New Tools for OOI Surface Profiler Data Delivery and Visualization

Ian Black, Jonathan P Fram and Craig M Risien, Oregon State University, College of Earth, Ocean, and Atmospheric Sciences, Corvallis, OR, United States
The Ocean Observatories Initiative (OOI) Coastal Surface Piercing Profiler (CSPP) is a rapidly deployable moored profiler that provides measurements from several meters above bottom to the ocean surface boundary layer. After profiling on ascent, it transmits the profiled data to shore at the surface and descends to its rest position. The platform collects physical (T,S,P, velocity) and biochemical (PAR, Chl-a, CDOM, OB, DO, NO3) variables at approximately one sample per 25 cm. The CSPP is currently deployed at the OOI Endurance Array Oregon and Washington shelf sites (80 and 87 m depth) year round and at the Oregon and Washington inshore sites (25 and 29 m depth) from spring through early fall. The default sampling is to profile at least twice daily over 90-day deployments. Paired with other OOI assets, the CSPP enhances our understanding of coastal ocean and ecosystem dynamics in the Northern California Upwelling System.

Over the last year, we have developed tools for data download and visualization of CSPP data. These tools provide a graphical interface to the OOI Data Portal machine-to-machine (M2M) interface. While we’ve used these tools for quality assessment and control of CSPP data, they also offer users easy access to this unique data set. Preliminary analysis of instrument and engineering datasets shows the occurrence of small spatial and temporal transient hypoxia and upwelling events. Real-time adjustments in profiler sampling could offer high-resolution collection on event scales without impact to the OOI’s overarching science goals. Adaptation of sampling and platform configuration through user request may add to research that focuses on small temporal and vertical scales and increase the overall number of applications and users of profiler data.

We will discuss some identifiable events, adaptive sampling practices performed at the observatory level, and methods for distributing archived and near real-time data to end users.