The new generation of geostationary weather satellite imagers has the advantage of high spatial and temporal resolution, and cloud observations from the imagers are widely used in various studies in the field of meteorology. Due to the observation mode of the satellite and the curvature of the Earth, it has a parallax problem, the impact of which needs to be considered when it is jointly applied with other information. To address the parallax problem of the Fengyun-4A imager, the Advanced Geosynchronous Radiation Imager (AGRI), a sensitivity analysis was first performed using the simulated cloud top height and the actual satellite zenith angle, and the results confirmed that the higher the cloud top height or the larger the satellite zenith angle, the greater the parallax, especially for the imager with higher spatial resolution. Cloud data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and three sets of typhoon best track sets were then used to examine the accuracy of AGRI cloud mask products and typhoon center positioning before and after the parallax correction. The results demonstrate the effectiveness of the parallax correction method used, and point out that parallax cannot be neglected in the accurate quantitative application of geostationary meteorological satellite datasets.

Monitoring and predicting highly localized weather events over a very short-term period, typically ranging from minutes to a few hours, are very important for decision makers and public action. Nowcasting these events usually relies on radar observations through monitoring and extrapolation. With advanced high-resolution imaging and sounding observations from weather satellites, nowcasting can be enhanced by combining radar, satellite, and other data, while quantitative applications of those data for nowcasting are advanced through using machine learning techniques. Those applications include monitoring the location, impact area, intensity, water vapor, atmospheric instability, precipitation, physical properties, and optical properties of the severe storm at different stages (pre-convection, initiation, development, and decaying), identification of storm types (wind, snow, hail, etc.), and predicting the occurrence and evolution of the storm. Satellite observations can provide information on the environmental characteristics in the pre-convection stage and are very useful for situational awareness and storm warning. This paper provides an overview of recent progress on quantitative applications of satellite data in nowcasting and its challenges, and future perspectives are also addressed and discussed.