Journal article
A simple Poisson–gamma model for modelling rainfall occurrence and amount simultaneously
Agricultural and Forest Meteorology, Vol.150(10), pp.1319-1330
2010
Abstract
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.
Details
- Title
- A simple Poisson–gamma model for modelling rainfall occurrence and amount simultaneously
- Authors
- Md Masud Hasan (Author) - University of the Sunshine Coast - Faculty of Science, Health and EducationPeter K Dunn (Author) - University of the Sunshine Coast - Faculty of Science, Health and Education
- Publication details
- Agricultural and Forest Meteorology, Vol.150(10), pp.1319-1330
- Publisher
- Elsevier BV
- Date published
- 2010
- DOI
- 10.1016/j.agrformet.2010.06.002
- ISSN
- 0168-1923
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Health and Sport Sciences - Legacy; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99449434502621
- Output Type
- Journal article
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- Agronomy
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