The movement of water due to eddies, or large-scale ocean currents, leads to the large-scale transport of important ocean properties called “tracers.” Tracers include heat, salinity, and anthropogenic carbon, all of which contribute to eddies playing an important role in global ocean and climate behavior. This process is typically described by the concept of turbulent diffusion. Turbulent diffusion is widely used to represent tracer transport in climate models. A recent study, published in Geophysical Research Letters, focuses on the turbulent diffusion function used in models, specifically a piece of that function known as a K-tensor. The research team, funded in part by CPO’s Climate Variability & Predictability (CVP) program, breaks the K-tensor down into its component parts, detailing many complex and interrelated properties. To deal with this complexity, climate models generally make assumptions about various properties that define the K-tensor. However, here researchers comprehensively show that the K-tensor is space-, time-, direction-, and tracer-dependent. In other words, how the K-tensor is described depends on all of these different factors at once and generalizing one factor can lead to changing what the K-tensor represents. The study authors use numerical flow simulations to illustrate how these individual component properties matter and impact flow and transport as a whole. This revealed complexity suggests that researchers should reconsider how turbulent diffusion is estimated and interpreted in climate models.