Assimilation of Ground-based Remote Sensing Observations into Storm-scale NWP for a Tornadic Event during PECAN Field Campaign

This study will examine the impact of assimilating thermodynamic and wind variables within the boundary layer from ground-based remote sensing observations on the analyses and ensemble forecasts of a tornadic event near Nickerson, Kansas on the evening of July 13, 2015. This EF3 tornadic event occurred during the Plains Elevated Convection at Night (PECAN) field campaign that took place from 1 June to 15 July 2015 in the Central Plains of the United States. During the field campaign Doppler Lidar and Atmospheric Emitted Radiance Interferometer (AERI) instrument were deployed. The Doppler Lidar measures the horizontal wind speed, direction and vertical velocities through the boundary layer or up to cloud-base (which ever is lower).  The AERI measures downwelling infrared radiation from which temperature and moisture profiles in the boundary layer up to ~ 3 km can be retrieved. Therefore, the combination of these two instruments provides high-temporal resolution observations of the boundary layer thermodynamic and kinematic evolution and structure. These observations are assimilated into a multiscale ensemble system with a 15 km grid spacing over the CONUS and 3 km grid spacing over Kansas and parts of surrounding states using an ensemble Kalman filter (EnKF) data assimilation technique. Two sets of data assimilation and forecast experiments will be conducted.  One experiment will only assimilate routinely available observations from metar, radiosonde, acars, satellite derive winds and marine platforms every hour and another experiment will assimilate Doppler Lidar and AERI observations in addition to the routinely available observations. Very short-term ensemble forecasts will be launched from the 3-km storm-scale ensemble. The impact of assimilating remote sensing observations in the ensemble forecast will be evaluated using both qualitative and quantitative verification metrics.