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X-WR-CALNAME:Ocean Observatories Initiative
X-ORIGINAL-URL:https://oceanobservatories.org
X-WR-CALDESC:Events for Ocean Observatories Initiative
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DTSTART:20260308T070000
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DTSTART:20261101T060000
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261207T080000
DTEND;TZID=America/New_York:20261211T170000
DTSTAMP:20260715T140949
CREATED:20260715T134133Z
LAST-MODIFIED:20260715T170853Z
UID:37676-1796630400-1797008400@oceanobservatories.org
SUMMARY:AGU 2026: Long-Term Ocean Observatories as Drivers of Sensor and Data Science Innovation
DESCRIPTION:Over the past two decades\, growing recognition of shifting baselines\, spatial variability\, and the value of long-duration ocean observations has driven expansion of long-term mobile and stationary ocean observatories\, including ARGO\, ONC\, OOI\, and more. These observatories have produced essential time-series data in ecologically and economically critical\, and often understudied\, marine environments. They also catalyzed major innovations in engineering and data science\, including development of robust hardware that can withstand years on the seafloor and survive severe surface conditions\, methods to mitigate drift and biofouling over extended deployments\, software and machine learning algorithms designed to handle the high volume and frequency of real-time data streams\, and procedures to ensure long-term storage\, quality control\, processing\, and delivery of enormous quantities of diverse instrument data. This session highlights advances in ocean observing technology and data processing tools\, emphasizing best practices and the sometimes unanticipated scientific and operational benefits of long-term ocean observatories. \nSubmit an Abstract to this Session \n\nPrimary Convener:\n\nMichael Vardaro\n\n\nUniversity of Washington Seattle Campus\n\n\n\n\n\n\nConveners:\n\nWendi Ruef\n\n\nUniversity of Washington Seattle Campus\n\n\n\nEdward Paul Dever\n\n\nOregon State University
URL:https://oceanobservatories.org/event/agu-2026-long-term-ocean-observatories-as-drivers-of-sensor-and-data-science-innovation/
LOCATION:San Francisco\, CA
CATEGORIES:Conferences
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261207T080000
DTEND;TZID=America/New_York:20261211T170000
DTSTAMP:20260715T140949
CREATED:20260715T141529Z
LAST-MODIFIED:20260715T143435Z
UID:37682-1796630400-1797008400@oceanobservatories.org
SUMMARY:AGU 2026: AI and Machine Learning for Sustained Ocean Observing: Progress and the Road Ahead
DESCRIPTION:Long-term\, large-scale ocean observing systems\, including the Ocean Observatories Initiative (OOI)\, Ocean Networks Canada (ONC)\, Argo\, GO-BGC\, and IOOS networks\, among others\, generate high-density\, multi-stream datasets at a volume and complexity that increasingly exceed the capacity of traditional analysis approaches. Advances in artificial intelligence (AI) and machine learning (ML) offer powerful tools for rapidily processing these data at scale and reveal patterns and scientific insights that would otherwise remain undetected. We invite contributions highlighting observatory science enhanced by AI and ML\, including but not limited to: seismic and acoustic event detection; computer vision applications; integration with modeling and data assimilation workflows; quality assurance\, quality control\, and anomaly detection; autonomous platform control\, data reduction and adaptive sampling; and cross-platform data synthesis. Work addressing model interpretability\, training data limitations\, and reproducibility is especially encouraged. Contributions are welcome across disciplines\, including physical oceanography\, biogeochemistry\, marine ecology\, and solid Earth science. \nSubmit and Abstract for this Session \n\nPrimary Convener:\n\nKatharine Bigham\n\n\nUniversity of Washington Seattle Campus\n\n\n\n\n\n\nConveners:\n\nBen Biffard\n\n\nOcean Networks Canada\, University of Victoria\n\n\n\nMartin Scherwath\n\n\nUniversity of Victoria\n\n\n\n\n\n\nStudent/Early Career Convener:\n\nAda Carter\n\n\nUniversity of Washington Seattle Campus
URL:https://oceanobservatories.org/event/agu-2026-ai-and-machine-learning-for-sustained-ocean-observing-progress-and-the-road-ahead/
LOCATION:San Francisco\, CA
CATEGORIES:Conferences
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261207T080000
DTEND;TZID=America/New_York:20261211T170000
DTSTAMP:20260715T140949
CREATED:20260715T143109Z
LAST-MODIFIED:20260715T143315Z
UID:37694-1796630400-1797008400@oceanobservatories.org
SUMMARY:AGU 2026 Annual Meeting
DESCRIPTION:AGU’s annual meeting\, the largest gathering of Earth and space scientists\, convenes 25\,000+ attendees from 100+ countries to share research\, connect\, collaborate\, and inspire one another. \nDiscover “Where Science Connects” at AGU26. Share your research with the global Earth and space science community.
URL:https://oceanobservatories.org/event/agu-2026/
LOCATION:San Francisco\, CA
CATEGORIES:Conferences
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