Using 4d-VAR to Move a Simulated Tropical Cyclone in a Mesoscale Model

It is shown that four-dimensional variational analysis (4d-VAR) is a data assimilation technique that has promise for calculating optimal perturbations for weather modification. Experiments described here demonstrate the ability of 4d-VAR to calculate perturbations to influence the future path of a simulated tropical cyclone. In “target” experiments, the Penn State/NCAR Mesoscale Model 5 4d-VAR system determines the optimal atmospheric state trajectory which simultaneously minimizes the size of the initial perturbation and the difference (using a quadratic norm) between the new forecast state and a goal atmospheric state in which the simulated cyclone has been repositioned. In experiments for Hurricane Iniki, the simulated hurricane successfully matched the goal state at the end of the 4d-VAR period, then continued on a track parallel to its original track, and missed the Hawaiian Island of Kauai. Perturbations to the initial conditions are small relative to the hurricane. When changes are restricted to the temperature field alone, the technique is less successful.