Accuracy of Climate Model Derived Energy-Datasets During Renewable Energy Lulls.

Weather and climate model data are increasingly used as the basis for assesing climate risk in energy system operations and planning.  The reliability of such studies is therefore heavily dependent on the quality of the input meteorological data and, in particular, the accurate representation of extreme events.

In this study, we analysed the representation of Dunkelflaute events over Europe (periods of calm and cloudy weather typically associated with increased power supply stress) using estimated national wind- and solar- capacity factors from two tailored climate products (C3S-Energy and one of its predecessors, ECEM). A particular focus was on the ability of the derived energy-variables from climate models to represent their respective reanalysis equivalents (C3S-Energy uses ERA5 as the reference, while ECEM relies on ERA-Interim).

Preliminary results suggest that there are potentially significant differences between the representation of Dunkelflaute events across the two datasets.  In particular, while the overall seasonal evolution of Dunkelflaute occurrence appears to be well represented (compared to their respective reanalyses), there are noticeable differences in winter-time Dunkelflaute frequency across many areas of Europe with the climate models typically simulating fewer Dunkelflautes in the northern part of the region and more frequent events in the south (potentially up to a ~few 10’s of percent depending on country and area). 

While the availability of datasets such as ECEM and C3S-Energy offers unprecedented opportunities for energy system experts to explore climate risk, these preliminary results nevertheless suggest that some care is required in their use.