Abstract
We investigate the sensitivity of mesoscale atmospheric predictability to the slope of the background kinetic energy spectrum E by adding initial errors to simulations of idealized moist midlatitude cyclones at several wavenumbers k for which the slope of E(k) is significantly different. These different slopes arise from 1) differences in the E(k) generated by cyclones growing in two different moist baroclinically unstable environments, and 2) differences in the horizontal scale at which initial perturbations are added, with E(k) having steeper slopes at larger scales.
When small-amplitude potential temperature perturbations are added, the error growth through the subsequent 36-hour simulation is not sensitive to the slope of E(k) nor to the horizontal scale of the initial error. In all cases with small-amplitude perturbations, the error growth in physical space is dominated by moist convection along frontal boundaries. As such, the error field is localized in physical space and broad in wavenumber (spectral) space. In moist mid-latitude cyclones, these broadly distributed errors in wavenumber space limit mesoscale predictability by growing up-amplitude rather than by cascading upscale to progressively longer wavelengths. In contrast, the error distribution in homogeneous turbulence is broad in physical space and localized in wavenumber space, and dimensional analysis can be used to estimate the error growth rate at a specific wavenumber k from E(k). Predictability estimates derived in this manner, and from the numerical solutions of idealized models of homogeneous turbulence, depend on whether the slope of E(k) is shallower or steeper than k−3, which differs from the slope-insensitive behavior exhibited by moist mid-latitude cyclones.
Radial and Angular Electron Ejection Patterns of Two-Electron Quantum Dots in THz Fields
