A simple Poisson–gamma model for modelling rainfall occurrence and amount simultaneously

Modelling rainfall is important for prediction and simulation purposes in many areas of planning, agriculture, forestry, meteorology and hydrology. Usually two different models are needed to understand the two important features of rainfall: the occurrence and the amount. Here we use a single model, a Tweedie generalized linear model, to model the occurrence and amount of rainfall simultaneously. Choosing a simple model with only sine and cosine terms as predictors, the model is fitted for 220 Australian stations, with 6 rainfall stations are taken as case studies. The model fits well to monthly rainfall data based on studying the probability of no rain each month, and mean monthly rainfall amounts. Using the model, simulating monthly rainfall data for the stations with inadequate rainfall records is possible. The model also allows for a disaggregation of monthly rainfall amounts into the number of rainfall events in each month and the mean amount of rainfall per event. This information can then be used in agriculture production system simulators for agricultural planning and management.

Research highlights▶ Rainfall occurrence and amounts can be modelled simultaneously using a Tweedie glm. ▶ Simple model with sine and cosine terms fits very well. ▶ The model is useful for simulating monthly rainfall in agricultural applications. ▶ The model provides mechanism for disaggregating monthly rainfall.