Assimilating Radar and Lidar Observations to Improve the Prediction of Bore Waves during the 2015 PECAN Field Campaign

This study assimilates reflectivity and radial velocity from the WSR-88D (NEXRAD) radar and lidar water vapor profiles observed during the 2015 Plains Elevated Convection at Night (PECAN) field campaign. The objective of PECAN is to improve the understanding and simulation of the processes that initiate and maintain convection and convective precipitation at night over the central portion of the Great Plains region of the United States. The assimilation of radar reflectivity and radial velocity observations could improve the forecast of location and timing of bore. The model and data assimilation system employed is the Pennsylvania State University (PSU) Weather Research and Forecasting model Ensemble Kalman Filter (WRF-EnKF) cycling data assimilation system. The lidars include the Atmospheric Lidar for Validation, Interagency Collaboration and Education (ALVICE), University of Wyoming King Air compact Raman lidar, Atmospheric Radiation Measurement (ARM) Raman lidar, and NCAR micropulse Differential Absorption Lidar (DIAL). The bore propagation was observed by radar in Kansas, on 14 July 2015, and a nocturnal convection initiated in close proximity to the bore/density current. Raman lidar water vapor mixing ratio observation shows that the bore structure was initiated at 7:00 UTC and lasted until 7:45 UTC on 14 July 2015 at Fixed PISA 2 (FP2). Without assimilating any observations, the WRF model simulation shows that model missed the location of the bore, even though it captured the bore structure quite well. We will show the results of assimilating lidar water vapor and surrounding WSR-88D radar observations with the goal of improving the location of the forecast convection and the timing of the resulting bore.