Transformation of Spatial Structure of the Surface Temperature Field in the Northern Hemisphere
https://doi.org/10.31857/S2587556620010057
Abstract
The selection of informative criteria and objective classification methods is the current task of climatology. In this paper we present the results of the clustering algorithm of climate. The temperature signals are classified by the degree of similarity of the phase modulation characteristics. Different time periods were considered. They correspond to the main trends in the global temperature dynamics. Such an approach may be a variant of the objective dynamic classification of the Northern Hemisphere climate. Data from 818 meteorological stations were used. The transformation of the system and changes in the degree of temperature dynamics’ consistency at different intervals of years are revealed. This made it possible to identify the most sensitive areas of the Northern Hemisphere. In these areas the stations changed its structural affiliation depending on global trends. With increasing global temperature, the structure of the regional fields is changing. Coherence of temperature fluctuations varies. There is a transition of many stations of more northern classes to more southern ones. The most sensitive to global climate trends are the territories of Fennoscandia and Central Europe, Greenland, the Russian Arctic and Subarctic, Florida Peninsula, and stations located in a mountainous terrain Eurasian areas and areas of influence of basic centers of atmospheric action.
About the Authors
N. N. Cheredko
Institute of monitoring of climatic and ecological systems SB RAS
Russian Federation
Tomsk
Russian Federation
Tomsk
V. A. Tartakovsky
Institute of monitoring of climatic and ecological systems SB RAS
Russian Federation
Tomsk
Russian Federation
Tomsk
Y. V. Volkov
Institute of monitoring of climatic and ecological systems SB RAS
Russian Federation
Tomsk
Russian Federation
Tomsk
V. A. Krutikov
Institute of monitoring of climatic and ecological systems SB RAS
Russian Federation
Tomsk
Russian Federation
Tomsk
References
1. Anisimov O.A., Zhiltsova E.L., Kokorev V.A. Spatial and temporal patterns of air temperature changes in Russia in the 20th century and early 21st century. Probl. Ekol. Monit. i Modelir. Ekosistem, 2011, vol. XXIV, pp. 83–98. (In Russ.).
2. Anisimov O.A., Zhiltsova E.L. Climate change estimates for the regions of Russia in the 20th century and at the beginning of the 21st century based on the observation data. Russ. Meteorol. Hydrol., 2012, vol. 37, no. 6, pp. 421–429.
3. Anisimov O.A., Kokorev V.A. The optimal choice of hydrodynamic models to assess the impact of climate change on the cryosphere. Led i Sneg, 2013, vol. 53, no. 1, pp. 83–92. (In Russ.). doi 10.15356/2076-6734-2013-1-83-92
4. Anisimov O.A., Lobanov V.A., Reneva S.A. Analysis of changes in air temperature in Russia and empirical forecast for the first quarter of the 21st century. Russ. Meteorol. Hydrol., 2007, vol. 32, no. 10, pp. 620–626.
5. Archive of the University of East Anglia. Available at: http://www.metoffice.gov.uk, http://www.cru.uea.ac.uk (accessed: 01.12.17).
6. Volkova М.А., Cheredko N.N., Sokolov K.I., Ogurtsov L.A. The current space-time structure of the extreme precipitation field in Western Siberia. Vestn. Tomsk. Gos. Univ., 2015, no. 390, pp. 202–210. (In Russ.).
7. Vtoroi otsenochnyi doklad Rosgidrometa ob izmeneniyakh klimata i ikh posledstviyakh na territorii Rossiiskoi Federatsii. Obshchee resyume [Second Roshydromet Assessment Report on Climate Change and its Consequences in the Russian Federation. Summary]. Moscow: Rosgidromet, 2014. 62 p.
8. Gruza G.V., Rankova E.Ya. Nablyudaemye i ozhidaemye izmeneniya klimata Rossii: temperatura vozdukha [Observed and Expected Climate Changes in Russia: Surface Air Temperature]. Obninsk: VNIIGMIMTsD, 2012. 194 p.
9. Zakusilov V.P., Zakusilov P.V. Use of component analysis to characterize the atmospheric circulation over a given geographical area. Vestn. Voronezh. Gos. Univ., Ser. Geogr. Geoekol., 2009, no. 2, pp. 67–71. (In Russ.).
10. Kondratyuk V.I. Svetlova T.P. Dalyuk I.V. Introduction of information-content homogeneous zones by climatic data. Tr. GGO, 2002, no. 551, pp. 51–57. (In Russ.).
11. Lyubushin A.A. Analiz dannykh system geofizicheskogo i ekologicheskogo monitoringa [Geophysical and Ecological Monitoring Systems Data Analysis]. Moscow: Nauka Publ., 2007. 228 p.
12. Poliakov D.V., Kuzhevskaya I.V. Use of cluster analysis for assessing heat and moisture during active vegetation in south of Western Siberia and its relation to T.G. Selyaninov hydrothermal coefficient. Vestn. Tomsk. Gos. Univ., 2012, no. 360, pp. 188–192. (In Russ.).
13. Rostov I.D., Rudykh N.I., Rostov V.I., Vorontsov A.A. Expressions of global climatic changes in coastal waters of Northern part of the Sea of Japan. Vestn. DVO RAN, 2016, no. 5, pp. 100–112. (In Russ.).
14. Rusin I.N., Mosolova G.I. Principles of climatic classifications and climatic forecast. Vestn. S.-Peterb. Univ., Ser 7: Geol. Geogr., 2010, no. 2, pp. 99–108. (In Russ.).
