科研之友
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摘要
Rainfall models are used to understand the effect of various climatological variables on rainfall amounts. The models also have potential uses in predicting and simulating rainfall. We use Tweedie generalized linear models to model monthly rainfall amounts and occurrence simultaneously with a set of predictors (sine term, cosine term, NINO 3.4, SOI and SOI phase). Models are fitted to the monthly rainfall data of 220 Australian stations with 4 stations as case studies. First, models with only sine and cosine terms (the base model) are fitted to model the cyclic pattern of rainfall data, and then one of the climatological variables is added each time in addition to the base model. On the basis of the BIC, the model with NINO 3.4 is preferred for most of the studied stations. Stations for which the model using the SOI is preferred appear in small clusters. Adding the climatological variables to the base model improves the fit of the model and makes substantial changes in the predicted mean monthly rainfall amount and probability of getting a dry month. The climatological variables have significant impacts on the amount of rainfall in most stations located on the eastern and northeastern regions of Australia. The models used lags one of the climatological covariates (i.e. value of the covariates of previous month with rainfall amount of a month) and are useful for one month lead rainfall prediction.
- 出版日期2012-6
