ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 1, pp. 205-215

Determination of turbulence zones in the upper troposphere based on satellite measurements

A.F. Nerushev 1 , R.V. Ivangorodsky 1 
1 Research and Production Association «Typhoon», Obninsk, Russia
Accepted: 22.01.2019
DOI: 10.21046/2070-7401-2019-16-1-205-215
The paper presents the method of determining the turbulence zones in the upper troposphere that is based on measurements of atmospheric self-radiation from geostationary meteorological satellites and uses extremal correlation algorithms. The features of the method applied to the determination of clear air turbulence (CAT) from the SEVIRI radiometer water vapor 6.2 µm channel measurements of European geostationary meteorological satellites of the second generation are considered. The results of the calculations of average monthly space turbulence zones with different values of the coefficient of horizontal mesoscale turbulent diffusion for 2007–2017 in the satellite view zone are presented. It is shown, that for the past 11 years there has been a significant increase in the area of zones occupied by relatively weak and moderate turbulence and a slight decrease in the area of zones with strong and very strong turbulence. A close relationship was revealed between the interannual variability of the monthly area means of turbulence zones and the corresponding variability of the characteristics of jet streams.
Keywords: clear air turbulence, characteristics of turbulence zones, geostationary meteorological satellites, upper troposphere, atmospheric tracers, extremal correlation algorithms
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  1. Atmosfera: spravochnik (Atmosphere: a handbook), Leningrad: Gidrometeoizdat, 1991, 509 p.
  2. Babii V. I., Melkomasshtabnaya struktura polya skorosti zvuka v okeane (Small Scale Structure of the Field of the Velocity of Sound in the Ocean), Leningrad: Gidrometeoizdat, 1983.
  3. Baranov A. A., Solonin S. V., Aviatsionnaya meteorologiya (Aeronautical meteorology), Leningrad: Gidrometeoizdat, 1975, 391 p.
  4. Vinnichenko N. K., Pinus N. Z., Shmeter S. M., Shur G. N., Turbulentnost’ v svobodnoi atmosfere (Turbulence in free atmosphere), Leningrad: Gidrometeoizdat, 1976, 288 p.
  5. Golitsyn G. S., An Explanation of the Relative Eddy Diffusion Law in the Atmosphere and on the Ocean Surface, Dokl. Earth Sci., 2001, Vol. 381, No. 8, pp. 939–941.
  6. Doklad ob osobennostyakh klimata na territorii Rossiiskoi federatsii za 2017 god (Report on features of climate in the territory of the Russian Federation for the year 2017), Moscow: Rosgidromet, 2018, 69 p., URL:
  7. Kamenkovich V. M., Osnovy dinamiki okeana (Fundamentals of Oceanic Dynamic), Leningrad: Gidrometeoizdat, 1973.
  8. Kramchaninova E. K., Nerushev A. F., Opredelenie turbulentnykh kharakteristik v zonakh opasnykh atmosfernykh yavlenii po sputnikovym dannym (Definition of turbulent characteristics in the areas of hazardous weather conditions on satellite data), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2008, Vol. 5, No. 1, pp. 484–490.
  9. Monin A. S., Yaglom A. M., Statisticheskaya gidromekhanika (Statistical hydromechanics), Vol. 2, Saint Petersburg: Gidrometeoizdat, 1996, 742 p.
  10. Nerushev A. F., Kramchaninova E. K., Metod opredeleniya kharakteristik atmosfernykh dvizhenii po dannym izmerenii meteorologicheskikh geostatsionarnykh sputnikov (Method for determining the characteristics of the atmospheric movements according to the measurements of meteorological geostationary satellites), Issledovanie Zemli iz kosmosa, 2011, No. 1, pp. 3–13.
  11. Nerushev A. F., Kramchaninova E. K., Solov’ev V. I., Opredelenie kharakteristik atmosfernykh dvizhenii po dannym mnogovolnovogo zondirovaniya iz kosmosa (Determination of Atmospheric Motion Characteristics from the Data of Multi-Wave Soundings from Space), Izvestiya RAN. Fizika atmosfery i okeana, 2007, Vol. 3, No. 4, pp. 442–450.
  12. Nerushev A. F., Visheratin K. N., Ivangorodskii R. V., Prostranstvenno-vremennaya izmenchivost’ vysotnykh struinykh techenii po dannym sputnikovykh izmerenii (Spatio-temporal variability of high-altitude jetstreams according to satellite measurements), Issledovanie Zemli iz kosmosa, 2017, No. 6, pp. 31–45.
  13. Shakina N. P., Ivanova A. R., Prognozirovanie meteorologicheskikh uslovii dlya aviatsii (Forecasting meteorological conditions for aviation), Moscow: Triada Ltd, 2016, 312 p.
  14. Jaeger E. B., Sprenger M., A Northern Hemispheric climatology of indices for clear air turbulence in the tropopause region derived from ERA40 reanalysis data, J. Geophysical Research: Atmospheres, 2007, Vol. 112, Issue D20, CiteID D20106.
  15. Kauffmann P., The business case for turbulence sensing systemsin the US air transport sector, J. Air Transport Management, 2002, Vol. 8, Issue 2, pp. 99–107.
  16. Meneguz E., Wells H., Turp D., An automated system to quantify aircraft encounters with convectively induced turbulence over Europe and the Northeast Atlantic, J. Applied Meteorology and Climatology, 2016, Vol. 55, No. 5, pp. 1077–1089.
  17. Sharman R., Tebaldi C., Wiener G., Wolff J., An integrated approach to mid- and upper-level turbulence forecasting, Weather and Forecasting, 2006, Vol. 21, No. 3, pp. 268–287.
  18. Storer L. N., Williams P. D., Joshi M. M., Global Response of Clear-Air Turbulence to Climate Change, Geophysical Research Letters, 2017, Vol. 44, Issue 19, pp. 9976–9984.
  19. Williams J. K., Using random forests to diagnose aviation turbulence, Machine Learning, 2014, Vol. 95, Issue 1, pp. 51–70.
  20. Williams P. D., Increased light, moderate, and severe clear-air turbulence in response to climate change, Advances in Atmospheric Sciences, 2017, Vol. 34, pp. 576–586.