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Abstract Many turbulence estimates require fitting model forms, typically nonlinear expressions, to observations that have been converted into spectra. Choosing a fitting method usually depends on user preference, such as calculation ease under the spectra's presumed statistical nature or reducing computation demands when turbulence quantities must be estimated onboard expendable instruments. Six different methods are assessed by fitting a known model against synthetic spectra with variability generated from two different statistical distributions. The assessment uses an inertial subrange model to estimate the turbulent kinetic energy dissipation rate from velocity spectra. However, the results and conclusions are relevant to fitting other turbulence inertial subrange models that follow a power law where is the spectral slope and contains the sought‐after turbulence parameter. The two most accurate methods require linearizing the spectral observations by taking the logarithm of the wavenumbers and the dependent spectra power density . These methods are less sensitive to outliers and deviations of the observations from a known statistical distribution. Some methods returned that deviated from the prescribed value by more than 50% depending on the number of samples fitted and the level of uncertainty of the spectra. Methods for estimating the spectral slope, , were also assessed to provide recommendations on using this parameter to flag data which deviates from the expected form so that the spectra (or wavenumbers) can be excluded from further analysis. 

We contend that ocean turbulent fluxes should be included in the list of Essential Ocean Variables (EOVs) created by the Global Ocean Observing System. This list aims to identify variables that are essential to observe to inform policy and maintain a healthy and resilient ocean. Diapycnal turbulent fluxes quantify the rates of exchange of tracers (such as temperature, salinity, density or nutrients, all of which are already EOVs) across a density layer. Measuring them is necessary to close the tracer concentration budgets of these quantities. Measuring turbulent fluxes of buoyancy (J_b), heat (J_q), salinity (J_S) or any other tracer requires either synchronous microscale (a few centimeters) measurements of both the vector velocity and the scalar (e.g., temperature) to produce time series of the highly correlated perturbations of the two variables, or microscale measurements of turbulent dissipation rates of kinetic energy (ϵ) and of thermal/salinity/tracer variance (χ), from which fluxes can be derived. Unlike isopycnal turbulent fluxes, which are dominated by the mesoscale (tens of kilometers), microscale diapycnal fluxes cannot be derived as the product of existing EOVs, but rather require observations at the appropriate scales. The instrumentation, standardization of measurement practices, and data coordination of turbulence observations have advanced greatly in the past decade and are becoming increasingly robust. With more routine measurements, we can begin to unravel the relationships between physical mixing processes and ecosystem health. In addition to laying out the scientific relevance of the turbulent diapycnal fluxes, this review also compiles the current developments steering the community toward such routine measurements, strengthening the case for registering the turbulent diapycnal fluxes as an pilot Essential Ocean Variable.