To study ocean currents, scientists typically release GPS-tagged buoys, record their velocities, and reconstruct the ocean currents that carry them. This recorded data can also be used to identify areas where water is rising from below the surface or sinking below the surface (a phenomenon known as “divergence”).
By accurately predicting ocean currents and identifying deviations, experts can better predict weather, measure ocean energy transfer rates, and estimate how oil will spread after a spill. You can
Until recently, scientists have primarily used a machine learning technique known as the “Gaussian process” to estimate currents and pinpoint divergence.
Although this method can make predictions even with sparse data, it often starts with physically incorrect assumptions, such as the latitude and longitude components of the current being irrelevant. For example, the model assumes that ocean current divergence and its vorticity (the eddy motion of water) act on the same magnitude and length scales, but marine scientists know this assumption to be untrue. increase.
To overcome these limitations, a team of computer scientists and oceanographers led by the Massachusetts Institute of Technology (MIT) recently developed a new model that incorporates knowledge of fluid dynamics to better reflect the physics that make up ocean currents. Did.
This new method uses what is known as the “Helmholtz decomposition” to model ocean currents by decomposing them into their vorticity components. This captures the swirling motion and divergence components of the water, and captures the sinking and rising of the water.
This technique is computationally expensive, but the additional cost is relatively small. In addition, it will help scientists make more accurate inferences from buoy data, effectively monitor the transport of biomass, carbon, plastics, nutrients and oil in the oceans, and better understand the impact of climate change on ocean currents. and can be tracked.
“Our method captures the physical assumptions better and more accurately. In this case, we already know a lot of the physics. It allows us to focus on learning what is important to us: what is the current leaving the buoy, what is this divergence and where is it happening?” Tamara Broderick is her Associate Professor of Science in Computers at MIT.
By evaluating this new model using both synthetic buoy data from the Gulf of Mexico and real ocean buoy data, the researchers found that it was able to predict tidal currents better than other machine learning approaches using standard Gaussian processes or neural algorithms. showed that our method is more accurate in predicting and identifying the divergence of . Communication network.
For example, in simulations involving eddies adjacent to currents, the new method accurately predicted no divergence, whereas other methods predicted divergence with very high confidence. A preprint of the study is available here.
In future work, scientists will incorporate a temporal component into the model (because ocean currents can vary both in space and time) to explore how noise, such as wind-generated noise, affects the data. We plan to better capture the
“Our hope is to take this noisy observed velocity field from the buoys and show what the actual divergence and actual vorticity is and predict away from those buoys. We believe our new technology will help with this,” said Broderick. concluded.
Why is it important to study ocean currents?
The study of ocean currents is important for many reasons. They play important roles in regulating climate, determining the distribution of marine life, shaping human activity, and more. Here’s a breakdown of why we study them:
climate regulation
Ocean currents distribute heat across the globe and help regulate climate. For example, the Gulf Stream carries warm water from the Gulf of Mexico to the North Atlantic Ocean and moderates the climate of Western Europe. Understanding these trends will enable scientists to create accurate climate forecasts and models.
biodiversity and ecosystems
Ocean currents affect the distribution of nutrients and, in turn, where marine life can live and thrive. Ocean currents carry cold, nutrient-rich water to the surface in a process called upwelling, supporting biodiversity hotspots. Studying ocean currents provides insight into marine ecosystems and the factors that affect their health and biodiversity.
Navigation and shipping
For centuries, sailors have used ocean currents for navigation. Understanding ocean currents creates more efficient transportation routes, saving time and fuel.
Diffusion of pollution
In the event of a spill or leakage (such as an oil spill), ocean currents help determine where the pollution will spread. By modeling these flows, we can predict the movement of such pollutants and devise better remediation strategies.
fisheries management
Many commercial fish species follow specific ocean currents throughout their life cycle. Knowing these patterns can help manage and protect fisheries.
weather forecast
Ocean currents play a role in the weather system. For example, El Niño, a warm ocean current, influences weather patterns around the world. Understanding these trends can contribute to more accurate weather forecasts.
Climate change research
Ocean currents are expected to change with climate change, impacting global weather patterns, sea levels and marine life. Studying them will help us understand the impacts of climate change and guide mitigation strategies.
Marine archeology and history
Ocean currents also affect the spread of artifacts from shipwrecks, providing clues to historical events and lost civilizations.
Overall, understanding ocean currents is crucial for a wide range of disciplines, including climate science, biology, navigation, conservation, and more.
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To Andrey Ionescu, Earth.com staff writer
Check us out on EarthSnap, a free app by Eric Ralls and Earth.com.
