Improving vortex position accuracy with a new multiscale alignment ensemble filter

To further reduce the scale mismatch between observations and states, a new option called MSA-O is introduced to decompose obser-vations into scale components during assimilation. Cycling DA experiments show that the MSA-O consistently outper-forms the traditional EnKF at equal computational cost. A more challenging scenario for the MSA is identified when the large-scale background flow and the small-scale vortex are incoherent in terms of their errors, making the displacement vectors not effective in reducing vortex position errors.

Observation availability for the small scales also limits the use of large Ns for the MSA. Potential remedies for these issues are discussed.