Impact of assimilating uncrewed aircraft system observations on river valley fog prediction

Two multirotor UASs were deployed during Frequent in situ Observations above Ground for Modeling and Advanced Prediction of fog (FOGMAP) which took place during the summer of 2022 in northern Kentucky. Targeted UAS missions were flown to sample the spatiotemporal variability of temperature and moisture in the vicinity of the Cincinnati/Northern Kentucky International Airport.

During each mission, the UAS performed near-continuous profiling at two locations between the surface to 120 m AGL throughout the night. Data denial experiments were performed using the ensemble adjustment Kalman filter available in NSF NCAR’s Data Assimilation Research Testbed (DART) to determine the impact of assimilating UAS observations on the skill of analyses and forecasts issued during potential fog events. Simulations that only assimilated conventional observations tended to have a dry bias in the analyses and forecasts.