UDC: 
DOI: 
10.22389/0016-7126-2017-926-8-39-48
1 Abdullin R.K.
2 Shikhov A.N.
Year: 
№: 
926
Pages: 
39-48

Perm State National Research University

1, 
2, 
Abstract:
The article describes a method of synthetic mapping of severe weather events at a regional scale level (on example of Perm Region). On its basis the maps of climatic extremes frequency and prevalent types of severe weather events are created for the first time. Using the weighted numerical score method, we have identified the area of maximum frequency of climatic extremes occurrence within Perm region. It is located in the mountainous region of Northern Urals. Also, a significant frequency of climatic extremes is typical in the southern part of the region. The area of minimum climatic extremes frequency is located near the Kama Reservoir. When performing this calculation, we took into account the approximate severity of each type of climatic extreme. Territory zoning according to prevailing types of severe weather events was carried out in two different methods. There are expert method and spatial cluster analysis. The zoning results, produced using the two methods, are characterized by a high degree of similarity. In both methods the similar areas of high frequency of heavy rainfall and snowfall, severe frosts and heatwaves occurrence were identified. The differences between zoning results are insignificant. This demonstrates the possibility of automated zoning method based on cluster analysis.
References: 
1.   Atlas prirodnyh i tekhnogennyh opasnostej i riskov chrezvychajnyh situacij v Rossijskoj Federacii. Pod red. S.K. Shojgu. M.: Feoriya, 2005, 271 p.
2.   Gavrilova S. A. Kartografirovanie prirodnykh chrezvychainykh situatsii na territorii Rossii: Avtoref. dis. na soisk. uch. st. kand. geogr. nauk. 25.00.33. [Mapping of natural emergencies on the territory of Russia: PhD Thesis abstract]. M.:MGU, 2013, 24 p.
3.   Gilyazov A.F. Klasternyi analiz kak instrument raionirovaniya territorii po krupnosti rechnykh nanosov (na primere basseina Volgi) [Cluster analysis as an instrument of territory zoning by the size of river sediments (on example of the Volga basin)]. Vestn. Udmurtskogo un-ta. Seriya 6. Biologiya. Nauki o Zemle, 2015, no. 2, pp. 149–158.
4.   Ivanova M. B. Matematicheskie metody v sotsial’noekonomicheskoi geografii [Mathematical methods in socioeconomic geography]. Perm’: izd. Perm. gos. un-ta, 2007, 315 p.
5.   Kalinin N. A. Monitoring, modelirovanie i prognoz sostoyaniya atmosfery v umerennykh shirotakh [Monitoring, modeling and forecasting of the state of the atmosphere in temperate latitudes]: Monografiya. Perm’: izd. Perm. gos. nats. issled. un-ta, 2015, 308 p.
6.   Svedeniya o neblagopriyatnykh usloviyakh pogody i opasnykh gidrometeorologicheskikh yavleniyakh, nanesshikh sotsial’nye i ekonomicheskie poteri na territorii Rossii. Vserossiiskii nauchno-issledovatel’skii institut gidrometeorologicheskoi informatsii ‒ mi. URL: http://meteo.ru/data/310-neblagopriyatnyeusloviya-pogody-nanjosshie-ekonomicheskie-poteri
7.   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 [Questions of weather forecasting, climate and atmospheric circulation], Perm’: izd. Perm. gos. un-ta, 1990, pp. 76–86.
8.   ArcGis Resources. ArcGIS Help 10.2, 10.2.1, and 10.2.2. Grouping Analysis (Spatial Statistics). URL: http://resources.arcgis.com/en/help/main/10.2/index.html#/na/005p00000051000000/
9.   Assunção R. M., Neves M. C., Câmara G., Da Costa Freitas C. (2006) Efficient regionalization techniques for socio-economic geographical units using minimum spanning trees. International Journal of Geographical Information Science, Volume 20(7), pp. 797‒811.
10.   Shi P. J., Karsperson R. World Atlas of Natural Disaster Risk. Springer, Heidelberg, pp. 368.
Citation:
Abdullin R.K., 
Shikhov A.N., 
(2017) Synthetic mapping of hazardous meteorological phenomena at the regional scale level. Geodesy and cartography = Geodezia i Kartografia, 926(8), pp. 39-48. (In Russian). DOI: 10.22389/0016-7126-2017-926-8-39-48
Publication History
Received: 11.01.2017
Accepted: 04.04.2017
Published: 17.09.2017

Content

2017 August DOI:
10.22389/0016-7126-2017-926-8

QR-code page

QR-код страницы