2. WEATHER, CLIMATE, AND FARMERS: AN OVERVIEW : Roger Stone Expert meeting 15-18 November 2004.

3. Some key underlying points: Improved seasonal to interannual climate prediction offers farmers and agricultural industry the opportunity to protect, or even to increase, economic well-being. These advances in science in meteorology and climatology should enable society to deal with the effects of weather and climate variability more effectively than ever before. ‘The effectiveness of forecast information depends strongly on the systems that distribute the information, the farmer’s modes of understanding and judgement about the information sources, and the ways in which the information is presented’ (after Stern and Easterling, 1999).

4. (From Stone et al; Nature, Nov 1996) We now have the capability to predict seasonal rainfall in many world regions

5. Forecasts are prepared in a variety of ways

7. It may be the case that the manner in which forecasts are prepared and disseminated has a major bearing on how or whether these forecasts can be utilised.

8. The value of forecasts to farmers will depend not only on their accuracy but also on the management options available to the user to take advantage of the forecasts (Nicholls, 1991).

9. Climate and weather information may have no value unless it changes management decisions. Management decisions require management tools

10. Climate Information and Forecasts and Decision Making Farm Harvest, Transport, Mill Catchment Marketing Policy Farm Harvest, Transport, Mill Catchment Marketing Policy Scale Axis Scale Axis Information Axis Information Axis General Targeted C l i m a t e Scale Information Irrigation Fertilisation fallow practice land prep planting weed manag. pest manag. Improved Planning for wet weather disruption – season start and finish Crop size forecast CCS, fibre levels Civil works schedule Land & Water Resource Management Environmenta l Management Water allocation Planning and policy associated with exceptional Events Industry Business and Resource Managers Government Crop size Crop sizeForecast Early SeasonEarly SeasonSupply Supply PatternsSupply Patterns -Shipping -Global Supply

12. Case study example from RSA: An integrated climate-farming/cropping systems forecast Planting date: 1 November (El Niño Years) Probability (%) of exceeding maize yields of 2.5 t/ha Planting date: 1 November (La Niña Years)

13. Forecasting the Australian Grain Crop; example of a fully integrated agrometeorological system Rainfall up to date and Climate Forecast Simple Agro- climatic model GeographicalInformationSystem Drought Probability 57911135791113 5 7 911 13 Month 0.5 1.0 1.5 2.0 2.5 0.5 1.0 1.5 2.0 2.5 NSWQLDSA VICWAAUS Wheat outlook for the 1999 season 10%Pred 50%Pred 90%Pred ABARE 10%NoP 90%NoP LTmed Spatial Statistics Crop Outlook Compare to reference yield expectation

17. Terms of Reference for the Expert Team on Weather, Climate and Farmers (a)To review and develop recommendations for enhancing more effective and regular communication, and dialogue for training and demonstration between agrometeorological services and farmers at the local level to provide better services to farmers; (b)To review the use of weather and climate data and make recommendations for improvements in applications of agrometeorological products, and advisories and forecasts for both short-term daily operational decisions and long-term strategic planning at the farm level; (c)To establish procedures and guidance for the proper use of agrometeorological information for crop, livestock, forestry and fisheries management; (d)To describe, using case studies from Member countries, successful applications of weather and climate for agriculture, and review the strengths, weaknesses and limitations for more general use; and To prepare reports for operational applications in accordance with timetables established by the OPAG and/or MG.

18. Thank you