Cloud Cover in the Australian Region: Development and Validation of a Cloud Masking, Classification and Optical Depth Retrieval Algorithm for the Advanced Himawari Imager

摘要: This paper presents a cloud masking, classification and optical depth retrieval algorithm using visible, near-infrared thermal-infrared bands. A time-series-based approach was developed for masking with quantitative validation against Cloud-Aerosol Lidar Orthogonal Polarization (CALIOP). An overall hit rate (the proportion of pixels identified by both sensors as either clear or cloudy) 87% found. However, analysis revealed that, under partially cloudy conditions, the small footprint CALIOP had major impact on rate. When are excluded ~98% found, even thin clouds 0.98 at all sites. Further assessment conducted comparing seasonal annual fraction that ISCCP (International Satellite Cloud Climatology Project) over Australia surrounding region. It showed high degree resemblance between two datasets in their total fraction. The geographical distribution classes also broad resemblance, though detailed differences exist, especially clouds, probably due to use different systems datasets. products generated from this study being used several applications including ocean colour remote sensing, solar energy, vegetation monitoring detection smoke health impacts, aerosol land surface bidirectional reflectance function (BRDF) retrieval. method herein can be applied other geostationary sensors.