Autonomous tracking of an oceanic thermal front by a Wave Glider

Temporal variation in the structure and location of dynamic ocean features make them challenging to observe. Beyond requiring sufficient persistence and speed of the sensor platform, effective observation is augmented by autonomous feature detection coupled with adaptive localization of mapping effort. These capabilities enable observations to remain localized within and around features of interest, thereby enhancing spatial and temporal resolution in their depiction. A Wave Glider is a wave‐propelled unmanned surface vehicle with solar energy collection to support payload and a backup propeller in calm sea state. The efficiency of this platform enables persistence (months), and its propulsion system provides speed (~1 m/s). Building on these capabilities, we aim at enabling the Wave Glider to autonomously recognize and track oceanic features that have strong surface expressions, accessible to near‐surface sensors. We present a method of using a Wave Glider to autonomously track an oceanic thermal front known to have biological importance and dynamic evolution. In October 2017, this method was applied to tracking and mapping an upwelling front in Monterey Bay, CA, over 39 hr. The field result demonstrates adaptive localization of mapping based on autonomous feature detection.