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METEOR: A Mobile (Portable) ocEan roboTic ObsErvatORy

Kanna Rajan, Fernando Aguado Agelet, Pierre F. J. Lermusiaux, João Borges de Sousa, Ajit Subramaniam, Joaquı́n Tintoré

发表年份
2021
引用次数
4

摘要

Abstract The oceans make this planet habitable and provide a variety of essential ecosystem services ranging from climate regulation through control of greenhouse gases to provisioning about 17% of protein consumed by humans. The oceans are changing as a consequence of human activity but this system is severely under sampled. Traditional methods of studying the oceans, sailing in straight lines, extrapolating a few point measurements have not changed much in 200 years. Despite the tremendous advances in sampling technologies, we often use our autonomous assets the same way. We propose to use the advances in multiplatform, multidisciplinary, and integrated ocean observation, artificial intelligence, marine robotics, new high-resolution coastal ocean data assimilation techniques and computer models to observe and predict the oceans “intelligently”—by deploying self-propelled autonomous sensors and Smallsats guided by data assimilating models to provide observations to reduce model uncertainty in the coastal ocean. This system will be portable and capable of being deployed rapidly in any ocean.

关键词

Environmental scienceRemote sensingData assimilationOcean observationsComputer scienceObservatoryMeteorologySystems engineeringEngineeringGeography

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