SuperDARN assimilative mapping

This procedure takes into account statistical properties of the background model errors, obtained through the empirical orthogonal function analysis technique described in a companion paper.

The assimilative mapping procedure is evaluated quantitatively using cross-validation and is found to reduce median prediction errors by up to 43% as compared to the existing linear regression-based SuperDARN mapping procedure. Furthermore, the mapped results from the assimilative procedure show a greater dynamic range in convection strength than do those of the regression-based procedure (i.e., the cross-polar cap potential is smaller for weak driving conditions and larger for strong driving conditions).