Neural network retrieval of deuterium to hydrogen ratio in atmosphere from IMG/ADEOS spectra / Gribanov K.G., Imasu R., Schmidt G.A., Toptygin A.Yu., Zakharov V.I. // Proceedings of SPIE - The International Society for Optical Engineering. - 2005. - V. 5655, l. . - P. 515-521.

ISSN:
0277786X
Type:
Conference Paper
Abstract:
A feedforward neural network has been developed for retrieval of the Deuterium to Hydrogen ratio (D/H) in atmospheric water vapour from high resolution atmospheric radiances observed from space. The learning and test sets for the neural network training were created by forward simulation of atmospheric emission spectra using FIRE - ARMS for a large set of given temperature, humidity and D/H vertical profiles. The D/H profiles were generated using output from an atmospheric GCM including isotope tracers. The developed neural network was applied for retrieval of total atmospheric column D/H from IMG/ADEOS data over the ocean. A latitudinal distribution of D/H was obtained. The results are in agreement with latitudinal distribution of D/H in the atmosphere obtained from the IMG/ADEOS data earlier by using conventional retrieval methodology. However, the neural network has better accuracy. The stability of the neural network retrieval scheme with different noise levels of the sensor is investigated, and we discuss the possibility of applying the neural network technique to the retrieval of D/H vertical profiles from TES/AURA spectra.
Author keywords:
Atmosphere; Deuterium; Neural network; Retrieval
Index keywords:
Deuterium; Earth atmosphere; Hydrogen; Radiation; Radioactive tracers; Radioisotopes; Water; Ocean color temperature scanner (OCTS); Passive sounding; Training sets; Water vapors; Neural networks
DOI:
10.1117/12.579496
Смотреть в Scopus:
https://www.scopus.com/inward/record.uri?eid=2-s2.0-20344393157&doi=10.1117%2f12.579496&partnerID=40&md5=bb51cae93172631e2f85079c18e43799
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Art. No. 84
Link https://www.scopus.com/inward/record.uri?eid=2-s2.0-20344393157&doi=10.1117%2f12.579496&partnerID=40&md5=bb51cae93172631e2f85079c18e43799
Affiliations Global Ecology and Remote Sensing Lab., Department of Physics, Ural State University, 51 Lenin Ave., Yekaterinburg, 620083, Russian Federation; Center for Climate System Research, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan; NASA Goddard Institute for Space Studies, Center for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY 10025, United States
Author Keywords Atmosphere; Deuterium; Neural network; Retrieval
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Correspondence Address Gribanov, K.G.; Global Ecology and Remote Sensing Lab., Department of Physics, Ural State University, 51 Lenin Ave., Yekaterinburg, 620083, Russian Federation; email: atmosphere@uraltc.ru
Editors Larar A.M.Suzuki M.Tong Q.
Sponsors SPIE
Conference name Multispectral and Hyperspectral Remote Sensing Instruments and Applications II
Conference date 9 November 2004 through 11 November 2004
Conference location Honolulu, HI
Conference code 64981
CODEN PSISD
Language of Original Document English
Abbreviated Source Title Proc SPIE Int Soc Opt Eng
Source Scopus