Dynamics of an idealized fluid model for investigating convective-scale data assimilation

Abstract

An idealized fluid model of convective-scale numerical weather prediction, intended for use in inexpensive data assimilation experiments, is described here and its distinctive dynamics are investigated. The model modifies the rotating shallow water equations to include some simplified dynamics of cumulus convection and associated precipitation, extending and improving the model of Würsch and Craig. Changes to this original model are the removal of ad hoc diffusive terms and the addition of Coriolis rotation terms, leading to a so-called 1.5-dimensional model. Despite the non-trivial modifications to the parent equations, it is shown that this shallow water type model remains hyperbolic in character and can be integrated accordingly using a discontinuous Galerkin finite element method for nonconservative hyperbolic systems of partial differential equations. Combined with methods to ensure well-balancedness and non-negativity, the resulting numerical solver is novel, efficient and robust. Classical numerical experiments in the shallow water theory, such as the Rossby geostrophic adjustment and flow over topography, are reproduced for the standard shallow water model and used to highlight the modified dynamics of the new model. In particular, it exhibits important aspects of convective-scale dynamics relating to the disruption of large-scale balance and is able to simulate other features related to convecting and precipitating weather systems. Our analysis here and preliminary results suggest that the model is well suited for efficiently and robustly investigating data assimilation schemes in an idealized ‘convective-scale’ forecast assimilation framework.

Keywords:

• shallow water models
• data assimilation
• numerical weather prediction
• convection dynamics
• discontinuous Galerkin finite element method

Acknowledgements

This work has been undertaken within a CASE award funded by the Engineering and Physical Sciences Research Council and Met Office. We thank Gordon Inverarity for numerous helpful discussions and comments on pre-submission drafts, Michael Würsch for his support at the outset of this work and one anonymous reviewer whose comments helped improve the readability of this manuscript, particularly relating to the construction and explanation of the model.

Notes

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by Engineering and Physical Sciences Research Council [grant number 1305398].