go through: Salim Bawadiyir
Weather and climate model data play an increasingly important role in assessing climate risks in energy system operations and planning. The reliability of these assessments depends heavily on the quality of the input meteorological data, particularly in terms of accurately representing extreme events that challenge energy system resilience.
Climate models offer one of the most significant advantages in modern energy planning – the ability to generate large data samples. These samples are critical for understanding long-term natural variations, such as interannual and decadal fluctuations, and for describing rare but impactful extreme weather events. As renewables become a cornerstone of Europe's energy mix, understanding how climate change affects high-impact weather events is critical to ensuring the resilience of power systems.
Rare events like low-probability, high-impact weather phenomena are notoriously difficult to capture using observational or reanalysis-based data sets. This is mainly due to the relatively short period of historical record, spanning decades to decades at most, depending on the chosen dataset (Bloomfield et al., 2018; Kay et al., 2023; Wohland et al., 2019 ). In contrast, the output of climate models can be used to perform powerful simulations of climate conditions in the “near” and “future decades”, covering hundreds of relevant weather years. This may provide a richer data set to examine the characteristics of rare and extreme conditions, but model performance will need to be carefully evaluated to ensure relevant meteorology is well represented.
An ongoing project at the university readIn partnership with the Electric Power Research Institute (EPRI), Aims to examine the quality of “energy” data generated using climate model output provided on the Copernicus Climate Change Service (C3S). There, European wind and solar generation and demand were estimated at a national scale based on high-resolution EURO-CORDEX regional climate model outputs. These data include projections under multiple greenhouse gas emission scenarios, providing insights consistent with European energy measures such as the ENTSO pan-European climate repository (Bartok et al., 2019; Dubus et al., 2023).
We analyzed the representation of Dunkelflaute events (periods of calm and cloudy weather typically associated with increased supply stress) in Europe using wind and solar capacity factors from two customized climate products: the recent “C3S-Energy” data set and its One of the predecessors is ECEM. We examined the representation of these events in model-derived energy datasets.
Our preliminary The results reveal significant differences in the way Dunkelflaute events are represented in the C3S-Energy and ECEM datasets. In particular, although the overall seasonal evolution of dark wind occurrence appears to be well represented (compared to the respective reanalyses), there are significant differences in winter dark wind frequency in many parts of Europe, with climate models generally simulating dark winds in northern regions Less frequently. These findings highlight the importance of careful interpretation when utilizing energy datasets derived from climate models. While these datasets provide unprecedented opportunities to explore climate risks in energy systems, careful validation and contextual understanding are necessary to ensure their effective application.
Figure 1: Percent difference in Dunkelflaute events (lasting at least 2 consecutive days or more) between C3S and ECEM datasets derived from EURO-CORDEX regional climate models (original GCMs: CNRM, EC-Earth, MPI and IPSL). The percentage difference is calculated as (GCM – reference reanalysis data), where ERA5 is the reference for C3S and ERA-Interim is the reference for ECEM.
Conclusion: Opportunities and Warnings
Integrating data sets such as ECEM and C3S-Energy into energy system planning is a transformative step in addressing climate risks. By leveraging high-resolution climate model outputs tailored for the energy sector, stakeholders can better prepare for renewable energy droughts and other climate-induced challenges. However, the observed differences in the representation of Dunkel Flute events highlight the need for continued climate model improvement and rigorous validation with real-world data.
As the energy industry continues its transition to renewable energy, these tools remain indispensable. However, their utility must be complemented by continued research, collaboration, and a commitment to improving the models that underpin our understanding of climate risks.
refer to
Bartok, B. et al. (2019). A climate prediction dataset tailored for the European energy sector. climate services. 16, p. 100138.
Bloomfield, H. et al. (2018). Long-term changes in winter surface Arctic Oscillation and Northern Hemisphere storms are rigorously assessed in the ERA20C reanalysis. Environmental Research Letters. 13.9, pp. 094004.
Dubus, L. et al. (2023). C3S Energy: Provides climate services for electricity supply and demand indicators in Europe based on ERA5 reanalysis and ENTSO-E data. Meteorological applications. 30.5, e2145.
Kay, G. et al. (2023). Changes in North Sea wind energy and the potential for long-term winter monsoon drought. Atmospheric Science Letters, e1158.
Wallander, J. et al. (2019). Wind speed trends in current twentieth-century reanalyses are inconsistent. Journal of Geophysical Research: Atmospheres. 124.4, pp. 1931-1940.
