Open Access
Idealized Tropical Cyclone Responses to the Height and Depth of Environmental Vertical Wind Shear
Author(s) -
Peter M. Finocchio,
Sharanya J. Majumdar,
David S. Nolan,
Mohamed Iskandarani
Publication year - 2016
Publication title -
monthly weather review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.862
H-Index - 179
eISSN - 1520-0493
pISSN - 0027-0644
DOI - 10.1175/mwr-d-15-0320.1
Subject(s) - wind shear , geology , vortex , tropical cyclone , shear (geology) , eye , atmospheric sciences , troposphere , wind gradient , wind speed , meteorology , thermal wind , climatology , physics , petrology , oceanography
Three sets of idealized, cloud-resolving simulations are performed to investigate the sensitivity of tropical cyclone (TC) structure and intensity to the height and depth of environmental vertical wind shear. In the first two sets of simulations, shear height and depth are varied independently; in the third set, orthogonal polynomial expansions are used to facilitate a joint sensitivity analysis. Despite all simulations having the same westerly deep-layer (200–850 hPa) shear of 10 m s−1, different intensity and structural evolutions are observed, suggesting the deep-layer shear alone may not be sufficient for understanding or predicting the impact of vertical wind shear on TCs. In general, vertical wind shear that is shallower and lower in the troposphere is more destructive to model TCs because it tilts the TC vortex farther into the downshear-left quadrant. The vortices that tilt the most are unable to precess upshear and realign, resulting in their failure to intensify. Shear height appears to modulate this tilt response by modifying the thermodynamic environment above the developing vortex early in the simulations, while shear depth modulates the tilt response by controlling the vertical extent of the convective vortex. It is also found that TC intensity predictability is reduced in a narrow range of shear heights and depths. This result underscores the importance of accurately observing the large-scale environmental flow for improving TC intensity forecasts, and for anticipating when such forecasts are likely to have large errors.