Evaluating the Impact of Improvement in the Horizontal Diffusion Parameterization on Hurricane Prediction in the Operational HWRF Model

This talk presents the upgrade of the horizontal diffusion parameterization in the operational Hurricane Weather Research and Forecasting (HWRF) Model. The horizontal mixing length (Lh) in HWRF was modified based on aircraft observations and extensive idealized and real-case numerical experiments. Idealized numerical simulations were firstly conducted to understand how the horizontal diffusion parameterization works in HWRF and its dynamical
influence on hurricane intensification. Then a series of sensitivity experiments was conducted to simulate Hurricane Earl (2010) in which only Lh was varied.

Results from the Earl forecasts confirmed the findings from previous theoretical and idealized numerical studies, in that both the simulated maximum intensity and intensity change rate are dependent on Lh. Comparisons between the modeled and observed structure of Hurricane Earl, such as storm size,
boundary layer heights, warm-core height and temperature anomaly, and eyewall slope, suggested that the Lh used in the HWRF Model should be decreased. Lowering Lh in HWRF has a positive impact on hurricane prediction based on over 200 retrospective forecasts of 10 Atlantic storms.Biases in both storm intensity and storm size are significantly reduced with the modified Lh.

These results motivate the need for a scale-aware parameterization of horizontal diffusion. Such a development is discussed.