Fringer
Oliver B.
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The formation and fate of internal waves in the South China Sea
Fringer
Oliver B.
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Preprint
Internal gravity waves, the subsurface analogue of the familiar surface gravity
waves that break on beaches, are ubiquitous in the ocean. Because of their strong vertical and horizontal currents, and the turbulent mixing caused by their
breaking, they impact a panoply of ocean processes, such as the supply of nutrients
for photosynthesis1, sediment and pollutant transport2 and acoustic transmission3;
they also pose hazards for manmade structures in the ocean4. Generated primarily
by the wind and the tides, internal waves can travel thousands of kilometres from
their sources before breaking5, posing severe challenges for their observation and
their inclusion in numerical climate models, which are sensitive to their effects6-7.
Over a decade of studies8-11 have targeted the South China Sea, where the oceans’
most powerful internal waves are generated in the Luzon Strait and steepen
dramatically as they propagate west. Confusion has persisted regarding their
generation mechanism, variability and energy budget, however, due to the lack of
in-situ data from the Luzon Strait, where extreme flow conditions make
measurements challenging. Here we employ new observations and numerical
models to (i) show that the waves begin as sinusoidal disturbances rather than
from sharp hydraulic phenomena, (ii) reveal the existence of >200-m-high
breaking internal waves in the generation region that give rise to turbulence levels
>10,000 times that in the open ocean, (iii) determine that the Kuroshio western
boundary current significantly refracts the internal wave field emanating from the
Luzon Strait, and (iv) demonstrate a factor-of-two agreement between modelled
and observed energy fluxes that enables the first observationally-supported energy
budget of the region. Together, these findings give a cradle-to-grave picture of
internal waves on a basin scale, which will support further improvements of their
representation in numerical climate predictions.