The Global Energy Balance Archive (GEBA) is a database for the central storage of the worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 dataset, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and contains in its 2017 version around 500 000 monthly mean entries of various surface energy balance components measured at 2500 locations. The database contains observations from 15 surface energy flux components, with the most widely measured quantity available in GEBA being the shortwave radiation incident at the Earth's surface (global radiation). Many of the historic records extend over several decades. GEBA contains monthly data from a variety of sources, namely from the World Radiation Data Centre (WRDC) in St. Petersburg, from national weather services, from different research networks (BSRN, ARM, SURFRAD), from peer-reviewed publications, project and data reports, and from personal communications. Quality checks are applied to test for gross errors in the dataset. GEBA has played a key role in various research applications, such as in the quantification of the global energy balance, in the discussion of the anomalous atmospheric shortwave absorption, and in the detection of multi-decadal variations in global radiation, known as global dimming and brightening. GEBA is further extensively used for the evaluation of climate models and satellite-derived surface flux products. On a more applied level, GEBA provides the basis for engineering applications in the context of solar power generation, water management, agricultural production and tourism. GEBA is publicly accessible through the internet via http://www.geba.ethz.ch. Supplementary data are available at https://doi.org/10.1594/PANGAEA.873078.

Solar photovoltaics (PV) plays an essential role in decarbonizing the European energy system. However, climate change affects surface solar radiation and will therefore directly influence future PV power generation. We use scenarios from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for a mitigation (SSP1-2.6) and a fossil-fuel-dependent (SSP5-8.5) pathway in order to quantify climate risk for solar PV in Europe as simulated by the Global Solar Energy Estimator (GSEE). We find that PV potential increases by around 5 % in the mitigation scenario, suggesting a positive feedback loop between climate change mitigation and PV potential. While increased clear-sky radiation and reduced cloud cover go hand in hand in SSP1-2.6, the effect of a decrease in clear-sky radiation is outweighed by a decrease in cloud cover in SSP5-8.5, resulting in an increase in all-sky radiation. Moreover, we find that the seasonal cycle of PV generation changes in most places, as generation grows more strongly in winter than in summer (SSP1-2.6) or increases in summer and declines in winter (SSP5-8.5). We further analyze climate change impacts on the spatial variability of PV power generation. Similar to the effects anticipated for wind energy, we report an increase in the spatial correlations of daily PV production with large inter-model agreement yet relatively small amplitude, implying that PV power balancing between different regions in continental Europe will become more difficult in the future. Thus, based on the most recent climate simulations, this research supports the notion that climate change will only marginally impact renewable energy potential, while changes in the spatiotemporal generation structure are to be expected and should be included in power system design.

Near-surface winds affect many processes on planet Earth, ranging from fundamental biological mechanisms such as pollination to man-made infrastructure that is designed to resist or harness wind. The observed systematic wind speed decline up to around 2010 (stilling) and its subsequent recovery have therefore attracted much attention. While this sequence of downward and upwards trends and good connections to well-established modes of climate variability suggest that stilling could be a manifestation of multidecadal climate variability, a systematic investigation is currently lacking. Here, we use the Max Planck Institute Grand Ensemble (MPI-GE) to decompose internal variability from forced changes in wind speeds. We report that wind speed changes resembling observed stilling and its recovery are well in line with internal climate variability, both under current and future climate conditions. Moreover, internal climate variability outweighs forced changes in wind speeds on 20-year timescales by 1 order of magnitude, despite the fact that smaller, forced changes become relevant in the long run as they represent alterations of mean states. In this regard, we reveal that land use change plays a pivotal role in explaining MPI-GE ensemble-mean wind changes in the representative concentration pathways 2.6, 4.5, and 8.5. Our results demonstrate that multidecadal wind speed variability is of greater relevance than forced changes over the 21st century, in particular for wind-related infrastructure like wind energy.