Due to the solar radiation effect, current air temperature sensors inside a thermometer screen or radiation shield may produce measurement errors that are 0.8 °C or higher. To improve the observation accuracy, an aspirated temperature measurement platform is designed. A computational fluid dynamics (CFD) method is implemented to analyze and calculate the radiation error of the aspirated temperature measurement platform under various environmental conditions. Then, a radiation error correction equation is obtained by fitting the CFD results using a genetic algorithm (GA) method. In order to verify the performance of the temperature sensor, the aspirated temperature measurement platform, temperature sensors with a naturally ventilated radiation shield, and a thermometer screen are characterized in the same environment to conduct the intercomparison. The average radiation errors of the sensors in the naturally ventilated radiation shield and the thermometer screen are 0.44 °C and 0.25 °C, respectively. In contrast, the radiation error of the aspirated temperature measurement platform is as low as 0.05 °C. This aspirated temperature sensor allows the radiation error to be reduced by approximately 88.6% compared to the naturally ventilated radiation shield, and allows the error to be reduced by a percentage of approximately 80% compared to the thermometer screen. The mean absolute error and root mean square error between the correction equation and experimental results are 0.032 °C and 0.036 °C, respectively, which demonstrates the accuracy of the CFD and GA methods proposed in this research.