Weakening of the Atlantic Niño variability under global warming

The Atlantic Niño is one of the most important tropical patterns of interannual climate variability, with major regional and global impacts. How global warming will influence the Atlantic Niño has been hardly explored, because of large climate model errors. We show for the first time that the state-of-the-art climate models robustly predict that equatorial Atlantic Niño variability will weaken in response to global warming. This is primarily because subsurface and surface temperature variations decouple as the upper equatorial Atlantic Ocean warms. The weakening is predicted by most (>80%) models following the highest emission scenarios in the Coupled Model Intercomparison Project Phases 5 and 6 considered here. These indicate a reduction in variability by the end of the century of 12-17%, and as much as 25% when accounting for model errors. Weaker Atlantic Niño variability will have major consequences for global climate and the skill of seasonal predictions.

Indian Ocean Dipole leads to Atlantic Niño

Atlantic Niño is the Atlantic equivalent of El Niño-Southern Oscillation (ENSO), and it has prominent impacts on regional and global climate. Existing studies suggest that the Atlantic Niño may arise from local atmosphere-ocean interaction and is sometimes triggered by the Atlantic Meridional Mode (AMM), with overall weak ENSO contribution. By analyzing observational datasets and performing numerical model experiments, here we show that the Atlantic Niño can be induced by the Indian Ocean Dipole (IOD). We find that the enhanced rainfall in the western tropical Indian Ocean during positive IOD weakens the easterly trade winds over the tropical Atlantic, causing warm anomalies in the central and eastern equatorial Atlantic basin and therefore triggering the Atlantic Niño. Our finding suggests that the cross-basin impact from the tropical Indian Ocean plays a more important role in affecting interannual climate variability than previously thought.

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

The Guinea Coast is the southern part of the West African continent. Its summer rainfall variability mostly occurs on interannual timescales and is highly influenced by the sea surface temperature (SST) variability in the eastern equatorial Atlantic, which is known as the Atlantic Niño (ATL3). Using historical simulations from 31 General Circulation Models (GCMs) participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we first show that these models are able to simulate reasonably well the rainfall annual cycle in the Guinea Coast, with, however, a wet bias during boreal summer. This bias is associated with too high mean summer SSTs in the eastern equatorial and south Atlantic regions. Next, we analyze the near-term, mid-term and long-term changes of the Atlantic Niño mode relative to the present-day situation, in a climate with a high anthropogenic emission of greenhouse gases. We find a gradual decrease of the equatorial Atlantic SST anomalies associated with the Atlantic Niño in the three periods of the future. This result reflects a possible reduction of the Atlantic Niño variability in the future due to a weakening of the Bjerkness feedback over the equatorial Atlantic. In a warmer climate, an oceanic extension of the Saharan Heat Low over the North Atlantic and an anomalous higher sea level pressure in the western equatorial Atlantic relative to the eastern equatorial Atlantic weaken the climatological trade winds over the equatorial Atlantic. As a result, the eastern equatorial Atlantic thermocline is deeper and responds less to Atlantic Niño events. Among the models that simulate a realistic rainfall pattern associated with ATL3 in the present-day climate, there are 15 GCMs which project a decrease of the Guinean Coast rainfall response related to ATL3, and 9 GCMs which show no substantial change in the patterns associated with ATL3. In these 15 models, the zonal wind response to the ATL3 over the equatorial Atlantic is strongly attenuated in the future climate. Similar results are found when the analysis is focused on the rainfall response to ATL3 over the equatorial Atlantic. There is a higher confidence in the reduction of the rainfall associated with ATL3 over the Atlantic Ocean than over the Guinea Coast. We also found a decrease of the convection associated with ATL3 in the majority of the models.

Atlantic Niño/Niña Prediction Skills in NMME Models

The Atlantic Niño/Niña, one of the dominant interannual variability in the equatorial Atlantic, exerts prominent influence on the Earth’s climate, but its prediction skill shown previously was unsatisfactory and limited to two to three months. By diagnosing the recently released North American Multimodel Ensemble (NMME) models, we find that the Atlantic Niño/Niña prediction skills are improved, with the multi-model ensemble (MME) reaching five months. The prediction skills are season-dependent. Specifically, they show a marked dip in boreal spring, suggesting that the Atlantic Niño/Niña prediction suffers a “spring predictability barrier” like ENSO. The prediction skill is higher for Atlantic Niña than for Atlantic Niño, and better in the developing phase than in the decaying phase. The amplitude bias of the Atlantic Niño/Niña is primarily attributed to the amplitude bias in the annual cycle of the equatorial sea surface temperature (SST). The anomaly correlation coefficient scores of the Atlantic Niño/Niña, to a large extent, depend on the prediction skill of the Niño3.4 index in the preceding boreal winter, implying that the precedent ENSO may greatly affect the development of Atlantic Niño/Niña in the following boreal summer.

Diabatic heating governs the seasonality of the Atlantic Niño

The Atlantic Niño is the leading mode of interannual sea-surface temperature (SST) variability in the equatorial Atlantic and assumed to be largely governed by coupled ocean-atmosphere dynamics described by the Bjerknes-feedback loop. However, the role of the atmospheric diabatic heating, which can be either an indicator of the atmosphere’s response to, or its influence on the SST, is poorly understood. Here, using satellite-era observations from 1982–2015, we show that diabatic heating variability associated with the seasonal migration of the Inter-Tropical Convergence Zone controls the seasonality of the Atlantic Niño. The variability in precipitation, a measure of vertically integrated diabatic heating, leads that in SST, whereas the atmospheric response to SST variability is relatively weak. Our findings imply that the oceanic impact on the atmosphere is smaller than previously thought, questioning the relevance of the classical Bjerknes-feedback loop for the Atlantic Niño and limiting climate predictability over the equatorial Atlantic sector.

Relating model bias and prediction skill in the equatorial Atlantic

We investigate the impact of large climatological biases in the tropical Atlantic on reanalysis and seasonal prediction performance using the Norwegian Climate Prediction Model (NorCPM) in a standard and an anomaly coupled configuration. Anomaly coupling corrects the climatological surface wind and sea surface temperature (SST) fields exchanged between oceanic and atmospheric models, and thereby significantly reduces the climatological model biases of precipitation and SST. NorCPM combines the Norwegian Earth system model with the ensemble Kalman filter and assimilates SST and hydrographic profiles. We perform a reanalysis for the period 1980–2010 and a set of seasonal predictions for the period 1985–2010 with both model configurations. Anomaly coupling improves the accuracy and the reliability of the reanalysis in the tropical Atlantic, because the corrected model enables a dynamical reconstruction that satisfies better the observations and their uncertainty. Anomaly coupling also enhances seasonal prediction skill in the equatorial Atlantic to the level of the best models of the North American multi-model ensemble, while the standard model is among the worst. However, anomaly coupling slightly damps the amplitude of Atlantic Niño and Niña events. The skill enhancements achieved by anomaly coupling are largest for forecast started from August and February. There is strong spring predictability barrier, with little skill in predicting conditions in June. The anomaly coupled system show some skill in predicting the secondary Atlantic Niño-II SST variability that peaks in November–December from August 1st.