Stirring, mixing, growing: microscale processes change larger scale phytoplankton dynamics

TL;DR

This paper demonstrates that incorporating microscale interactions into Lagrangian models significantly improves understanding and prediction of large-scale phytoplankton dynamics and biogeochemical processes.

Contribution

It introduces an enhanced Lagrangian modeling framework that captures interactions across scales, addressing limitations of previous models.

Findings

Improved modeling of phytoplankton bloom phenology.

Better representation of vertical variability in mixed layers.

Enhanced understanding of microscale influence on large-scale biogeochemical cycles.

Abstract

The quantitative description of marine systems is constrained by a major issue of scale separation: most marine biochemical processes occur at sub-centimeter scales, while the contribution to the Earth's biogeochemical cycles is expressed at much larger scales, up to the planetary one. In spite of vastly improved computing power and observational capabilities, the modeling approach has remained anchored to an old view that sees the microscales as unable to substantially affect larger ones. The lack of a widespread theoretical appreciation of the interactions between vastly different scales has led to the proliferation of numerical models with uncertain predictive capabilities. We show that an enhanced Lagrangian modeling framework, allowing for those interactions, can easily tackle puzzling problems such as the phenology of phytoplankton blooms, or vertical variability in mixed layers.