Multiple regression modelling approach for rainfall prediction using large-scale climate indices as potential predictors
by H.M. Rasel; Monzur Alam Imteaz; Fatemeh Mekanik
International Journal of Water (IJW), Vol. 11, No. 3, 2017

Abstract: Some studies established the associations with different climate indices (Southern Oscillation Index, Indian Ocean Dipole and Southern Annular Mode) and seasonal rainfalls of different parts of Australia. Nevertheless, maximum predictability of South Australian rainfall was only 20% with individual effects of potential predictor. To establish a better relationship for South Australian spring rainfall prediction, this paper presents two further investigations: 1) relationship of lagged climate indices with rainfall; 2) combined influence of these lagged climate indicators on rainfall. Multiple linear regression (MLR) modelling was used to evaluate the influence of combined predictors. Three rainfall stations were selected from South Australia as a case study. It was revealed that significantly increased rainfall predictability has been achieved through MR models using the influences of combine-lagged climate predictors. The rainfall predictability ranging from 41% to 45% has been achieved using combined lagged-indices, whereas maximum 33% predictability can be achieved using individual climate index.

Online publication date: Thu, 03-Aug-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Water (IJW):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email