Quantifying the Impact of UAS-Sensed Data on High-Resolution, Limited-Area WRF Forecasts Using NCAR’s Data Assimilation Research Testbed (DART)

High-resolution, short-term, limited-area WRF forecasts were provided by NCAR for the 2018 ISARRA flight week (LAPSE-RATE) in Colorado’s San Luis Valley. During the flight week, UASs outfitted with temperature, humidity, and wind sensors were flown at various locations in the valley, targeting specific weather phenomena (e.g. drainage flows, the pre-convection initiation environment, and morning boundary layer evolution). These observations provide high spatial and temporal resolution data of the lower atmosphere in data-sparse regions. The potential of assimilating UAS-sensed data into mesoscale models to improve fine-scale predictions of low-level winds and turbulence is assessed by performing a series of data assimilation experiments using the Ensemble Adjustment Kalman Filter (EAKF) available within DART. Simulations with and without UAS data assimilation are performed for a drainage flow case in which a targeted swarm of UAS was deployed to sample a region where drainage flow winds were predicted. Methods developed to assimilate UAS data into a high resolution model using EAKF and corresponding challenges will be discussed.