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FAO-WMO Roving Seminar on Crop-Yield Weather Modelling. Lecture Notes and Exercises









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    It is suggested that the approach used by FAO and a number of developing countries for crop forecasting at the national level strikes a good compromise between input requirements and ease of validation. The article thus describes the FAO crop modelling and forecasting philosophy.
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    Development of a Weather Yield Index (WYX) for Maize Crop Insurance in Malawi 2006
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    The methodology has demonstrated the possibility of producing weather based maize yield index for Crop Insurance for any point in Malawi every ten days starting from planting time. Real-time pixel based maize yield indices covering the whole country with a resolution of 0.05 degrees latitude and longitude can be objectively produced. The methodology is repeatable by anybody who has access to basic weather data. The methodology uses gridded information that is not too sensitive to individual miss ing stations, provided sufficient data points are available and the interpolation process takes into account topography and climatic gradients. The methodology is temper-resistant, potential beneficiaries of the insurance are not in a position to directly or indirectly manipulate the yield index.
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    AgroMetShell Manual 2004
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    This AgroMetShell (AMS) manual has been prepared by the SADC Regional Remote Sensing Unit (RRSU), Harare, Zimbabwe. This is a joint collaboration been the Agrometeorology Group, Environment and Natural Resources Service (SDRN), Food and Agriculture organization of the United Nations and the SADC Regional Early Warning System. The manual is a step-by-step handbook for use in data preparation, running the water requirement satisfaction index (WRSI) water balance model, image creation and yield est imation once the models have been developed for crop monitoring and early warning for food security.

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