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Victor Venema, Sebastián Gimeno García, Steffen Meyer,

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.

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Victor Venema, Sebastián Gimeno García, Steffen Meyer,

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  1. 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

  2. 3D cloud fields with measured power spectra and LWC height distributions for radiative transfer calculations Victor Venema, Clemens Simmer, Susanne Crewell, Ulrich Löhnert University of Bonn Sebastián Gimeno García, Thomas Trautmann University of Leipzig / DLR Steffen Meyer, Andreas Macke University of Kiel

  3. 3 LWC template [kg/m ] LWC Surrogate 2.2 0.5 6 6 0.4 2 4 4 0.3 1.8 Height [km] 2 2 0.2 1.6 0.1 0 0 1.4 0 2 4 6 0 2 10.5 11 1.5 Time [hr] UT 0 2 4 6 3D surrogate clouds 2D Measurement 3D LWC field

  4. Problem • Radiative transfer through clouds • Radiative transfer models • Realistic cloud fields • Dynamical cloud models • Fractal clouds • Empirical surrogate clouds • Stay closer to the measurement

  5. Empirical surrogate clouds • Surrogate clouds have (statistical) properties of measured clouds • Retrievals & parameterisations • Empirical alternative • Validation, closure experiments • Close to the measured cloud field

  6. Power spectrum • Fourier transform, square the coefficients • Describes the linear spatial correlations in the field • Signal is a super positioning of sinuses • Equivalent to an spatial autocorrelation function • Gaussian PDF

  7. Amplitude distribution • Amplitude (LWP, LWC, ) alone is already good: See Independent Pixel Approximation (IPA) • Especially very important are the cloud free portions • Together with power spectrum it also ‘defines’ the structure

  8. Iterative algorithm (Schreiber and Schmitz)

  9. Add an dimension • Assume isotropy • Rotate and scale power spectrum

  10. LWC profiles Template Surrogate

  11. R Surrogate 3 LWC template [kg/m ] LWC Surrogate e f f 2.2 0.5 6 6 6 6 0.4 2 4 4 4 4 0.3 1.8 Height [km] 2 2 2 2 0.2 1.6 0.1 0 0 0 0 1.4 0 2 4 6 0 2 4 6 0 2 2 10.5 11 1.5 1.5 Time [hr] UT 0 2 4 6 0 2 4 6 3 LWC template [kg/m ] LWC Surrogate 1.5 8 8 2 6 6 1 4 4 Height [km] 1.5 2 2 0.5 0 0 0 2 4 6 8 1 0 13.2 13.4 Time [hr] UT 0 2 4 6 8 3D surrogate clouds R Surrogate e f f 8 8 6 6 4 4 2 2 0 0 0 2 4 6 8 2 2 1.5 1.5 1 1 0 2 4 6 8

  12. Validation surrogate clouds • Which statistical parameters are needed to describe cloud structure? • Does the distribution and spectrum suffice? • Method • Modelled 3D LWC fields (template) • Make surrogates from their statistics • Calculate radiative properties • Compare them

  13. Surrogate stratocumulus (Duynkerke et al., FIRE) Templates Surrogates

  14. Surrogate stratocumulus Rel. bias: 2 10-4, Rel. RMS: 2 10-4 Rel. bias: < 7 10-4, Rel. RMS: 6 10-3

  15. Templates Surrogates Surrogate cumulus (Brown et al., ARM)

  16. Surrogate cumulus Rel. bias: < 1 10-2 Rel. RMS: 1 10-2 Rel. bias: < 2.3 10-2 Rel. RMS: < 4 10-2

  17. Conclusions and outlook • Validation LES: description is good • More validation cases available? • stratocumulus with holes, dense cumulus • Raining clouds, more cloud top structure • Scanning measurement • More samples • Better decorrelation • Anisotropic power spectrum

  18. More information - Webpage • Algorithms (Matlab) • Examples • Measurements • Theoretical conditions • Articles in PDF • http://www.meteo.uni-bonn.de/ victor/themes/surrogates/ • Google: surrogate cloud fields

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