Application Note
Marine - Compact weather stations on buoys for coastal monitoring
OSIL Fulmar Buoy and Gill MaxiMet come together to deliver environmental data collection
Background
Coastal zones face significant threats from climate change and rising sea levels, which together drive increasingly intense storms, flooding, and erosion. Assessing and predicting coastal vulnerability requires systematic and sustained monitoring of the physical, chemical, and biological processes occurring in these zones.
The PREDICT multidisciplinary project is funded by Science Foundation of Ireland (SFI), the Geological Survey of Ireland and the Marine Institute (MI) and coordinated in Dublin City University (DCU). Principal Investigators in Maynooth University (MU), University College Cork (UCC) and the Geological Survey Ireland (GSI) oversee the project which aims to establish a coordinated program of coastal ocean observations. The initiative focuses on validating, calibrating, and maximising the extraction of data from satellite earth observation systems, with Dublin Bay serving as an experimental proof of concept.
The project’s goal is to develop AI models capable of predicting environmental changes across various settings. It integrates data from mathematical modeling, remote and in-situ sensing, physical and chemical oceanography, and seabed mapping, including data collected from the Dublin Bay buoy.
These AI models are expected to support future planning in diverse areas, including coastal mapping, flood prediction, marine habitats and fisheries management, climate change adaptation, environmental protection, and policy development.
Challenge
Environmental monitoring buoys play a critical role in collecting environmental data, especially in challenging marine environments. These buoys therefore need to be designed for durability, user-friendliness, and quick deployment. Additionally, the ability to integrate with other data sources is essential, as the data collected by the buoys is often complemented by satellite and other observational systems.
To meet the project’s goals, an expert provider of integrated systems for environmental monitoring was required. This provider would be responsible for developing and delivering the buoy, including installation of various sensors such as a weather station, and ensuring the collection of high-quality data necessary for the project’s objectives.
Solutions
Ocean Scientific International Ltd (OSIL) was selected to provide a multidisciplinary data buoy platform which was installed in Dublin Bay to monitor environmental changes. The 1.9m OSIL Fulmar buoy was chosen for its robust design and advanced capabilities. The buoy records and transmits a wide range of environmental parameters, including salinity, temperature, pH, partial pressure of CO2, turbidity, dissolved oxygen, and chlorophyll. It also collects a full suite of meteorological measurements.
Data from the buoy is relayed via GSM, with an Iridium satellite Short Burst Data system as a backup. This ensures continuous data availability, which is accessible to the public through a dedicated interactive web portal. Here the environmental data is catalogued, mapped and displayed, facilitating collaboration and partnership planning.
To collect weather data, the MaxiMet® GMX501 compact weather station from Gill Instruments was chosen. Known for its reliability across a range of land and marine-based environments, the MaxiMet station is robust, energy-efficient, and easy to integrate with the buoy’s control and AI systems. Its performance and durability make it an ideal choice for this project.
OSIL Fulmar Buoy fitted with MaxiMet GMX501 (pictured)
MaxiMet® GMX5O1
Compact, integrated weather station installed on OSIL Fulmar Buoy, providing weather data for the PREDICT project in Dublin Bay
Recommended compact weather station for marine applications...
MaxiMet is an advanced compact weather station designed and manufactured by Gill Instruments using proven technology to measure meteorological and environmental parameters to international standards.