Forcing singular vectors and other sensitive model structures

Model tendency perturbations can, like analysis perturbations, be an effective way to influence forecasts. In this paper, optimal model tendency perturbations, or forcing singular vectors, are computed with diabatic linear and adjoint T42L40 versions of the European Centre for Medium‐Range Weather F...

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Published inQuarterly journal of the Royal Meteorological Society Vol. 129; no. 592; pp. 2401 - 2423
Main Authors Barkmeijer, J., Iversen, T., Palmer, T. N.
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 01.07.2003
Wiley
Subjects
Earth, ocean, space
Exact sciences and technology
External geophysics
Meteorology
Model error
Optimal forcing
Weather analysis and prediction
Perturbation function
Weather forecast
Sensitivity analysis
Diabatic approximation
Adjoint method
Forecast model
Linear model
Model error Optimal forcing
Singular vector
Non linear model
Forecast skill
Cost function
Forcing
Performance
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ISSN0035-9009
1477-870X
DOI10.1256/qj.02.126

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Summary:Model tendency perturbations can, like analysis perturbations, be an effective way to influence forecasts. In this paper, optimal model tendency perturbations, or forcing singular vectors, are computed with diabatic linear and adjoint T42L40 versions of the European Centre for Medium‐Range Weather Forecasts' forecast model. During the forecast time, the spatial pattern of the tendency perturbation does not vary and the response at optimization time (48 hours) is measured in terms of total energy. Their properties are compared with those of initial singular vectors, and differences, such as larger horizontal scale and location, are discussed. Sensitivity calculations are also performed, whereby a cost function measuring the 2‐day forecast error is minimized by only allowing tendency perturbations. For a given number of minimization steps, this approach yields larger cost‐function reductions than the sensitivity calculation using only analysis perturbations. Nonlinear forecasts using only one type of perturbation confirm an improved performance in the case of tendency perturbations. For a summer experiment a substantial reduction of the systematic error is shown in the case of forcing sensitivity. Copyright © 2003 Royal Meteorological Society.
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ISSN:0035-9009
1477-870X
DOI:10.1256/qj.02.126