292 Aerosol Effects on Simulated Supercell Thunderstorms in Environments with Different Relative Humidity and Vertical Wind Shear

Wednesday, 9 July 2014
Evan A. Kalina, Univ. of Colorado, Boulder, CO; and K. Friedrich, H. Morrison, and G. H. Bryan
Manuscript (2.0 MB)

Handout (3.8 MB)

A variety of convective modes have been shown to exhibit sensitivity to aerosol concentration, yet there is a lack of research that examines the changes in microphysical processes, cold pool size and strength, and accumulated precipitation across the continuum of realistic aerosol concentrations, particularly in supercell thunderstorms. Here, we simulate a supercell thunderstorm (Fig. 1) at 1-km grid spacing with the Weather Research and Forecasting (WRF) model, using 15 different cloud condensation nuclei (CCN) concentrations (ranging from 100 cm-3 to 10 000 cm-3) and four different environmental soundings with varying low-level relative humidity (RH) and vertical wind shear values (Fig. 2). The Morrison double-moment microphysics scheme is used with modifications to include explicit prediction of cloud droplet number concentration and a variable shape parameter for the raindrop size distribution.

Results indicate that additional changes in the microphysical process rates are negligible beyond CCN = 3000 cm-3 (Fig. 3). Changes in cold pool characteristics with CCN concentration, however, are non-monotonic and highly dependent on the environmental conditions (Fig. 4). In moist conditions with moderate vertical wind shear, the cold pool area is nearly constant with respect to CCN concentration (Fig. 4a and Fig. 4b), while the area is reduced by 84% (Fig. 4c) and 22% (Fig. 4d) in the soundings with dry RH and large vertical wind shear, respectively. With the exception of the dry RH sounding, domain-averaged precipitation peaks between 500 cm-3 and 5000 cm-3, after which it remains constant or slowly decreases (Fig. 5). For the dry RH sounding, the domain-averaged precipitation monotonically decreases with CCN concentration (Fig. 5c). The different responses for moist and dry soundings are mostly attributable to the enhanced (decreased) latent cooling from melting hail near the surface in the moist (dry) soundings as CCN concentration increases. Spatial plots of accumulated precipitation reveal enhancement (by up to 25 mm) near and to the immediate left of the left- and right-moving updraft tracks, except for the dry RH sounding (Fig. 6).

Finally, the sensitivity of the results to whether the shape parameter (μ) in the raindrop size distribution is allowed to vary is investigated (Fig. 7). In moist conditions with moderate vertical wind shear, the size of the cold pool decreases by ~13% as the CCN concentration increases in the μ = 0 runs (Fig. 7b), while little change occurs when μ is allowed to vary (Fig. 4a). Domain-averaged precipitation also slowly decreases with CCN concentration when μ = 0 (Fig. 7c), despite increasing between CCN = 100 cm-3 and CCN = 5000 cm-3 in the variable μ runs (Fig. 5a). The differences between the two sets of simulations are due to a larger reduction in low-level latent cooling with CCN concentration in the μ = 0 simulations, likely caused by differences in the aggressiveness of size sorting between the μ = 0 and variable μ simulations.

Fig. 1. Horizontal cross-sections of simulated radar reflectivity (assuming a 10-cm wavelength) at z = 1 km AGL at a) t = 30 min, b) t = 60 min, c) t = 90 min, and d) t = 120 min using the default (def) sounding and a CCN concentration of 10 000 cm-3.

Fig. 2. Skew-T log-P diagram with the soundings used to initialize the WRF model, including the default (def) sounding and the soundings used for the sensitivity tests: low relative humidity (loRH; dashed line), high relative humidity (hiRH; dotted line), and high vertical wind shear (hiWS; rightmost wind barbs). The solid red line is the temperature profile, while the dewpoint temperature profiles are shown in blue. The wind speed and direction are represented by two sets of wind barbs on the right side of the diagram: one set for the hiWS sensitivity test and one set for all other simulations (def).

Fig. 3. Vertically integrated, horizontally averaged microphysical process rates versus CCN concentration at t = 120 min for a) def, b) hiRH, c) loRH, and d) hiWS soundings.

Fig. 4. Total area (solid lines) and mean perturbation potential temperature (dashed lines) of the cold pool at the lowest model level (z = 170 m) at t = 100 min (blue lines) and t = 120 min (red lines) versus CCN concentration for a) def, b) hiRH, c) loRH, and d) hiWS soundings.

Fig. 5. Domain-averaged, accumulated surface precipitation at t = 90 min (blue line), t = 100 min (green line), t = 110 min (yellow line), and t = 120 min (red line) versus CCN concentration for a) def, b) hiRH, c) loRH, and d) hiWS soundings.

Fig. 6. Difference in accumulated surface precipitation between the dirtiest (CCN = 10 000 cm-3) and cleanest (CCN = 100 cm-3) simulations at t = 120 min (color fill) for a) def, b) hiRH, c) loRH, and d) hiWS soundings. The purple and black contours indicate the maximum updraft speeds that were observed at z = 5 km for the duration of the cleanest and dirtiest simulations, respectively. These contours range from 10 m s-1 to 30 m s-1 at an interval of 10 m s-1. The approximate locations of the main left- and right-moving updrafts at several times during the simulations are also indicated.

Fig. 7. As in a) Fig. 3, b) Fig. 4, c) Fig. 5, and d) Fig. 6, but for simulations with the default sounding and the shape parameter μ in the raindrop size distribution set to zero.

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