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Title: THE EMPEROR'S NEW CLOTHES: SOFTWARE, WETWARE, OR NOWHERE? THE THRONY ROAD TO ADOPTION: CLIMATE-PRODUCT DISSEMINATION FOR AGRICULTURE IN THE UNITED STATES

Author
item Garbrecht, Jurgen
item Schneider, Jeanne

Submitted to: World Meteorological Organization
Publication Type: Proceedings
Publication Acceptance Date: 1/24/2005
Publication Date: 2/15/2005
Citation: Garbrecht, J.D., Schneider, J.M. 2005. The emperor's new clothes: software, wetware, or nowhere? The thorny road to adoption: climate-product dissemination for agriculture in the United States. In: Proceedings of the World Meteorological Organization. p. 22-25.

Interpretive Summary: Practical applications of climate forecasts require computer software to calculate climate indices, simulate agricultural impacts, and evaluate profitability, risk and decision options. However, availability of such software packages does not guarantee adoption and use of forecast and prediction products by the agricultural end-user. The broader adoption issue hinges on effective dissemination and communication of agriculture-specific decision information and its integration into the end-user's decision process. To date, agricultural applications have mostly been conducted by research agencies as demonstration projects, and existing software and prediction products have not been broadly adopted by the agricultural end-user. In this short review of the issues, adoption impediments were discussed, existing dissemination models for climate forecasts and prediction products were reviewed, and an approach to promote adoption of prediction products and decision information was proposed. In the proposed approach, resource intensive components of climate forecasting and impact prediction are developed by government agencies, and a consulting service provides site- and problem-specific interpretation of the prediction products and develops end-user decision information. Limiting the scope and cost of personalized consulting to site-specific interpretation and decision support makes the service accessible to small agricultural users. The adoption of forecast and prediction products by the agricultural end-user could increase productivity, enhance profitability and reduce economic risk for agricultural enterprises.

Technical Abstract: Practical applications of climate forecasts require software to calculate climate indices, simulate agricultural impacts, and evaluate profitability, risk and decision options. However, availability of such software packages does not guarantee adoption and use of forecast and prediction products by the agricultural end-user. The broader adoption issue hinges on effective dissemination and communication of agriculture-specific decision information and its integration into the end-user's decision process. To date, agricultural applications have mostly been conducted by research agencies as demonstration projects, and existing software and prediction products have not been broadly adopted by the agricultural end-user. Adoption impediments are primarily associated with (1) limitations in forecasting ability and associated prediction products; (2) constraints related to the decision process and decision maker; and (3) lack of relevant and accessible prediction products and decision information for agricultural applications. An approach to development and dissemination of forecast and prediction products is proposed. The approach combines the top-down "loading-dock" approach for the development and dissemination of resource intensive components of climate forecasting and impact prediction, and a bottom-up consulting approach for the site- and problem-specific interpretation of the prediction products and development of end-user decision information. Limiting the scope and cost of personalized consulting to site-specific interpretation and decision support makes the service accessible to small agricultural users. The adoption of forecast and prediction products by the agricultural end-user could increase productivity, enhance profitability, and reduce economic risk for agricultural enterprises.