| Summary: | Climate change significantly impacts global agricultural production, giving rise to considerable uncertainties. To explore these climate impacts, three independent methods have been employed: manipulated experiments, process-based crop models, and empirical statistical models. However, the uncertainty stemming from the use of different methods has received insufficient attention, and its implications remain unclear, necessitating a systematic review. In this study, we conducted a comprehensive review of numerous previous studies to summarize the historic development and current status of each method. Through a method comparison, we identified their respective strengths, limitations, and ideal areas of application. Additionally, we outlined potential prospects and suggested directions for future improvements, including clarifying the response mechanisms, updating simulation technologies, and developing multi-method ensembles. By addressing the knowledge gap regarding method differences, this review could contribute to a more accurate assessment of climate impacts on agriculture.
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