Examination of the Quality of GOSAT/CAI Cloud Flag Data over Beijing Using Ground-based Cloud Data  

作　　者：霍娟 章文星 曾晓夏 吕达仁 刘毅 

机构地区：[1]Key Laboratory for Atmosphere and Global Environment Observation, Institute of Atmospheric Physics,Chinese Academy of Sciences

出　　处：《Advances in Atmospheric Sciences》2013年第6期1526-1534,共9页大气科学进展（英文版）

基　　金：support from the Strategic Pilot Science and Technology project of the Chinese Academy of Sciences(Grant No.XDA05040200);the National Natural Science Foundation of China(Grant No.41275040)

摘　　要：It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.

关 键 词：Greenhouse Gases Observing Satellite Thermal and Near-infrared Sensor for Carbon Observa-tion-Cloud and Aerosol Imager all-sky imager CLOUD 

分 类 号：P414.4[天文地球—大气科学及气象学]