Integral scientists contributed to research and development of a device that collects data from the world’s oceans.
Research by Kaus Raghukumar, Ph.D., Grace Chang, Ph.D., Frank Spada, and Craig Jones, Ph.D., of Integral, along with colleagues Tim Janssen, Ph.D., and A. Gans, was cited in a recent Washington Post article on the deployment of a network of more than 1,000 Sofar Ocean Spotter buoys to improve predictive models for ocean and weather conditions. Data from the device could also be used for research on climate change.
The technology is also being used to support marine renewable energy projects—potentially reducing the cost of wave energy by incorporating real-time information about surface wave motions. Integral scientists are collaborating with Sandia National Laboratories, Baylor University, and University of Alaska, Fairbanks, using machine-learning methods to improve the accuracy of wave field predictions. The results are being used to inform a wave-to-wire wave energy management system and increase certainty in power forecasts to microgrids. An array of Spotters is providing data that will be used to validate and improve wave model predictions.
Research and performance data on Spotter was first published in the June 2019 issue of the Journal of Atmospheric and Oceanic Technology. Spotter research and development was supported in part by the U.S. Department of Energy, Advanced Research Projects Agency – Energy (ARPA-E), under Award Number DE-AR0000514.