Driving Mesoscale Processes with Global Data Assimilative Models (Invited)

Global large scale ionosphere-thermosphere (IT) data assimilation methods have evolved to the point where they are able to estimate several IT state variables simultaneously over the entire globe.The large scale state variables estimated by data assimilative techniques can then be used to drive physical models of mesoscale and small scale processes. This allows for the possibility of being able to accurately predict mesoscale and small scale processes and structures from knowledge of the large scale driving physics. However, the accuracy of any such predictions will depend a) upon the accuracy of the estimated large scale state variables from data assimilation as well as b) the accuracy of the mesoscale and small scale models. In this presentation, we will focus upon the current capability of the data assimilation models IDA4D and EMPIRE to accurately estimate large scale IT state variables at equatorial latitudes. We will then discuss how these large scale state variables can be used to drive mesoscale models of the equatorial ionosphere and thermosphere. Results will be presented of large scale estimates of equatorial electron density and electric potential from analysis of IDA4D/EMPIRE and ingestion of C/NOFS observations