STARDEX and ETCCDI Climate Indices Based on E-OBS and CARPATCLIM

Part Two: ClimData in Use
  • Hristo ChervenkovEmail author
  • Kiril Slavov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11189)


In part one of the present article are described the motivation for the creation, the content, structure and the access point to the free available database of climate indices ClimData. Part two is dedicated on the possibilities of climate indices-based analysis with ClimData. They are demonstrated with some thermal absolute-thresholds and percentile-based indices. Most significant outcome of the study, beside the creation of ClimData itself, is the clearly expressed warming signal in the considered climate indices. This outcome agrees generally with the prevailing number recent studies. This signal is spatially dominating over Europe, almost everywhere statistically significant and coherent in the STARDEX and ETCCDI variants of the same indices. The latter suggest that relatively small modifications of the index-definitions or selection of the input data are not sufficient enough to change the general picture of revealed changes.


Climate indices E-OBS CARPATCLIM STARDEX ETCCDI ClimData database 



We thank to the anonymous reviewers for their comments and suggestions which led to an overall improvement of the original manuscript. The project for creation of ClimData and this study is entirely based on free available data and software. The authors would like to express their deep gratitude to the organizations and institutes (CARPATCLIM, ECA&D, STARDEX, ETCCDI, Unidata and others), which provides free of charge software and data. Without their innovative data services and tools this project would be not possible. This work was partially supported by the European Commission under H2020 project VI–SEEM (Contract No. 675121) and by the Bulgarian National Science Fund (grant DN-14/3/13.12.2017).


  1. 1.
    Alexander, L.V., et al.: Global observed changes in daily climate extremes of temperature and precipitation. J. Geophys. Res. 111(D5) (2006).
  2. 2.
    Birsan, M.V., Dumitrescu, A., Micu, D.M., Cheval, S.: Changes in annual temperature extremes in the carpathians since AD 1961. Nat. Hazards 74(3), 1899–1910 (2014). Scholar
  3. 3.
    Chervenkov, H., Slavov, K., Ivanov, V.: STARDEX and ETCCDI Climate Indices Based on E-OBS and CARPATCLIM-part one: general description. In: Numerical Methods and Applications (in press)Google Scholar
  4. 4.
    Lakatos, M., Szentimrey, T., Bihari, Z., Szalai, S.: Investigation of climate extremes in the Carpathian region on harmonized data. In: International Scientific Conference on Environmental Changes and Adaptation Strategies (2013)Google Scholar
  5. 5.
    Moberg, A., et al.: Indices for daily temperature and precipitation extremes in Europe analyzed for the period 1901–2000. J. Geophys. Res. 111(D22), 1–25 (2006). Scholar
  6. 6.
    Sen, P.K.: Estimates of the regression coefficient based on kendall’s tau. J. Am. Stat. Assoc. 63(324), 1379–1389 (1968). Scholar
  7. 7.
    Sillmann, J., Röckner, E.: Indices for extreme events in projections of anthropogenic climate change. Clim. Change 86(1–2), 83–104 (2007). Scholar
  8. 8.
    Theil, H.: A rank-invariant method of linear and polynomial regression analysis. Advanced Studies in Theoretical and Applied Econometrics, pp. 345–381. Springer, Netherlands (1992). Scholar
  9. 9.
    Zhang, X., Hegerl, G., Zwiers, F.W., Kenyon, J.: Avoiding in homogeneity in percentile-based indices of temperature extremes. J. Clim. 18(11), 1641–1651 (2005). Scholar
  10. 10.
    Zhang, X., et al.: Indices for monitoring changes in extremes based on daily temperature and precipitation data. Wiley Interdisc. Rev. Clim. Change 2(6), 851–870 (2011). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.National Institute of Meteorology and HydrologyBulgarian Academy of SciencesSofiaBulgaria

Personalised recommendations