XХIХ International Symposium "Atmospheric and Ocean Optics. Atmospheric Physics"
June 26-30, 2023, Moscow
Participant Organizations
Organization: National Research Tomsk State University, Tomsk, Russia
List of reports:
- Bobrovnikov S.M., Gorlov E.V., Murashko S.N., Zharkov V.I.
EVALUATION OF LASER PARAMETERS FOR EFFECTIVE EXCITATION OF PHOSPHORUS OXIDE FLUORESCENCE
- Borzilov A.G., Kazakov D.V., Konyaev P.A., Lukin V.P., Soin E.L., Torgaev A.V.
OPTICAL AND ACOUSTIC MEASUREMENTS OF ATMOSPHERIC TURBULENCE ON HORIZONTAL PATHS IN THE ATMOSPHERE
- Leschinskiy D.V., Danilkin E.A., Starchenko A.V.
Large eddy simulation OF TURBULENT FLOWS IN THE URBAN LANDSCAPE
- Matvienko O.B, Litvinova A.E
Analysis of a swirling gas flow combustion in a channel with a porous insert
- Cheredko N.N., Malyshkov S.Yu., Gordeev V.F., Krutikov V.A., Tartakovsky V.A.
INVESTIGATION OF ATMOSPHERIC AND LITHOSPHERIC ANOMALIES CONSISTENCY IN THE TOMSK REGION IN WINTER
- Zbirannik A.A. , Antokhina O.Yu., Antokhin P.N.
Formation of extreme precipitation in the south of Eastern Siberia during atmospheric blocking over the European territory of Russia in July of 2010
- Volkov S.N., Samokhvalov I.V., Kim D.-H.
Matrix polarization lidar for the study of asian dust on the main lines of laser radiation
- Loboda E. L., Agafontsev M.V., Staroseltseva A.A., Staroseltseva A.A.
FLAME BURNING PLANT COMBUSTIBLE MATERIALS INTERRUPTION AS A RESULT OF EXTERNAL SHORT-TERM EXPOSURE
- Sherstobitov A.M.
Numerical investigation of the accuracy of radial wind velocity estimates obtained using a two-pulse coherent Doppler lidar at various noise levels
- Starchenko A.V., Del I.V., Odintsov S.L.
NUMERICAL PREDICTION OF WIND GUSTS IN TOMSK USING THE WRF MODEL
- Kan N.V., Konoshonkin A.V., Shishko V.A., Timofeev D.N., Russkova T.V., Kustova N.V.
Solution of the problem of light scattering by ice non-spherical particles obtained within the geometric and physical optics approximations for problems of laser pulse propagation
- Del I.V., Starchenko A.V.
PREDICTION OF ATMOSPHERIC AIR POLLUTION BY PM2.5 PARTICLES BASED ON ARTIFICIAL NEURAL NETWORKS
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