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Stochastic modelling of model errors: a simulation study
Author(s) -
Tsyrulnikov M. D.
Publication year - 2005
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.05.19
Subject(s) - advection , residual , white noise , stochastic modelling , meteorology , rossby wave , ensemble forecasting , state variable , sensitivity (control systems) , statistical physics , mathematics , geology , climatology , statistics , algorithm , physics , thermodynamics , electronic engineering , engineering
In the setting with known ‘truth’, the spatio‐temporal structure of forecast‐model (tendency) errors is studied. The shallow‐water model is used as the ‘truth’ and the vorticity equation as a forecast model. It is found that state‐dependent model errors (MEs) are of primary importance. The residual state‐independent (stochastic) part of MEs can be modelled with the advection‐diffusion equation driven by the white noise. The ME effective advection velocity appears to be very different from the wind and resembles the Rossby‐wave phase velocity. Three versions of increasing complexity for the advection and diffusion operators are proposed. Ensemble‐based adequacy checks of the proposed ME model are presented. Sensitivity of the ensemble forecast‐error spatial and temporal structure to various aspects of the ME model used to create the ensemble is investigated. Copyright © 2005 Royal Meteorological Society