%ARios-Berrios, Rosimar [National Center for Atmospheric Research, Boulder, Colorado]%BJournal Name: Journal of the Atmospheric Sciences; Journal Volume: 77; Journal Issue: 2; Related Information: CHORUS Timestamp: 2020-12-07 17:54:55 %D2020%IAmerican Meteorological Society %JJournal Name: Journal of the Atmospheric Sciences; Journal Volume: 77; Journal Issue: 2; Related Information: CHORUS Timestamp: 2020-12-07 17:54:55 %K %MOSTI ID: 10133632 %PMedium: X %TImpacts of Radiation and Cold Pools on the Intensity and Vortex Tilt of Weak Tropical Cyclones Interacting with Vertical Wind Shear %XAbstract

Idealized numerical simulations of weak tropical cyclones (e.g., tropical depressions and tropical storms) in sheared environments indicate that vortex tilt reduction and convective symmetrization are key structural changes that can precede intensification. Through a series of ensembles of idealized numerical simulations, this study demonstrates that including radiation in the simulations affects the timing and variability of those structural changes. The underlying reason for those effects is a background thermodynamic profile with reduced energy available to fuel strong downdrafts; such a profile leads to weaker lower-tropospheric ventilation, greater azimuthal coverage of clouds and precipitation, and smaller vortex tilt with radiation. Consequently, the simulations with radiation allow for earlier intensification at stronger shear magnitudes than without radiation. An unexpected finding from this work is a reduction of both vortex tilt and intensity variability with radiation in environments with 5 m s−1 deep-layer shear. This reduction stems from reduced variability in nonlinear feedbacks between lower-tropospheric ventilation, cold pools, convection, and vortex tilt. Sensitivity experiments confirm the relationship between those processes and suggest that microphysical processes (e.g., rain evaporation) are major sources of uncertainty in the representation of weak, sheared tropical cyclones in numerical weather prediction models.

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