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A new algorithm for the downscaling of 3-dimensional cloud fields. Victor Venema Sebastián Gimeno García Clemens Simmer. Applications. Downscaling 3D CRM/NWP model fields Downscaling of 2D satellite measurements Coarse mean LWC Coarse cloud fraction. Requirements downscaling method.
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A new algorithm for the downscaling of 3-dimensional cloud fields Victor VenemaSebastián Gimeno García Clemens Simmer
Applications • Downscaling 3D CRM/NWP model fields • Downscaling of 2D satellite measurements • Coarse mean LWC • Coarse cloud fraction
Requirements downscaling method • Nonlinear processes • Sub (coarse) scale distribution • IPA-bias: if you average instead of (ir)radiances • Non-local processes • For example spatial correlations • 3D bias: ignore horizontal photon transport to low
Downscaling - Cumulus • High resolution original => • Coarse means • No clear subpixels • 2 coarse fields • Input downscaling • Real application start with coarse fields • Compare high-resolution fields • Physical • Radiative Coarse means Original No. clear subpixels
Downscaling - Cumulus • High resolution original => • Coarse means • No clear subpixels • 2 coarse fields • Input downscaling • Real application start with coarse fields • Compare high-resolution fields • Physical • Radiative Coarse means No. clear subpixels Surrogate
Downscaling - Cumulus • High resolution original => • Coarse means • No clear subpixels • 2 coarse fields • Input downscaling • Real application start with coarse fields • Compare high-resolution fields • Physical • Radiative Coarse means Original No. clear subpixels Surrogate
Cumulus validation data • Diurnal cycle of Cu • Land (ARM) • 51 fields • High resolution • 64x64 pixels • Horizontal resolution 100m • Coarse resolution • 16x16 • Horizontal resolution 400m • Nc = 300 cm-3 Brown, A.R., R.T. Cederwall, A. Chlond, P.G. Duynkerke, J.C. Golaz, M. Khairoutdinov, D.C. Lewellen, A.P. Lock, M.K. MacVean, C.H. Moeng, R.A.J. Neggers, A.P. Siebesma and B. Stevens, 2002. Large-eddy simulation of the diurnal cycle of shallow cumulus convection over land, Q. J. R. Meteorol. Soc., 128(582), 1075-1093.
Stratocumulus validation data • Dissolving broken Sc • Ocean (ASTEX) • 29 fields • High resolution • 200x200 pixels • Horizontal resolution 50m • Coarse resolution • 20x20 • Horizontal resolution 500m • Nc = 200 cm-3 Chosson, F., J.-L. Brenguier and L. Schüller, "Entrainment-mixing and radiative Transfer Simulation in Boundary-Layer Clouds", J Atmos. Res.
Algorithm • Preparations • Calculate power spectrum coarse LWC field • Extrapolate spectrum to smaller scales • Main iterative loop • Adjust to the extrapolated spectrum • Adjust to the coarse fields • Remove jumps at edges of coarse field
Extrapolation power spectrum • Algorithm works with any power spectrum • Cumulus clouds • Assumption: • Intermediate to small scales are fractal • follow power law (Variance=akb) • Linear regression in log-log spectrum • Fitting range: • small scales of coarse field (intermediate scales full field) • Stratocumulus cloud • Not fractal at intermediate scales • Assumption: • Shape power spectrum same for all clouds • Computed an average isotropic spectrum over all clouds • Scaled by average variance at intermediate scales
Original Extrapolated Surrogate Coarse field Example 3D fields Cumulus Stratocumulus
Original Extrapolated Surrogate Coarse field Example 3D fields Cumulus Stratocumulus
Reflectance SZA 0° Reflectance SZA 60° Transmittance SZA 0° Transmittance SZA 60° Scatterplot irradiances Cu Two Extrapolated Coarse field Interpolated originals surrogate field
Reflectance SZA 0° Reflectance SZA 60° Transmittance SZA 0° Transmittance SZA 60° Scatterplot irradiances Sc Two Extrapolated Coarse field Interpolated originals surrogate field
Conclusions • Downscaling algorithm works • Large improvement for irradiancescompared to coarse cloud fields • Extrapolation is a significant error source • Low number of pixels in coarse fields • Best extrapolation method is application dependent
Outlook • Importance of the coarse cloud fraction field • Include a distribution for the anomalies • Wavelets, increment distributions? • Applications • Downscaling CRM/NWP model fields • Anomalies, small-scale spectrum from LES or observations • Downscaling of satellite measurements • Coarse LWP fields • High resolution in situ LWC, Reff measurements
Outlook • Importance of the coarse cloud fraction field • Include a distribution for the anomalies • Wavelets, increment distributions? • Applications • Downscaling CRM/NWP model fields • Anomalies, small-scale spectrum from LES or observations • Downscaling of satellite measurements • Coarse LWP fields • High resolution in situ LWC, Reff measurements Thank you for your attention!