Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 8, issue 1
Articles | Volume 8, issue 1
https://doi.org/10.5194/amt-8-281-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-8-281-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 8, issue 1
Research article
 | 
14 Jan 2015
Research article |  | 14 Jan 2015

Use of neural networks in ground-based aerosol retrievals from multi-angle spectropolarimetric observations

A. Di Noia, O. P. Hasekamp, G. van Harten, J. H. H. Rietjens, J. M. Smit, F. Snik, J. S. Henzing, J. de Boer, C. U. Keller, and H. Volten

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Short summary
A neural network algorithm has been developed to retrieve aerosol microphysical parameters from ground-based measurements of skylight intensity and polarization. The neural network is capable of producing accurate estimates of aerosol optical thicknesses, effective radii and refractive index. In addition, it is shown that the use of the neural retrievals as initial guess for an iterative retrieval algorithm results in improved convergence and retrieval accuracy.
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