4D-Var has been operational at ECMWF since November 1997. In the near future, data assimilation algorithms will have to cope with the cost of higher resolution and increased volumes of data, in particular high density satellite data. In addition to the number of observations, it is expected that new types of data such as cloud and rain will be assimilated. This will require an improved agreement between the inner and outer loop to allow for the analysis of small scale phenomena and humidity.

We describe the main characteristics of the operational algorithm including the incremental formulation, the used data types and the main approximations involved. A revised algorithm introduced operationally in January 2003 includes modifications of the cost function in the inner loop to make it quadratic, the use of a conjugate gradient minimisation and a new preconditioning, a new interpolated trajectory and a multi-incremental configuration.

Some limitations of the current system will be pointed out as well as the potential impact on the 4D-Var algorithm of future changes in the use of observations. This is joint work with Mike Fisher, Lars Isaksen and Erik Andersson, ECMWF.