Using Satellite Data for Studying Storm Top Dynamical Processes: A Review of Recent Findings

Severe storm systems are difficult to make in-situ observations mainly because the danger involved in doing so. Consequently, remote sensing data are extremely valuable to the study of thunderstorm physics and dynamics if we can correctly interpret these data. Satellite data are superior to other types of remote sensing data (such as radar) when wide area coverage and continuous observation are necessary as satellites regularly scan over large swaths of earth surface and geostationary satellites can provide continuous observations of storm systems.

The real problem of using satellite data for storm studies is in the correct interpretation of the data. We observe many features at the top of storms, such as the enhanced-V (cold-V), above anvil cirrus plumes, close-in warm area, cold ring, pancake clouds, and storm top ship wave signatures. What are the physical mechanisms responsible for producing these features? The understanding of the physics behind these features can greatly facilitate the usage of satellite storm data for nowcasting and study of severe weather.

In this study, we used a cloud resolving model to simulate real storm cases so as to demonstrate that satellite observed storm top features can be successfully reproduced by a physics-based cloud model, and that the model physics can be used to explain how these features occur. We will show model results that match very closely the satellite observations. Both geostationary and polar orbiting data (mainly that of the NASA A-train, but also Suomi NPP) will be shown and discussed. We will also show some occasional aircraft observations that fill some data gaps where it is hard for a satellite to obtain to demonstrate the validity of the model interpretation.

The future applications of these findings will also be discussed.