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Theoretical aspects of upscale error growth through the mesoscales: an analytical model
Author(s) -
Bierdel L.,
Selz T.,
Craig G.C.
Publication year - 2017
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 - 10.1002/qj.3160
Subject(s) - geostrophic wind , mesoscale meteorology , instability , data assimilation , convective instability , convection , mechanics , meteorology , hydrostatic equilibrium , physics , statistical physics , geology , quantum mechanics
Recent numerical studies suggest that convective instability and latent heat release quickly amplify errors in numerical weather predictions and lead to a complete loss of predictability on scales below 100 km within a few hours. These errors then move further upscale, eventually contaminating the balanced flow and projecting on to synoptic‐scale instabilities. According to this picture, the errors have to transition from geostrophically unbalanced to balanced motion while propagating through the mesoscale. Geostrophic adjustment was suggested as the dynamical process of this transition, but so far has not been clearly identified. In the current study, an analytical framework for the geostrophic adjustment of an initial point‐like pulse of heat is developed on the basis of the linearized, hydrostatic Boussinesq equations. The heat pulse is thought to model a convective cloud or an error within the prediction of a cloud. A time‐dependent solution for both transient and balanced flow components is derived from the analytical model. The solution includes the Green's function of the problem, which enables the extension of the model to arbitrary heat sources by linear superposition. Spatial and temporal scales of the geostrophic adjustment mechanism are deduced and diagnostics are proposed that could be used to demonstrate the geostrophic adjustment process in complex numerical simulations of midlatitude convection and upscale error growth.