  A hidden Markov model is developed to simulate tropical cyclone intensity
evolution dependent on the surrounding large-scale environment. The model
considers three unobserved (hidden) discrete states of intensification and
associates each state with a probability distribution of intensity change. The
storm's transit from one state to another is described as a Markov chain. Both
the intensity change and state transit components of the model are dependent on
environmental variables including potential intensity, vertical wind shear,
relative humidity, and ocean feedback. This Markov environment-dependent
hurricane intensity model (MeHiM) is used to simulate the evolution of storm
intensity along the storm track over the ocean, and a simple decay model is
added to estimate the intensity change when the storm moves over land. Data for
the North Atlantic (NA) basin from 1979-2014 (555 storms) are used for model
development and evaluation. Probability distributions of 6-h and 24-h intensity
change, lifetime maximum intensity, and landfall intensity based on model
simulations and observations compare well. Although the MeHiM is still limited
in fully describing rapid intensification, it shows a significant improvement
over previous statistical models (e.g., linear, nonlinear, and finite mixture
models).
