Projection of Effects of Climate Change on Rice Yield and Keys to Reduce Its Uncertainties

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The increase in atmospheric CO2 concentration and accompanying global warming should affect crop productivity. A number of experiments and simulations have been conducted to predict the impacts of climate change on rice yield. When conducting large-scale evaluation of rice yield, there are large uncertainties, which resulted from a number of sources, such as those in the greenhouse gas (GHG) emission scenarios, global climate models (GCMs) and its gaps between global and local climates. In addition, the rice development models themselves include uncertainties. In this paper, we present our recent studies on large-scale evaluation by crop models and trials to elucidate and reduce uncertainties accompanied with each aspect of evaluation. In modeling technique aspect, statistical approach for model parameters and the use of multi-scenarios and multi-GCMs are reviewed. In field experiment aspect, we present a field survey on spikelet sterility in the hot summer of 2007 and some insights from free-air CO2 enrichment (FACE) experiment. They strongly suggest the necessity for developing a process-based rice development model including heat balance. The synthesized process-based model study in tandem with FACE experiments contributes not only for reducing the evaluation uncertainties, but also for validating the adapting or avoiding studies of heat stress or negative influence on rice under projected climate change.