Theoretical and Applied Climatology

, Volume 124, Issue 1–2, pp 161–178 | Cite as

Daily temperature grids for Austria since 1961—concept, creation and applicability

  • Johann HieblEmail author
  • Christoph Frei
Original Paper


Current interest into past climate change and its potential role for changes in the environment call for spatially distributed climate datasets of high temporal resolution and extending over several decades. To foster such research, we present a new gridded dataset of daily minimum and maximum temperature covering Austria at 1-km resolution and extending back till 1961 at daily time resolution. To account for the complex and highly variable thermal distributions in this high-mountain region, we adapt and employ a recently published interpolation method that estimates nonlinear temperature profiles with altitude and accounts for the non-Euclidean spatial representativity of station measurements. The spatial analysis builds upon 150 station series in and around Austria (homogenised where available), all of which extend over or were gap-filled to cover the entire study period. The restriction to (almost) complete records shall avoid long-term inconsistencies from changes in the station network. Systematic leave-one-out cross-validation reveals interpolation errors (mean absolute error) of about 1 °C. Errors are relatively larger for minimum compared to maximum temperatures, for the interior of the Alps compared to the flatland and for winter compared to summer. Visual comparisons suggest that valley-scale inversions and föhn are more realistically captured in the new compared to existing datasets. The usefulness of the presented dataset (SPARTACUS) is illustrated in preliminary analyses of long-term trends in climate impact indices. These reveal spatially variable and eventually considerable changes in the thermal climate in Austria.


Interpolation Method Interpolation Error Background Field Mean Absolute Error Gridded Dataset 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Special thanks are given to Michael Hofstätter for thematic discussion, to Walter Pawlica, Irena Grubi-Tonkovic, Marc Olefs and Ivonne Anders (all ZAMG) for technical support, to Christopher Thurnher and Hubert Hasenauer (Institute of Silviculture, BOKU) for customised provision of gridded data and to the ZAMG’s sister institutes in the neighbouring countries for unbureaucratic provision of station data: Luca Maraldo and Günther Geier (Hydrographisches Amt der autonomen Provinz Bozen – Südtirol), Daniel Wolf (MeteoSchweiz), Hermann Mächel (DWD), Petr Skalak (CHMI), Pavol Nejedlík (SHMU), Zita Bihari (OMSZ), Gregor Vertačnik and Mojca Dolinar (ARSO) and Andrea Cicogna (ARPA-OSMER FVG). Furthermore, we thank two anonymous reviewers for their constructive suggestions. The project SPARTACUS was funded by the Austrian Federal Ministry of Science and Research.


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Copyright information

© Springer-Verlag Wien 2015

Authors and Affiliations

  1. 1.Zentralanstalt für Meteorologie und Geodynamik (ZAMG)ViennaAustria
  2. 2.Federal Office of Meteorology and Climatology (MeteoSwiss)ZürichSwitzerland

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