Diagnosing deep convection from global analyses |
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| Authors: | Prof Dr M Hantel L Haimberger |
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| Institution: | (1) Present address: Institut für Meteorologie und Geophysik der Universität Wien, Hohe Warte 38, A-1190 Vienna, Austria |
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| Abstract: | Summary Convection, a sub-gridscale process, is coupled to the gridscale motions via the averaged budget equations. In this study atmospheric convection is represented by the vertical eddy flux of equivalent temperature, referred to asconvective flux. It is demonstrated with a thermodynamic diagnostic model for an atmospheric column (DIAMOD) that the convective flux can, with tolerable error, be diagnosed from daily global gridscale analyses. These yield the gridscale budget of equivalent temperature. The budget is the observable quantity, it is in balance with the unobservable convective flux. We reproduce the known result that in convectively active atmospheric columns the budget is negative in lower and positive in upper layers. The corresponding vertical mean slope of the budget controls the convective strength; the slope is strongly negative for deep convection.In the global mean column the convective flux converges upward throughout the entire atmosphere. In actual convective situations, however, the flux diverges in lower layers, reaches highest intensity somewhere between 700–500 hPa and converges in the upper atmosphere. We find maximum fluxes around 600 W/m2 in individual tropical columns and extreme fluxes exceeding 1000 W/m2 in midlatitude columns. In the monthly mean however, the convective flux is clearly larger in the tropics; it also reaches to significantly higher levels in the tropics than in midlatitudes. While these qualitative results are invariant against using both routine analysis and reanalysis data from different sources (ECMWF and NCEP) our results change quantitatively when changing the data sources. We attribute this effect to differences in the sub-gridscale parameterization implicit in the objective data assimilation of the weather centres which are not completely removed by the incoming observation data in the final analyses.With 12 Figures |
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