EGU2020-19710, updated on 10 May 2023
https://doi.org/10.5194/egusphere-egu2020-19710
EGU General Assembly 2020
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Understanding Sahelian rainfall skill in the NMME seasonal forecast

Veronica Martin-Gomez, Elsa Mohino, and Belén Rodriguez-Fonseca
Veronica Martin-Gomez et al.
  • Universidad Complutense de Madrid, Departamento de Física de la Tierra y Astrofísica (vero.martin.gomez@gmail.com)

Sahelian rainfall presents variability from internannual to interdecadal timescales, which is influenced by the sea surface temperature anomalies (SSTa) in different basins. At interannual times scales it has been shown that this variability depends on the SSTa over the equatorial Pacific, Atlantic and eastern Mediterranean. In this work we consider the set of models from the North American Multi-model ensemble (NMME) in order to analyze their skill in reproducing the Sahelian precipitation variability and relate it to their skill in reproducing the variability of the SSTa over the equatorial Pacific, equatorial Atlantic and eastern Mediterranean as well as their ability to simulate their teleconnections with Sahel rainfall.

Results show that the skill in predicting Sahel rainfall is low, decreases rapidly with lead time and is highly model dependent. Skill is improved for those models that are able to correctly simulate the Pacific SST - Sahel rainfall teleconnection.  Models present a good ability to reproduce the Mediterranean SST – Sahel teleconnection, and skill in Sahel rainfall prediction is more dependent on the correct prediction of the Mediterranean SST anomalies. These results suggest a path to increase skill in Sahel rainfall prediction.

How to cite: Martin-Gomez, V., Mohino, E., and Rodriguez-Fonseca, B.: Understanding Sahelian rainfall skill in the NMME seasonal forecast, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19710, https://doi.org/10.5194/egusphere-egu2020-19710, 2020.

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