在地基高光譜遙感中，特征向量法獲取的溫濕廓線以初值的方式對物理反演進行約束，其反演精度對物理反演結果有著重要的影響。利用AERI的觀測輻射資料和同站點的探空數據，基于特征向量法分析了溫度廓線與濕度廓線反演的異同點；研究了主成分個數的選擇問題，綜合考慮反演精度和特征向量中包含的信息將反演溫度廓線和濕度廓線的最優主成分個數定為7。為提高反演精度，引入地面溫度、濕度、氣壓作為影響因子，試驗結果表明，考慮反演精度和穩定性，地面氣壓的引入相比于其他2種單一氣象要素以及3種氣象要素組成的因子集表現更好，尤其是對邊界層中下部的溫濕廓線有著明顯的提升，并隨著高度的降低提升作用更明顯，溫度廓線RMSE降低最高達到1.5 K，濕度廓線RMSE降低最高達到0.42 g/kg。同時，分析了對數反演形式對濕度廓線的影響，結果表明，以水汽混合比的形式反演時取自然對數對反演精度的影響較小；將反演得到的水汽混合比轉化為相對濕度后，取自然對數對反演精度有12%以上的提升。
The initial profile, which is calculated by the eigenvector regression algorithm in the groundbased hyperspectral remote sensing, has a significant impact on the accuracy of the physical retrieval. Based on the eigenvector regression algorithm, the similarities and differences between the retrievals of temperature profiles and water vapor profiles are analyzed using the radiance data observed by AERI and coincident radiosonde profiles. The optimal number of principal components is analyzed when retrieving the temperature and water vapor profiles. Considering both the accuracy and the information contained in the eigenvectors, the optimal numbers of principal components are both set to 7. In order to improve the accuracy of remote sensing, the surface temperature, humidity and pressure are introduced as the influence factors. The experiment results show that the introduction of surface pressure has a better performance than the other two single meteorological elements and the assemble of factors composed of all three meteorological elements, especially for the accuracy and stability of temperature and water vapor profiles in the middle and lower parts of the boundary layer. With the decrease of altitude, the RMSE of temperature profiles decreases to a maximum of 1.5 K, and the RMSE of temperature profiles decreases to a maximum of 0.42 g/kg. At the same time, the impact of logarithmic water vapor mixing ratio on the retrieval of water vapor profiles is analyzed. The result shows that the introduction of the logarithmic profile has little effect on the accuracy of the retrieval. However, the accuracy of the water vapor profile gains more than 12% when converting mixing ratio to relative humidity.