In this study, a stochastic rainfall generator was developed to create continuous time series with high temporal resolution of 10 min. The rainfall-generation process involved Monte Carlo simulation for stochastically generating parameters such as quantity, duration, inter-event time, and type. A bivariate copula used preserve the correlation between quantity duration in generated series. modif...

A 70-year record of daily monsoon-season rainfall at a network of 13 stations in central-western India is analyzed using a 4state homogeneous hidden Markov model (HMM). The diagnosed states are seen to play distinct roles in the seasonal march of the monsoon, can be associated with “active” and “break” monsoon phases and capture the northward propagation of convective disturbances associated wi...

A 70-year record of daily monsoon-season rainfall at a network of 13 stations in central-western India is analyzed using a 4state homogeneous hidden Markov model (HMM). The diagnosed states are seen to play distinct roles in the seasonal march of the monsoon, can be associated with “active” and “break” monsoon phases and capture the northward propagation of convective disturbances associated wi...

Rainfall in Kerala State, the southern part of Indian Peninsula in particular is caused by the two monsoons and the two cyclones every year. In general, climate and rainfall are highly nonlinear phenomena in nature giving rise to what is known as the ‘butterfly effect’. We however attempt to train an ABF neural network on the time series rainfall data and show for the first time that in spite o...

Several authors have had apparent success in applying continuous-time point process models to rainfall occurrence sequences. In this paper, it is shown that if rainfall occurrences are interpreted as the events of a point process (and not as a censored sample), the continuous-time point process methodology and estimation procedures are not directly applicable since they fail to account for the ...

Rainfall data of high temporal resolution are required in a multitude of hydrological applications. In the present paper, a temporal rainfall disaggregation model is applied to convert daily time series into an hourly resolution. The model is based on the principles of random multiplicative cascade processes. Its parameters are dependent on (1) the volume and (2) the position in the rainfall se...