Application of Microwave Remote-Sensing Data for Tropical Cyclone Fullness Extraction

Tropical cyclone fullness (TCF) is a dimensionless metric that integrates the inner- and outer-core scales of tropical cyclones to characterize storm wind structures, with particular significance for operational typhoon forecasting. Spaceborne microwave sensors offer a new technical approach to accurately extract TCFs by enabling direct observation of typhoon ocean surface winds regardless of weather conditions. Adopting super typhoon Mawar (2023) as an example, this study proposes a TCF extraction method based on the collection of spaceborne synthetic aperture radar, scatterometer, and radiometer data. Multisource spaceborne microwave sensor data estimated typhoon metrics are then comprehensively compared with best-track reports. Results show that multisource spaceborne microwave-sensor data have good applicability in TCF estimation. The root mean square error and correlation coefficient between the satellite-retrieved and best-track data are 0.08 and 0.78, respectively. Although the typhoon intensity is underestimated by the ocean wind products obtained from ASCAT-B and ASCAT-C spaceborne scatterometers, the estimates for the radius of maximum wind (rmax) and the radius of 17 m s−1 winds (r17) are accurate. The ASCAT-B measured rmax and r17 are 21.91 km and 39.22 km, respectively, with the corresponding ASCAT-C-measured values being 16.72 km and 48.82 km, respectively. This study demonstrates the independent suitability of multisource microwave sensors for TCF extraction, despite their differing frequency bands and spatial resolutions.