Weakened impact of the Atlantic Niño on the future equatorial Atlantic and Guinea Coast rainfall

Worou, Koffi; Goosse, Hugues; Fichefet, Thierry; Kucharski, Fred

doi:10.5194/esd-13-231-2022

Cited by 10 publications

(26 citation statements)

References 67 publications

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“…The enhanced low-level convergence over the warm oceanic area is accompanied by an ascent of moist air, which is then advected by the low-level circulation towards the Guinea Coast. This provides favourable conditions for the rainfall occurrence over this region (Polo et al, 2008;Rodríguez-Fonseca et al, 2015;Schubert et al, 2016;Lübbecke et al, 2018;Worou et al, 2020Worou et al, , 2022. Over the 1901-2016 period, the eastern equatorial Atlantic positive correlation with the rainfall over the Guinea Coast was stationary during the boreal summer (Losada et al, 2012;Diatta and Fink, 2014;Worou et al, 2020).…”

Section: Introductionmentioning

confidence: 90%

“…The changes of the equatorial Atlantic mean state under the highest greenhouse gas emission scenario (SSP5-8.5) lead to a weakened variability of the AEM in the future (Worou et al, 2022;Crespo et al, 2022;Yang et al, 2022). Worou et al (2022) showed a projected weakening of the trade winds climatology over the equatorial Atlantic and a deeper thermocline in the 365 eastern equatorial Atlantic which would lead to a reduction of the coupling between the surface and the thermocline depth.…”

Section: (A)(g))mentioning

confidence: 99%

“…Crespo et al (2022) demonstrated that the models with the strongest warm sea surface biases exhibit the weakest change in both the AEM variability and the third component of the Bjerknes feedback. Given the positive SST biases in most of the CMIP6 models in the eastern Atlantic basin (Richter and Tokinaga, 2020;Worou et al, 2022;Crespo et al, 2022), improving these biases would likely increase the change in the AEM variability, suggesting that the projected weakened AEM variability is robust despite these biases. Moreover, despite the increase in the total variability of the majority of the extreme indices under global warming in the future (Section 3.2), there is a reduction of the proportion of variance explained by the AEM for these extreme indices.…”

Section: (A)(g))mentioning

confidence: 99%

“…They underlined a greater role of a more stable tropical Atlantic atmosphere background in a future warmer climate(Jia et al, 2019), in reducing the AEM variability, compared to the weakening associated with the deepening of the eastern equatorial Atlantic thermocline. Subsequently, the variability of the JAS rainfall over the equatorial Atlantic and Guinea Coast that is related to the different phases of AEM is reduced(Worou et al, 2022).Figure 7(g) shows a clear decrease in the variability of the total wet-day precipitation averaged over the Guinea Coast, which is associated with one standard deviation of the AEM in the near-term, mid-term and long-term future periods, compared to the present-day situation. This result is in accordance with Worou et al (2022).…”

mentioning

confidence: 92%

“…This highlights the importance of the AEM in driving part of the rainfall variability in the coastal Guinea. Nevertheless, the variability of the AEM is projected to decrease under future global warming (Worou et al, 2022;Crespo et al, 2022;Yang et al, 2022). This would reduce the Guinea Coast rainfall variability associated with one standard deviation of the AEM.…”

Section: Introductionmentioning

confidence: 99%

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Future changes in the mean and variability of extreme rainfall indices over the Guinea Coast and role of the Atlantic equatorial mode

Worou

Fichefet

Goosse

2022

Preprint

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Abstract. The occurrence of climate extremes could have dramatic impacts on various sectors such as agriculture, water supply, and energy production. Over the last decades, less frequent and more intense rainfalls have been observed in the coastal areas of West Africa (the Guinea Coast). Part of this variability in the extreme rainfalls can be related to the Atlantic equatorial mode (AEM) whose positive phases are associated with an enhancement of the mean rainfall over the Guinea Coast and an increase in the intensity and frequency of rainfall events. The climate models that participate in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) simulate reasonably well the rainfall extremes over the Guinea Coast and West Africa. However, less attention has been paid to the evaluation of the modelled rainfall extremes associated with the AEM under different climate conditions, while the variability of the AEM is expected to decrease in the future. Here, we use historical and SSP5-8.5 simulations from 24 models that contributed to CMIP6 to investigate the near-term, mid-term and long-term future links between the AEM and the extreme rainfall events over the Guinea Coast. The extreme rainfall responses to the AEM are reasonably well represented over the 1995–2014 period, although there are substantial biases in their magnitudes. Future changes indicate an increase in the mean and variability of the majority of the extreme indices over the Guinea Coast. The average across the 12 indices of their percentage of long-term changes in mean and variability equals to +10.46 % and +16.44 %, respectively. By contrast, the decreased variability of the AEM in a warmer climate leads to a reduced magnitude of the rainfall extreme responses associated to AEM over the Guinea Coast. The multi-model median values of the long-term changes in the variance explained by the AEM for the different extreme indices range between −8.25 % and −64.97 %. As a consequence, while in absolute there is a projected increase in the variability of most of the extreme rainfall indices, the contribution of the AEM to this variability weakens in a warmer future climate.

