Abstract
Since the 1960’s, meteorological satellites have been able to monitor Atlantic hurricanes, Pacific typhoons, and tropical cyclones in the Indian Ocean. However, these satellites' images have been acquired by passive remote sensing instruments that operate in the visible and infrared bands. Thus, visible images (and most infrared images) only display the cloud-top structure of tropical cyclones and make it a challenge to study the intense air-sea interaction near the sea surface. On the other hand, active remote-sensing sensors, such as spaceborne microwave remote scatterometers and synthetic aperture radars (SARs), can “see” through clouds and facilitate observations of the air-sea interaction processes. Compared with scatterometers, SAR acquires images and provides the wind field at much higher resolution. Because of this, the eye of a tropical cyclone at surface level can be identified. A SAR sensor emits pulses of microwave radiation that penetrate clouds. The backscattered signals received by the SAR can be processed into a high-resolution image and calibrated to represent the normalized radar cross-section (NRCS) of the sea surface. The NRCS is a measure of sea surface roughness, which depends on wind speed and direction, the presence of swell waves, and is affected by rain as well. In this project, 15 RADARSAT-2 and 108 Sentinel-1 SAR images of Atlantic and Indian Ocean tropical cyclones and Pacific typhoons from 2016-2020, which display clear eye structure, or “eye hits”, were analyzed with ancillary tropical cyclone intensity information. Statistical analyses were performed to obtain the size distribution of the eyes of the tropical cyclones being analyzed in this study. To measure the size of the storm eye, we created a mask in each image where the dark NRCS was present in the inner core of the tropical cyclone. Additionally, we assigned an azimuthal wavenumber for each shape of the tropical cyclone eye. The results, combined with those of Li et al. (2013)’s study, showed that concentric and asymmetrical circular eyes were present in the most intense storms, and that Category-4 tropical cyclones had the smallest eye. Additionally, most of the images contained dark rain bands and boundary layer rolls.