Why does 4D-Var beat 3D-Var?
Version of Record online: 29 DEC 2006
Copyright © 2005 Royal Meteorological Society
Quarterly Journal of the Royal Meteorological Society
Volume 131, Issue 613, pages 3247–3257, October 2005 Part C
How to Cite
Lorenc, A. C. and Rawlins, F. (2005), Why does 4D-Var beat 3D-Var?. Q.J.R. Meteorol. Soc., 131: 3247–3257. doi: 10.1256/qj.05.85
- Issue online: 29 DEC 2006
- Version of Record online: 29 DEC 2006
- Manuscript Revised: 13 OCT 2005
- Manuscript Received: 16 MAY 2005
- Incremental variational four-dimensional data assimilation;
A set of four experiments is described which measure the expected beneficial aspects of incremental four-dimensional variational (4D-Var) compared to 3D-Var data assimilation systems: allowing for the time of each observation in the full and increment fields with which it is compared, and using time-evolved covariances. Judging each scheme by the overall accuracy of resulting numerical weather prediction forecasts compared to observations, each aspect is shown to provide benefit.
On other measures of analysis quality, such as the fit of short-period forecasts and analyses to observations, the benefits of 4D-Var are less clear; it is sometimes worse. Perhaps 4D-Var is improving the analysis of growing modes, which are more important for forecasts, without improving all aspects of the analysis.
Our basic 4D-Var was not provided with many observations distributed in time, and had very simple parametrizations. There is an expectation of enhanced benefits as these aspects are developed. Copyright © 2005 Royal Meteorological Society