Abstract
This study uses Observing System Simulation Experiments (OSSEs) to examine the reconstruction of biogeochemical variables in the Southern Ocean from an array of autonomous profiling floats. In these OSSEs, designed to be relevant to the Southern Ocean Carbon and Climate Observation and Modeling (SOCCOM) project, the simulated floats move with oceanic currents and sample dissolved oxygen and inorganic carbon. The annual mean and seasonal cycle of these fields are then reconstructed and compared to the original model fields. The reconstruction skill is quantified with the reconstruction error (RErr), defined as the difference between the reconstructed and actual model fields, weighted by a local measure of the spatiotemporal variability. The square of the RErr is small (<0.5) for 150 floats in most of the domain, which is interpreted to mean that the reconstruction skill is high. An idealized analytical study demonstrates that the RErr depends on the magnitude of the seasonal cycle, spatial gradients, speed of float movement, amplitude of mesoscale variability, and number of floats. These factors explain a large part of the spatial variability in the RErr and can be used to predict the reconstruction skill of the SOCCOM array. Furthermore, our results demonstrate that an array size of 150 floats is a reasonable choice for reconstruction of surface properties and annual‐mean 2000 m inventories, with the exception of the seasonal cycle in parts of the Indo‐Atlantic, and that doubling this number to 300 results in a very modest increase in the reconstruction skill for dissolved oxygen.
Key Points
OSSEs for the SOCCOM array estimate the skill of reconstructing maps of biogeochemical tracers from float profiles in the Southern Ocean
The reconstruction skill depends on the magnitude of the seasonal cycle, mesoscale variability, and spatial gradients
Movement and number of floats are important, and an array size of 150 floats is a reasonable choice for the Southern Ocean
