Binary Time Series Climate Change Gamma Time Series Generalized Linear Models Markov Chain Rainfall Modeling
Issue Date:
2003
Publisher:
Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Citation:
Pliska Studia Mathematica Bulgarica, Vol. 14, No 1, (2003), 91p-106p
Abstract:
We consider development of daily precipitation models based
on [3] for some sites in Bulgaria. The precipitation process is modelled as
a two-state first-order nonstationary Markov model. Both the probability
of rainfall occurrance and the rainfall intensity are allowed depend on the
intensity on the preceeding day. To investigate the existence of long-term
trend and of changes in the pattern of seasonal variation we use a synthesis
of the methodology presented in [3] and the idea behind the classical running
windows technique for data smoothing. The resulting time series of model
parameters are used to quantify changes in the precipitation process over
the territory of Bulgaria.
