Coupled models to predict tropical cyclone intensity and structure change will eventually be used to issue forecasts to the public who increasingly rely on the most advanced weather forecasting systems to prepare for landfall. It has become increasingly clear over the past decade that ocean models will have to include realistic initial conditions to simulate not only the oceanic response to hurricane forcing, but also to simulate the atmospheric response to oceanic forcing. There are now countless examples of this phenomena in the global problem. One clear example occurred due south of New Orleans during the passages of Katrina and Rita (2005) as they both explosively deepened over the Gulf of Mexico's Loop Current and the warm core eddy. The observed intensity changes were more correlated with the ocean heat content (OHC) variations (and deep isotherms) than with the relatively flat sea surface temperature distribution. One effective approach to monitor the OHC is through utilization of satellite altimetry when combined with improved climatologies and ARGO profiling floats.

In-situ measurements acquired prior, during and subsequent to hurricane passage have improved over the past two decades with the emergence of aircraft technologies. Given the need for both momentum and thermal structure, aircraft expendable current profilers have yielded significant insights into the shear-induced mixing processes across the base of the wind-forced mixed layer from several experiments including the NOAA/ONR sponsored Hurricane Gilbert (1988) wake experiments. Given the need for the evolving thermal, momentum and haline structures, Lagrangian floats and drifters have added critical data to our knowledge base in the wake structures such as Frances (2004) and more recently in the ONR sponsored ITOP experiment in the western Pacific Ocean (2010). Lagrangian technologies when complemented with aircraft based measurements from synoptic Eulerian grids increase our ability to measure the oceanic parts of the coupled system approaching the same resolution and accuracy as the atmospheric part. Moreover, optimal utilization of advanced high frequency radar technology to map currents, winds, and waves in real time provide much needed data in the coastal oceans to improve surge and inundation models that are also part of the coupled predictive systems.

Data assimilation is an effective method for providing initial and boundary conditions to the ocean component of coupled tropical cyclone prediction models. The thermal energy available to intensify and maintain a storm depends temperature, salinity and thickness of the upper ocean warm layer. Using a blend of satellite and in-situ data sets, the ocean model must be initialized so that the dynamical ocean features such as warm (cold) eddies associated with relatively large (small) OHC values are in the correct locations relative to the forecasted tracks. Upper-ocean heat and momentum budgets and the ensuing sea-air fluxes also require a carefully evaluated choice of entrainment mixing schemes. While this remains an open question, little is known about how kinetic energy input from the surface wind stress into the ocean is dissipated and redistributed by small-scale turbulent mixing processes in the mixed layer under tropical cyclone force winds. This sub-grid scale process needs to be explored with new technologies such as self-propelled autonomous underwater vehicles capable of measuring oceanic variables at higher spatial and temporal sampling than possible with the current suite of instruments.

By carefully combining these various mature and emerging technologies for observing and modeling, we can build realistic oceanic components required for the coupling to atmospheric models. From a Global perspective, this melding of various technologies represents transformative science to improve predictive coupled modes. The end-user of this transformative science is the public who increasingly rely on accurate information from forecasters to adequately prepare for severe landfalling systems.