Data for "Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6"

Supporting data for the paper "Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6" by Effenberger, Ludwig (2024), the corresponding code and documentation can be accessed on GitHub once the paper is published. The paper is currently under review, a pre-print is accessible on arXiv. CMIP6 data [1] can be downloaded from the ESGF data node [2]. Power generation for earlier years can be downloaded for the individual German TSOs [3], for later years they are available through the SMARD database [4]. Turbine data is provided by Manske et al. [5]. The reanalysis dataset used is ERA5 [6]. Turbine data is from windpowerlib [7]. [1] Wolfgang A Müller, Johann H Jungclaus, Thorsten Mauritsen, Johanna Baehr, Matthias Bittner, R Budich, Felix Bunzel, Monika Esch, Rohit Ghosh, Helmut Haak, et al. Ahigher-resolution version of the max planck institute earth system model (MPI-ESM1.2-HR). Journal of Advances in Modeling Earth Systems, 10(7):1383–1413, 2018. [2] ESGF, July 2024. URL https://esgf-metagrid.cloud.dkrz.de/search. [3] OPSD. Open power system data platform, July 2024. URL https://open-power-system-data.org/data-sources. [4] Bundesnetzagentur. Smard, July 2024. URL https://www.smard.de/en/downloadcenter/download-market-data/. [5] David Manske and Julius Schmiedt. Geo-locations and System Data of Renewable Energy Installations in Germany, July 2023. URL https://doi.org/10.5281/zenodo.8188601. [6] Hans Hersbach, Bill Bell, Paul Berrisford, Shoji Hirahara, Andr.s Hor.nyi, Joaqu.n Mu.oz-Sabater, Julien Nicolas, Carole Peubey, Raluca Radu, Dinand Schepers, et al. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730):1999–2049, 2020.