EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

How well in advance can we predict cold spells over France?

Naveen Goutham1, Hiba Omrani1, Omar Himych2, and Riwal Plougonven3
Naveen Goutham et al.
  • 1EDF Lab Paris-Saclay, Palaiseau, France
  • 2Université Paris-Saclay, France
  • 3Laboratoire de Météorologie Dynamique-IPSL, Ecole Polytechnique, Institut Polytechnique de Paris, ENS, PSL Research University, Sorbonne Université, CNRS, France

France is committed to achieving climate neutrality by 2050. In this respect, the heating sector, one of the largest energy-consuming sectors in France, is undergoing rapid electrification. In 2022, electricity contributed to the heating of more than 40% of French dwellings. As a result, the French electricity demand is increasingly becoming thermosensitive. Accordingly, for every 1°C drop in temperature below the threshold (i.e., 15°C) during winter, the electricity demand increases by ~2.4 GW in France. With a notable share of French nuclear reactors reaching their end of service life, several recent episodes of widespread cold spells over France have raised concerns about energy security. Hence, anticipating cold spells well in advance is increasingly becoming important for the smooth operation of the energy sector. In this regard, we assess the predictability of several recent episodes of cold spells on seasonal timescales over France using the seasonal predictions from the European Centre for Medium-Range Weather Forecasts. Additionally, we test a recently developed statistical downscaling methodology in forecasting cold spells over France, using the forecasts of upper-level fields, which are better predicted than the surface fields. On comparing the dynamical and statistical predictions, we show that the statistical predictions, relying upon the information contained in the better-predicted upper-level fields, perform significantly better than the dynamical counterparts in predicting cold spells beyond a month.

How to cite: Goutham, N., Omrani, H., Himych, O., and Plougonven, R.: How well in advance can we predict cold spells over France?, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5201,, 2023.