地基微波辐射计资料在降水分析中的应用

为了提升国产地基微波辐射计反演大气温湿廓线的精度，增强本地部署设备的观测性能，研究实现了地基微波辐射计的神经网络直接样本反演法和观测亮温预处理的神经网络间接样本反演法。将算法应用于武汉华梦科技有限公司研制的HRA002型国产地基微波辐射计，在武汉国家基本气象站开展了与探空以及美国3台MP-3000A微波辐射计的对比观测试验。试验结果显示，HRA002直接样本反演采用改进网络反演水汽密度、相对湿度均方差分别降低约0.94 g·m^-3、5%；观测亮温经过预处理后与模拟亮温的相关性提升明显，预处理前后反演的低层温度、水汽密度和相对湿度与探空观测的均方差分别从2.4 K、3.26 g·m^-3和18.79%改善为1.58 K、2.18 g·m^-3和14.55%，略高于直接样本反演；与3台MP-3000A的反演结果相比，HRA002采用直接样本反演方法的温度廓线总体优于MP-3000A，HRA002采用间接样本反演方法的水汽密度和相对湿度总体上平均偏差占优而均方差稍逊。研究结果表明改进后的直接样本反演法更贴合辐射计硬件性能，反演精度较高；亮温预处理显著提升了间接样本反演精度，在反演精度总体接近的情况下，弥补了直接样本反演法需要长期观测数据的缺陷；综合采用上述两种算法能够提升国产地基微波辐射计本地化、个体化的观测性能，在反演大气参量廓线方面具有可用性。

A method to improve the accuracy of continuous measuring of vertical profiles of temperature and water vapor density by means of a ground-based microwave radiometer

In order to improve the accuracy of the ground-based microwave radiometer retrievals of the atmospheric temperature and humidity profile, and enhance the observation performance of locally deployed devices, this study implements two kinds of neural network methods for ground-based radiometer. One is called neural network direct sample retrieval algorithm, and the other is the neural network indirect sample retrieval algorithm based on the preprocessing of the observed brightness temperature. In this paper, these two retrieval algorithms are applied to the HRA002 domestic ground-based microwave radiometer developed by Wuhan Huameng Technology Co., Ltd., and the comparative observation experiments with soundings and three US MP-3000A microwave radiometers are carried out at the Wuhan National Basic Weather Station. The experiments results show that the mean square error of water vapor density and relative humidity retrieved by the improved network in direct sample retrieval is reduced by 0.94 g·m^-3 and 5% respectively. The correlation between the observed brightness temperature and the simulated brightness temperature is improved significantly after preprocessing, the mean square error of the retrieval of lower-level temperature, water vapor density and relative humidity compared with sounding are improved from 2.4 K, 3.26 g·m^-3 and 18.79% to 1.58 K, 2.18 g·m^-3 and 14.55%. The accuracy of the HRA002 indirect sample retrieval method is slightly lower than that of the direct sample retrieval method, but the accuracy of the two methods is close. Compared with the retrieval results of 3 MP-3000A, the temperature profile of HRA002 using the direct sample retrieval method is generally better than MP-3000A, while the average deviations of water vapor density and relative humidity using indirect sample retrieval method of HRA002 is better than others, but the mean square errors are slightly lower. The research results in this paper show that the improved direct sample inversion method is more suitable for radiometer hardware performance and has higher retrieval accuracy, and the brightness temperature preprocessing of HRA002 can effectively improve the accuracy of indirect sample retrieval, making up for the defect that the direct sample retrieval method needs long-term observation data. The results also show that the use of direct sample and indirect sample retrieval algorithms can improve the localized and individualized observation performance of domestic microwave radiometers, and is useful in retrieving atmospheric parameter profiles.