Observation Targeting

Observations of small-scale atmospheric prcesses become critical for convection-allowing model forecasts when convective processes are explicitly simulated. However, the selection of additional observations to improve forecasts is often subjective, even though objective methods exist to select observations in dynamically relevant regions. Ensemble sensitivity analysis (ESA) provides a framework to determine additional observing locations that dynamically relate earlier state variables (e.g., 2-m temperature) and a particular forecast metric (e.g., reflectivity) to reduce forecast uncertainty after the new observation is assimilated. I have examined ESA-based targeting at convection-allowing resolutions in idealized simulations (e.g., Hill et al. 2020b) and continue to explore its utility for real-data cases and storm-scale applications, for instance, targeting in-storm observations with Unmanned Aerial Systems and assimilating them into CM1 model simulations.