Vol. 35, issue 06, article # 1

Abstract:

We consider the usefulness of satellite data to estimate atmospheric instability and precipitable water vapor for the cases with severe convective events occurred over the European Russia and the Ural region. The initial sample includes 305 squalls, tornado, and large hail events. We evaluated the values of the instability parameter Lifted Index (LI) and precipitable water vapor (PW) using MODIS Atmospheric Profile Product data as well as the ERA5 reanalysis data. It was found that the median values of LI and PW according to the MODIS and ERA5 data are rather close, while the extreme values substantially differ. Local areas with very strong instability and high PW were identified from MODIS data, but not detected according to the reanalysis data. We found major limitations of the MODIS data associated with rather low frequency of imagery and the lack of information on the instability parameters for cloudy pixels. In particular, it reduced the sample size from 305 to 95 cases.

Keywords:

convective hazardous weather event, squall, tornadoe, MODIS satellite data, convective instability, precipitable water vapor, ERA5 reanalysis

Figures:

References:

1. Rasmussen E.N., Blanchard D.O. A baseline climatology of sounding-derived supercell and tornado forecast parameters // Weather Forecast. 1998. V. 13. P. 1148–1164.
2. Brooks H.E., Doswell III C.A., Zhang X., Chernokulsky A., Tochimoto E., Hanstrum B., Nascimento E., Sills D., Antonescu B., Barrett B. A Century of Progress in Severe Convective Storm Research and Forecasting. AMS, 2019. Chapter 18. P. 18.1–18.41.
3. Kalinin N.A., Shihov A.N., Chernokul'skij A.V., Kostarev S.V., Bykov A.V. Usloviya vozniknoveniya sil'nyh shkvalov i smerchej, vyzyvayushchih krupnye vetrovaly v lesnoj zone Evropejskoj chasti Rossii i Urala // Meteorol. i gidrol. 2021. N 2. P. 35–49.
4. Chakraborty S., Fu R., Massie S.T., Stephens G. Relative influence of meteorological conditions and aerosols on the lifetime of mesoscale convective systems // Proc. Nat. Acad. Sci. 2016. V. 113, N 27. P. 7426–7431.
5. Chen Q., Fan J., Yin Y., Han B. Aerosol impacts on mesoscale convective systems forming under different vertical wind shear conditions // J. Geophys. Res: Atmos. 2020. V. 125, N 3. DOI: 10.1029/2018JD030027.
6. Púčik T.P., Groenemeijer P., Rýva D., Kolář M. Proximity soundings of severe and nonsevere thunderstorms in central Europe // Mon. Weather Rev. 2015. V. 143. P. 4805–4821.
7. Taszarek M., Brooks H.E., Czernecki B. Sounding-derived parameters associated with convective hazards in Europe // Mon. Weather Rev. 2017. V. 145. P. 1511–1528.
8. Brooks H.E. Proximity soundings for severe convection for Europe and the United States from reanalysis data // Atmos. Res. 2009. V. 93. P. 546–553.
9. Taszarek M., Allen J.T., Púcik T., Hoogewind K.A., Brooks H.E. Severe convective storms across Europe and the United States. Part II: ERA5 environments associated with lightning, large hail, severe wind, and tornadoes // J. Clim. 2020. V. 33, N 24. P. 10263–10286.
10. Taszarek M., Brooks H. E., Czernecki B., Szuster P., Fortuniak K. Climatological aspects of convective parameters over Europe: A comparison of ERA-Interim and sounding data // J. Clim. 2018. V. 31. P. 4281–4308.
11. Taszarek M., Pilguj N., Allen J.T., Gensini V., Brooks H.E., Szuster P. Comparison of convective parameters derived from ERA5 and MERRA-2 with rawinsonde data over Europe and North America // J. Clim. 2021. V. 34, N 8. P. 3211–3237.
12. Adler R.F., Markus M.J., Fenn D.D. Detection of severe Midwest thunderstorms using geosynchronous satellite data // Am. Meteorol. Soc. 1985. V. 113. P. 769–781.
13. Setvák M., Lindsey D.T., Novák P., Wang P.K., Radová M. Kerkmann J., Grasso L., Su S-H., Rabin R.M., Šťástka J. Charvát Z. Satellite-observed cold-ring-shaped features atop deep convective clouds // Atmos. Res. 2010. V. 97, N 1–2. P. 80–96.
14. Shihov A.N., Chernokul'skij A.V., Sprygin A.A., Azhigov I.O. Identifikatsiya mezomasshtabnyh konvektivnyh oblachnyh sistem so smerchami po sputnikovym dannym // Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 2019. V. 16, N 1. P. 223–236.
