Williams, Peter M (1998) Modelling Seasonality and Trends in Daily Rainfall Data. In: Advances in Neural Information Processing Systems.

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Abstract

This paper presents a new approach to modelling daily rainfall using neural networks. We fist model the conditional distributions of rainfall amounts, in such a way that the model itself determines the order of the process, and the time-dependent shape and scale of the conditional distributions. After integrating over particular weather patterns, we are able to extracxt seasonal variations and long-term trends.

Item Type:	Conference or Workshop Item (Paper)
Schools and Departments:	School of Engineering and Informatics > Informatics
Depositing User:	EPrints Services
Date Deposited:	06 Feb 2012 20:05
Last Modified:	07 Jun 2012 14:43
URI:	http://sro.sussex.ac.uk/id/eprint/23941

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