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