Making climate model forecasts more useful
S. B. Power A D , N. Plummer B and P. Alford CA Centre for Australian Weather and Climate Research, Bureau of Meteorology, Melbourne, Vic. 3000, Australia.
B National Climate Centre, Bureau of Meteorology, Melbourne, Vic. 3000, Australia.
C Formerly National Climate Centre, Bureau of Meteorology, Melbourne, Vic. 3000, Australia.
D Corresponding author. Email: s.power@bom.gov.au
Australian Journal of Agricultural Research 58(10) 945-951 https://doi.org/10.1071/AR06196
Submitted: 14 June 2006 Accepted: 8 October 2007 Published: 30 October 2007
Abstract
There is considerable potential for seasonal to inter-annual climate forecasts derived from dynamic models of the earth’s climate to be used widely to help improve management of important real-world issues in a variety of different areas (e.g. disaster management, agriculture, water management, health, natural resource management, food security, and insurance). Unfortunately, several factors currently inhibit this potential, e.g. low skill, low awareness, mismatches in what model forecasts can provide and what users need, and the complexity and probabilistic nature of the information provided. Substantial effort around the world is currently directed towards reducing these impediments. For example, climate model development continues behind the scenes, and techniques such as multi-model ensemble forecasting are progressing rapidly. Communication strategies that enable probabilistic information to be communicated more effectively have been developed and exciting developments such as the emergence of the Argo float program have dramatically improved our ability to initialise forecast systems. We can also look forward to greater computing power in the future, which will allow us to increase the resolution of the models used to perform forecasts. Research on the integration of climate forecasts with risk-management tools more useful to managers is also occurring.
The great potential for much wider use of climate model forecasting cannot be denied. However, it will only be realised if models continue to be developed further, if climatic variability continues to be closely monitored from the surface, the atmosphere, the ocean, and from space, and if these data are made readily available to the research community.
Acknowledgments
We thank Holger Meinke, Jenny Fegent, Peter Hayman, and an anonymous reviewer for many helpful comments on earlier drafts, and participants of the Brisbane 2005 workshop on the impact of climate predictions in agriculture, in Brisbane, Australia.
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