A key motivation to use data assimilation for plane-tary science is in order to recover information about day-to-day atmospheric variability, or ‘weather’. Whilst there is no immediate need for a regular weather forecast in most planetary science, data assimilation offers the prospect of a systematic rea-nalysis of past and present spacecraft data. This is especially valuable when, as is often the case, a planet is being observed from only one or two orbital platforms at any one time and synoptic-scale weather system may translate and change signifi-cantly between satellite passes. Observations are often sparse and incomplete. This leads to problems of aliasing and potential ambiguity in a convention-al data analysis
