Multi-scale Satellite Data Sensitivity Study on Cloud Analysis of Strong Typhoon

The traditional obervation interval of Fengyun geostationary meteorological series satellite is 1 hour for a single satellite. During flooding season, the obervation frequency is imporived to half an hour. Double satellite observation mode can provide remote sensing data every 15 minutes. Due to the difference of observation angles and calibration error between different satellites, remote sensing data sometimes appear consistency and uniformity deviation. So improving observation frequency for a single satellite is the best way to get high quality remote sensing data. Rapid scan mode of geostationary meteorological satellites is an important method to monitor all kinds of weather processes.National Satellite Meteorological Center uses retired FY-2C satellite to carry out high frequency rapid regional scan observation trials and get continuous data with an average of 10-minute interval. Based on high frequency observations, Hovmöller diagram and coefficient of variation are used to analyze the sensitivity of multi-scale satellite data on monitoring the structure of a strong typhoon Muifa (2011).The research results show that the high frequency observations can clearly demonstrate the evolution of a strong typhoon cloud structure. Each channel with different spatial and temporal resolution has different sensitiveness in monitoring the structure feature of cloud. Reflectivity at visible channel with 1.25-kilometer spatial resolution and 10-minute temporal resoution can well show features of typhoon cloud. Under the same observation temporal resolution condition, lowering spatial resolution has great impact on monitoring the structure of cloud. If the spatial resolution keeps the same, reduced observation temporal resolution has less effect on extracting the characteristics of clouds. Using Hovmöller diagram to compare cloud brightness temperature characteristics through infrared window channel under different temporal resolution, it can be seen that there is no great difference between 10-minute and 30-minute observation modes. The cloud features are greatly reduced after the observation interval being changed to 60 minutes. The results also show that the cloud characteristics change greatly during 60 minutes based on brightness temperature coefficient of variation difference. Because the brightness temperature coefficient of variation at water vapor channel is smaller than infrared channel, the evolution of cloud characters observed by infrared window channel is more sensitive than that by water vapor channel. So improved observation temporal resolution can get more cloud information through infrared window channel.