Estimation of cloud base height for FY-4A satellite based on random forest algorithm
Received:January 06, 2019  Revised:January 22, 2019  download
Citation:
Hits: 332
Download times: 312
Author NameAffiliationE-mail
TAN Zhong-Hui National University of Defense Technology tzh_go@126.com 
MA Shuo National University of Defense Technology mashuo0601 
HAN Ding Unit No of PLA  
GAO Ding Unit No of PLA  
YAN Wei National University of Defense Technology  
Abstract:Based on upstream products of FY-4A and A-Train satellites data, an estimation algorithm of cloud base height for FY-4A has been presented utilizing Random Forest model. The algorithm is evaluated in the comparison with CloudSat and CALIPSO. The results show that cloud base height for top layer cloud can be generated by using upstream products of FY-4A. Compared with CloudSat and CALIPSO, the mean absolute error is less than 1km and the relationship coefficient is bigger than 0.8. The presence of multi-layer clouds may result in underestimate of cloud base height, the error in cloud top height may also introduce uncertainties in estimation of cloud thickness and cloud base height. In addition, error of the cloud base height tend to increase as the cloud thickness increasing.
keywords:FY-4A, Cloud base height, Random Forest, A-Train
View Full Text  HTML  View/Add Comment  Download reader

Copyright:《Journal of Infrared And Millimeter Waves》