Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques - Richard Matthias Herrmann; Christoph Ritter; Christine Böckmann; Sandra Graßl (Remote Sensing, 2025)
In this work, we revise the retrieval of extinction coefficient profiles from Raman Lidar. This is an ill-posed problem, and we show that methods like Levenberg–Marquardt or Tikhonov–Phillips can be applied. We test these methods for a synthetic Lidar profile (known solution) with different noise realizations. Further, we apply these methods to three different cases of data from the Arctic: under daylight (Arctic Haze), under daylight with a high and vertically extended aerosol layer, and at nighttime with high extinction. We show that our methods work and allow a trustful derivation of extinction up to clearly higher altitudes (at about half a signal-to-noise ratio) compared with the traditional, non-regularized Ansmann solution. However, these new methods are not trivial and require a choice of parameters, which depend on the noise of the data. As the Lidar signal quality quickly decreases with range, a separation of the profile into several sub-intervals seems beneficial.