PNNL

Abstract

For a better utilization of the ground-based microwave radiometer, it is important to detect the cloud presence in the measured data. Here, we introduce a simple and fast cloud detection algorithm by using the optical characteristics of the clouds in the infrared atmospheric window region. The new algorithm utilizes the brightness temperature (Tb) measured by an infrared radiometer installed on top of a microwave radiometer. The two step algorithm consists of a spectral test followed by a temporal test. The measured Tb is first compared with a predicted clear sky Tb obtained by an empirical formula as a function of surface air temperature and water vapor pressure. For the temporal test, the temporal variability of the measured Tb during one minute compares with a dynamic threshold value, representing the variability of the clear sky condition. It is designated as cloud free data only when both the spectral and temporal tests confirm a cloud free data. Overall, most of the thick and uniform clouds are successfully screened out by the spectral test, while the broken and fast-varying clouds are screened out by the temporal test. The algorithm is validated by comparison with the collocated ceilometer data for 6 months, from January 2013 to June 2013. The overall proportion correct is about 88.3% and the probability of detection is 90.8 %, which are comparable with or better than those of previous similar approaches. Two thirds of failures occur when the new algorithm detects clouds while the ceilometer does not detect, resulting in different values of the probability of detection with different cloud base altitude, 93.8, 90.3, and 82.8% for low, mid, and high clouds, respectively. Finally, due to the characteristics of the spectral range, the new algorithm is found to be insensitive to the presence of inversion layers.