Impact of Adjoint-Derived Optimal Perturbations on Tropical Cyclone Intensity Forecasts

Tropical cyclone intensity change forecasts remain a challenge, due to model limitations and initial conditions errors and uncertainties. Adjoint-derived sensitivities to initial conditions can help determine the key dynamical and thermodynamical processes that influence the intensity. This presentation describes the results of a case study of Hurricane Harvey (2017) – an underforecast rapidly intensifying tropical cyclone. The response functions chosen for this study include the perturbation dry air mass in a column above the tropical cyclone center, the pressure tendency following the cyclone center, and difference in forecasted pressure and maximum potential intensity. Guided by adjoint-derived sensitivities, optimal perturbations, on order of typical analysis error, are calculated to understand how changes to the initial state will evolve dynamically to influence the TC’s intensity. Diagnosis of the perturbation evolution points to key dynamical processes influencing TC intensification. The implications of these results on the efficacy of targeted observing for this cyclone will be discussed.