Climatic Change

, Volume 118, Issue 3–4, pp 871–883 | Cite as

Temporal and spatial patterns of modern climatic warming: case study of Northern Eurasia

  • Oleg Anisimov
  • Vasily Kokorev
  • Yelena Zhil’tsova
Article

Abstract

Century-scale near-surface air temperature data from 744 weather stations in Russia and neighboring countries indicate that the temperature variations have distinct temporal patterns. Two periods, near the beginning and at the end of the 20th century, experienced the largest warming rates. Temperature changes in both periods were not uniform in time or space. We used statistical criteria and applied them to data at the weather stations to define a “tipping point” corresponding to the beginning of the modern climatic period. Results indicate that the position of this point depends on location, and in most cases falls into the interval from the early 1970s through the late 1980s. By means of spatial correlation analysis we delineated regions with coherent air temperature changes and calculated the region-specific rates and magnitudes of changes. We compared the distribution of regional tipping points in time and over space with large-scale atmospheric circulation patterns over northern Eurasia. We analyzed the 20th—early 21st century changes in the relative frequencies of the three circulation forms defined by Vangengheim-Girs classification, and found their qualitative correspondence with the spatial temperature patterns and spread of the tipping points in time. These results improve our knowledge about the regional structure and drivers of modern climate change in northern Eurasia, which is likely to hold the fingerprint of the anthropogenic signal. Findings of this study can be used to obtain insight into regional climatic changes in northern Eurasia over the next few decades.

Supplementary material

10584_2013_697_MOESM1_ESM.doc (1.7 mb)
ESM 1(DOC 1.72 mb)

References

  1. Anisimov OA, Lobanov VA, Reneva SA, Shiklomanov NI, Zhang T (2007) Uncertainties in gridded air temperature fields and their effect on predictive active layer modeling. J Geophys Res 112 (F02S14). doi:10.1029/2006JF000593
  2. Barriopedro D, Garcia-Herrera R, Lupo AR, Hernandez E (2006) A climatology of northern hemisphere blocking. J Clim 19(6):1042–1063CrossRefGoogle Scholar
  3. Bengtsson L, Semenov VA, Johannessen OM (2004) The early twentieth-century warming in the Arctic—a possible mechanism. J Clim 17:4045–4057CrossRefGoogle Scholar
  4. Dzerdzeievsky BL (1968) Mechanisms of atmospheric circulation of the Northern henisphere in the 20th century. Nauka, MoscowGoogle Scholar
  5. Dzerdzeievsky BL (1975) General circulation of the atmosphere and climate. Selected papers. Nauka, MoscowGoogle Scholar
  6. Girs AA (1960) Fundamentals of the long range weather prediction. Hydrometeoizdat, LeningradGoogle Scholar
  7. Hansen J, Ruedy R, Sato M, Lo K (2010) Global surface temperature change. Rev Geophys 48:RG4004. doi:10.1029/2010RG000345:1-29 CrossRefGoogle Scholar
  8. Hazeleger W, Severijns C, Semmler T, Ştefănescu S, Yang S, Wang X, Wyser K, Dutra E, Baldasano JM, Bintanja R, Bougeault P, Caballero R, Ekman AML, Christensen JH, van den Hurk B, Jimenez P, Jones C, Kållberg P, Koenigk T, McGrath R, Miranda P, Van Noije T, Palmer T, Parodi JA, Schmith T, Selten F, Storelvmo T, Sterl A, Tapamo H, Vancoppenolle M, Viterbo P, Willén U (2010) EC-earth: a seamless earth-system prediction approach in action. Bull Am Meteorol Soc 91(10):1357–1363CrossRefGoogle Scholar
  9. Kallberg P, Simmons S, Uppala S, Fuentes M (2004) The ERA-40 Archive, ERA-40 Project Report Series No. 17. European Center for Medium-Range Weather Forecasts, Reading, UK. http://www.ecmwf.int/publications/library/do/references/list/192
  10. Matsuura K, Willmott CJ (2005) Arctic land-surface air temperature: 1930–2004 gridded monthly time series (version 1.03). http://climate.geog.udel.edu/~climate/html_pages/Arctic4_files/README.arctic.t_ts4.html
  11. Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol 25(6):693–712CrossRefGoogle Scholar
  12. Palmer TN, Doblas-Reyes FJ, Weisheimer A, Rodwell MJ (2008) Toward seamless prediction: calibration of climate change projections using seasonal forecasts. Bull Am Meteorol Soc 89(4):459–470CrossRefGoogle Scholar
  13. Scaife AA, Buontempo C, Ringer M, Sanderson M, Gordon C, Mitchell JFB (2009) Toward seamless prediction: calibration of climate change projections using seasonal forecasts. Bull Am Meteorol Soc 90(10):1549–1551CrossRefGoogle Scholar
  14. Scherrer SC, Croci-Maspoli M, Schwierz C, Appenzeller C (2006) Two-dimensional indices of atmospheric blocking and their statistical relationship with winter climate patterns in the Euro-Atlantic region. Int J Climatol 26(2):233–249CrossRefGoogle Scholar
  15. Serreze MC, Hurst CM (2000) Representation of mean Arctic precipitation from NCEP-NCAR and ERA reanalyses. J Clim 13(1):182–201CrossRefGoogle Scholar
  16. Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) (2007) Climate change 2007: the physical science basis. Contribution of working group I to the Fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  17. Toth Z, Pena M, Vintzileos A (2007) Bridging the gap between weather and climate forecasting: research priorities for intraseasonal prediction. Bull Am Meteorol Soc 88(9):1427–1429CrossRefGoogle Scholar
  18. Zhil’tsova EL, Anisimov OA (2009) Contrasting global gridded temperature and precipitation archives against observations in Russia. Meteorol Hydrol 10:79–90Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Oleg Anisimov
    • 1
  • Vasily Kokorev
    • 1
  • Yelena Zhil’tsova
    • 1
  1. 1.Department of ClimatologyState Hydrological InstituteSt. PetersburgRussia

Personalised recommendations