Results of Simulations

In all runs the tracks of the simulated storms were actually similar and close to that of Katrina. The observed and simulated minimum pressures of the storm with time are shown in Fig. 6. The WRF model used does not allow exact assimilation of the initial TC intensity, so that the modelled hurricane was initially weaker than the real one. Nevertheless, the model was able to reproduce the main features of the hurricanes evolution, including the formation of the super hurricane with the minimum pressure of about 915-920 hPa. The main result that follows from Fig. 6 is that aerosols, affecting the hurricane clouds, affect both its structure and intensity. One can see that TC moving within a dirty air has smaller intensity that in that moving in clean air during the entire simulation. This effect (see below) can be attributed to the convection invigoration at TC periphery, which was caused

WRF Forecast for Hurricane Katrina Min Sea Level Pressure 28/8/05 12Z - 29/8/05 21Z , every 3hr

WRF Forecast for Hurricane Katrina Min Sea Level Pressure 28/8/05 12Z - 29/8/05 21Z , every 3hr

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Fig. 6 The observed and simulated minimum pressures of the storm with time The WRF model used does not allow exact assimilation of the initial TC intensity, and the modelled hurricane was initially weaker than the real one. Nevertheless, the model was able to reproduce the main features of the hurricanes evolution, including the formation of the super hurricane with the minimum pressure of about 915-920 hPa. The warm rain prevention at the TC periphery decreased minimum pressure by 7-10 mb

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Fig. 6 The observed and simulated minimum pressures of the storm with time The WRF model used does not allow exact assimilation of the initial TC intensity, and the modelled hurricane was initially weaker than the real one. Nevertheless, the model was able to reproduce the main features of the hurricanes evolution, including the formation of the super hurricane with the minimum pressure of about 915-920 hPa. The warm rain prevention at the TC periphery decreased minimum pressure by 7-10 mb by turning off the warm rain (representative of the potential impacts of high concentrations of aerosols on formation of droplets). As a result, some fraction of air moving within the inflow layer ascends at the periphery instead reaching the TC eye wall. Hence, the rate of latent heat release decreases within the eye wall, which results in some increase in the central pressure and increase in the maximum wind (and eyewall) radius.

Figure 7 illustrates the aerosol effects (as it was simulated by in the study) on microphysical and dynamical structure of the TC. One can see a good qualitative correspondence of obtained values of super cooled CWC and those found in the 2-D cloud simulations: the CWC maximum in dirty air is about 5 gkg-1, while in the clean air it does not exceed 2 gkg-1. One can see an aerosol-induced increase in the total ice content at the TC periphery in agreement with the results of the 2D model with the spectral microphysics. The maximum values of total ice content are also in good agreement with the 2-D results. The difference in the condensate mass contents in simulations WR and NWRP-30 indicates the differences in the latent heat release and the vertical updrafts (the third row panels). The maximum vertical velocity in many small clouds arising in dirty air exceeds 10 ms-1, while in the TC central zone the typical maximum vertical velocity ranges mainly from 4 to 10 ms_1. One can see that aerosols increase the intensity of convection within cloud bands

Fig. 7 Maximum values of super cooled CWC above the 5 km-level (upper row), total ice content (middle) and vertical velocities at t = 6 h in simulations with warm rain permitted (left) and no warm rain (right)

located at the distance of 250-300 km from the TC center. This radius corresponds to the TC remote cloud bands. Analysis of the vertical cross-sections of the differences of azimuthally averaged fields of total ice content (Qice), cloud water content (Qc), rain content (Qr), and vertical velocity between NWRP30 and WR runs (Fig. 8). One can see that aerosols invigorate convection and increase precipitation at the distance of about 250 km, decreasing, at the same time, the convection intensity between the remote rain bands and the eye wall. As a result, convection within the circle with radius of about 250 km weakens, preventing intense lightning at closer distance to the TC center.

