Improving the Retrieval of Cloudy Atmospheric Profiles from Brightness Temperatures Observed with a Ground-Based Microwave Radiometer

Atmospheric temperature and humidity retrievals from ground-based microwave remote sensing are useful in a variety of meteorological environmental applications. Though the influence clouds is usually considered current retrieval algorithms, resulting estimates still biased high overcast conditions compared to radiosonde observations. Therefore, there need improve quality cloudy conditions. This paper presents an approach make brightness (TB) correction for cloud before data can be used inversion vertical profiles atmospheric humidity. A three-channel method proposed parameter estimation, i.e., total 22 channels radiometer, three adopted set up relationship between parameters temperatures, so that observations estimate thickness water content complete rest retrieval. Based on two years atmosphere Beijing, comparison with (RAOB) shows: (1) this study have higher correlation RAOB notably better than vendor-provided LV2. The bias close zero at all heights, RMSE greatly reduced >5 °C <2 layer, about 1.5 km 5 km. LV2, especially above 2 height. (2) vapor density profile near zero, while LV2 has positive as large 4 g/m3. g/m3, 10 That is, both evidently less greater improvement lower troposphere below Correlation improved even more density. increases one within boundary but only 0.8 0.5 height, 0.7 1 km, (3) named Cloud Impact index, determined by concentration thickness, together base been defined show BIAS “high-CI subsample” larger those “low-CI subsample”, indicating high-CI impact necessary.