2026-07-07T02:06:58Z https://researchdata.tuwien.ac.at/oai2d

oai:researchdata.tuwien.ac.at:8fbh2-n1291 2026-04-17T13:54:24Z openaire_data

4.3 TUW.TUDATA 10.48436/8fbh2-n1291 oai:researchdata.tuwien.ac.at:8fbh2-n1291 Benesch, Claudia Claudia Benesch TU Wien TU Wien 2026 2026-04-16 2026-04-17 10.48436/nq3gx-fgn49 Creative Commons Attribution Non Commercial Share Alike 4.0 International Climate Exposure Maps and Distributions of Austrian Power Grid Overhead Lines The data contains figures (jpg data format) displaying the maps and cumulative curves of overhead line length vs. 41 climate indicators Context and methodology Climate indicator data were taken from the ROBINE dataset  Power grid topology was taken from OpenStreetMap (extraction date 04/03/2026) Figures were created in Python using libraries like osmnx, rasterio, geopandas, matploblib etc. Technical details Both "absolute" and "relative" figures are shown: "absolute" refers to global warming levels (GWL) 1,2,3,4 shown relative to the pre-industrial reference period "relative" refers to GWL-2,3,4 relative to GWL-1 (2001 - 2020, historical period)  "Distributions" and "images" are shown: The naming for distributions contains: indicator number and indicator name "all" referring to figures containing both high- and low-voltage grid lines "cumulative" referring to the fact that cumulative distributions were generated The naming for "images" contains: "combined" to indicate that plot for different GWLs were combined into one plot indicator name "all" referring to figures containing both high- and low-voltage grid lines Scientific paper is in the making Results The results show that exposure of overhead lines to weather phenomena like wet snowfall is expected to decrease, while it is going to stagnate or increase only slightly for extreme storm days and wind gusts. In contrast, the risk due to heavy precipitation, thunderstorms and heat is expected to increase significantly. Further details Not all climate indicators are relevant for power grid overhead lines, as the underlying climate dataset was developed for a wide range of energy infrastructure components. Austrian Research Promotion Agency 028jc0449 FO999905703 Infradapt