The emergence of concurrent high‐resolution physical and bio‐optical measurements in the upper ocean and their applications

TLDR

Upper ocean processes span nine orders of magnitude, making adequate sampling challenging, but recent sensor advances have rapidly improved capabilities. The study highlights several research applications enabled by concurrent physical and bio‑optical measurements. Recent oceanic measurement systems, deployed on ships, the Research Platform FLIP, moorings, and drifters, enable concurrent physical and bio‑optical data collection and underscore the need for complementary in situ and satellite datasets for analysis and modeling. Concurrent physical and bio‑optical data sets now benefit studies of phytoplankton production variability, upper‑ocean heating, small‑scale mixing, discharge dispersion, and climate‑change carbon cycling, with recent platform data illustrating the merits of each sampling mode.

Abstract

Time and space scales of processes relevant to the upper ocean ecosystem span more than 9 orders of magnitude, consequently adequate sampling of the oceanic environment is a major challenge. However, new capabilities for studying upper ocean physical and bio‐optical processes have developed rapidly within the past decade with the advancement of sensor technology and data acquisition and storage capabilities. Several oceanic measurement systems have been designed recently to enable the collection of physical and bio‐optical data concurrently. Problems concerning variability in primary production by phytoplankton, upper ocean heating, small‐scale physical mixing and advection, the dispersion of oceanic discharges, and global scale climate change related to the carbon cycle can now benefit from in situ concurrent physical and bio‐optical data sets. The ocean sampling platforms utilized for deployment of these systems have included ships, the stable platform Research Platform FLIP , moorings and drifters. Examples of recent data sets obtained from these platforms are presented, and the merits of each of these sampling modes are described. In addition, the needs for complementary in situ and remotely sensed (for example, from satellites) data sets for both analytical and modeling efforts are summarized. Several research applications of the new technology are highlighted.