Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 21, 2024
Number 1 Number 2 Number 3
Volume 20, 2023
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 19, 2022
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 18, 2021
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 17, 2020
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 16, 2019
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 15, 2018
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 14, 2017
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 13, 2016
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 12, 2015
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 11, 2014
Number 1 Number 2 Number 3 Number 4
Volume 10, 2013
Number 1 Number 2 Number 3 Number 4
Volume 9, 2012
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 8, 2011
Number 1 Number 2 Number 3 Number 4
Volume 7, 2010
Number 1 Number 2 Number 3 Number 4
Issue 6, 2009
Volume 1 Volume 2
Issue 5, 2008
Volume 1 Volume 2
Issue 4, 2007
Volume 1 Volume 2
Issue 3, 2006
Volume 1 Volume 2
Issue 2, 2005
Volume 1 Volume 2
Issue 1, 2004
Volume 1
Search
Find:
русский
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, 2017, Vol. 14, No. 7, pp. 308-318

Estimation of the frequency of hazardous convective weather events using remote sensing data (by the example of Perm Region)

R.K. Abdullin 1 , A.N. Shikhov 1 
1 Perm State University, Perm, Russia
Accepted: 15.09.2017
DOI: 10.21046/2070-7401-2017-14-7-308-318
The article describes different approaches to estimating the frequency of local hazardous convective weather events, using long-term remote sensing data. The results of direct estimate (using ground-based observation data and damage reports) and indirect estimate (from remote sensing data) of the frequency of hazardous weather events are compared by the example of the Perm Region. A long-term series of Terra/Aqua MODIS satellite images were used to estimate the repeatability of mesoscale convective systems occurrence. The estimation of the thunderstorms frequency was performed according to the World Wide Lightning Location Network (WWLLN) data. It is shown that the southwestern and northwestern parts of the area are characterized by the highest frequency of convective weather phenomena, and the minimum frequency corresponds to the northeast of the region. The spatial distribution of mesoscale convective systems, estimated by the MODIS data, and thunderstorms (according to WWLLN data) is characterized by a high degree of similarity. This shows the objectivity of the obtained estimates from remote sensing data. At the same time, the frequency of hazardous convective weather events, estimated using ground-based observation data and damage reports, is significantly different from them. This may be due to the data incompleteness on reported local convective phenomena in conditions of low population density and sparse observational network.
The spatial distribution of mesoscale convective systems, estimated by the MODIS data, and thunderstorms (according to WWLLN data) is characterized by a high degree of similarity. This shows the objectivity of the obtained estimates by the remote sensing data. At the same time, the frequency of hazardous convective weather events, estimated using ground-based observation data and damage reports, is significantly different from them. This may be due to the data incompleteness on reported local convective phenomena, in conditions of low population density and the observational network.
Keywords: hazardous convective weather events, frequency, mesoscale convective systems, MODIS data, WWLLN data
Full text

References:

  1. Lenskaya O.Yu., Metodicheskie voprosy ispol'zovaniya sputnikovoi i radiolokatsionnoi informatsii v mezomasshtabnom prognoze (na primere opasnykh yavlenii pogody v Moskve 24 iyulya 2001 g.) (Methodical issues of the use of satellite and radar data in the mesoscale forecast (by the example of dangerous weather phenomena in Moscow on July 24, 2001)), Vestnik Chelyabinskogo un-ta, 2007, No. 6, pp. 66‒79.
  2. Petukhov I.N., Rol' massovykh vetrovalov v formirovanii lesnogo pokrova v podzone yuzhnoi taigi (Kostromskaya oblast'): Diss. kand. biol. nauk (The role of large forest windfalls disturbances in the formation of forest cover in the subzone of the southern taiga (Kostroma Region). Cand. biol. sci. thesis), Kostroma, 2016, 150 p.
  3. Shikhov A.N. Otsenka posledstvii stikhiinykh prirodnykh yavlenii dlya lesnykh resursov Permskogo kraya po mnogoletnim ryadam dannykh kosmicheskoi s"emki (Estimation of forest damage from natural disasters in Perm region using the long-term series of space imagery), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz Kosmosa, 2014, Vol. 11, No. 1, pp. 21–30.
  4. Shklyaev V.A., Osobennosti raspredeleniya konvektivnykh yavlenii na Urale (Features of distribution of convective phenomena in the Urals), Voprosy prognoza pogody, klimata i tsirkulyatsii atmosfery: mezhvuz. sb. nauch. Trudov, Perm', 1990, pp. 76–86.
  5. 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.
  6. Boruff B.J., Easoz J.A., Jones S.D., Landry H.R., Mitchem J.D., Cutter S.L., Tornado hazards in the United States, Climate Research, 2003, Vol. 24, pp. 103–117.
  7. Cintineo J.L., Smith T.M., Lakshmanan V., Brooks H.E., Ortega. K.L., An objective high-resolution hail climatology of the contiguous United States, Weather and Forecasting, 2012, Vol. 27 (5), pp. 1235–1248.
  8. Diffenbaugh N.S., Scherer M., Trapp R.J., Robust increases in severe thunderstorm environments in response to greenhouse forcing, Proceedings of the National Academy of Sciences of the United States of America, 2013, Vol. 110 (41), pp. 16361–16366.
  9. Ferraro R., Beauchamp J., Cecil D., Heymsfield G., A prototype hail detection algorithm and hail climatology developed with the advanced microwave sounding unit (AMSU), Atmospheric Research, 2015, Vol. 163, pp. 24–35.
  10. Groenemeijer P., Kuhne T., A climatology of tornadoes in Europe: results from the European Severe Weather Database, Monthly Weather Review, 2014, Vol. 142, pp. 4775–4790.
  11. Hansen M.C., Potapov P.V., Moore R., Hancher M., Turubanova S.A., Tyukavina 1.A., Thau D., Stehman S.V. Goetz S.J., Loveland T.R., Kommareddy A., Egorov A., Chin L., Justice C.O., Townshend J.R.G., High-Resolution Global Maps of 21st-Century Forest Cover Change, Science, 2013, Vol. 342, pp. 850–853.
  12. Jurković P.M., Mahović N.S., Počakal D., Lightning, overshooting top and hail characteristics for strong convective storms in Central Europe, Atmospheric Research, 2015, Vol. 161162, pp. 153168.
  13. Meredith E.P., Semenov V.A., Maraun D., Park W., Chernokulsky A.V., Crucial role of Black Sea warming in amplifying the 2012 Krymsk precipitation extreme, Nature Geoscience, 2015, Vol. 8 (8), pp. 615619.
  14. Nisi L., Martius O., Hering A., Kunz M., Germann U., Spatial and temporal distribution of hailstorms in the Alpine region: A long-term, high resolution, radar-based analysis, Quarterly Journal of the Royal Meteorological Society, 2016. Vol. 142 (697), pp. 1590–1604.
  15. Punge H.J., Bedka K.M., Kunz M., Werner A., A new physically based stochastic event catalog for hail in Europe, Natural Hazards, 2014, Vol. 73, pp. 16251645.
  16. ScanEx Image Processor v.4.0. Programma obrabotki dannykh distantsionnogo zondirovaniya Zemli (Earth Remote Sensing Data Processing Software), Moscow, 2013, 346 p.
  17. Virts K.S., Wallace J.M., Hutchins M.L., Holzworth R.H., Highlights of a new ground-based, hourly global lightning climatology, Bulletin of the American Meteorological Society, 2013, Vol. 94 (9), pp. 1381–1391.
  18. Wan Z., MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD) Version 3.3, Institute for Computational Earth System Science, University of California, Santa Barbara, 1999, 75 p.