Determination of the Total Ozone Content in Atmospheric Column according to the Data of Electro-L No. 3 Spacecraft Using Neural Networks Satellite

被引：1

作者：

Bloshchinskiy, V. D. ^{[1
]}

Kuchma, M. O. ^{[1
]}

Kukharsky, A. V. ^{[2
]}

机构：

[1] Far Eastern Ctr State Res Ctr Space Hydrometeorol, Khabarovsk, Russia

[2] State Res Ctr Space Hydrometeorol Planeta, Moscow, Russia

来源：

IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS | 2022年 / 58卷 / 12期

关键词：

remote sensing; MSU-GS; Electro-L; gas; ozone; artificial neural network;

D O I：

10.1134/S0001433822120040

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

The paper considers a method for retrieval of the total ozone content in the atmospheric column on the basis of artificial neural networks according to the MSU-GS instrument of the Electro-L No. 3 geostationary spacecraft. The tests and comparisons of the retrieved values of the total ozone content according to the MSU-GS data with the ground-based measurements from the AERONET and WOUDC archives, as well as with satellite estimates based on the OMPS instrument data, show a high correlation and accuracy. The mean absolute error when compared with OMPS is 1.9 DU; with AERONET, 13.4; and with WOUDC, 15.7. The correlations are 99.8%, 89.6% and 86.9%, respectively. The results obtained indicate good accuracy and efficiency of the proposed method for retrieval of the total ozone content.

引用

页码：1627 / 1632

页数：6

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