INTERACTIONS OF DYNAMICS AND OBSERVATIONS IN A 4-DIMENSIONAL VARIATIONAL ASSIMILATION

A four-dimensional (4D) variational assimilation (4DVAR) seeks an opti mal balance between observations scattered in time and space over a fi nite 4D analysis volume and a priori information. In some cases, 4DVAR is able to closely fit both observations and the a priori initial est imate by making very small changes to the initial conditions that corr espond to those rapidly growing perturbations that have large amplitud e at the observation locations and times. Some observations may occur at locations and times for which the amplitudes of rapidly growing per turbations are not large. To fit such data, larger changes to the init ial conditions are necessary. Such cases may result in amplification o f the analysis increments away from the observation locations. This si tuation occurs generally for surface data, because of the damping effe ct of surface exchange processes. These interactions are seen in exper iments using single observations. To further explore the impact of sur -face data in 4DVAR, experiments were conducted with and without ERS-1 C-band measurements of backscatter. As expected and in contrast to co nventional approaches, the impact is not confined to the lower troposp here and the analysis increments are balanced. The study focuses on th e case of a small intense North Atlantic storm that struck the coast o f Norway on New Year's Day 1992. The scatterometer data have a signifi cant, apparently positive, impact on the 4DVAR analysis in this case. The example using scatterometer data also demonstrates the ease with w hich 4DVAR assimilates nonstandard data, which have a complex, highly nonlinear relationship with the model variables.