Adaptive constraints for feature tracking

In this paper extensions to an existing tracking algorithm are described. T hese extensions implement adaptive tracking constraints in the form of regi onal upper-bound displacements and an adaptive track smoothness constraint. Together, these constraints make the tracking algorithm more flexible than the original algorithm (which used fixed tracking parameters) and provide greater confidence in the tracking results. The result of applying the new algorithm to high-resolution ECMWF reanalysis data is shown as an example o f its effectiveness.