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Numerical Simulation of the Effects of Mesoscale Convergence on Convective Rain Showers

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  • 1 Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, Alberta, Canada
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Abstract

A nonhydrostatic axisymmetric cloud model is used to quantify the effects of persistent mesoscale convergence on cumulus development and convective rainfall. The model was initialized by environmental conditions adopted from sounding and Doppler radar velocity data sampled on 19 August 1992 in central Alberta. The sounding showed a moist warm air mass with a moderate amount of convective available potential energy and the wind field had boundary layer convergence but almost no vertical shear in the lowest 5 km. The simulated rainfall intensity and accumulation compared well with radar observations.

The dependence of the convective rainfall on the characteristics of the convergence zone is investigated by intercomparing model simulators with different convergence magnitudes, convergence depths, and convergence profiles. Increasing the magnitude or the depth of convergence causes stronger convection and more precipitation. Rainfall increases monotonically (but nonstrictly linearly) with the convergence magnitude. Doubling the convergence magnitude from 1 × 10−4 to 2 × 10−4 s−1 increases the rainfall by a factor of 2.6, while rainfall increases by only 2.3 times when the convergence is doubled from 1.25 × 10−4 to 2.5 × 10−4 s−1. The nonlinear effects become even more apparent when changing the depth of convergent layers. Even when keeping the vertical mass flux constant, the depth of the convergence affects greatly the timing and amount of the surface rainfall. This is related to the fact that humidity tends to decrease with height and therefore the upward moisture flux is weakest for the deepest convergence layer for a fixed upward momentum flux. The model suggests that rainfall is mostly controlled by the amount of vapor converging into the column below cloud base.

Abstract

A nonhydrostatic axisymmetric cloud model is used to quantify the effects of persistent mesoscale convergence on cumulus development and convective rainfall. The model was initialized by environmental conditions adopted from sounding and Doppler radar velocity data sampled on 19 August 1992 in central Alberta. The sounding showed a moist warm air mass with a moderate amount of convective available potential energy and the wind field had boundary layer convergence but almost no vertical shear in the lowest 5 km. The simulated rainfall intensity and accumulation compared well with radar observations.

The dependence of the convective rainfall on the characteristics of the convergence zone is investigated by intercomparing model simulators with different convergence magnitudes, convergence depths, and convergence profiles. Increasing the magnitude or the depth of convergence causes stronger convection and more precipitation. Rainfall increases monotonically (but nonstrictly linearly) with the convergence magnitude. Doubling the convergence magnitude from 1 × 10−4 to 2 × 10−4 s−1 increases the rainfall by a factor of 2.6, while rainfall increases by only 2.3 times when the convergence is doubled from 1.25 × 10−4 to 2.5 × 10−4 s−1. The nonlinear effects become even more apparent when changing the depth of convergent layers. Even when keeping the vertical mass flux constant, the depth of the convergence affects greatly the timing and amount of the surface rainfall. This is related to the fact that humidity tends to decrease with height and therefore the upward moisture flux is weakest for the deepest convergence layer for a fixed upward momentum flux. The model suggests that rainfall is mostly controlled by the amount of vapor converging into the column below cloud base.

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