15. Salugashvili R.S. Climate fluctuations within the first natural synoptic area and climatic zoning. Uch. Zap. Kazan. Univ., Ser. Estestv. Nauki, 2012, vol. 154, no. 3, pp. 216–227. (In Russ.).
16. Sivogolovko E.V. Methods of estimation of smooth clustering quality. Komp’yut. Instr. v Obrazovanii, 2011, no. 4, pp. 14–31. (In Russ.).
17. Tartakovsky V.A. Synchronous analysis of the Wolf numbers and temperature series from weather station in the Northern Hemisphere of the Earth. Optika Atmosf. i Okeana., 2015, vol. 28, no. 2, pp. 182–188. (In Russ.).
18. Cheredko N.N., Zhuravlev G.G., Kuskov A.I. Estimation of modern climate trends and their synchronicity in the Altai region. Vestn. Tomsk. Gos. Univ., 2014, no. 379, pp. 200–208. (In Russ.).
19. Cheredko N.N., Tartakovsky V.A., Krutikov V.A., Volkov Yu.V. Climate classification in the Northern Hemisphere using phases of temperature signals. Atmos. Ocean. Opt., 2017, vol. 30, no. 1, pp. 63–69. doi 10.1134/S1024856017010043
20. Sherstyukov B.G. Regional’nye i sezonnye zakonomernosti izmenenii sovremennogo klimata [Regional and Seasonal Patterns of Changes in the Current Climate]. Obninsk: VNIIGMI-MTsD, 2008. 247 p.
21. Beniston M. Warm winter spells in the Swiss Alps: Strong heat waves in a cold season? A study focusing on climate observations at the Saentis high mountain site. Geophys. Res. Lett., 2005, vol. 32, no. 1, L01812. doi 10.1029/2004GL021478
22. DeGaetano A.T. Spatial grouping of United States climate stations using a hybrid clustering approach. Int. J. Climatol., 2001, vol. 21, no. 7, pp. 791–807.
23. Deliège A., Nicolay S. Köppen–Geiger climate classification for Europe recaptured via the Hölder regularity of air temperature data. Pure Appl. Geophys., 2016, vol. 173, no. 8, pp. 2885–2898.
24. Gabor D. Theory of communication. J. Inst. Electr. Eng.-Part III: Radio Com. Eng., 1946, vol. 93, no. 26, pp. 429–441.
25. Gallardo C., Gil V., Hagel E., Tejeda C., Castro M. Assessment of climate change in Europe from an ensemble of regional climate models by the use of KöppenTrewartha classification. Int. J. Climatol, 2013, vol. 33, no. 9, pp. 2157–2166.
26. Köppen W. Klassification der Klimate nach Temperatur, Niederschlag und Jahreslauf. Peterm. Mitt., 1918, pp. 194–203, 243–248.
27. Köppen W. Das geographische System der Klimate. Berlin: Verlag von Gebrüder Bornträger, 1936. 44 p.
28. Kottek M., Grieser J., Beck C., Rudolf B., Rubel F. World map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 2006, vol. 15, no. 3, pp. 259–263.
29. Ohmura A. Enhanced temperature variability in highaltitude climate change. Theor. Appl. Climatol., 2012, vol. 110, no. 4, pp. 499–508. doi 10.1007/s00704-012-0687-x
30. Peel M.C., Finlayson B.L., Mcmahon T.A. Updated world map of the Köppen-Geiger climate classication. Hydrol. Earth Syst. Sci. Discuss., 2007, vol. 4, no. 2, pp. 439–473.
31. Rohli R.V., Joyner T.A., Reynolds St. J., Shaw C., Vazquez J.R. Globally Extended K¡ppen–Geiger climate classification and temporal shifts in terrestrial climatic types. Phys. Geogr., 2015, vol. 36, no. 2, pp. 142–157.
32. Rubel F., Brugger K., Haslinger K., Auer I. The climate of the European Alps: Shift of very high resolution Köppen-Geiger climate zones 1800–2100. Meteorologische Zeitschrift, 2017, vol. 26, no. 2, pp. 115–125.
33. Schöner W., Böhm R., Auer I. 15 years of high-mountain research at Sonnblick Observatory (Austrian Alps) – from “the house above the clouds” to a unique research platform. Theor. Appl. Climatol., 2012, vol. 110, no. 4, pp. 491–498.
34. Supan A. Die Temperaturzonen der Erde. Peterm. Mitt., 1879, no. 25, pp. 349–358.
35. Zhang X., Yan X. Spatiotemporal change in geographical distribution of global climate types in the context of climate warming. Clim. Dyn., 2014, vol. 43, nos. 3–4, pp. 595–605. doi 10.1007/s00382-013-2019-y
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- Changes in the synchronization regimes of climatic processes are a sign of a system transition to another state.
- Climate classification by the coherence of temperature fluctuations is an objective way to study the transformation of climate structures.
- In periods of different directions of global trends, the regional structure of the consistency of temperature changes is different.
- The territories most sensitive to global climatic trends have been identified.
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For citations:
Cheredko N.N., Tartakovsky V.A., Volkov Y.V., Krutikov V.A. Transformation of Spatial Structure of the Surface Temperature Field in the Northern Hemisphere. Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya. 2020;(1):47-55. (In Russ.) https://doi.org/10.31857/S2587556620010057
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