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Section: Introductionmentioning

confidence: 90%

Section: (A)(g))mentioning

confidence: 99%

Section: (A)(g))mentioning

confidence: 99%

mentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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Future changes in the mean and variability of extreme rainfall indices over the Guinea Coast and role of the Atlantic equatorial mode

Worou

Fichefet

Goosse

2022

Preprint

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Uncertainty on Atlantic Niño Variability Projections

Prigent,

Imbol Koungue,

Imbol Nkwinkwa

et al. 2023

Geophysical Research Letters

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Sources of uncertainty (i.e., internal variability, model and scenario) in Atlantic Niño variability projections were quantified in 49 models participating in the Coupled Model Intercomparison Phases 5 (CMIP5) and 6 (CMIP6). By the end of the twenty‐first century, the ensemble mean change in Atlantic Niño variability is −0.07 ± 0.10˚C, with 80% of CMIP models projecting a decrease, and representing a 16% reduction relative to the 1981–2005 ensemble mean. Models' projections depict a large spread, with variability changes ranging from 0.23˚C to −0.50˚C. Internal variability is the main source of uncertainty until 2045 but model uncertainty dominates thereafter, eventually explaining up to 80% of the total uncertainty. The scenario uncertainty remains low (<1%) throughout the twenty‐first century. The total uncertainty on Atlantic Niño variability projections is not improved when considering only CMIP models with a realistic zonal equatorial Atlantic sea surface temperature gradient.

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The Atlantic Niño Mode: A Thermodynamic or a Dynamic Phenomenon?

Eusebi Borzelli,

Carniel,

Carniel

et al. 2024

JGR Oceans

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The Atlantic Niño is an important source of the year‐to‐year variability of the tropical Atlantic, consisting in an irregular oscillation of the Sea Surface Temperature (SST) in the eastern tropical Atlantic. The physical mechanism underlying this oscillation is topic of debate. Some theories, known as dynamical, suggest that the Atlantic Niño is driven by internal wave dynamics. Other theories, termed thermodynamic, propose that the eastern tropical Atlantic SST variability is caused by thermodynamic processes associated with heat fluxes at the ocean surface and/or heat transport by oceanic currents. Here, we examine the SST variability from 1940 to 2022 and find that it can be described in terms of two spatial modes: one in the central and the other in eastern tropical Atlantic. However, focusing on the period from 1993 to 2022, these patterns behave differently. In 1993–2009 they concur in determining the eastern tropical Atlantic SST variability, while in 2010–2022 they act in opposite direction. Therefore, we use Sea Surface Height data and heat fluxes advected by oceanic currents to explore the relative contribution of wave dynamics and heat advection to the eastern tropical Atlantic SST fluctuation. We show that, between 1993 and 2010, the eastern tropical Atlantic SST variability is mainly determined by heat advected from the south by horizontal currents, while between 2010 and 2022 it can be explained in terms of wave dynamics. This finding suggests that the two spatial patterns determining the eastern tropical Atlantic SST variability, are two distinct physical phenomena forced by different physical mechanisms.

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Weakened impact of the Atlantic Niño on the future equatorial Atlantic and Guinea Coast rainfall

Cited by 10 publications

References 67 publications

Future changes in the mean and variability of extreme rainfall indices over the Guinea Coast and role of the Atlantic equatorial mode

Future changes in the mean and variability of extreme rainfall indices over the Guinea Coast and role of the Atlantic equatorial mode

Uncertainty on Atlantic Niño Variability Projections

The Atlantic Niño Mode: A Thermodynamic or a Dynamic Phenomenon?

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