Atmospheric Sciences Research Spotlight

How Sea Surface Temperatures Affect an Atmospheric Phenomenon

New research sheds light on the complex interplay between the atmosphere and the ocean and how both affect the Madden-Julian Oscillation.

Source: Journal of Geophysical Research: Atmospheres


Tropical disturbances affect growing seasons across Asia, monsoons in India and West Africa, and even hurricanes and floods in the United States. Unlike the relatively stationary El Niño–Southern Oscillation, the so-called Madden-Julian Oscillation (MJO) travels eastward around the globe at roughly 5 meters per second every 30–60 days. Despite the MJO’s importance, global models often struggle to simulate it accurately.

Most models point to the central role of column moisture in regulating the MJO’s observed characteristics. Specifically, column moisture builds up prior to the oscillation’s development, and then, once it’s fully established, column moistening to the east and drying to the west cause the disturbance to propagate eastward. Still, atmosphere-only models alone can’t perfectly simulate the MJO. Models that couple the atmosphere to the ocean are an improvement over atmosphere-only models, but the effects of air-sea coupling aren’t consistent across models: They can accelerate or slow the MJO’s propagation speed and encourage eastward propagation in cases where movement is weak or nonexistent.

At the root of this interplay are variations in sea surface temperature (SST)—a function of atmospheric fluxes of heat and momentum and the ocean’s response to those fluxes. These variations influence the atmosphere, in turn, through a variety of processes, but assessing which feedbacks are most important to the MJO is difficult. Here DeMott et al. set out to measure the effects of SST variations within the MJO life cycle to better understand the processes through which the ocean affects the MJO.

The researchers used data from the European Centre for Medium-Range Weather Forecasts Interim Reanalysis, a synthesis of observations supplemented with model forecasts to produce up-to-date global estimates of surface and upper air temperature, winds, and humidity. These data allowed the researchers to quantify the effect of SST variations on surface fluxes throughout the MJO for a period spanning 1986–2013. The team then analyzed the SST regulation of the surface fluxes to see how it affected column moisture and MJO propagation.

Previous research has shown that wind-driven surface fluxes in the vicinity of MJO convection can directly energize and moisten the atmosphere, providing a positive feedback to maintain MJO convection. However, this research discovered that sea surface temperature variations actually reduce wind-driven fluxes and that SSTs can have varying effects on the MJO at different locations.

Along the equator, SST perturbations directly preserved MJO convection, but away from the equator, SST variations weaken convection. This effect is thought to improve MJO propagation, which is also aided by warm SSTs east of MJO convection.

The current study looked only at how fluctuations in the SST directly influence the tropical disturbance’s journey around the globe. Future research is needed to determine how other SST-related processes affect the phenomenon. (Journal of Geophysical Research: Atmospheres, doi:10.1002/2016JD025098, 2016)

—Shannon Hall, Freelance Writer

Citation: Hall, S. (2016), How sea surface temperatures affect an atmospheric phenomenon, Eos, 97, doi:10.1029/2016EO057821. Published on 23 August 2016.
© 2016. The authors. CC BY-NC-ND 3.0
  • davidlaing

    This study rather eloquently points out the futility of relying on static models to give us an accurate picture of what is actually going on in Earth systems, particularly atmospheric ones. In aqueous chemistry, we learned quite a while ago that kinetic calculations were a lot more reliable than equilibrium calculations. A similar epiphany applies to atmospherics. We need to get over our infatuation with models (i.e., what we think is going on) and to rely instead on accurate measurements of the system of interest to see what is happening in the real world.