Estimating Argo Float Trajectories Under Ice

Abstract

Abstract Since the Argo program began, 568 floats returned almost 31,000 profiles, at high‐southern latitudes, with no measured position. These data are either disseminated with positions linearly interpolated between known positions, or with no geographic positions. Here, we present a simple method for estimating unknown Argo float trajectories. We try to identify trajectories that approximately follow contours along three different properties: potential vorticity (f/H), sea‐level, and density at 1,000 m. No single property‐constraint can be used to estimate trajectories for all position‐gaps. Each constraint fails for 9%–18% of gaps, where no continuous contour between the end‐points exists. But all constraints fail for the same position‐gap, for fewer than 1% of cases. For a given position‐gap, when a trajectory is identified using two or three different constraints, we select the shortest trajectory to be used to “fill the gap”. This selection process could be performed better by an Expert Operator, inspecting each estimated trajectory, and selecting the trajectory that is most consistent with a priori knowledge of the circulation in the vicinity of the position‐gap. Nonetheless, using the objective metric for selection, we find that 41.2% of position‐gaps use the f/H‐constraint, 32.1% use density, and 25.8% use sea‐level. We assess the estimated trajectories for consistency, by comparing bottom depths beneath trajectories to the deepest measurements in each profile. We find inconsistencies for 11.6% of position‐gaps using our method, compared to 28.0% using linearly‐interpolated trajectories. Adoption of the estimated trajectories for measurements under ice may yield benefits to many applications.

Keywords

• Ocean observing
• Argo
• ice
• trajectories