Abstract
We present an analytical formulation to compute the total-backscatter range-dependent error bars from the well-known Klett's elastic-lidar inversion algorithm. A combined error-propagation and statistical formulation approach is used to assess inversion errors in response to the following error sources: observation noise (i.e., signal-to-noise ratio) in the reception channel, the user's uncertainty in the backscatter calibration, and in the (range-dependent) total extinction-to-backscatter ratio provided. The method is validated using a Monte Carlo procedure, where the error bars are computed by inversion of a large population of noisy generated lidar signals, for total optical depths tau < or = 5 and typical user uncertainties, all of which yield a practical tool to compute the sought-after error bars.
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