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The Met Office global four-dimensional variational data assimilation scheme

✍ Scribed by F. Rawlins; S. P. Ballard; K. J. Bovis; A. M. Clayton; D. Li; G. W. Inverarity; A. C. Lorenc; T. J. Payne

Publisher
John Wiley and Sons
Year
2007
Tongue
English
Weight
330 KB
Volume
133
Category
Article
ISSN
0035-9009

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✦ Synopsis

Abstract

The Met Office has developed a 4D‐Var data assimilation system, which was implemented in the global forecast system on 5 October 2004. This followed a development path based on the previous 3D‐Var configuration, with many aspects kept in common. A 4D‐Var capability was provided by the introduction of a linear perturbation forecast model based on the Unified Model, the non‐hydrostatic grid‐point model producing our operational forecasts.

There were clear advantages in verification of forecasts compared to the equivalent 3D‐Var configuration, with an improvement of 2.6% in a composite skill score verified against observations during pre‐operational trials. The largest differences in model evolution occur in storm‐track regions in the extratropics. Overall, improvements in verification scores as measured against observations were larger than those measured against analyses, particularly at upper levels. There is an improvement in verification of surface parameters (10 m wind, 1.5 m temperature and relative humidity) against analyses. The strongest impact on fitting observations is seen for satellite radiances with weighting functions peaking in the stratosphere and upper troposphere. The largest changes to assimilation increments occurred in the top model levels, particularly wind increments which became much larger near the model top.

Similarities were found in the signal of 4D‐Var versus 3D‐Var for models at two different resolutions, from which we infer that low‐resolution trials remain valid for exploring some aspects of 4D‐Var before confirmation in full‐scale tests. © Crown Copyright 2007. Reproduced with the permission of the Controller of HMSO. Published by John Wiley & Sons, Ltd

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