Collaborative Research: Assessing Oceanic Predictability Sources for MJO Propagation

“The body of evidence from decades of work suggests a paradigm of the Madden Julian Oscillation (MJO) as a primarily atmospheric disturbance whose initiation, maintenance, and propagation characteristics may be flavored by surface turbulent fluxes that are modulated by sea surface temperature (SST) variations. The longer-than-synoptic timescale of the MJO and its impact on a variety of high-impact global weather phenomena implies an opportunity to increase global weather prediction skill if the MJO can be reliably predicted. Impediments to MJO predictions include 1) poor predictions of whether a given convective event will propagate from the Indian Ocean to the West Pacific Ocean, where the global teleconnection response is strongest; and 2) a lack of understanding of the processes that initiate MJO convection. The onset of MJO convection can be preceded by a variety of atmospheric precursor signals whose individual expressions can vary from event to event, and can influence prediction skill. Once the MJO initiates, forecast skill tends to be highest for high amplitude events. Both climate and forecast simulations of the MJO are improved in coupled atmosphere–ocean models, suggesting a source of predictability from ocean feedbacks. Leveraging these potential sources of predictability for MJO forecasts remains challenging in light of low amplitude or decaying MJO events, and the variable influence of ocean feedbacks on MJO development. These prediction challenges are rooted in our limited understanding of key underlying physical processes involving MJO evolution and ocean–atmosphere interactions.

To improve our understanding, we propose a multi-pronged approach based on separating observed MJO events into three classes: strong, weak, and “eastward-decaying” (i.e., those that terminate before crossing the Maritime Continent). Factors that differentiate these classes of MJO events and their predictability will be explored as follows:
1. The Subseasonal-to-Seasonal (S2S) database will be used to analyze the predictability of and prediction skill for the three MJO classes, focusing on atmospheric and oceanic precursor signals. Ocean reanalysis data will provide additional context.
2. Specific ocean feedback processes will be tested in hindcast simulations using coupled models with a demonstrated ability to simulate the MJO. Particular attention will be given to MJO events associated with high-impact weather.
3. An ad hoc set of air-sea interaction diagnostics currently being developed in conjunction with WCRP S2S and WGNE MJO Task Force members (and others) for climate simulations will be expanded for application to hindcast simulations.

The proposed work is relevant to MAPP Competition 2 because:
1) it will improve the understanding of MJO predictability,
2) it has the potential to advance predictions of subseasonal and seasonal phenomena,
3) it uses existing (S2S database) and new model experiments to explore how the MJO is influenced by coupling between Earth system components (ocean–atmosphere),
4) it addresses predictability in the context of key underlying physical processes,
5) it actively seeks collaborative activities with WCRP S2S and WGNE MJO Task Force scientists to deliver a set of MJO air–sea interaction diagnostics.

This research will advance core capabilities in 1) understanding and modeling and 2) predictions and projections. It addresses NOAA’s long-term climate goals for “improved scientific understanding of the changing climate system” and “assessment of current and future states of the climate system that identify potential impacts and inform science.””