Potential sources of variability in the vortex precession process prior to the onset of tropical cyclone rapid intensification

Predictions of significant changes in tropical cyclone (TC) intensity, particularly rapid intensification (RI), have emerged as a more challenging topic than forecasting TC tracks, since intensification of TCs involves multi-scale physical processes with significant contributions from convective-scale phenomena. Before the onset of RI, intensifying TCs are known to experience a precession process, in which a tilted vortex rotates counter-clockwise around the center of circulation and the developing storm attains an axisymmetric structure. From both modeling and observational studies, there is an agreement in the qualitative features of the precession process among TCs, but the quantitative features, such as the vortex tilt magnitude, the duration of the precession process, and whether or not the vortex is able to complete the precession process, vary among TCs. The predictability of the variety of precession processes and subsequent RI is reported to be ultimately dominated by the chaotic nature of moist convection, which controls the timing of RI. Given the large influence of RI on TC intensity forecasts, it is important to advance the understanding of its sources of uncertainty.

In this study, we have explored the characteristics of the vortex structures that undergo a short/long/incomplete precession process using a simple toy-model of the vortex precession process, together with fully dynamic sensitivity experiments using convection-permitting Weather Research and Forecasting model (WRF-ARW) simulations with modified moisture initializations. It is found that there are potential thresholds in the strength of the vortex that govern whether it will complete the precession process and initiate RI, and that convective processes within the inner-core region played a key role in the RI for Hurricane Harvey. More systematic analysis with a large number of cases will be conducted to reveal which observations may effectively constrain the onset of RI and lead to further advancements in TC forecasting.