Kinetic energy is a fundamental measure of wind variations in the atmosphere, and its spectrum tells us how weather forecast errors evolve. Atmospheric researchers have long believed that the kinetic energy spectrum in the troposphere has a certain shape based on classical turbulence theories, aircraft observations, and simple model simulations. In a new study, CIRES researchers from the Physical Sciences Laboratory analyzed several state-of-the-art observed and modeled wind fields to challenge this belief and raised serious doubts as to this shape at mesoscale (approximately the size of Lake Superior or smaller). Their findings were recently published in the Journal of Atmospheric Sciences.

The researchers found that current state-of-the-art atmospheric reanalysis datasets have dramatically inconsistent mesoscale spectra. They traced these inconsistencies to large and inconsistent contributions of global kinetic energy from the kinetic energy in expansive regions of tropical precipitation and nearby complex terrain, which are not accounted for in classical turbulence theories. They also showed a large sensitivity of the mesoscale kinetic energy in the NOAA GFS forecast model to the representation of tropical clouds and thunderstorms, and damping processes. In light of such inconsistencies and sensitivities, the researchers concluded that the true mesoscale spectrum remains basically unknown at present.

The findings from this research suggest that, instead of pursuing more detailed forecasts by increasing model resolutions, modelers should try to improve global weather forecasts by focusing on improving how latent heat release and damping processes are represented in their models.

Wang, Jih-Wang Aaron and Prashant D. Sardeshmukh (August 2021): Inconsistent Global Kinetic Energy Spectra in Reanalyses and Models. J. Atmos. Sci., 78(8), 2589-2603, https://doi.org/10.1175/JAS-D-20-0294.1.

Posted: August 13, 2021