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SUMMARY:Global\, non-hydrostatic\, cloud-permitting\, medium-range forecas
 ts using the spectral transform method: progress and challenges - Nils Wed
 i\,   (European Centre for Medium-Range Weather Forecasts (ECMWF))
DTSTART:20120927T144500Z
DTEND:20120927T151000Z
UID:TALK40215@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Numerical weather prediction (NWP) requires an answer in real 
 time with a window of approximately one hour to run a medium-range global 
 forecast such that it can be delivered in time to its customers worldwide.
  While computational efficiency remains one of the most pressing needs of 
 NWP\, it is an open question how to most efficiently use the computer powe
 r available over the next twenty years\, while seeking the most accurate a
 nd cost-effective solution. At the same time\, there are significant scien
 tific challenges to increase resolution further\, changes to the governing
  equations\, and how sub-gridscale (SGS) processes are represented. ECMWF 
 plans to implement a global horizontal resolution of approximately 10km by
  2015 for its assimilation and deterministic forecast system\, and approxi
 mately 20km for the ensemble prediction system (EPS). The scales resolved 
 at these resolutions are still hydrostatic and the efficiency of the conte
 mporary hydrostatic\, semi-Lagrangian\, semi-imp licit solution procedure 
 using the spectral transform method is likely to remain a relevant benchma
 rk. However\, due to the relative cost increase of the Legendre transforms
  compared to the gridpoint computations\, very high resolution spectral mo
 dels may become prohibitively expensive. Moreover\, spectral-to-gridpoint 
 transformations require data-rich global communications at every timestep 
 that may become too expensive on massively parallel computers. Recent prog
 ress in the development of fast spherical harmonics transforms (Tygert\, 2
 008\,2010) based on the butterfly scheme (ONeil et al\, 2010) mitigate the
  computational expense of the spectral transforms. Results are presented t
 hat demonstrate the cost-effectiveness of the fast Legendre transforms (FL
 T) on the ibm_power7 architecture. The FLTs save both memory and computing
  time enabling the "world's first" successful T7999 (or equivalently ~2.5k
 m horizontal resolution) global weather forecast with a spectral transform
  model. \n\nTygert\, M.\, Fast algorithms for spherical harmonic expansion
 s\, II\, J. of Comput. Physics\, Vol. 227 (8)\, 2008\, 4260-4279. \n\nTyge
 rt\, M.\, Fast algorithms for spherical harmonic expansions\, III\, J. of 
 Comput. Physics\, Vol. 229 (18)\, 2010\, 6181-6192. \n\nONeil\, M.\, F. Wo
 olfe\, V. Rohklin\, An algorithm for the rapid evaluation of special funct
 ion transforms\, Appl. Comput. Harmon. Anal.\, Vol. 28(2)\, 2010\, 203-226
 . \n\n
LOCATION:Seminar Room 1\, Newton Institute
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