David García-León – RAAS Division – Centro Euro-Mediterraneo sui Cambiamenti Climatici
An effective design, implementation and monitoring of area-targeted agricultural policies crucially rest on the availability of high-resolution yield forecasts of major crops. Operational yield forecasting systems use process-based methods or statistical (data-driven) methods as tools to produce crop yield forecasts. Statistical data-driven methods are regarded as good alternatives to process-based models for the sub-national monitoring of cereal crop yields, since they can easily handle more data and can be calibrated simultaneously to different areas. However, some data-related challenges must be addressed to develop an integrated seasonal crop yield forecasting system able to produce local yield forecasts based on statistical models. These challenges have to do with the availability of reliable agro-climatic data and the predictability of the model inputs. The aim of this study is to assess the performance of statistical models of wheat and maize calibrated with meteorological data at different spatial aggregation levels and to examine the predictive content of diversely initialised seasonal climate forecasts.
NOTE: The seminars will be held at the CMCC premises in Bologna, Viale Berti Pichat 6/2 – Meeting Room (Second Floor).