OpenWaveLogger v2026 (OWL-v2026): an open source, low cost, easy to build, high performance logger for wave data measurements
Jean Rabault, Joey Voermans, Takuji Waseda, Takehiko Nose, Tsubasa Kodaira, Koya Sato, Alexander Babanin, Gaute Hope, Malte M\"uller, Lars Willas Dreyer, {\O}ystein Lande, Atle Jensen, {\O}yvind Breivik

TL;DR
The paper introduces OWL-v2026, an affordable, easy-to-assemble open-source logger for high-frequency wave data, enabling better in-situ ocean wave measurements for climate and weather models.
Contribution
It presents a low-cost, high-performance, open-source wave data logger built from off-the-shelf components, with validated high-frequency logging capabilities.
Findings
Successfully logged data continuously over 10 days at 208Hz.
Achieved power autonomy of approximately 20 days with three D-cell lithium batteries.
Timestamp accuracy typically better than 10ms.
Abstract
Ocean wave models are critical for weather and climate forecasting, and accurate in-situ wave observations are essential for validating and improving these models. Open-source, community-driven buoys have democratized wave observations via telemetry in recent years, but these systems transmit only limited amounts of data. Full high-frequency time series, required to study detailed wave physics, can still in most cases only be collected in situ using data loggers. Yet open-source, low-cost logger solutions remain scarce compared to their telemetry-enabled counterparts. Here we present the Openlogartemis Wave Logger (OWL-v2026), an open-source, low-cost, easy-to-build, high-performance logger for wave data measurements. The OWL-v2026 is built from off-the-shelf components from the maker community, requiring only through-hole soldering for assembly, and totals approximately 220USD per…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
