Atmospheric predictability is insensitive to the slope of the background kinetic energy spectrum

Thesis (Master's)--University of Washington, 2021The sensitivity of atmospheric predictability to the slope of the background kinetic energy (KE) spectrum is investigated by adding low-level potential temperature perturbations of varying scales and amplitudes to convection-permitting idealized simulations of moist baroclinic waves using the Weather Research and Forecasting (WRF) model. When perturbations are small in amplitude, error growth through 36 hour lead times is insensitive to initial error scale and the slope of the background KE spectrum. In physical space, this insensitivity occurs because short-range predictability is limited by rapid growth from moist processes such as cold frontal convection, regardless of the initial error scale. In spectral space, this insensitivity occurs because errors grow up-amplitude at all scales rather than via an explicit upscale cascade from the smallest scales. These results are confirmed using two different baroclinic wave simulations: one with a widely-used but unrealistic base state which pro- duces a flat KE spectrum in the mesoscales, and another with more realistic moist processes and a k^{−2} mesoscale KE spectrum. The observed insensitivity of error growth in moist baroclinic waves to the slope of the background KE spectrum contrasts with error growth in homogeneous isotropic turbulence, which is local in spectral space and highly sensitive to the KE spectral slope