A Synergy Method to Improve Ensemble Weather Predictions and Differential SAR Interferograms

摘要

A compensation of atmospheric effects is essential for mm-sensitivity in differential interferometric synthetic aperture radar (DInSAR) techniques. Numerical weather predictions are used to compensate these disturbances allowing a reduction in the number of required radar scenes. Practically, predictions are solutions of partial differential equations which never can be precise due to model or initialisation uncertainties. In order to deal with the chaotic nature of the solutions, ensembles of predictions are computed. From a stochastic point of view, the ensemble mean is the expected prediction, if all ensemble members are equally likely. This corresponds to the typical assumption that all ensemble members are physically correct solutions of the set of partial differential equations. DInSAR allows adding to this knowledge. Observations of refractivity can now be utilised to check the likelihood of a solution and to weight the respective ensemble member to estimate a better expected prediction.