Tropical cyclogenesis sensitivity and predictability

It has been suggested in a number of previous studies that tropical cyclogenesis may be sensitive to aspects of large-scale forcing as well as mesoscale dynamics that organize areas of deep tropical convection. In this study, we explore the hypothesis that tropical cyclogenesis is sensitive to small perturbations to the basic properties of the background state through organized mesoscale convection and synoptic-scale forcing. The adjoint and tangent linear models for the atmospheric portion of the nonhydrostatic Coupled Atmosphere/Ocean Mesoscale Prediction System (COAMPS) are used to explore the mesoscale sensitivity of tropical cyclogenesis to the initial state. A unique aspect of this system is that an exact adjoint to the explicit microphysics has been developed. The forward, adjoint and tangent linear models are applied at horizontal resolutions ranging from 13-40 km and are used to explore predictability issues for several tropical cyclones and non-developing storms in the Western Pacific including during the 2008 ONR THORPEX Pacific Asian Regional Campaign (T-PARC) and the ONR Tropical Cyclone Structure-08 (TCS08) and the 2010 Interaction of Typhoon and Ocean Project (ITOP).

Results indicate that 24-h forecasts of tropical cyclone formation in the Western Pacific are very sensitive to the initial state. The adjoint-based sensitivity fields indicate highly structured patterns in the wind, thermal, and microphysical fields that project on to the model simulated deep convection, which ultimately influences the intensification rate. Relatively small basic state perturbations based on the adjoint calculations on the order of observational errors (1 m/s, 1 K) lead to rapid growth rates in the near-surface horizontal velocity of more than 15 m/s and 10 hPa deepening rate of the central pressure over 24 h. The sensitivity of tropical cyclogenesis to the sea surface temperature and ocean mixed layer depth also will be addressed using a coupled version of the adjoint modeling system, which makes use of a prognostic ocean mixed layer model.