Skip to main content

A non-homogeneous hidden Markov model for precipitation occurrence

Buy Article:

The full text article is temporarily unavailable.

We apologise for the inconvenience. Please try again later.


A non-homogeneous hidden Markov model is proposed for relating precipitation occurrences at multiple rain-gauge stations to broad scale atmospheric circulation patterns (the so-called ‘downscaling problem’). We model a 15-year sequence of winter data from 30 rain stations in south-western Australia. The first 10 years of data are used for model development and the remaining 5 years are used for model evaluation. The fitted model accurately reproduces the observed rainfall statistics in the reserved data despite a shift in atmospheric circulation (and, consequently, rainfall) between the two periods. The fitted model also provides some useful insights into the processes driving rainfall in this region.

Keywords: Climate change; EM algorithm; Hidden Markov model; Monte Carlo maximum likelihood; Precipitation model

Document Type: Research Article

Affiliations: 1: University of Washington, Seattle, USA 2: Commonwealth Scientific and Industrial Research Organisation, Wembley, Australia

Publication date: January 1, 1999


Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more