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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 1, pp. 223-236

Identification of mesoscale convective cloud systems with tornadoes using satellite data

A.N. Shikhov 1 , A.V. Chernokulsky 2 , A.A. Sprygin 3 , I.O. Azhigov 1 
1 Perm State University, Perm, Russia
2 A.M. Obukhov Institute of Atmospheric Physics RAS, Moscow, Russia
3 Central Aerological Observatory, Dolgoprudnyi, Russia
Accepted: 02.10.2018
DOI: 10.21046/2070-7401-2019-16-1-223-236
The study is carried out to estimate capability of using Meteosat-8 SEVIRI satellite data for the detection of tornado-generating mesoscale convective systems (MCSs) and supercell storms. We consider the cloud top temperature, overshooting tops, cold-rings, and cold U-V shaped features as signatures of tornado formation. The study is performed for 2017–2018, on the example of several tornado outbreaks in the European Russia and Ural region. The tornado events are identified by witness and media reports and by satellite-based analysis of tornado-induced forest damage tracks. For the first time in this region, overlapping of actual tornado tracks with Meteosat-8 images allows to detect the features of MCSs and supercell storms that yielded tornadoes. It is found, that the extremely low cloud top temperature and overshooting tops have a relatively weak correlation with tornado events. Whereas, the cold-rings and cold U-V shaped features are related more tightly with strong tornadoes, and hence can be considered as the signatures of strong mesocyclones. The importance of convective instability conditions is highlighted. Particularly, Meteosat data show good capability to detect tornado-generating MCSs and supercell storms that are formed in the environments with strong convective instability (and strong updrafts). However, the local supercell storms that generate tornadoes in the conditions with weak or moderate convective instability, have no typical signatures on the cloud top. Consequently, their satellite-based detection is difficult.
Keywords: tornado, mesoscale convective system, supercell, Meteosat-8 data, cloud top temperature, overshooting top, cold ring, signature
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References:

