Ash, A.J. Dr; (07) 4753 8540; (07) 4753 8600; Andrew.Ash@tag.csiro.au
Research Organisation: CSIRO Tropical Agriculture, PMB Aitkenvale, QLD 4814
Collaborators: CSIRO Wildlife and Ecology, Alice Springs (Stafford Smith); CSIRO Marine Research (McIntosh); CSIRO Atmospheric Research (Smith); QCCA, Indooroopilly (McKeon, Hall, Stone); QCCA, Toowoomba (Hammer); Bureau Of Meteorology (Voice); Western Australia Department of Agriculture (Abrecht).
Sponsor: LWRRDC, Land and Water Resources Research and Development Corporation.
1. Determine a set of skilful and industry targeted climate prediction indices based on ocean data (such as SST) and intermediate-complexity coupled ocean-atmosphere models (eg. Kleeman, Cane-Zebiak) for specific agricultural regions across Australia;
2. Optimise the use of statistical and intermediate coupled ocean-atmosphere forecasts in farming production/economics models for the extensive grazing, dryland grains and sugar industries. Evaluate the use of and potential improvements afforded by newer fully dynamic coupled ocean-atmosphere models and modern data assimilation techniques;
3. Assess the production, economic and resource-based value of these systems compared to current best-practice in the absence of climate forecasts;
4. Ensure industry participation in the application and assessment of these systems by close collaboration with Agribusiness, QCCA and other relevant industry bodies.
This project aims to evaluate forecasts based on ocean data (such as Sea Surface Temperatures) and intermediate-complexity coupled ocean-atmosphere models. These forecasts have the potential to be more useful over a larger area of Australia, and may also give some improvement in lead time over SOI-based forecasts. Intermediate coupled ocean-atmosphere models (eg. Kleeman, Cane-Zebiak) also offer potential to agriculture, particularly with regard to increased lead times. Finally, newer fully-dynamical coupled ocean-atmosphere model forecasts will soon become available.
New forecasts must be developed and evaluated in conjunction with industry needs, and because these needs vary by industry and location a collaborative approach is necessary. The value of these new forecasts will be tested for the grains, extensive grazing and sugar industries across Australia. The forecasts will be assessed using agricultural models that simulate production under a range of management strategies in a way that we can compare forecasts with no-forecasts. The output from the models will be used to assess economic impacts and to develop simple rules of thumb for adoption by industry.
Progress: Project is now underway.
Period: starting date 1998-07; completion date 2001-06.
Keywords: seasonal forecasts, ocean-atmosphere models, value of forecasts, agricultural systems analysis, sugar crops, cereal crops, livestock production systems
Publications: None as yet