title: A Markov modulated Poisson process model for rainfall increments.
abstract: The problems encountered when using traditional rectangular pulse hierarchical point process models for fine temporal resolution and the growing number of available tip-time records suggest that rainfall increments from tipping-bucket gauges be modelled directly. Poisson processes are used with an arrival rate modulated by a Markov chain in continuous time. The paper shows how, by using two or three states for this chain, much of the structure of the rainfall intensity distribution and the wet/dry sequences can be represented for time-scales as small as 5 minutes.
authors.affiliation: Department of Civil and Environmental Engineering, Imperial College, London, UK.
authors.forename: C
authors.initials: C
authors.lastname: Onof
authors.forename: B
authors.initials: B
authors.lastname: Yameundjeu
authors.forename: J P
authors.initials: JP
authors.lastname: Paoli
authors.forename: N
authors.initials: N
authors.lastname: Ramesh
mesh_terms: D004784:Environmental Monitoring / Q000295:instrumentation / Q000706:statistics & numerical data; D008390:Markov Chains; D015233:Models, Statistical; D011891:Rain