Tuesday, 13 January 2009: 2:45 PM
A Coupled Ocean-Atmosphere Model for Tropical Cyclone Studies – Boundary Layer Interactions and the Response to Tropical Cyclone Passage
Room 128A (Phoenix Convention Center)
Tropical cyclone (TC) modeling has increased rapidly in recent decades, while the skill for forecasting intensity has not followed suit. One of the hypotheses for the inability of the numerical models to replicate the intensity changes seen in observations is the lack of a realistic ocean and its associated feedbacks into the atmospheric boundary layer immediately above the surface. This study attempts to investigate this hypothesis via a fully coupled ocean-atmosphere modeling system. The atmosphere and ocean models are the Weather Research and Forecast (WRF) Advanced Research WRF (ARW) (Michalakes et al., 2004) and the Hybrid Coordinate Ocean Model (HYCOM) (Bleck, 2002; Chassignet et al., 2003; Halliwell, 2004), respectively. The models are coupled both spatially and temporally via the Model Coupling Toolkit (MCT) (Larson et al., 2005; Jacob et al., 2005). During the coupling phase, a wave model – the Wave Watch III (Tolman, 2002g), is included with flux and sea-state parameterizations valid for high wind speeds (Bourassa, 2006). The TC initial state for WRF-ARW is derived from the H*WIND (Powell and Houston, 1996) and hydrostatic balance constraints.
Results from a series of coupled-model experiments, including events from the 2008 North Atlantic Basin TC season will be presented. The oceanic response is investigated, first, using one-way ocean/atmosphere interactions (ie. the atmosphere forcing the ocean) with and without the wave model. The ocean response will also investigated in a two-way interactive mode (ie. the atmosphere forcing the ocean and the ocean feeding back into the atmosphere), also with and without the wave model. Latent and sensible heat fluxes will be evaluated as well the sea-surface temperature and the response of the upper-ocean mixed layer to TC passage. Conclusions as to the coupled model's successes and failures will be derived based on available observations for the respective experiments.