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Atmospheric and Oceanic Optics

, Volume 32, Issue 2, pp 165–170 | Cite as

The Analysis of Capabilities of Neural Networks in CO2 Sounding with Spaceborne IPDA-Lidar with the Use of Different A Priori Data

  • G. G. MatvienkoEmail author
  • A. Ya. SukhanovEmail author
  • S. V. BabchenkoEmail author
REMOTE SENSING OF ATMOSPHERE, HYDROSPHERE, AND UNDERLYING SURFACE

Abstract

The possibility of retrieving, using a neural network, the columnar carbon dioxide concentration profile when sounding from a space orbit of 450 km and from a balloon at altitudes of 23 and 10 km are analyzed. The use of a priori data on temperature, pressure, and reflected and scattered signals is 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 μJ at a resolution of 60 km.

Keywords:

atmosphere spaceborne lidar carbon dioxide greenhouse gas neural network 

Notes

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Copyright information

© Pleiades Publishing, Ltd. 2019

Authors and Affiliations

  1. 1.V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of SciencesTomskRussia

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