基于欧洲中尺度天气预报中心(ECMWF)大气廓线库和RTTOV9.3辐射传输正向模式,探讨了大气CH₄混合比浓度垂直廓线和柱总量的经验正交函数(EOF)反演方法,并利用地基傅里叶热红外光谱仪(FTS)观测数据和红外EOSAQUA卫星的大气红外传感器(AIRS)实际观测资料进行反演实验和验证。并且与地基傅里叶热红外光谱仪(FTS)观测结果相比,300hPa以下EOF模型反演的CH₄混合比均方根相对误差小于AIRS的CH₄产品,CH₄柱总量的相对误差也小于AIRS产品。与AIRS的CH₄产品相比,EOF模型反演的CH₄混合比廓线相关系数为0.97,均方根相对误差小于2.5%。验证结果表明EOF模型可以为物理反演提供很好的初始值,由于其稳定且运算更快捷,在业务化运行方面具有很大应用前景。

This paper presents an improved Empirical Orthogonal Functions (EOF) model for estimating methane profilesfrom spaceborne hyperspectral infrared observations based on profile dataset from European Centre for Medium-RangeWeather Forecasts (ECMWF) and radiative transfer model RTTOV9.3. The model was applied to Atmospheric InfraredSounder (AIRS) observations, validated by ground-based Fourier Transform Spectrometer (FTS) observations and AIRS v5.0 CH₄ products. Compared with FTS measurements, the Root Mean Square (RMS) relative error of CH₄ mixing ratio of EOFretrieval was smaller than that of AIRS v5.0 CH₄ product for data lower than 300 hPa, and the relative error of CH₄ columnamount of EOF retrieval was also smaller. Compared with AIRS v5.0 CH₄ product, the coefficient of determination for CH₄profiles retrieved from EOF model was 0.9715, and the RMS relative errors were smaller than 2.5%. The validation resultsshow that the EOF model could provide a good initial value for physical retrieval and is a promising operational approach dueto high stability and efficiency.