Dr. Alexander Yu. Toptygin Profile

Dr. Alexander Yu. Toptygin

at Ural State Univ

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Publications (4)

Proceedings Article | 12 December 2006 Paper

Application of multilayer perceptron to high-resolution infrared measurement retrieval

Konstantin Gribanov, Alexander Yu. Toptygin, Vyacheslav Zakharov

Proceedings Volume 6580, 65800R (2006) https://doi.org/10.1117/12.724933

KEYWORDS: Methane, Satellites, Sensors, Temperature metrology, Humidity, Infrared radiation, Infrared sensors, Neurons, Data modeling, Neural networks

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Proceedings Article | 12 December 2006 Paper

Method and results of retrieval of HDO/H2O in atmosphere from IMG/ADEOS and FTIR data

A. Yu. Toptygin, K. Gribanov, V. Zakharov, Y. Kasai, A. Kagawa, Y. Murayama, R. Imasu, G. Schmidt, G. Hoffmann, J. Jouzel

Proceedings Volume 6580, 65800X (2006) https://doi.org/10.1117/12.724949

KEYWORDS: FT-IR spectroscopy, Atmospheric modeling, Transmittance, Solar radiation models, Error analysis, Spectral resolution, Spectroscopy, Atmospheric monitoring, Atmospheric sensing, Knowledge management

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Here we present a Principal Components (PCs) method of retrieval of the HDO/H₂O vertical profile using atmospheric radiances observed from space by sensor like IMG as well as atmospheric transmittance spectra observed by ground based FTIR. The method is based on the expansion of the retrieved profile on eigenvectors of covariance matrix of model profiles extracted from the isotopic Atmospheric General Circulation Model (AGCM). A priori information of covariance matrix compensates partially the lack of information containing in weighting functions for HDO in lower atmospheric layer (0-1 km) and layers above 10 km. Error estimation of the retrieval scheme was made using closed model computations with synthetic spectra ofIMG and known sets of T, H₂0, HDO profiles and its value is within 8% - 70% for vertical profile and not greater than l8% for columnar value of HDO/H20 ratio. The method was applied to IMG/ADEOS spectra measured over the ocean in clear sky conditions. Latitudinal distributions ofHDO/H20 profile and columnar HDO/H₂0 ratio are retrieved over Pacific Ocean for the time interval from winter of 1996 to summer of 1997. The retrieved HDO/H₂0 from IMG/ADEOS data and simulated with isotopic AGCM are in a good agreement. FTIR is Poker Flat high resolution ground based Fourier transform spectrometer for up-looking observation of atmosphere in the spectral range from 750-4300 cm^-1 with resolution 0.0019 cm^-1 and high signal to noise ratio. The spectrometer is located at the Poker Flat Research Range (Altitude 0.61km; latitude 65.11N; longitude 147.42W) of the Geophysical Institute at the University of Alaska Fairbanks. Poker Flat FTS is operating from 1999, observation modes are atmospheric emission and solar radiation absorption. The measured atmospheric traiismittances are supported by sonde observations of T and water vapour profiles. The HDO/H₂0 PCs retrieval method was also adapted for using the high spectral resolution atmospheric transmittances observed by FTIR. Linear regression of PCs of the HDO/H₂0 profiles was obtained in this case. Error estimation of the retrieval scheme was made using closed model computations with synthetic spectra ofthe FTIR and known sets of T, H₂0, HDO profiles and its value is within 6% - 67% for vertical profile but not greater than lO% for columnar value of HDO/H₂0 ratio. As an example, HDO/H₂0 vertical profiles were retrieved using a few samples of FTIR spectra observed at the Poker Flat Research Range from 2000 to 2004 and compared with isotope AGCM outputs for Alaska's atmosphere.

Proceedings Article | 20 January 2005 Paper

Seasonal methane content in atmosphere of the permafrost boundary zone in Western Siberia determined from IMG/ADEOS and AIRS/AQUA data

Alexander Toptygin, Konstantin Gribanov, Ryoichi Imasu, W. Bleuten, Vyacheslav Zakharov

Proceedings Volume 5655, (2005) https://doi.org/10.1117/12.579494

KEYWORDS: Methane, Neural networks, Carbon, Atmospheric sensing, Climate change, Sensors, Humidity, Atmospheric monitoring, Neurons, Atmospheric modeling

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Proceedings Article | 20 January 2005 Paper

Neural network retrieval of deuterium to hydrogen ratio in atmosphere from IMG/ADEOS spectra

Konstantin Gribanov, Ryoichi Imasu, Gavin Schmidt, Alexander Toptygin, Vyacheslav Zakharov

Proceedings Volume 5655, (2005) https://doi.org/10.1117/12.579496

KEYWORDS: Neural networks, Neurons, Hydrogen, Atmospheric sensing, Humidity, Sensors, Spectral resolution, Matrices, Databases, Atmospheric modeling

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