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This survey considers those studies conducted into estimating errors in satellite derived large scale space-time means (of the order of 250 km by 250 km by a month) for rainfall, cloud cover, sea surface processes and the Earth's radiation budget, resulting from their incomplete coverage of the space-time volume over which the mean is evaluated. Many of these studies have focused on estimating the errors in space-time means post satellite launch and compare mean data derived from such satellites with that from an independent data set. Pre-launch studies tend to involve computer simulations of a satellite overflying and sampling from an existing data set and hence the two approaches give values for sampling errors for specific cases. However, more generic sampling papers exist that allow the exact evaluation of sampling errors for any instrument or combination of instruments if their sampling characteristics and the auto-correlation of the parameter field are known. These generic and simulation techniques have been used together on the same data sets and are found to give very similar values for the sampling error and are presented. Also considered are studies in which data from several satellites, or satellite and ground based measurements are combined to improve estimates in the above means. This improvement being brought about not only by increased spatial and temporal coverage but also by a reduction in retrieval error.