Applicability of regression methods to reconstructing missing data in lidar sensing of the atmosphere

V. S. Komarov; Yu. B. Popov

doi:10.1117/12.370551

19 November 1999 Applicability of regression methods to reconstructing missing data in lidar sensing of the atmosphere

V. S. Komarov, Yu. B. Popov

Proceedings Volume 3983, Sixth International Symposium on Atmospheric and Ocean Optics; (1999) https://doi.org/10.1117/12.370551
Event: Sixth International Symposium on Atmospheric and Ocean Optics, 1999, Tomsk, Russian Federation

Abstract

The methodology and accuracy estimates of numerical reconstruction of the missing information by the regression methods from the data of ground-based observations or the data obtained for lower altitude levels are considered as applied to wind lidar sensing. It is shown that the bivariate linear regression method can be used to reconstruct the vertical wind profiles only at altitudes up to 100 - 250 m, and the method of multidimensional extrapolation provides good results of reconstruction of these profiles at altitudes up to 1000 - 1200 m from the data obtained for the layer 0 - 300 m in winter and 0 - 500 m in summer.

Citation Download Citation

V. S. Komarov and Yu. B. Popov "Applicability of regression methods to reconstructing missing data in lidar sensing of the atmosphere", Proc. SPIE 3983, Sixth International Symposium on Atmospheric and Ocean Optics, (19 November 1999); https://doi.org/10.1117/12.370551

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