Despite the success, AMVs are difficult to use for a some basic reasons:
1. Assimilation systems require error information for the measurements and that the spatial errors are uncorrelated. Currently, there is little error information associated with the vectors and there are spatially correlated errors inherent in the technique.
2. What does the AMV represent in terms of air motion? It has long been recognized that cloud motion does not necessarily represent air motion at a specific level. Nevertheless, tracking clouds and other features has been done since the first geostationary satellites were placed in orbit over 30 years ago.
There are several measures of the errors or quality of the AMVs, but each modeling center still applies unique thinning or blacklisting, many of which are empirically based. The goal is to better understand the errors in AMVs and provide estimates of these errors for both the vector and the assigned height, thereby producing wind sets that require less screening at the NWP sites.