Everingham, Y. L. and Muchow, R. C. and Stone, R. C. and Coomans, D. H. (2003) Using Southern Oscillation index phases to forecast sugarcane yields: a case study for northeastern Australia. International Journal of Climatology, 23 (10). pp. 1211-1218. ISSN 0899-8418
Abstract
Climate is a key driver of sugarcane productivity. Advance knowledge of the likely climate and its impact on production could add value to production, harvest and marketing efforts. A climate forecast system that incorporates five patterns or phases of the southern oscillation index is used to assess whether an early indication of sugarcane yield anomalies in Australia can be produced. results indicate that, for certain sugarcane growing regions, the climate forecast systems offers better estimates of the direction of the anomaly when compared with no climate forecast system. Improved results of the direction of the yield anomaly can be obtained some 7 months prior to the commencement of harvest. This information can then be used by marketers to plan better the customer allocations, shipping schedules and storage requirements for the next season. Advance knowledge of the crop size can also assist industry decisons makers in scheduling when the harvest season should commence. Further research is required to determine if other climatic indices, such as sea-surface temperatures, can improve yield estimation. Consideration also needs to be given to determining whether the magnitude and direction of the yield anomaly can be more accurately forecasted with varying lead times.
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| Item Type: | Article (Commonwealth Reporting Category C) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | Files associated with this item cannot be displayed due to copyright restrictions. |
| Faculty/School / Institute/Centre: | Historic - Faculty of Sciences - Department of Biological and Physical Sciences (Up to 30 Jun 2013) |
| Faculty/School / Institute/Centre: | Historic - Faculty of Sciences - Department of Biological and Physical Sciences (Up to 30 Jun 2013) |
| Date Deposited: | 11 Oct 2007 01:13 |
| Last Modified: | 21 Nov 2013 01:16 |
| Uncontrolled Keywords: | SOI; climate; forecast; sugarcane; yield; Australia; Monte Carlo |
| Fields of Research (2008): | 04 Earth Sciences > 0401 Atmospheric Sciences > 040107 Meteorology 04 Earth Sciences > 0401 Atmospheric Sciences > 040105 Climatology (excl.Climate Change Processes) 07 Agricultural and Veterinary Sciences > 0703 Crop and Pasture Production > 070301 Agro-ecosystem Functionand Prediction |
| Fields of Research (2020): | 37 EARTH SCIENCES > 3701 Atmospheric sciences > 370108 Meteorology 37 EARTH SCIENCES > 3702 Climate change science > 370202 Climatology 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3004 Crop and pasture production > 300402 Agro-ecosystem function and prediction |
| Socio-Economic Objectives (2008): | D Environment > 96 Environment > 9603 Climate and Climate Change > 960304 Climate Variability (excl. Social Impacts) |
| Identification Number or DOI: | https://doi.org/10.1002/joc.920 |
| URI: | http://eprints.usq.edu.au/id/eprint/2724 |
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