Improved representation of turbulent processes in numerical models of tropical cyclones (TCs) is expected to improve intensity forecasts. To this end, the authors use a large-eddy simulation (with 31-m horizontal grid spacing) of an idealized category 5 TC to understand the role of turbulent processes in the inner core of TCs and their role on the mean intensity. Azimuthally and temporally averaged budgets of the momentum fields show that TC turbulence acts to weaken the maximum tangential velocity, diminish the strength of radial inflow into the eye, and suppress the magnitude of the mean eyewall updraft. Turbulent flux divergences in both the vertical and radial directions are shown to influence the TC mean wind field, with the vertical being dominant in most of the inflowing boundary layer and the eyewall (analogous to traditional atmospheric boundary layer flows), while the radial becomes important only in the eyewall.

The validity of the downgradient eddy viscosity hypothesis is largely confirmed for mean velocity fields, except in narrow regions which generally correspond to weak gradients of the mean fields, as well as a narrow region in the eye. This study also provides guidance for values of effective eddy viscosities and vertical mixing length in the most turbulent regions of intense TCs, which have rarely been measured observationally. A generalized formulation of effective eddy viscosity (including the Reynolds normal stresses) is presented.

This work is currently published in the Journal of the Atmospheric Sciences.

Predicting the rapid intensification (>15.0 m s⁻¹ increase in 10 m wind speed over 24 h or less) of tropical cyclones (TC) remains a challenge in the broader context of numerical weather prediction largely due to their multiscale dynamics. Ocean observations show that the size and magnitude of sea surface temperature (SST) anomalies associated with cold wakes and ocean eddies play important roles in TC dynamics. In this study, a combination of spectral and structure function analyses is utilized to generate realistic realizations of multiscale anomalies characteristic of the SST conditions in which Hurricane Irma (2017) underwent rapid intensification (RI). We investigate the impact of the length scale of these SST anomalies and the role of translation speed on the variance in RI onset timing.

Length-scale-induced convective asymmetries, in addition to the mean magnitude of SST anomalies beneath the storm eye, are shown to modulate the variance in RI onset timing. The size of the associated SST length scales relative to the storm size is critical to the magnitude of variance in RI onset timing, as smaller length scales are shown to lack the spatial extent required to induce preferential convective asymmetries. Storm translation speed is also shown to influence the variance in RI onset timing for larger-length-scale ensembles by altering the exposure time of the eye to these SST anomalies. We find that an interplay between SST-induced convective asymmetries, the magnitude of SST anomalies underneath the eye/eyewall, and storm translation speed play crucial roles in modulating the variance in RI onset timing.

This work is currently published in the Journal of the Atmospheric Sciences.