Quantifying the Temporal Uncertainties of Nonlinear Turbulence Simulations

TL;DR

This paper evaluates methods for quantifying temporal uncertainties in nonlinear turbulence simulations, focusing on their application to gyrokinetic simulations and the challenges near instability thresholds.

Contribution

It systematically assesses existing uncertainty quantification methods and explores ARMA models for forecasting turbulence quantity uncertainties in plasma simulations.

Findings

ARMA models effectively forecast long-term uncertainty.

Standard methods face challenges near instability thresholds.

Quantification of time-averaging uncertainties improves validation.

Abstract

Nonlinear initial value turbulence simulations often exhibit large temporal variations in their dynamics. Quantifying the temporal uncertainty of turbulence simulation outputs is an important component of validating the simulation results against the experimental measurements, as well as for code-code comparisons. This paper assesses different methods of uncertainty quantification of temporally varying simulated quantities previously used within plasma turbulence community, to evaluate their strengths and potential pitfalls. The use of Autoregressive Moving-Average (ARMA) models for forecasting the uncertainty of turbulence quantities at later simulation times is also studied. These discussions are framed in the practical context of calculating the time-averaging uncertainties of turbulent energy fluxes calculated via gyrokinetic simulations. Particular attention is paid to how standard approaches are challenged as the driving gradient is reduced to the critical value for instability onset.