Retrieval of cloud base height and cloud geometric thickness based on PARASOL oxygen A band Huazhe Shang
State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences
Abstract
The base heights and geometric thicknesses of clouds are important cloud characteristics and are highly important for climate, weather, and aviation safety. The current measurement methods have limitations: ground-based observations have limited ranges, active remote sensing has insufficient spatiotemporal coverage, and passive remote sensing cannot directly retrieve cloud base information. Therefore, a new cloud base height retrieval method, which is a cloud base height retrieval method based on the PARASOL oxygen A-band (OA), is proposed in this paper. On this basis, multiangle polarization can be used to obtain the top heights of clouds with high precision. Then, by combining the top height of a cloud with its base height, the geometric thickness of the cloud can be acquired. Simulation experiments involving radiative transfer models indicate that the OA exhibits regular sensitivity to the CBH . Within the OA, the ratio of narrow-channel (763 nm) to wide-channel (765 nm) radiation intensities increases as the CBH increases. Owing to the uniform distribution of oxygen in the atmosphere, the OA remains relatively stable. Additionally, the wealth of information derived from multiangle remote sensing can further increase the accuracy of retrievals. Therefore, the multiangle OA is incorporated into the model training process. CBHs obtained from CloudSat are used as the true values. The longitude, latitude, and multiangle OA information obtained from PARASOL Level 1 is utilized to retrieve the CBHs. After several machine learning algorithms are compared, the deep neural network (DNN) model with the best accuracy is selected as the retrieval model. The method of CBH reversal based on multiangle OA remote sensing and the DNN has a mean absolute error (MAE) of 0.78 km, a bias of 0.22 km, and a correlation coefficient (R) of 0.82. By integrating machine learning with the multiangle OA, this method offers a novel approach for CBH retrieval.
Keywords: multi-angle,oxygen A band,cloud base height,cloud geometric thickness,PARASOL,CloudSat
