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Dr. Siegfried Raasch Institut für Meteorologie und Klimatologie Universität Hannover

Broadening of convective cells during cold air outbreaks: A high resolution study using a parallelized LES-Model. Dr. Siegfried Raasch Institut für Meteorologie und Klimatologie Universität Hannover. Contents.

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Dr. Siegfried Raasch Institut für Meteorologie und Klimatologie Universität Hannover

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  1. Broadening of convective cellsduring cold air outbreaks:A high resolution study using a parallelized LES-Model Dr. Siegfried Raasch Institut für Meteorologie und Klimatologie Universität Hannover

  2. Contents • PALM – a parallelized LES-model- model equations- parallelization principles and strategy- performance analysis • High resolution study of convective cells- broadening of convective cells during cold air outbreaks • Studies within AFO2000 and DEKLIM- effects of surface inhomogeneities on boundary layer turbulence (including cloud coverage)

  3. PALM equations • Advantages of using the set of liquid water potential temperature • and total water content ql and q (see e.g. Deardorff, 1976): • ql and q are conservative quantities (as long as precipitation-, radiation-and freezing-processes are excluded), especially in case of condensation • no problems if saturation happens only in parts of the volume (otherwise, a subgrid-scale condensation scheme would be necessary) • no extra variable for the liquid water content (less demand of memory) • for dry convection or convection without condensation, the set of ql and qis equal to potential temperature and specific humidity • no additional terms for phase changes necessary in the prognosticequations

  4. Example: LES of a convective boundary layer (CBL) • computational domain: 2000 m x 2000 m x 3000 m • grid spacing: 25 m • grid points: 80 x 80 x 65 • inversion height zi: 800 m • simulation period: 1 h start animation

  5. Why to use a parallel computer? • Many open problems in boundary layer research require extreme computational power- interactions between turbulent structures of different scale: organized convection during cold-air outbreaks flow around obstacles- stably stratified turbulence: entrainment layers catabatic flows- test of subgrid-scale models • Normal sized LES studies are running much faster than on single-processor computers- large number of runs with parameter variations in a short time

  6. best domain decomposition: Program requirements for efficient use of massively parallel computers • load balancing • small communication overhead • scalability (up to large numbers of processors) S. Raasch and M. Schröter, 2001:PALM – A Large-Eddy Simulation Model Performing on Massively Parallel Computers. Meteorol. Z., 10, 363-372.

  7. Decomposition consequences (I) central finite differences cause local data dependencies solution: introduction of ghost points j i

  8. Decomposition consequences (II) FFT and linear equation solver cause non-local data dependencies solution: transposition of 3D-arrays Example: transpositions for solving the poisson equation

  9. speedup: Scalability and performance (I) • Results for SGI/Cray-T3E (160*160*64 gridpoints)

  10. Cell broadening (I) Cold air outbreak over the north atlantic

  11. 102.4 km 102.4 km Cell broadening (II) vertical velocity at z = 1800 m (from: Müller und Chlond, 1996: BLM, 81,289-323)

  12. Cell broadening (III) Palm-Results: 704 * 704 * 82 gridpoints ~10 GByte 115 h on 256 PEs vertical velocity at z = 2150 m liquid water content ql at z = 3100 m

  13. Cell broadening (IV) with condensation percentage of total energy without condensation percentage of total energy for more information see: M.Schröter and S. Raasch, 2002: Broadening of Convective Cells. AMS 15th Symposium on Boundary Layers and Turbulence, Wageningen.

  14. Effects of inhomogeneities (I) prescribed surface heat flux

  15. updraft-areas downdraft-areas Effects of inhomogeneities (II) vertical velocity in ms-1 (phase-averaged)

  16. Effects of inhomogeneities (III)

  17. Effects of inhomogeneities (IV) S. Raasch and G. Harbusch, 2001:An Analysis of Secondary Circulations and their Effects Caused by Small-Scale Surface Inhomogeneities Using LES. Boundary-Layer Meteorol., 101, 31-59.

  18. Effects of inhomogeneities (V) Further results: • Inhomogeneities lead to a TKE increase in the mixed layer • Secondary circulations may oscillate in time M. O. Letzel and S. Raasch, 2002:Large-Eddy Simulation of Thermally Induced Oscillations in the Convective Boundary Layer. Annual J. Hydraulic Eng., JSCE, 46, 67-72. Future studies within DEKLIM and AFO2000: • Effects of irregular inhomogeneities and comparison with observations • Runs with humidity • Effects of secondary circulations and of inhomogeneous latent heat flux on e.g. cloud coverage

  19. IMUK – Uni-Hannover Dept. of Civil Engineering Dept. of Atmospheric Sciences Tokyo Inst. of Technology Yonsei University, Seoul PALM user groups:

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