Quantifying the benefits of a long-lead ENSO prediction model to enhance harvest management—A case study for the Herbert sugarcane growing region, Australia
✍ Scribed by Yvette L. Everingham; Natalie E. Stoeckl; Justin Cusack; John A. Osborne
- Publisher
- John Wiley and Sons
- Year
- 2011
- Tongue
- English
- Weight
- 223 KB
- Volume
- 32
- Category
- Article
- ISSN
- 0899-8418
- DOI
- 10.1002/joc.2333
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✦ Synopsis
Abstract
In the Australian sugarcane industry, the decision about when to start the harvest season (which runs from approximately June through to November) must be made no later than March. This is necessary to give sugar milling personnel sufficient time to complete important mill maintenance procedures prior to commencement of harvest. The harvest season must start early enough so that all sugarcane is harvested before the rainy season commences, but late enough to capitalize on the higher sugar content in the cane stalk, which forms the basis of industry payment. An early indication (e.g. January) about likely rainfall conditions during the latter half of the harvest season (e.g. September to November) would provide crucial information to industry planners when deciding the start of the harvest season. By coupling a long‐lead statistical ENSO prediction scheme with the cane payment system, we investigated the ability of the climate forecast model to deliver a quantitative benefit to the Herbert sugarcane region. Through the use of bootstrapped confidence intervals, we found the region could benefit by up to 1.9 million AUD per annum by starting the harvest season later than that conventionally practiced when warm ENSO conditions were predicted for the end of the harvest season. Copyright © 2011 Royal Meteorological Society