Optika Atmosfery i Okeana Journal

Vol. 31, issue 12, article # 6

Matvienko G. G., Sukhanov A. Ya., Babchenko S. V. Analysis of neural network capabilities in IPDA spaceborne lidar sensing of CO₂ using heterogeneous a priori data. // Optika Atmosfery i Okeana. 2018. V. 31. No. 12. P. 974–980. DOI: 10.15372/AOO20181206 [in Russian].
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Abstract:

A possibility of retrieving the columnar concentration of carbon dioxide using a neural network is analyzed, as well as the concentration profile when sounding from a space orbit of 450 km and from an aerostat at altitudes of 23 and 10 km. Possibilities of using a priori data on temperature, pressure, and reflected and scattered signals are considered. The errors of retrieval of the columnar CO₂ are 0.15% and 0.5% at altitudes lower than 2 km for lidar with a telescope diameter of 1 m and laser pulse energy of 50 mJ at a resolution of 60 km.

Keywords:

atmosphere, spaceborne lidar, carbon dioxide, greenhouse gas, neural network

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