Henry R. Winterbottom, Eric P. Chassignet, and Carol Anne Clayson

1. Tropical Cyclone Vortex Specification The HYbrid Coordinate Ocean Model (HYCOM) (Bleck, 2002; Chassignet et al., 2003; Halliwell, 2004) is the ocean model while the Advanced Research Weather Research and Forecasting (WRF-ARW) (Michalakes et al., 2004) is the atmospheric model. This modeling system is in the process of being coupled via the Model Coupling Toolkit (MCT). During the atmosphere and ocean coupling phase, a wave model parameterization (Wave-Watch III; Tolman, 2002) will be used TCs within the modeling system are constructed using available in-situ observations for surface winds. Composite profiles which define the thermodynamic and kinematic structures of TCs are prescribed and balanced constraints are applied during the construction of the vortex in order to compensate for numerical model induced gradient and geostrophic adjustments. Figure 3 illustrates the GFS first-guess and H*WIND derived surface wind analyses for TC Ike (2008). Figure 3: Surface wind analysis for TC Ike (2008) at 00Z 09 September for GFS (left) and H*WIND analysis (right). Shading is wind speed (kts) and black contours are sea-level pressure (hPa). Initial Results Figure 1: WRF-ARW 2-minute topography (13 km) and HYCOM 2-minute bathymetry (0.08 degree) for coupled ocean-atmosphere modeling system. Currently, the modeling system is run in one-way mode (i.e.. the atmosphere forcing ocean without an ocean feedback). The ocean model initial conditions and boundary conditions are from the GODAE global HYCOM ocean prediction system (www.hycom.org). Near real-time model run results can be viewed online at the following sites: together with flux parameterizations derived from observations within high-wind speed environments (Bourassa, 2006). Finally, in an effort to better represent the TC structure at model initialization, a vortex specification methodology is employed which makes used of near real-time analyses (H*WIND; Powell and Houston, 1996) and composite profiles for boundary layer wind speeds and troposphere thermodynamics. This presentation high-lights the aspects of the coupling configuration and the initialization of the atmospheric model via the synthetic vortex methodology. WRF-ARW: http://www.coaps.fsu.edu/~hwinter/wrfarwtc HYCOM: http://www.coaps.fsu.edu/~hwinter/hycomtc Figure 4 provides an example of ocean variables related to TC forecasting. Model Coupling HYCOM and WRF-ARW are co-located as shown in Figure 1. The bathymetry and terrain resolutions are 2-minute and the grid resolutions at 1/12 degree and 8.81-km, respectively. Model initial and lateral boundary conditions are obtained from the 1/12 degree global HYCOM and 0.5 degree GFS. Figure 4: WRF-ARW/HYCOM one-way coupled model ocean forecast. TC heat- potential (left) and upper 50-meter ocean heat-content (right). Figure 2: Coupled-model feedback loop. Henry R. Winterbottom, Eric P. Chassignet, and Carol Anne Clayson A Coupled Atmosphere-Ocean Model System for Tropical Cyclone Studies Motivation Alternative coupling methodologies (other than MCT) are also being explored including the MCEL and ESMF. During the coupling phase, the atmospheric variables of U, V, T, q, and radiation are passed to the ocean model which returns an updated SST value to the atmosphere. The wave model coupling will be employed to improve wind stresses in high-wind environments (Bourassa, 2006). Figure 2 illustrates the coupled-model feedback loop. A collaborative effort between the Center for Ocean-Atmosphere Prediction Studies (COAPS) and the Department of Meteorology at the Florida State University has resulted in the development of a basin-scale coupled ocean-atmosphere prediction system specifically designed to study the aspects of air-sea interactions occurring during multi-tropical cyclone (TC) passages. Methodology Future Work A near-real time, fully coupled version of the modeling system will be tested during the 2009 North-Atlantic TC season. The resulting forecasts will be compared against concurrent TC guidance model forecasts in order to assess both the skill and deficiencies of the system. Necessary improvments will then be addressed. The authors acknowledge Alan Wallcraft (NRL), George Halliwell (RSMAS), and Mark D. Powell (HRD/AOML) for their respective assistances in this effort.