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Abstract. Phytoplankton form the base of marine food webs and playan important role in carbon cycling, making it important to quantify ratesof biomass accumulation and loss. As phytoplankton drift with oceancurrents, rates should be evaluated in a Lagrangian as opposed to an Eulerianframework. In this study, we quantify the Lagrangian (from Bio-Argo floatsand surface drifters with satellite ocean colour) and Eulerian (fromsatellite ocean colour and altimetry) statistics of mesoscale chlorophylland velocity by computing decorrelation time and length scales and relatethe frames by scaling the material derivative of chlorophyll. Because floatsprofile vertically and are not perfect Lagrangian observers, we quantify themean distance between float and surface geostrophic trajectories over thetime spanned by three consecutive profiles (quasi-planktonic index, QPI) toassess how their sampling is a function of their deviations from surfacemotion. Lagrangian and Eulerian statistics of chlorophyll are sensitive to thefiltering used to compute anomalies. Chlorophyll anomalies about a 31 dtime filter reveal an approximate equivalence of Lagrangian and Euleriantendencies, suggesting they are driven by ocean colour pixel-scale processesand sources or sinks. On the other hand, chlorophyll anomalies about aseasonal cycle have Eulerian scales similar to those of velocity, suggestingmesoscale stirring helps set distributions of biological properties, andratios of Lagrangian to Eulerian timescales depend on the magnitude ofvelocity fluctuations relative to an evolution speed of the chlorophyllfields in a manner similar to earlier theoretical results for velocityscales. The results suggest that stirring by eddies largely sets Lagrangiantime and length scales of chlorophyll anomalies at the mesoscale.
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A Global Comparison of Marine Chlorophyll Variability Observed in Eulerian and Lagrangian Perspectives
Abstract Ocean chlorophyll time series exhibit temporal variability on a range of timescales due to environmental change, ecological interactions, dispersal, and other factors. The differences in chlorophyll temporal variability observed at stationary locations (Eulerian perspective) or following water parcels (Lagrangian perspective) are poorly understood. Here we contrasted the temporal variability of ocean chlorophyll in these two observational perspectives, using global drifter trajectories and satellite chlorophyll to generate matched pairs of Eulerian‐Lagrangian time series. We found that for most ocean locations, chlorophyll variances measured in Eulerian and Lagrangian perspectives are not statistically different. In high latitude areas, the two perspectives may capture similar variability due to the large spatial scale of chlorophyll patches. In localized regions of the ocean, however, chlorophyll variability measured in these two perspectives may significantly differ. For example, in some western boundary currents, temporal chlorophyll variability in the Lagrangian perspective was greater than in the Eulerian perspective. In these cases, the observing platform travels rapidly across strong environmental gradients and constrained by the shelf topography, potentially leading to greater Lagrangian variability in chlorophyll. In contrast, we found that Eulerian chlorophyll variability exceeded Lagrangian variability in some key upwelling zones and boundary current extensions. In these cases, variability in the nutrient supply may generate intermittent chlorophyll anomalies in the Eulerian perspective, while the Lagrangian perspective sees the transport of such anomalies off‐shore. These findings aid with the interpretation of chlorophyll time series from different sampling methodologies, inform observational network design, and guide validation of marine ecosystem models.
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- Award ID(s):
- 2149501
- PAR ID:
- 10441350
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Oceans
- Volume:
- 128
- Issue:
- 7
- ISSN:
- 2169-9275
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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