Comment on bg-2022-103

Abstract

Phytoplankton form the base of marine food webs and play an important role in carbon cycling, making it important to quantify rates of biomass accumulation and loss. Since phytoplankton drift with ocean currents, rates should be evaluated in a Lagrangian as opposed to Eulerian framework. In this study, we quantify the Lagrangian (from Bio-Argo floats and surface drifters with satellite ocean colour) and Eulerian (from satellite ocean colour and altimetry) statistics of mesoscale chlorophyll and velocity by computing decorrelation time and length scales and relate the frames by scaling the material derivative of chlorophyll. Because floats profile vertically and are not perfect Lagrangian observers, we quantify the mean distance between float and surface geostrophic trajectories over the time spanned by three consecutive profiles (Quasi-Planktonic Index; QPI) to assess how their sampling is a function of their deviations from surface motion. Lagrangian-Eulerian statistics of chlorophyll are sensitive to the filtering used to compute anomalies. Chlorophyll anomalies about a 31-day time filter reveal approximate equivalence of Lagrangian and Eulerian tendencies, suggesting they are driven by ocean-colour-pixel-scale processes and sources or sinks. Chlorophyll anomalies about a seasonal cycle have Eulerian scales similar to those of velocity, suggesting mesoscale stirring helps set distributions of biological properties, and ratios of Lagrangian to Eulerian timescales depend on observer speed relative to an evolution speed of the chlorophyll fields in a manner similar to earlier theoretical results for velocity scales. By lagging surface chlorophyll patches, floats underestimate the Lagrangian tendency and advective terms, and the Eulerian tendency primarily sets timescales; however, since the QPI increases with profiling interval, frequent profiling can generate more accurate time series of phytoplankton accumulation.