  1. Veltishchev N.F., Stepanenko V. M., Mezometeorologicheskie protsessy (Mesoscale meteorological processes), Moscow, 2006, 101 p.
  2. Volkova E. V., Uspenskii A. B., Otsenki parametrov oblachnogo pokrova v svetloe vremya sutok po dannym geostatsionarnogo meteosputnika METEOSAT-8 (Estimation of cloud cover parameters in daily time with the use of Meteosat-8 geostationary satellite data), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2008, Vol. 5, No. 1, pp. 441–450.
  3. Volkova E. V., Uspenskii A. B., Kukharskii A. V., Spetsializirovannyi programmnyi kompleks polucheniya i validatsii sputnikovykh otsenok parametrov oblachnosti i osadkov (Specialized complex of programs for retrieving and validating satellite estimates of cloud and precipitation), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2015, Vol. 12, No. 3, pp. 7–26.
  4. Dyadyuchenko V., Pavlyukov Yu., Vylegzhanin I., Dopplerovskie radiolokatory v Rossii (Doppler weather radars in Russia), Nauka v Rossii, 2014, No. 1, pp. 23–27.
  5. Shikhov A. N., Azhigov I. O., Monitoring vetroval’nykh narushenii lesnogo pokrova, vyzvannykh shkvalami i smerchami na territorii Evropeiskoi Rossii i Urala v 2017 g. (Monitoring of windthrows in the European Russia, induced by squalls and tornadoes in 2017), 15-ya Vserossiiskaya otkrytaya konferentsiya “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” (15th All-Russia Open Conf. “Current Problems in Remote Sensing of the Earth from Space”), Book of Abstracts, Moscow: IKI RAN, 2017, p. 406.
  6. Shikhov A. N., Bykov A. V., Izuchenie dvukh sluchaev sil’nykh smerchei v Predural’e (The study of two cases of severe tornadoes in the Predural’e region), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2015, Vol. 12, No. 3, pp. 124–133.
  7. Shikhov A. N., Azhigov I. O., Bykov A. V., Smerchi i shkvaly na Urale v iyune 2017 goda: analiz po sputnikovym dannym (A satellite-based analysis of squalls and tornadoes in the Urals region in June 2017), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, No. 1, pp. 272–281.
  8. Adler R. F., Markus M. J., Fenn D. D., Detection of severe midwest thunderstorms using geosynchronous satellite data, American Meteorological Society, 1985, Vol. 113, pp. 769–781.
  9. Antonescu B., Schultz D. M., Holzer A., Groenemeijer P., Tornadoes in Europe: An Underestimated Threat, Bulletin of the American Meteorological Society, 2017, Vol. 98(4), pp. 713–728.
  10. Bedka K. M., Overshooting cloud top detections using MSG SEVIRI infrared brightness temperatures and their relationship to severe weather over Europe, Atmospheric Research, 2011, Vol. 99(2), pp. 175–189.
  11. Bluestein H. B., Severe Convective Storms and Tornadoes. Observations and Dynamics, Berlin, Heidelberg: Springer-Verlag, 2013, 456 p.
  12. Brooks H. E., Proximity soundings for severe convection for Europe and the United States from reanalysis data, Atmospheric Research, 2009, Vol. 93, pp. 546–553.
  13. Bukharov M. V., Kukharskii A. V., Misnik L. A., Automated work place “Planeta-Meteoobzor” for monitoring hazardous weather associated with convective clouds, Russian Meteorology and Hydrology, 2008, Vol. 33(2), pp. 102–105.
  14. Chernokulsky A. V., Shikhov A. N., 1984 Ivanovo tornado outbreak: Determination of actual tornado tracks with satellite data, Atmospheric Research, 2018, Vol. 207, pp. 111–121.
  15. Chernokulsky A. V., Kurgansky M. V., Zakharchenko D. I., Mokhov I. I., Genesis Environments and Characteristics of the Severe Tornado in the South Urals on August 29, 2014, Russian Meteorology and Hydrology, 2015, Vol. 40(12), pp. 794–799.
  16. Chernokulsky A., Kurgansky M., Mokhov I., Selezneva E., Shikhov A., Azhigov I., Zakharchenko D., Antonescu B., Kühne T., The modern climatology of Northern Eurasia tornadoes and waterspouts, 9th European Conf. Severe Storms (ECSS-2017), Book of Abstracts, 2017, p. 109.
  17. Dmitrieva T. G., Peskov B. E., Synoptic conditions, nowcasting, and numerical prediction of severe squalls and tornados in Bashkortostan on June 1, 2007 and August 29, 2014, Russian Meteorology and Hydrology, 2016, Vol. 41(10), pp. 673‒682.
  18. Kerkmann J., Lutz H. J., König M., Prieto J., Pylkko P., Roesli H. P., Rosenfeld D., Zwatz-Meise V., Schmetz J., Schipper J., Georgiev C., Santurette P., MSG Channels Interpretation Guide, EUMETSAT, 2006, available at: http://oiswww.eumetsat.org/WEBOPS/msg_interpretation/index.html.
  19. Klaes K. D., A status update on EUMETSAT programmes and plans, Proc. SPIE, 2017, Vol. 10402, Art. No. 1040202.
  20. Kurgansky M.V, Chernokulsky A. V., Mokhov I. I., The tornado over Khanty-Mansiysk: An exception or a symptom? Russian Meteorology and Hydrology, 2013, Vol. 38, pp. 539–546.
  21. Lindsey D. T., Hillger D. W., Grasso L., Knaff J. A., Dostalek J. F., GOES climatology and analysis of thunderstorms with enhanced 3.9-μm reflectivity, Monthly Weather Review, 2006, Vol. 134, pp. 2342–2353.
  22. Novitskii M. A., Pavlyukov Y. B., Shmerlin B. Y., Makhnorylova S. V., Serebryannik N. I., Petrichenko S. A., Tereb L. A., Kalmykova O. V., The tornado in Bashkortostan: the potential of analyzing and forecasting tornado-risk conditions, Russian Meteorology and Hydrology, 2016, Vol. 41(10), pp. 683–690.
  23. Putsay M., Simon A., Szenyán I., Kerkmann J., Horváth G., Case study of the 20 May 2008 tornadic storm in Hungary ― Remote sensing features and NWP simulation, Atmospheric Research, 2011, Vol. 100(4), pp. 657–679.
  24. Reynolds D. W., Observations of damaging hailstorms from geosynchronous satellite digital data, Monthly Weather Review, 1980, Vol. 108, pp. 337–348.
  25. Shikhov A. N., Chernokulsky A. V., A satellite-derived climatology of unreported tornadoes in forested regions of northeast Europe, Remote Sensing of Environment, 2018, Vol. 204, pp. 553‒567.