Diagnosing deep convection from global analyses

Citation
M. Hantel et L. Haimberger, Diagnosing deep convection from global analyses, METEOR ATM, 67(1-4), 1998, pp. 135-152
Citations number
54
Categorie Soggetti
Earth Sciences
Journal title
METEOROLOGY AND ATMOSPHERIC PHYSICS
ISSN journal
01777971 → ACNP
Volume
67
Issue
1-4
Year of publication
1998
Pages
135 - 152
Database
ISI
SICI code
0177-7971(1998)67:1-4<135:DDCFGA>2.0.ZU;2-K
Abstract
Convection, a sub-gridscale process, is coupled to the gridscale motions vi a the averaged budget equations. In this study atmospheric convection is re presented by the vertical eddy flux of equivalent temperature, referred to as convective flux. It is demonstrated with a thermodynamic diagnostic mode l for an atmospheric column (DIAMOD) that the convective flux can, with tol erable error, be diagnosed from daily global gridscale analyses. These yiel d the gridscale budget of equivalent temperature. The budget is the observa ble quantity, it is in balance with the unobservable convective flux. We re produce the known result that in convectively active atmospheric columns th e budget is negative in lower and positive in upper layers. The correspondi ng 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 t he entire atmosphere. In actual convective situations, however, the flux di verges in lower layers, reaches highest intensity somewhere between 700-500 hPa and converges in the upper atmosphere. We find maximum fluxes around 6 00 W/m(2) in individual tropical columns and extreme fluxes exceeding 1000 W/m(2) in midlatitude columns. In the monthly mean, however, the convective flux is clearly larger in the tropics; it also reaches to significantly hi gher levels in the tropics than in midlatitudes. While these qualitative re sults 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 assimilat ion of the weather centres which are not completely removed by the incoming observation data in the final analyses.