1.4 Assessing the Ability of Variable-Resolution Global Models to Forecast Tropical Cyclones

Wednesday, 9 January 2013: 9:30 AM
Ballroom F (Austin Convention Center)
Colin M. Zarzycki, University of Michigan, Ann Arbor, MI; and C. Jablonowski and M. A. Taylor

Modeling of tropical cyclones in General Circulation Models (GCMs) has historically been a difficult task due to small storm size and intense convective processes which require significant parameterization. Even with recent improvements in operational forecast model resolution, cyclone prediction difficulties persist. In an effort to help alleviate these issues, the use of limited area models (LAMs) with high resolution has become popular, although these models typically lack two-way communication with the exterior domain. Variable-resolution global dynamical models can serve as the bridge between traditional global forecast models and high-resolution LAMs by providing high resolution in regions such as low-latitude ocean basins where tropical cyclones are prevalent. These models can utilize existing computing platforms to approach 10 kilometer resolution near tropical regions of interest while maintaining global continuity, therefore eliminating the need for the externally-forced and possibly numerically and physically inconsistent boundary conditions required by LAMs.

A statically-nested, variable-mesh option has recently been introduced into the National Center for Atmospheric Research (NCAR) Community Atmosphere Model's (CAM) Spectral Element (SE) dynamical core. The SE dynamical core is also known as the 'High-Order Method Modeling Environment' (HOMME) and is scheduled to become the NCAR default in CAM version 5.2. We present short-term CAM-SE model simulations of historical tropical cyclones and compare the model's prediction of storm track and intensity to other global and limited area models used operationally by hurricane forecast centers. We also discuss the performance of existing parameterizations in CAM with respect to tropical cyclone forecasting as well as consider the potential computational benefits of using a variable-resolution global model as a numerical weather prediction tool.

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