Tropical Cyclone Intensity Estimation From Spaceborne Microwave Scatterometry and Parametric Wind Models

Spaceborne microwave sensors, measuring co-/cross-polarization (VV/VH) normalized radar cross section signals, have been widely used for tropical cyclone (TC) monitoring. However, considerable gaps remain to obtain TC intensity since these satellite data either blur inner-core structures (e.g., scatterometer data) or have limited spatial-temporal coverage (e.g., synthetic aperture radar (SAR) data). This study aims to get more accurate TC intensity estimates from scatterometers, which have good global coverage but relatively low spatial resolution. To overcome the blurring effect in scatterometers, we propose a new technique for guidance on TC intensities, with maximum 1-min sustained winds calculated as a function of decay parameters provided by the parametric Rankine-type model. The technique is employed on advanced scatterometer (ASCAT) data acquired between 2016 and 2017, validated with simultaneous SAR VH geophysical model function measurements and best-track (BT) estimates. When validated with BT estimates, the method enhances the blurred maximum winds, where the standard deviation of difference decreased from 6.3 to 3.49 m/s and the coefficient of determination increased from 0.7 to 0.89. Besides, it is noteworthy that the proposed technique performs slightly better than the Mayers-Ruf method. The promising results indicate that the technique can provide more representative TC maximum 1-min sustained wind estimates from ASCAT data, thus contributing to the further exploitation of scatterometer data for TC warnings.

Automated summary

Spaceborne microwave sensors are widely used for tropical cyclone monitoring, but there are still challenges in obtaining accurate intensity estimates due to issues such as blurred inner-core structures and limited spatial-temporal coverage. This study proposes a new technique to overcome these challenges and provides more accurate TC intensity estimates from scatterometer data.