Ten years of airborne Doppler radar observations are used to study convective updrafts' kinematic and reflectivity structures in tropical cyclone (TC) rainbands. An automated algorithm is developed to identify the strongest rainband updrafts across 12 hurricane‐strength TCs. The selected updrafts are then collectively analyzed by their frequency, radius, azimuthal location (relative to the 200–850 hPa environmental wind shear), structural characteristics, and secondary circulation (radial/vertical) flow pattern. Rainband updrafts become deeper and stronger with increasing radius. A wavenumber‐1 asymmetry arises, showing that in the downshear (upshear) quadrants of the TC, updrafts are more (less) frequent and deeper (shallower). In the downshear quadrants, updrafts primarily have in‐up‐out or in‐up‐in secondary circulation patterns. The in‐up‐out circulation is the most frequent pattern and has the deepest updraft and reflectivity tower. Upshear, the updrafts generally have out‐up‐in or in‐up‐in patterns. The radial flow of the updraft circulations largely follows the vortex‐scale radial flow shear‐induced asymmetry, being increased low‐level inflow (outflow) and midlevel outflow (inflow) in the downshear (upshear) quadrants. It is hypothesized that the convective‐scale circulations are significantly influenced by the vortex‐scale radial flow at the updraft base and top altitudes. Other processes of the convective life cycle, such as bottom‐up decay of aging convective updrafts due to increased low‐level downdrafts, can influence the base altitude and, thus, the base radial flow of the updraft circulation. The findings presented in this study support previous literature regarding convective‐scale patterns of organized rainband convection in a mature, sheared TC.
While the total cover of broken cloud fields can in principle be obtained from one-dimensional measurements, the cloud size distribution normally differs between two-dimensional (area) and one-dimensional retrieval (chord length) methods. In this study, we use output from high-resolution Large Eddy Simulations to generate a transfer function between the two. We retrieve chord lengths and areas for many clouds, and plot the one as a function of the other, and vice versa. We find that the cloud area distribution conditional on the chord length behaves like a gamma distribution with well-behaved parameters, with a mean μ=1.1L and a shape parameter β=L−0.645. Using this information, we are able to generate a transfer function that can adjust the chord length distribution so that it comes much closer to the cloud area distribution. Our transfer function improves the error in predicting the mean cloud size, and is performs without strong biases for smaller sample sizes. However, we find that the method is still has difficulties in accurately predicting the frequency of occurrence of the largest cloud sizes.
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