Articles | Volume 10, issue 12
https://doi.org/10.5194/gmd-10-4419-2017
https://doi.org/10.5194/gmd-10-4419-2017
Development and technical paper
 | 
05 Dec 2017
Development and technical paper |  | 05 Dec 2017

The ABC model: a non-hydrostatic toy model for use in convective-scale data assimilation investigations

Ruth Elizabeth Petrie, Ross Noel Bannister, and Michael John Priestley Cullen

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Cited articles

Ames, W. F.: Numerical Methods for Partial Differential Equations, Nelson, London, 1958.
Bannister, R. N.: A review of forecast error covariance statistics in atmospheric variational data assimilation. II: Modelling the forecast error covariance statistics, Q. J. Roy. Meteorol. Soc., 134, 1971–1996, 2008.
Bannister, R. N.: How is the Balance of a Forecast Ensemble Affected by Adaptive and Nonadaptive Localization Schemes?, Mon. Weather Rev., 143, 3680–3699, 2015.
Bannister, R. N.: A review of operational methods of variational and ensemble-variational data assimilation, Q. J. Roy. Meteorol. Soc., 143, 607–633, https://doi.org/10.1002/qj.2982, 2017.
Bannister, R. N., Migliorini, S., and Dixon, M.: Ensemble prediction for nowcasting with a convection-permitting model – II: forecast error statistics, Tellus A, 63, 497–512, 2011.
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Short summary
The model and experiments in this paper are to study atmospheric flows on small (kilometre) scales. Compared to larger-scale flows, kilometre-scale motion is more difficult to predict, and geophysical balances are less valid. For these reasons, data assimilation (or DA, the task of using observations to initialise models) is more difficult, as the character of forecast errors (which have to be corrected by DA) is more difficult to represent. This model will be used to study small-scale DA.
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