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Impact of the GEM model simplified physics on extratropical singular vectors
Author(s) -
Zadra Ayrton,
Buehner Mark,
Laroche Stéphane,
Mahfouf Jeanfrançois
Publication year - 2004
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1256/qj.03.208
Subject(s) - extratropical cyclone , data assimilation , mathematics , orographic lift , meteorology , statistical physics , mathematical analysis , physics , precipitation
Abstract A simplified physics package, containing parametrizations of vertical diffusion, subgrid‐scale orographic drag, stratiform precipitation and convective precipitation, was built for the four‐dimensional variational data assimilation system that is being developed for the Canadian Global Environmental Multiscale model. To validate this package and measure its impact on the behaviour of unstable disturbances, a series of singular vector experiments was conducted. In a control experiment with vertical diffusion only, a set of 45 extratropical singular vectors was generated for a northern hemisphere winter case, using the total energy norm and an optimization time interval of 48 hours. Subsequently, the remaining components of the simplified physics were activated one by one and their influence was measured by changes in the energy partition, energy growth and spatial distribution of singular vectors. Cross‐propagation tests were also made, where singular vectors from one experiment were evolved with the tangent‐linear model of another. Results show that the orographic drag reduces the growth of singular vectors while the moist physics enhance the growth and shifts the energy of singular vectors toward smaller scales. Integrations of the nonlinear model with full physics indicate that, for amplitudes typical of analysis increments, the evolution of extratropical singular vectors is well described by the linearized model although growth rates are reduced by nonlinearities. © Crown copyright, 2004. Royal Meteorological Society

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