Monday, 3 November 2014: 5:00 PM
Madison Ballroom (Madison Concourse Hotel)
Violent tornadoes in the Southeast and Central US during spring are often accompanied by smoke from biomass burning in Central America. We analyzed the effect of smoke on a historic severe weather outbreak that occurred 27 April 2011 using a coupled aerosol, chemistry and weather model (WRF-Chem system) along with aerosol optical depth (AOD) data assimilation (GSI system) and a suite of satellite and ground-based observations. Smoke from Central American biomass burning was present in the boundary layer and lower free troposphere before and during the storm outbreak. Simulations show that adding smoke to the environment already conducive to severe thunderstorm development increases the likelihood of significant tornado occurrence, which is assessed by analyzing effects of smoke on meteorological conditions (tornado parameters) used by prediction centers to forecast tornado occurrence and severity. Further analysis shows that the mechanism responsible for the parameter intensification has two parts. First, through indirect effects, stratiform clouds present during and before the outbreak became optically thicker, which reduced the amount of solar radiation reaching the ground and produced more stable conditions and higher low-level shear in the mixed layer. Second, through semi-direct effects, soot contained in the smoke heated the aerosol layer stabilizing the atmosphere and enhancing cloud cover below the aerosol layer, producing a more stable boundary layer and conditions leading to higher probability of violent tornadoes. This mechanism was assessed for other outbreaks occurring over multiple years showing that similar effects were often found, and the conditions for which the smoke intensifies these events will be summarized. The inclusion of aerosol-cloud-radiation interactions in weather forecasts may help improve the predictability of these extreme events, which can improve the timeliness and accuracy of severe weather alerts within future operational forecast systems.
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