Everingham, Y.L., Zamykal, D., and McKinna, L.I. (2009) RAIN FORECASTER - a seasonal climate forecasting tool. In: Proceedings of the 2009 Conference of the Australian Society of Sugar Cane Technologists (31) pp. 50-64. From: 2009 Conference of the Australian Society of Sugar Cane Technologists, 5 - 8 May, 2009, Ballina, NSW, Australia.

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Abstract

Like most agricultural industries, the Australian sugar industry is exposed to the elements of the climate. Knowing if the season ahead is likely to be wetter or drier can assist industry decision makers plan for the future. RAIN FORECASTER is a computer program that can forecast rainfall and wet days using phases of the Southern Oscillation Index (SOI) and anomalies in sea surface temperatures in the Niño 3.4 region which forms part of the central equatorial Pacific Ocean. RAIN FORECASTER also incorporates the long lead forecasting model developed by Florida State University (FSU). The Florida State University model allows industry to assess early in the year (e.g. January, February) if there is likely to be a wet finish to the harvest season. Whilst RAIN FORECASTER can be used as an operational prediction tool, it is also a learning tool that can be used to understand how climate indices influence rainfall patterns. For example, by experimenting with RAIN FORECASTER, three key rules emerge common to most sugarcane growing regions located along the eastern coast of Australia. These rules are: (i) consistently positive SOI phases and/or negative Niño 3.4 anomalies (La Niña) during the harvest season favour wetter harvest conditions; (ii) consistently negative SOI phases and/or positive Niño 3.4 anomalies (El Niño) during the harvest season favour drier harvest conditions, and (iii) La Niña projections for the harvest season made by the FSU model early in the year, increase the risk of a wetter finish to the harvest. RAIN FORECASTER can be used for forecasting conditions outside the harvest season, but different results may appear for different regions. RAIN FORECASTER is a simple tool that provides an excellent basis for exploring how climate conditions are influenced by variations in atmospheric and oceanic conditions.

Item ID:	11226
Item Type:	Conference Item (Research - E1)
ISSN:	0726-0822
Keywords:	Southern Oscillation; El Niño; La Niña; autumn; barrier; rainfall; wet days
Date Deposited:	24 May 2010 23:59
FoR Codes:	01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics @ 34% 04 EARTH SCIENCES > 0401 Atmospheric Sciences > 040105 Climatology (excl Climate Change Processes) @ 33% 07 AGRICULTURAL AND VETERINARY SCIENCES > 0701 Agriculture, Land and Farm Management > 070199 Agriculture, Land and Farm Management not elsewhere classified @ 33%
SEO Codes:	82 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 8203 Industrial Crops > 820304 Sugar @ 34% 96 ENVIRONMENT > 9609 Land and Water Management > 960904 Farmland, Arable Cropland and Permanent Cropland Land Management @ 33% 97 EXPANDING KNOWLEDGE > 970104 Expanding Knowledge in the Earth Sciences @ 33%
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