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Introduction In the framework of this paper we ll consider the forecasting of yield changes based on remote sensing data Projections of climate change impacts on crop yields are subject to uncertainties and quantification of such uncertainty is essential for the effective use of the projection results for adaptation and mitigation purposes Variance decomposition of the yield projections showed that uncertainty in the projections caused by climate and crop models is likely to change with prediction period and climate change uncertainty generally had a larger impact on projections downscaled climate projections had significant bias that can introduce significant uncertainties in yield projections Therefore they have to be bias corrected before use Using climate projections to drive process based or statistical crop models to predict crop yield is the main way of performing impact assessments Lobell et al 2008 Lobell and Burke 2010 This highlights the importance of quantifying the uncertainties in crop yield prediction that are caused by using different climate projections and crop models which was neglected in many impact assessments and has only recently been emphasized
