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News/Events: News Articles: September 3, 2013

A Year at Sea Studying Ocean Turbulence

Caltech glider, “Tashtego,” on the deck of the RRS James Cook following recovery from the North Atlantic. The glider had just completed a five month deployment collecting data from 804 dives to a depth of 1000m. Caltech undergraduate Madeleine Youngs (right) is seen inspecting the glider and some of the marine life that came back with it!

In early September 2013, Caltech undergraduate Madeleine Youngs pulled a bright yellow oceanic robot out of waters 500km off the coast of England to mark the end of a remarkable field program to monitor upper ocean turbulence over a full year. This project, called OSMOSIS (Ocean Surface Mixing Ocean Submesoscale Interaction Study) and involving researchers from the US and UK, was designed to monitor changes in the ocean’s mixed layer. The mixed layer extends from the surface of the ocean to a depth of tens to hundreds of meters. The combination of breaking surface waves and cooled water sinking through these depths means the mixed layer represents the limited region of the ocean in direct contact with the atmosphere. The mixed layer regulates heat storage in the surface ocean and gas exchange with the atmosphere. The mixed layer also influences ocean ecosystems by determining the depth to which phytoplankton get mixed, and consequently whether they experience sufficient light levels to grow.

To study the evolution of the mixed layer, nine ocean moorings and seven ocean gliders were deployed over a period of a year, starting in September 2012, in a small region of the North Atlantic. We observed a steady deepening of the mixed layer from shallow values in late summer (50 m) to deep values in the stormy winter months (300 m) and a rapid shallowing, or shoaling, again in early spring. Of principal interest, though, were brief but large deviations from these broad trends. ESE assistant professor Andy Thompson was part of the team that used autonomous underwater vehicles (AUVs) know as ocean gliders to better understand this variability. Ocean gliders (see image) are robots that can modify their buoyancy to “glide” up and down through the ocean and record water properties such as temperature, salinity, dissolved oxygen and fluorescence. The gliders’ of use buoyancy for propulsion, as opposed to a motor, reduces the need for power. Thus for a fraction of the cost of traditional ocean research vessels, gliders allow persistent monitoring of the ocean. Furthermore, the gliders communicate in real-time, rising to the surface five times a day to relay position and data and to upload new sampling commands. At the end of the OSMOSIS field program, over 4,200 new profiles of ocean properties were collected, including coverage during winter months when mixing rates are high, but weather conditions make it difficult to observe these processes from ships.

Despite the importance of the ocean mixed layer, it is one aspect of the Earth system that is poorly represented in global climate models. The reason is that climate models must use coarse representations of the ocean. For example, a single mixed layer depth in a climate model may represent properties over a 100 km by 100 km box, whereas in the real ocean, mixed layer depths may differ by hundreds of meters over a distance as small as a kilometer. By using smaller models of upper ocean flows and comparing them to observations, Thompson and colleagues hope to better understand what physical processes control these differences and how their effects influence larger-scale properties that are represented in climate models. An exciting aspect of this research is the link with ecosystem dynamics that control ocean carbon uptake and support fisheries of the North Americas and Europe. Each year, sometime between early March and early May, phytoplankton concentrations, which remain low throughout winter months, explode in an event known as the spring bloom. The timing of these events have been notoriously difficult to predict. By coupling modern turbulence and biological models and comparing them with our glider observations, we hope to improve our ability to predict the timing of these events and gain a deeper understanding of their phenomenon.

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