| Summary: | Farmers’ perception of climate change is crucial in adaptation intention and process. However, farmers’ perceptions may not be timely, accurate and systematically consistent with the direction and significance of observational records. Although some research compared farmers’ perceptions and climate data, little attention has been paid to comprehensibly analyse both data sources discrepancies based on empirical studies results. By combining bibliometrics and a systematic review approach, we identify which approaches are used to compare perceived and observed data, how both patterns have been mutually evolved, which factors determine their (in)consistency, and if their accordance and robustness affect farmers’ adaptive capacity. We analyse a portfolio of 147 papers collected from the Scopus library catalogue since 2000. The bibliometric analysis was coupled with an exploratory analysis of 98 papers selected from the original portfolio. The literature is extensive, fast-growing, and spans several disciplines. We identify four consolidated research lines: (a) perceived risk and farmers’ adaptive capacity nexus, (b) crop vulnerability due to temperature increase and erratic rainfall patterns, (c) forecasting use and influence in farmers’ decisions, and (d) climate change awareness conditioning farmers’ profiles. Nonetheless, we observe some research gaps: (a) a conceptual mismatch in ‘normal pattern’ or ‘drought’ meaning, (b) poor or limited data from meteorological stations, (c) overlook or oversimplification of local knowledge in describing perception, (d) farmers’ memory weaknesses to keep track of climate alterations, and (e) a geographical dissonance in favour of Global South regions. Our science-metric study also reveals some research questions to be consolidated: Can the perception of extreme events increase climate change awareness? Can greater awareness reduce discrepancy with observed data? How do heuristics and socio-psychological filters influence farmers’ awareness and interpretation of climate data? We suggest putting major efforts into reinforcing these research lines as part of a novel domain-dependent trend to reduce the discrepancy.
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