Understanding how climate variability affects oilseed yields is crucial for ensuring a stable oil supply in regions such as China, where self-sufficiency in edible vegetable oils is low. Here, we found coherent patterns in the interannual variability of Sea Surface Temperature (SST) anomalies and percent crop yield anomalies in the three ocean basins, and then quantified the contribution of these SST modes to oilseed crop yield anomalies. Our analysis revealed that, at the national level, the six tropical SST modes collectively accounted for 51% of soybean, 52% of rapeseed, and 33% of peanut yield anomalies in China. Tropical Indian Ocean variability exerts the greatest impact on soybean and peanut yield variability, whereas the most significant impact on rapeseed yield anomalies is attributed to El Ni & ntilde;o-Southern Oscillation. Finally, this study examined the specific ways in which changes in SST modes can affect oilseed crop yields using changes in local meteorological variables. Our findings revealed the relationship between tropical SST variability and oilseed crop yields, providing a detailed understanding of the diverse connections between SST modes and oilseed crop yield. This study deepens our knowledge of the influence of climate variability on agriculture, offering valuable insights for devising strategies to mitigate the adverse effects of climate variability on oilseed crop production in China. Our research explored the connection between changes in sea surface temperatures and the yield of main oilseed crops in China: soybeans, rapeseed, and peanuts. We discovered that certain temperature patterns in tropical oceans significantly impact these yields. For instance, temperature changes in the tropical Indian Ocean mostly affect soybean and peanut yields, while the climate phenomenon known as El Ni & ntilde;o greatly influences rapeseed yields. By understanding these relationships, we can better anticipate future yield changes and ensure a steady edible oil supply in China. This knowledge is essential for developing strategies to neutralize any negative effects of changing climate conditions on China's oilseed farming. A clear connection was found between sea surface temperature (SST) anomalies and crop yield anomalies in China Tropical Indian Ocean variability majorly impacts soybean and peanut yields, while El Ni & ntilde;o-Southern Oscillation significantly affects rapeseed yields The study reveals how SST patterns affect crop yields via local meteorological variables such as vapor pressure deficit and temperature