利用TP/WVP-3000型地基微波辐射计12通道亮温观测资料，发展了一套大气温湿及液态水廓线反演算法。首先对近20年历史探空数据进行数据转换、插值等处理后，分无云和有云两种类型，运用MWMOD微波辐射传输模式，计算无云情况下的微波亮温集，根据相对湿度廓线，利用模式的绝热液水含量分析方法，模拟计算出液态水廓线及对应的微波亮温数据集，利用改进BP神经网络计算模型，通过神经网络学习训练，获取代表该地区的神经网络系数，用于反演计算大气温度、水汽密度、相对湿度和液态水廓线。与GPS探空数据对比，反演的大气温度廓线在7 km以下误差均在3 K以内，水汽密度廓线在6 km以下误差均在3 g/m2以内，部分底层廓线的反演值与GPS探空观测接近，获得了较好的反演结果。同时，通过模式分析出云水廓线，弥补GPS探空不足，利用微波辐射计观测进行验证，估算雷达路径积分衰减，用于试验降水雷达反演分析。%An atmospheric profile retrieval algorithm was proposed based on the MWMOD microwave radiation transmission model and neural network using a twelve channel microwave radiometer. Temperature profile, water vapor profile, relative humidity profile, liquid water profile, integrated water vapor and liquid water path were retrieved through an analysis of the observed microwave radiation brightness and temperature, which are very important for an airborne field campaign. The error of the inversion temperature profile was lower than 3 K in the 7 km, and the one of humidity profiles was lower 3 g/m2 in the 6 km. The inversion results were better in some cases. The path-integrated attenuation (PIA) of the ground-base radar could be computed by analyzing the liquid water content of cloud, and could be validated using the observation of TP/WVP-3000 Radiometer. Using a ground-based multi-channel microwave radiometer, GPS radiosonde data and MWMOD model, the integrated attenuation of the Ka-band radar was computed and the attenuation correction was accomplished. The retrieval data has important reference value for estimating the attenuation of ground-based weather radar echoes.
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