The Analysis of Capabilities of Neural Networks in CO2 Sounding with Spaceborne IPDA-Lidar with the Use of Different A Priori Data
- 作者: Matvienko G.G.1, Sukhanov A.Y.1, Babchenko S.V.1
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隶属关系:
- V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences
- 期: 卷 32, 编号 2 (2019)
- 页面: 165-170
- 栏目: Remote Sensing of Atmosphere, Hydrosphere, and Underlying Surface
- URL: https://journals.rcsi.science/1024-8560/article/view/188720
- DOI: https://doi.org/10.1134/S102485601902009X
- ID: 188720
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详细
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.
作者简介
G. Matvienko
V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences
编辑信件的主要联系方式.
Email: mgg@iao.ru
俄罗斯联邦, Tomsk, 634055
A. Sukhanov
V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences
编辑信件的主要联系方式.
Email: say@iao.ru
俄罗斯联邦, Tomsk, 634055
S. Babchenko
V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences
编辑信件的主要联系方式.
Email: bsv@iao.ru
俄罗斯联邦, Tomsk, 634055
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