Improvement of wind retrieval algorithm for Rayleigh Doppler lidar

Abstract

In the process of wind retrieval for Rayleigh Doppler lidar, besides atmospheric temperature and pressure, the accuracy of the wind retrieval result is also affected by Mie signal. When the Mie scattering sigal is large, especially in the cases such as high altitude clouds or volcanic ash and so on, the wind retrieval result will largely deviate from the ture value if the aerosol signal is ignored due to temperature uncertainty and Mie signal contamination. A nonlinear iterative algorithm is proposed, which can retrieve both wind and atmospheric temperature by using the mesured signal with outgoing laser pointing to the zenith. The initial operating point of laser is optimized. Simulation results show that the proposed algorithm can retrieve scattering ratio effectively, and by combination with the nonlinear iterative algorithm of wind retrieval, this algorithm can eliminate the effect of aerosol backscattering signal and then improve the atmopheric wind speed and the temperature retrieval accuracy effectively.