Integrating seasonal climate prediction and agricultural models for insights into agricultural practice.
Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate-crop-economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based 'discussion support systems' contribute to learning and farmer-researcher dialogue. Integrated climate-crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis.
Hansen
James W
JW
International Research Institute for Climate Prediction, The Earth Institute at Columbia University, 121 Monell Building, Lamont-Doherty Earth Observatory, PO Box 1000/61 Route 9 W, Palisades, NY 10964-8000, USA. jhansen@iri.columbia.edu
D002980:Climate; D018556:Crops, Agricultural / Q000254:growth & development* / Q000600:supply & distribution; D005544:Forecasting; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D012621:Seasons