地基微波辐射计的亮温观测与模拟数据的一致性分析和云检测

Consistency Analysis of Experimental and Simulated Brightness Temperature based on Ground-based Microwave Radiometer and Cloud Detection

为了利用辐射计观测数据"晴空样本"判断辐射计各通道的工作状态,并找出各通道的订正关系、进一步研究"云天样本",针对在广州市从化区进行观测试验的一台微波辐射计的亮温观测数据(TBM)和相应地点的NCEP大气层结资料,通过辐射传输方程计算得到模拟数据(TBC)并进行全样本一致性对比,根据多通道亮温差值阈值法识别出"晴空样本"与"云天样本"(以及少量歧义数据)。对"晴空"样本进行回归分析,判断该辐射计的工作状态、建立TBM-TBC订正关系,并应用于"全样本"观测数据进行线性订正。根据辐射计云底高度数据与订正后的亮温差值的时间序列对比,证明了多通道亮温差值阈值法识别晴空效果较好。经过订正后的"晴空样本"可直接用于后续的大气温湿度反演流程,而识别出的"云天样本"(含雨天)为后续云参数反演及亮温数据的云影响订正并进入下一步的大气温湿度反演流程打下了基础。

In order to estimate the working state of the radiometry channels by using ＂clear sky＂ samples and to find out the correction relationship for each channel to further investigate the ＂cloud＂ samples, we firstly make a consistency analysis of observed brightness temperature data （TBM） obtained from Microwave Radiometer located in Conghua district of Guangzhou province and the simulated brightness tempera- ture data （Tl3c） calculated by using NCEP atmospheric profile data based on the radiative transfer equation.Then,the ＂clear sky＂ samples and ＂cloud＂ samples （including few ambiguous data） are identified using multi-channel brightness temperature difference threshold method.Finally,the linear correction for the ＂clear sky＂ samples based on the regression analysis are used to establish the correction relationship between TBM and TBC to estimate the working state of the ground-based microwave radiometer.According to the comparison of the time series between the cloud bottom height data of radiometer and the corrected brightness temperature, it is proved that the multi-channel brightness temperature difference threshold method is good to identify the clear sky.The corrected ＂clear sky＂ samples can be directly used in the subsequent air temperature and humidity inversion process,and the identified ＂cloud＂ samples （including rain samples） provide a base for the subsequent cloud parameter inverse algorithm and the cloud effect correction of the brightness temperature data, which can be further used in the subsequent inverse of the air temperature and humidity for all the samples.