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Breakdown of hydrostatic balance at convective scales in the forecast errors in the Met Office Unified Model
Author(s) -
VetraCarvalho S.,
Dixon M.,
Migliorini S.,
Nichols N. K.,
Ballard S. P.
Publication year - 2012
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.1925
Subject(s) - data assimilation , hydrostatic equilibrium , covariance , convection , numerical weather prediction , meteorology , covariance matrix , environmental science , mathematics , physics , statistics , quantum mechanics
For data assimilation in numerical weather prediction, the initial forecast‐error covariance matrix P f is required. For variational assimilation it is particularly important to prescribe an accurate initial matrix P f , since P f is either static (in the 3D‐Var case) or constant at the beginning of each assimilation window (in the 4D‐Var case). At large scales the atmospheric flow is well approximated by hydrostatic balance and this balance is strongly enforced in the initial matrix P f used in operational variational assimilation systems such as that of the Met Office. However, at convective scales this balance does not necessarily hold any more. Here we examine the extent to which hydrostatic balance is valid in the vertical forecast‐error covariances for high‐resolution models in order to determine whether there is a need to relax this balance constraint in convective‐scale data assimilation. We use the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and a 1.5 km resolution version of the Unified Model for a case study characterized by the presence of convective activity. An ensemble of high‐resolution forecasts valid up to three hours after the onset of convection is produced. We show that at 1.5 km resolution hydrostatic balance does not hold for forecast errors in regions of convection. This indicates that in the presence of convection hydrostatic balance should not be enforced in the covariance matrix used for variational data assimilation at this scale. The results show the need to investigate covariance models that may be better suited for convective‐scale data assimilation. Finally, we give a measure of the balance present in the forecast perturbations as a function of the horizontal scale (from 3–90 km) using a set of diagnostics. Copyright © 2012 Royal Meteorological Society and British Crown Copyright, the Met Office