EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Seasonal forecasts of the Saharan heat low characteristics: a multi-model assessment

Cedric Gacial Ngoungue Langue1,4, Christophe Lavaysse4,5, Mathieu Vrac2, Philippe Peyrillé3, and Cyrille Flamant1
Cedric Gacial Ngoungue Langue et al.
  • 1Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS) – UMR 8190 CNRS–Sorbonne Université–UVSQ, 78280 Guyancourt, France
  • 2Laboratoire des Sciences du Climat et de l'Environnement, CEA Paris-Saclay l'Orme des Merisiers, UMR 8212 CEA–CNRS–UVSQ, Université Paris-Saclay & IPSL, 91191 Gif-sur-Yvette, France
  • 3Centre National de Recherches Météorologiques (CNRM) – Université de Toulouse, Météo-France, CNRS, 31057 Toulouse CEDEX 1, France
  • 4Université Grenoble Alpes, CNRS, IRD, G-INP, IGE, 38000 Grenoble, France
  • 5European Commission, Joint Research Centre (JRC), 21027 Ispra, VA, Italy

The Saharan heat low (SHL) is a key component of the West African Monsoon system at the synoptic scale and a driver of summertime precipitation over the Sahel region. Therefore, accurate seasonal precipitation forecasts rely in part on a proper representation of the SHL characteristics in seasonal forecast models. This is investigated using the latest versions of two seasonal forecast systems namely the SEAS5 and MF7 systems from the European Center of Medium-Range Weather Forecasts (ECMWF) and Météo-France respectively. The SHL characteristics in the seasonal forecast models are assessed based on a comparison with the fifth ECMWF Reanalysis (ERA5) for the period 1993–2016. The analysis of the modes of variability shows that the seasonal forecast models have issues with the timing and the intensity of the SHL pulsations when compared to ERA5. SEAS5 and MF7 show a cool bias centered on the Sahara and a warm bias located in the eastern part of the Sahara respectively. Both models tend to underestimate the interannual variability in the SHL. Large discrepancies are found in the representation of extreme SHL events in the seasonal forecast models. These results are not linked to our choice of ERA5 as a reference, for we show robust coherence and high correlation between ERA5 and the Modern-Era Retrospective analysis for Research and Applications (MERRA). The use of statistical bias correction methods significantly reduces the bias in the seasonal forecast models and improves the yearly distribution of the SHL and the forecast scores. The results highlight the capacity of the models to represent the intraseasonal pulsations (the so-called east–west phases) of the SHL. We notice an overestimation of the occurrence of the SHL east phases in the models (SEAS5, MF7), while the SHL west phases are much better represented in MF7. In spite of an improvement in prediction score, the SHL-related forecast skills of the seasonal forecast models remain weak for specific variations for lead times beyond 1 month, requiring some adaptations. Moreover, the models show predictive skills at an intraseasonal timescale for shorter lead times.

How to cite: Ngoungue Langue, C. G., Lavaysse, C., Vrac, M., Peyrillé, P., and Flamant, C.: Seasonal forecasts of the Saharan heat low characteristics: a multi-model assessment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13503,, 2022.

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