Vegetable crops production in the field and changes in physiological aspects of crops during the growing season may be affected by the increased temperatures associated with climate change. The objectives of this research were to evaluate the performance of an air temperature gradient using the computational fluid dynamics (CFD) technique and validation of performance throughout Kimchi cabbage growth and physiological responses to air temperature in a greenhouse temperature gradient (GTG). We simulated temperature differences with CFD in a semi-closed plastic tunnel, which is a GTG. The accuracy of CFD improved by vertical and horizontal temperature profiles was evaluated for the performances of a GTG. The growth of Kimchi cabbage was examined and validated using a temperature gradient within a GTG. Correlation coefficients of measured heights were 1.120, 0.597, and 0.459. Root mean square error was below 0.103, which means the CFD simulation values were highly accurate. The error analysis showed that it was possible to accurately predict temperature gradient changes within a GTG using CFD techniques. CFD results showed an average error of 0.597 °C compared to field monitoring results. The maximum temperature difference of the GTG was 5.7 °C, suggesting a well-controlled set point (6 °C difference between outside conditions and inside conditions of the GTG). On a cloudy day, the GTG set differential temperature (dT) was well maintained, while the accuracy of the GTG’s dT was degraded on sunny days because of interference by solar radiation. There was a significant difference in the growth, net photosynthetic rate, transpiration rate, and intercellular CO₂ concentration along with temperature differences in the GTG. CFD can simulate temperature gradient distribution in a GTG and predict the temperature difference for equipment with different specifications. These facilities can be used in climate change-related studies, such as assessment of crop production area optimization, crop physiological response to temperature, vulnerability assessment of crop production under increasing temperatures, or extreme weather.

田间蔬菜作物的生产和生长季节作物生理方面的变化可能会受到与气候变化相关的温度升高的影响。本研究的目的是使用计算流体动力学 (CFD) 技术评估空气温度梯度的性能，并验证整个泡菜生长的性能以及温室温度梯度 (GTG) 中对空气温度的生理反应。我们使用 CFD 模拟了半封闭塑料隧道（GTG）中的温差。通过垂直和水平温度曲线提高的 CFD 精度评估了 GTG 的性能。使用 GTG 内的温度梯度检查和验证泡菜的生长。测量高度的相关系数为 1.120、0.597 和 0.459。均方根误差低于 0.103，这意味着 CFD 模拟值高度准确。误差分析表明，可以使用 CFD 技术准确预测 GTG 内的温度梯度变化。与现场监测结果相比，CFD 结果显示平均误差为 0.597 °C。GTG 的最大温差为 5.7 °C，表明设定点控制良好（GTG 的外部条件和内部条件之间的差异为 6 °C）。在阴天时，GTG的设定温差（dT）保持良好，而在晴天，由于太阳辐射的干扰，GTG的dT精度会下降。生长、净光合速率、蒸腾速率、₂浓度以及 GTG 中的温差。CFD 可以模拟 GTG 中的温度梯度分布，并预测不同规格设备的温差。这些设施可用于与气候变化相关的研究，例如作物产区优化评估、作物对温度的生理反应、温度升高或极端天气下作物生产的脆弱性评估。