constrained surrogatesConstrained surrogates height profilesheight profiles
– cloud basecloud base– cloud topcloud top– cloud covercloud cover– average LWCaverage LWC
HistogramsHistograms– LWPLWP– LWCLWC– number of layersnumber of layers
Power spectra & lengthPower spectra & length– LWPLWP– Highest cloud topHighest cloud top– Lowest cloud baseLowest cloud base
Coarse mean surrogatesCoarse mean surrogates InputInput
– Local coarse mean LWPLocal coarse mean LWP, , ττ
– Local coarse mean cloud fractionLocal coarse mean cloud fraction– Power spectrum, extrapolated to small Power spectrum, extrapolated to small
scalesscales
Combine satellite and ground based orCombine satellite and ground based orin situ measurementsin situ measurements– Measured small scale spectrum or PDFMeasured small scale spectrum or PDF
Downscaling modelsDownscaling models– A priory small scale spectrumA priory small scale spectrum
InstrumentsInstruments 3 microwave radiometers,3 microwave radiometers, 3 cloud radars, 3 cloud radars, 4 Micro Rain Radars (MRRs), 4 Micro Rain Radars (MRRs), 2 wind profiler-RASS systems, to measure 2 wind profiler-RASS systems, to measure
wind and temperature profiles, wind and temperature profiles, 4 lidar ceilometers, 4 lidar ceilometers, 2 lidars2 lidars numerous radiation, precipitation, turbulence numerous radiation, precipitation, turbulence
and meteorological instruments.and meteorological instruments.
LES Surrogates - RadiationLES Surrogates - Radiation
OriginalOptical depth
dist
ance
(km
)
0
1
2
IAAFT surrogateOptical depth
dist
ance
(km
)
0
1
2
Fourier surrogateOptical depth
dist
ance
(km
)
0
1
2
PDF surrogateOptical depth
distance (km)
dist
ance
(km
)
Optical depth
0 1 20
1
2
30 40 50 60 70
OriginalTransmittance
IAAFT surrogateTransmittance
Fourier surrogateTransmittance
PDF surrogateTransmittance
distance (km)
Transmittance
0 1 2
0.2 0.3
OriginalActinic flux
IAAFT surrogateActinic flux
Fourier surrogateActinic flux
PDF surrogateActinic flux
distance (km)
IAF
(W m-1 nm-1)
0 1 2
500 550 600
OriginalRadiance
IAAFT surrogateRadiance
Fourier surrogateRadiance
PDF surrogateRadiance
distance (km)
Radiance
(W m-2 sr-1 m-1)
0 1 2
0.08 0.1 0.12
Fourier &distribution
RadianceActinic fluxTransmittanceOptical depth
Fourier
Distribution
Original
LES Surrogates - RadiationLES Surrogates - Radiation