15. Mitra A.K., Sharma A.K., Bajpai I., Kundu P.K. An atmospheric instability derived with MODIS profile using real-time direct broadcast data over the Indian region // Nat. Hazards. 2012. V. 63, N 2. P. 1007–1023.
16. Borbas E., Seemann S.W., Kern A., Moy L., Li J., Gumley L., Menzel W.P. MODIS atmospheric profile retrieval algorithm theoretical basis document collection 6, 2011. 32 p. URL: https://modis.gsfc.nasa.gov/data/dataprod/mod07.php.
17. Gorbatenko V.P., Krechetova S.Yu., Belikova M.Yu., Nechepurenko O.E. Sravnenie indeksov neustojchivosti atmosfery, vosstanavlivaemyh po dannym radiozondirovaniya i spektroradiometra MODIS v dni s grozami, nad territoriej Zapadnoj Sibiri // Meteorol. i gidrol. 2015. N 5. С. 10–19.
18. Gorbatenko V.P., Krechetova S.Yu., Belikova M.Yu., Razumova O.V. Identifikatsiya mezomasshtabnoj konvektsii i groz po dannym MODIS i aerologicheskogo zondirovaniya // Vestn. Tom. gos. un-ta. 2012. N 3365. P. 169–174.
19. Nechepurenko O.E. Identifikatsiya mezomasshtabnoj konvektsii po dannym sputnikovogo monitoringa: dis. kand. fiz-mat. nauk. Tomsk, 2020. 138 p.
20. Xavier V.F., Chandrasekar A., Singh R., Simon B. The impact of assimilation of MODIS data for the prediction of a tropical low-pressure system over India using a mesoscale model // Int. J. Remote Sens 2006. V. 27. P. 4655–4676.
21. Govindankutty M., Chandrasekar A. Effect of 3DVAR assimilation of MODIS temperature and humidity profiles on the dynamic and thermodynamic features of three monsoon depressions over the Bay of Bengal // Meteorol. Atmos. Phys. 2010. V. 107. P. 65–79.
22. Hersbach H., Bell B., Berrisford P., Hirahara S., Horányi A., Muñoz-Sabater J., Nicolas J., Peubey C., Radu R., Schepers D., Simmons A., Soci C., Abdalla S., Abellan X., Balsamo G., Bechtold P., Biavati G., Bidlot J., Bonavita M., De Chiara G., Dahlgren P., Dee D., Diamantakis M., Dragani R., Flemming J., Forbes R., Fuentes M., Geer A., Haimberger L., Healy S., Hogan R.J., Hólm E., Janisková M., Keeley S., Laloyaux P., Lopez P., Lupu C., Radnoti G., de Rosnay P., Rozum I., Vamborg F., Villaume S., Thépaut J.-N. The ERA5 global reanalysis // Quant. J. Roy. Meteorol. Soc. 2020. V. 146. P. 1999–2049.
23. Shikhov A.N., Chernokulsky A.V., Azhigov I.O., Semakina A.V. A satellite-derived database for stand-replacing windthrow events in boreal forests of European Russia in 1986–2017 // Earth Syst. Sci. Data. 2020. V. 12. P. 3489–3513.
24. Shihov A.N., Abdullin R.K., Chernokul'skij A.V., Azhigov I.O., Yarynich Yu.I., Sprygin A.A., Korenev D.P. Sozdanie kartograficheskoj bazy dannyh i veb-servisa «Konvektivnye opasnye meteorologicheskie yavleniya na territorii Tsentral'nogo federal'nogo okruga» // InterKarto. InterGIS. Geoinf. obespechenie ustojchivogo razvitiya territorij: materialy mezhdunar. konf. M: Geogr. fakul'tet MGU, 2021. V. 27. Pt. 3. P. 120–135.
25. Chernokulsky A.V., Shikhov A.N., Bykov A.V., Azhigov I.O. Satellite-based study and numerical forecasting of two tornado outbreaks in the Ural region in June 2017 // Atmosphere. 2020. V. 11. N 11. DOI: 10.3390/ atmos11111146.
26. Chernokul'skij A.V., Kurganskij M.V., Mohov I.I., Shihov A.N., Azhigov I.O., Selezneva E.V., Zaharchenko D.I., Antonesku B., Kune T. Smerchi v rossijskih regionah // Meteorol. i gidrol. 2021. N 2. P. 17–34.
27. LAADS DAAC. Level-1 and Atmosphere Archive and Distribution System Distributed Active Archive Center. [Electron resource]. URL: https://ladsweb.modaps.eosdis. nasa.gov/search/ (last access: 31.05.2021).
28. Shikhov A., Chernokulsky A., Kalinin N., Bykov A., Pischalnikova E. Climatology and formation environments of severe convective windstorms and tornadoes in the Perm region (Russia) in 1984–2020 // Atmosphere. 2021. V. 12, N 11. DOI: 10.3390/atmos12111407.
29. Chernokulsky A., Shikhov A., Bykov A., Kalinin N., Kurgansky M., Sherstyukov B., Yarinich Y. Diagnosis and modelling of two destructive derecho events in European Russia in the summer of 2010 // Atmos. Res. 2022. V. 267. Art. No. 105928.