A Nonhomogeneous Hidden Markov Model for Precipitation Occurrence
نویسندگان
چکیده
A nonhomogeneous 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 southwestern Australia. The rst 10 years of data are used for model development and the remaining 5 years are used for model evaluation. The tted 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 tted model also provides some useful insights into the processes driving rainfall in this region.
منابع مشابه
Statistical downscaling of precipitation through nonhomogeneous stochastic weather typing
We present a novel statistical downscaling method that provides accurate and relatively transparent simulations of local-scale precipitation characteristics. The method combines large-scale upper-air circulation with surface precipitation fields, and is based on a nonhomogeneous stochastic weather typing approach. Here we applay the method to downscale precipitation at 37 rain gauges in the sta...
متن کاملA Nonhomogeneous Hidden Markov Model for Precipitation
A stochastic model for relating precipitation occurrences at multiple rain gauge stations to broad-scale atmospheric circulation patterns (the so-called \downscaling problem") is proposed. The model is an example of a nonhomogeneous hidden Markov model and generalizes existing downscaling models in the literature. The model assumes that atmospheric circulation can be classi ed into a small numb...
متن کاملمدل سازی فضایی-زمانی وقوع و مقدار بارش زمستانه در گستره ایران با استفاده از مدل مارکف پنهان
Multi site modeling of rainfall is one of the most important issues in environmental sciences especially in watershed management. For this purpose, different statistical models have been developed which involve spatial approaches in simulation and modeling of daily rainfall values. The hidden Markov is one of the multi-site daily rainfall models which in addition to simulation of daily rainfall...
متن کاملDownscaling of daily rainfall occurrence over Northeast Brazil using a Hidden Markov Model
A hidden Markov model (HMM) is used to describe daily rainfall occurrence at ten gauge stations in the state of Ceará in northeast Brazil during the February–April wet season 1975–2002. The model assumes that rainfall occurrence is governed by a few discrete states, with Markovian daily transitions between them. Four “hidden” rainfall states are identified. One pair of the states represents wet...
متن کامل