Multi-Scale Data Assimilation of the 13 June 2010 Tornadic Supercell Storm Environment during VORTEX2

Multi-Scale Data Assimilation of the June 13, 2010 Tornadic Supercell Storm Environment during VORTEX2 Therese Thompson, Glen Romine, Louis Wicker, Xuguang Wang

The success of ensemble data assimilation (hereafter DA) at convective-scales is limited by a number of challenges, including the difficulties associated with accurately analyzing mesoscale phenomenon in the storm environment. A promising new technique combines radar DA with simultaneous assimilation of conventional observations, hereafter referred to as multi-scale DA. A framework for multi-scale DA is developed to enable accurate analysis of both storms and their parent environment.

Multi-scale DA is applied to the 13 June 2010 case during VORTEX2. On 13 June a cold pool from overnight convection created an outflow boundary that was located near the Oklahoma-Texas Panhandle border in the afternoon. New convection developed along a cold front in the Texas Panhandle. The sub-severe convection slowly moved to the northeast and a cell moved over the intersection of the two boundaries, intensified, gained supercell characteristics, and became tornadic. This case represents a complex mesoscale environment and storm evolution that was not captured well with conventional observations or WSR-88D radars. Thus, this case presents a challenging event to analyze and predict, and will demonstrate the benefit of multi-scale DA in generating initial conditions for ensemble forecasts.

A mesoscale WRF model domain (15 km horizontal grid resolution), and a nested convective-allowing WRF model domain (3 km horizontal grid resolution), are used along with the DART data assimilation toolkit for the analysis and forecast of the storm environment and convection on 13 June 2010. Several aspects of multi-scale DA cycling are investigated through comparisons of ensemble forecast performance relative to a control 6-hourly cycled analysis system. Results indicate that increased cycling frequency of conventional observations improves forecasts of the mesoscale storm environment and convection. The addition of radar observations in hourly DA cycling leads to further improvement in forecast skill, which is tied to better forecasts of the outflow boundary from overnight convection and subsequent convective evolution. Lastly, the initialization of the multi-scale DA system is found to have an impact on the characteristics of the near-storm environment.