As was discussed above, an increase of CWC and ice content in the zones of high vertical velocity should foster lightning formation. Figure 9 shows the fields representing the product of CWC and ice mass contents of low and high density ice. This product will be referred to as lightning probability (LP). This product is maximum within the area of maximum updrafts. The Fig. 9 (upper right panel) is plotted at time instance of lightning activity depicted in Fig. 1 (left and middle panel). One can see that LP field calculated in NWRP-30 resembles very well the

Fig. 8 The vertical cross-sections of (NWRP30-WR) differences of azimuthally averaged fields of total ice content Qtice, cloud water content (Qc), rain content (Qr), and vertical velocity. One can see that aerosols invigorate convection (and precipitation) at the distance about 250 km (the differences are positive), decreasing at the same time the convection intensity between the remote rain bands and the eye wall. As a result, convection within the about 250 km radius circle weakens, preventing intense lightning at closer distance to the TC center

Fig. 8 The vertical cross-sections of (NWRP30-WR) differences of azimuthally averaged fields of total ice content Qtice, cloud water content (Qc), rain content (Qr), and vertical velocity. One can see that aerosols invigorate convection (and precipitation) at the distance about 250 km (the differences are positive), decreasing at the same time the convection intensity between the remote rain bands and the eye wall. As a result, convection within the about 250 km radius circle weakens, preventing intense lightning at closer distance to the TC center

Fig. 9 Lightning probability (LP) (relative units) accumulated for different time periods of TC evolution in case of clouds developing in clean air (left) and dirty air (right). The LP is calculated as a product of updrafts, CWC and total ice content. In the upper row LP is calculated for the period t = 3-6 hours, and in the bottom row LP for the period t = 24-27 hours

Fig. 9 Lightning probability (LP) (relative units) accumulated for different time periods of TC evolution in case of clouds developing in clean air (left) and dirty air (right). The LP is calculated as a product of updrafts, CWC and total ice content. In the upper row LP is calculated for the period t = 3-6 hours, and in the bottom row LP for the period t = 24-27 hours structure of observed lightning: a) the maximum lightning takes place within a comparatively narrow ring of the 250-300 km radius; Time averaging of the LP over the period of a few hours results in appearance of several rings of enhanced lightning related to different time instances: b) lightning at TC central zone is as a rule weaker than at the rain bands at TC periphery. In contrast, in the WR simulation lightning is much weaker and concentrated in the eye wall, which does not agree with the observations. The lower panels correspond to time when the entire TC has penetrated to the land and rapidly decays. One can see that while in clean air lightning weakens over the land, it continues in dirty air. Moreover, the lightning rate increases in the TC central zone. These figures show that aerosols significantly affect the spatial distribution of intense convection in TCs.

The results indicate also that aerosols affect cloud structure, intensity and spatial distribution of precipitation of TCs approaching and penetrating the land. Figure 10

Fig. 10 The field of precipitation rate in the experiment with warm rain allowed over the entire computational area (WR-simulation) (left) and in case when warm rain has been turned off at the TC periphery (NWRP-30) (right) during the TC landfall

shows the fields of precipitation rate in the experiment with warm rain allowed over the entire computational area (WR-simulation) and in case when warm rain has been turned off at the TC periphery (NWRP-30). One can see that in case the aerosol effects are taken into account, precipitation takes place over larger area, but the intensity in the TC center is weaker.

Figure 11 shows time dependences of precipitation averaged over 3 h periods within the TC zone (the internal grid) in ''warm rain'' and ''no warm rain'' simulations. During first 5 hours precipitation rate in the NWRP-30 is larger than in the WR run, supposedly due to increase of precipitation at the TC perephery. Later on, an increase in the aerosol concentration decreases precipitation within the TC zone, because the decrease in precipitation rate in the central zone of the TC. These results can serve as numerical justification and explanation of the observed weekly cycle of intensity and precipitation of landfalling TCs found by Cerveny and Balling (1998) who attributed these changes to the weekly variation of anthropogenic aerosol concentration.

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