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Coastal upwelling is a wind-driven ocean process. It brings cooler, saltier, and usually nutrient-rich deep water upward to replace surface water displaced offshore due to Ekman transport. The nutrients carried up by upwelling are important for primary production and fisheries. Ocean life can aggregate at the boundary between stratified water and upwelling water-the upwelling front. In an upwelling water column, temperature, salinity, and other water properties are much more homogeneous over depth than in stratified water. Drawing on this difference, we set up a key measure for differentiating upwelling and stratified water columns-the vertical temperature difference between shallow and deep depths. The vertical temperature difference is large in stratified water but small in upwelling water. Based on this classifier, we developed a method for an autonomous underwater vehicle (AUV) to autonomously detect and track an upwelling front. During the Controlled, Agile, and Novel Observing Network (CANON) Experiment in April 2011, the Tethys long-range AUV ran the algorithm to autonomously track an upwelling front in a dynamic coastal upwelling region in Monterey Bay, CA. The AUV transected the upwelling front 14 times over two days, providing a very high-resolution depiction of the front.