Climate indicators for Austria from 1961 to 2025 at 1 km resolution

This repository provides a comprehensive dataset of 117 climate indicators for Austria on a 1-km spatial grid. The indicators are organized into seven groups based on their input variables: temperature, precipitation, snow, runoff, radiation, humidity and mixed.

Methods

The climate indicators are derived using a variety of established definitions, including those from: Klein Tank et al. (2009), Hartmann et al. (2013), Climdex, Bioclim and Chimani et al. (2019). Additionally, the dataset incorporates indicators developed through collaborative discussions with internal climate service providers at GeoSphere Austria.

Temporal aggregation

The climate indicators are provided in annual, seasonal, or both temporal aggregations, depending on their specific definitions. Furthermore, the dataset includes a variety of spatial and temporal aggregations:

• Area means: spatial averages calculated across all available fields for all temporal aggregations (seasonal/annual)
• Climatological fields: spatial climatologies for two time periods:
  • 1961 to 1990 (past)
  • 1991 to 2020 (recent)
• Significance fields: p-value from a two-tailed Mann-Whitney U-test between the two climatological periods

Input data sources

The data these indicators have been calculated from are daily climatological fields from:

• Temperature (minimum/mean/maximum): SPARTACUS (Hiebl. et al, 2015) [v2.1]
• Accumulated precipitation: SPARTACUS (Hiebl et al, 2017) [v2.1]
• Absolute and relative sunshine duration: SPARTACUS (Hiebl et al, 2024) [v2.1]
• Reference evapotranspiration: WINFORE (Haslinger and Bartsch, 2016) [v2.1]
• Snow and runoff variables: SNOWGRID (Olefs et al, 2020) [v2.1]

The input data can be downloaded from the GeoSphere Austria Data Hub:

• Temperature: https://doi.org/10.60669/m6w8-s545
• Precipitation: https://doi.org/10.60669/m6w8-s545
• Evapotranspiration: https://doi.org/10.60669/f6ed-2p24
• Sunshine duration: https://doi.org/10.60669/m6w8-s545
• Snow and runoff: https://doi.org/10.60669/fsxx-6977

Visualizations

The dataset includes a variety of visualizations to aid in the interpretation of the climate indicators:

• Trends:
  • Anomaly timeseries plots for the area means
  • Warming stripes for area means
• Spatial maps:
  • Climatological fields for the two time periods (1961–1990 and 1991–2020).
  • Differences between the climatological fields.
  • p-values from significance tests.
  • Proportion of significant changes per parameter category.

Spatial coverage

The dataset covers the following area of interest in the ETRS89 / Austria Lambert projection (EPSG:3416), corresponding to 105736 km² within the SPARTACUS domain:

The geographical extent of the dataset is documented in `spatial_extent.gpkg`, which contains the following layers:

        layer_name geometry_type features fields                 crs_name
1        AT_border Multi Polygon        1     14 ETRS89 / Austria Lambert
2 SPARTACUS_domain Multi Polygon        1      0 ETRS89 / Austria Lambert
3   WINFORE_domain       Polygon        1      0 ETRS89 / Austria Lambert
4  SNOWGRID_domain       Polygon        1      0 ETRS89 / Austria Lambert
5             grid       Polygon   105736      3 ETRS89 / Austria Lambert

which contain the following information:

1. the official national border of Austria (as provided by BEV, https://doi.org/10.48677/bf810ec9-3869-4290-96d2-cc1d2d5196e5)
2. SPARTACUS domain derived from the grid
3. WINFORE domain derived from the grid
4. SNOWGRID domain derived from the grid
5. the actual 1 km grid; Includes three columns for each input dataset, indicating data availability for each grid cell (1 = available, 0 = no data).

How to Cite

Please cite our accompanying data descriptor paper:

Lehner, S., Schlögl, M. Climate indicators for Austria since 1961 at 1 km resolution. Sci Data (2026). https://doi.org/10.1038/s41597-026-06834-y

References

• Klein Tank A.M.G., Zwiers F.W., Zhang X. (2009): Guidelines onanalysis of extremes in a changing climate in supportof informed decisions for adaptation. (WCDMP-72,WMO-TD/No. 1500) 2009, 56, https://library.wmo.int/idurl/4/48826.
• Hartmann, D.L., A.M.G. Klein Tank, M. Rusticucci, L.V. Alexander, S. Brönnimann, Y. Charabi, F.J. Dentener, E.J. Dlugokencky, D.R. Easterling, A. Kaplan, B.J. Soden, P.W. Thorne, M. Wild and P.M. Zhai. (2013): Observations: Atmosphere and Surface. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
• Hiebl, J., & Frei, C. (2016): Daily temperature grids for Austria since 1961—concept, creation and applicability. Theor. Appl. Climatol., 124, 161–178 (2016). https://doi.org/10.1007/s00704-015-1411-4.
• Hiebl, J. & Frei, C. (2017): Daily precipitation grids for Austria since 1961—development and evaluation of a spatial dataset for hydroclimatic monitoring and modelling. Theor. Appl. Climatol., 132, 327–345. https://doi.org/10.1007/s00704-017-2093-x
• Hiebl, J., Bourgeois, Q., Tilg, A.-M. & Frei, C. (2024): Daily sunshine grids for Austria since 1961 – combining station and satellite observations for a multi-decadal climate-monitoring dataset. Theor. Appl. Climatol., 155, 8337–8360. https://doi.org/10.1007/s00704-024-05103-5.
• Haslinger, K. & Bartsch, A. (2016): Creating long-term gridded fields of reference evapotranspiration in Alpine terrain based on a recalibrated Hargreaves method. Hydrol. Earth Syst. Sci., 20, 1211–1223. https://doi.org/10.5194/hess-20-1211-2016.
• Chimani, B., Matulla, C., Eitzinger, J., Hiebl, J., Hofstätter, M., Kubu, G., ... & Thaler, S. (2019). Guideline zur Nutzung der OeKS15-Klimawandelsimulationen sowie der entsprechenden gegitterten Beobachtungsdatensätze. CCCA Data Centre, 450. Available at: https://ccca.ac.at/wissenstransfer/starc-impact-guideline.
• Olefs, M., Koch, R., Schöner, W., & Marke, T. (2020): Changes in Snow Depth, Snow Cover Duration, and Potential Snowmaking Conditions in Austria, 1961–2020—A Model Based Approach. Atmosphere, 11(12), 1330. https://doi.org/10.3390/atmos11121330.