Determining Key Model Parameters of Rapidly Intensifying Hurricane Guillermo(1997) using the Ensemble Kalman Filter

7 In this work we determine key model parameters for rapidly intensifying Hurricane Guillermo 8 (1997) using the Ensemble Kalman Filter (EnKF). The approach is to utilize the EnKF as 9 a tool to only estimate the parameter values of the model for a particular data set. The 10 assimilation is performed using dual-Doppler radar observations obtained during the period 11 of rapid intensification of Hurricane Guillermo. A unique aspect of Guillermo was that during 12 the period of radar observations strong convective bursts, attributable to wind shear, formed 13 primarily within the eastern semicircle of the eyewall. To reproduce this observed structure 14 within a hurricane model, background wind shear of some magnitude must be specified; as 15 well as turbulence and surface parameters appropriately specified so that the impact of the 16 shear on the simulated hurricane vortex can be realized. To identify the complex nonlinear 17 interactions induced by changes in these parameters, an ensemble of model simulations have 18 been conducted in which individual members were formulated by sampling the parameters 19 within a certain range via a Latin hypercube approach. The ensemble and the data, derived 20 latent heat and horizontal winds from the dual-Doppler radar observations, are utilized in the 21 EnKF to obtain varying estimates of the model parameters. The parameters are estimated 22 at each time instance, and a final parameter value is obtained by computing the average 23 over time. Individual simulations were conducted using the estimates, with the simulation 24 using latent heat parameter estimates producing the lowest overall model forecast error. 25