The Dependence of the Predictability of Mesoscale Convective Systems on the Horizontal Scale and Amplitude of Initial Errors in Idealized Simulations

Abstract

Abstract Recent work has suggested that modest initial relative errors on scales of O(100) km in a numerical weather forecast may exert more control on the predictability of mesoscale convective systems at lead times beyond about 5 h than 100% relative errors at smaller scales. Using an idealized model, the predictability of deep convection organized by several different profiles of environmental vertical wind shear is investigated as a function of the horizontal scale and amplitude of initial errors in the low-level moisture field. Small- and large-scale initial errors are found to have virtually identical impacts on predictability at lead times of 4–5 h for all wind shear profiles. Both small- and large-scale errors grow primarily up in amplitude at all scales rather than through an upscale cascade between adjacent scales. Reducing the amplitude of the initial errors improves predictability lead times, but this improvement diminishes with further reductions in the error amplitude, suggesting a limit to the intrinsic predictability in these simulations of slightly more than 6 h at scales less than 20 km. Additionally, all the simulated convective systems produce a k−5/3 spectrum of kinetic energy, providing evidence of the importance of the unbalanced, divergent gravity wave component of the flow produced by thunderstorms in generating the observed atmospheric kinetic energy spectrum.