Retrieval of environmental parameters from multiply-scattered return signals of ground-based and airborne lidars

摘要

Abstract: We present some examples of calculations of polarized multiply scattered return signals of ground-based and airborne multichannel LIDARs (such as the Microlidar of the DLR) and we discuss the applied numerical methods. These methods are variance reduction Monte Carlo algorithms allowing for controlling the empirical variance. We show how variance reduction Monte Carlo algorithms allowing for controlling hte empirical variance. We show how variance reduction Monte Carlo methods may be combined with properly chosen uniform grid search or random search procedures to retrieve one or more environmental parameters from a given (measured or calculated) LIDAR return signal. Such a procedure is time consuming, of course, but it will allow for the retrieval of several parameters simultaneously and for a sensitivity analysis. A retrieval method based on Monte Carlo methods and random search including such a sensitivity analysis gives much more information than the usual inversion procedures (e.g. based on integral equations and often uncheckable environmental assumptions). We present some examples of the (simultaneous) retrieval of the extinction coefficient and the particle size distribution of a cloud from the multiply scattered return signal of gorund-based and airborne LIDARs and a sensitivity analysis of this retrieval. !13