ROBINE-AT: Climatological hazard indicators for a ROBust and INtegrated Energy infrastructure in AusTria

The energy sector faces constant challenges due to the anticipated green transition and the underlaying change of climate. To be able to assess potential risks during the transition towards renewable energy sources, we present ROBINE-AT, a high-resolution climatological dataset for Austria, consisting of 41 hazard maps for the Global Warming Levels 1.0 (2001-2020), 2.0, 3.0 and 4.0. The maps cover potential dangers for Austria's energy system due to various impacts, including heat and cold stress, calm and storm days, extreme precipitation and flooding, dry spells as well as lightning strike and wildfire dangers. The data is based on six downscaled and bias-adjusted climate projections of the CMIP5 and CMIP6 generation. With its range of indicators and its fine resolution of 1 km, specifically targeted for regions with complex orography like Austria, ROBINE-AT is a ready-to-apply data set for assessing risks for the energy system by combining the provided hazards with custom exposure and vulnerability.

The structure is as follows:

• Maps.zip contains one *.tif file per indicator and GWL, representing the actual data.
• Tables.zip contains a tabular format for every indicator, where one entry for every of Austria's NUTS3 regions is shown for every GWL. Tables for maximum, minimum and average NUTS3 values are available.
• Tables_percentages.zip shows similar tables, but displays the changes of the GWLs in relation to the historical GWL-1.0°C value in %. Regions, in which the historical value is zero, are set to 'nan'.
• The file indicator_number_and_unit_dicts.txt includes Python-ready dictionaries, linking the indicator numbers and units to the indicator names, which are also used as file names.
• Plots.zip contains one *.png file per indicator, visualising the difference between the values in the historical observations (GWL-1.0°C, 2001-2020) and the other GWLs.

The script used to generate the data is available under https://doi.org/10.5281/zenodo.14973624.

We also recommend complementary datasets originating in the same study:

• Climate Impact Maps:  https://doi.org/10.5281/zenodo.17063332 
• Electricity Demand and Supply Profiles: https://doi.org/10.5281/zenodo.15681180 

Funding Information: The project ROBINE is funded by the Climate and Energy Fund (KLI.EN) through the Austrian Research Promotion Agency (FFG) under project number FO999905716, as part of the Energy Research Call 2022 (Energieforschung 2022).