Advances in the Lead Time of Sahel Rainfall Prediction With the North American Multimodel Ensemble

• Published in: Geophysical Research Letters
• Main Authors: Giannini, Alessandra, Ali, A., Kelley, C, Lamptey, B, Minoungou, B, Ndiaye, O
• Other Authors: Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Centre Régional AGRHYMET (CRA), Columbia University New York, School of Earth and Environment Leeds (SEE), University of Leeds
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2020
• Subjects: [SDE]Environmental Sciences; North Atlantic
• Online Access: https://hal.sorbonne-universite.fr/hal-02879922; https://hal.sorbonne-universite.fr/hal-02879922/document; https://hal.sorbonne-universite.fr/hal-02879922/file/short-nmme-paper_hal%2BSI.pdf; https://doi.org/10.1029/2020GL087341

International audience We assess the deterministic skill in seasonal climate predictions of Sahel rainfall made with the North American Multimodel Ensemble (NMME). We find that skill for a regionally averaged rainfall index is essentially the same for forecasts for the July–September target season made as early as February/March and as late as June. The two dominant influences on the climate of the Sahel, the North Atlantic and the global tropical oceans, shape this predictability. Multimodel ensemble skill hinges on the combination of skillful predictions of the El Niño–Southern Oscillation made with one model (CMC2‐CanCM4) with those of North Atlantic sea surface temperatures made with another (NASA‐GEOSS2S).