ARiSE

The El Niño Southern Oscillation (ENSO) is the leading mode of interannual climate variability on earth. It consists of irregular, alternating phases of warm (El Niño) or cold (La Niña) Sea Surface Temperature (SST) anomalies in the tropical Pacific Ocean, but has global climate impacts through atmospheric teleconnections. It is predictable 2-3 seasons in advance, so ENSO is also a major source of global seasonal climate predictability. State-of-the-art ENSO forecasts however have not performed well for “extreme” El Niño events such as those in 1982-83, 1997-98 or 2015-2016. With climate projections suggesting that such extreme events may become more frequent, it is vital to improve our understanding of the processes involved in these ENSO events. ENSO grows through the Bjerknes feedback, a positive feedback loop between the ocean and the atmosphere. In this feedback loop, an SST anomaly induces deep atmospheric convection. The resulting changes in surface wind drive an ocean response that strengthens the initial SST anomaly, allowing ENSO events to grow. While the oceanic component of this feedback loop is well understood, there are far fewer studies of its atmospheric component. Yet, the atmospheric component of the Bjerknes feedback exhibits strong non-linearities which have been recently suggested to play a key role in extreme El Niño events. Deep convection indeed only occurs for SSTs above ~27.5°C, implying that the atmosphere will be more responsive to SST fluctuations in the warm western Pacific than in the colder eastern Pacific. The conceptual models used to understand ENSO do not account for this non-linearity, or for other potentially-important sources of atmospheric non-linearities such as heat flux feedbacks. Additionally, the capacity of Coupled General Circulation models (CGCMs) used for ENSO research and forecasting to reproduce the non-linear atmospheric response to ENSO SST anomalies has not been systematically evaluated so far. Previous work suggests that this non-linearity likely plays a key role in linking the models’ systematic biases to their documented underestimation of the Bjerknes feedback. Developing tools to quantify, understand and model the non-linear wind response to ENSO SST anomalies is thus a vital prerequisite to a) understanding extreme El Niño mechanisms and b) being able to diagnose the source of ENSO biases in CGCMs. ARiSE proposes to use observational analyses and a hierarchy of atmospheric and coupled models (from conceptual to general circulation models) to better describe the non-linear atmospheric response to ENSO and its impact on ENSO properties, and in particular extreme El Niño events. In Work Package (WP) 1, we will use observations and two types of atmospheric GCMs to produce a seasonally-dependent transfer function between SST and wind stress variations, and explore its non-linearity. In WP2, we will develop the simplest possible atmospheric model that encapsulates essential dynamical and thermodynamical non-linearities for ENSO, and investigate their impact on ENSO, in an intermediate and a conceptual model. In WP3, we will use the results from the previous WPs to improve our understanding of ENSO in CGCMS: a) we will diagnose the specific mechanisms of extreme El Niños in a CGCM; b) we will evaluate links between atmospheric non-linearities and ENSO biases in the CMIP database. This will provide tools for improving ENSO representation in state-of-the-art CGCMs used in forecast mode. The current project gathers a unique blend of oceanographers and atmospheric scientists with good expertise in ENSO, including developers of some models used in the project. This project also benefits from the support of several renowned international collaborators on their own funds. ARiSE is a unique opportunity to make a step change in our understanding of tropical air-sea interactions, the role of the atmosphere in extreme El Niños with potentially large societal impacts.