Extensive High-Resolution Synthetic Aperture Radar (SAR) Data Analysis of Tropical Cyclones: Comparisons with SFMR Flights and Best Track

Abstract

To produce more precise descriptions of air-sea exchanges under Tropical Cyclones (TCs), spaceborne Synthetic Aperture Radar (SAR) instruments provide unique capabilities to probe the ocean surface conditions, at very high spatial resolution, and on synoptic scales. Using highly-resolved (3 km) wind fields, an extensive database is constructed from Radarsat-2 and Sentinel-1 SAR acquisitions. Spanning 161 tropical cyclones, the database covers all TC intensity categories that have occurred in five different TC basins, and include 29 cases coincident with SFMR measurements. After locating the TC center, a specific methodology is applied to filter out areas contaminated by heavy precipitations to help extract, for each acquisition, the maximum wind speed (Vmax), its associated radius (Rmax), and corresponding outer wind radii (R34/50/64-kt). These parameters are then systematically compared with Best-Track (BTK), and when available, SFMR airborne measurements. For co-located SFMR and SAR observations, comparisons yield root-mean-squares of 3.86 m s−1 and 3 km, for ocean surface wind speeds and TC Rmax, respectively. High correlations remain for category 5 cases, with Vmax exceeding 60 m s−1. The largest discrepancies are found between BTK and SAR Rmax estimates, with Rmax fluctuations poorly captured by BTK, especially for rapidly evolving category 3,4 and 5 TCs. In heavy precipitation (>35 mm h−1), the SAR C-band measurements may be impacted, with local ambiguities associated to rain features, as revealed by external rain measurements. Still, this large dataset demonstrates that SAR measurements have unique high-resolution capabilities, capturing the inner- and outer-core radial structure of the TC vortex, and provide independent and complementary measurements than those used for BTK estimates.

Self‐Similarity of Surface Wave Developments Under Tropical Cyclones

“…To further note, severe weather systems are difficult to fully characterize, making remote sensing techniques essential for observing surface processes. At time, satellite observations can produce spatially well-resolved snapshots of surface winds (e.g., Combot et al, 2020;Mouche et al, 2019). However, most extreme events may still be undersampled, and this lack of observations cannot always lead to fully characterize spatio-temporal surface wind forcing conditions.…”

Tropical Cyclone Winds from WindSat, AMSR2, and SMAP: Comparison with the HWRF Model

“…This includes further study of the biases between the satellites and HWRF in different rain regimes. We also wish to extend our comparisons of the satellite TC-winds with other external sources, such as the Synthetic Aperture Radar (SAR) aboard the Sentinel and RADARSAT-2 satellites [29][30][31], as well as other models.…”

Uncertainty of Tropical Cyclone Wind Radii on Sea Surface Temperature Cooling

“…There is hope though. New inner core remotely sensed observations that use cross-polarization, such as those from Synthetic Aperture Radar (SAR), can instantaneously estimate the surface winds (see Combot et al, 2020;Mouche et al, 2019) and are becoming available to operations in near real-time. To augment SAR observations, other all-weather wind estimates from multi-banded (Alsweiss et al, 2018;Chang et al, 2015;Shibata, 2002Shibata, , 2006 and L band radiometers (Meissner et al, 2017;Reul et al, 2016Reul et al, , 2017Yueh et al, 2016) also help, but are often limited by their >20 km resolutions and/or latency issues.…”

“…However, the wind radii (collectively referred in this work as TC size) are difficult to both observe and simulate since they are continually affected by environmental factors and TC motion (Chan and Chan, 2012, 2013; Hill & Lackmann, 2009; Mok et al., 2018). Even with recently available satellite imagery techniques, the observational uncertainty in TC size is still an issue (Combot et al., 2020; Knaff & Sampson, 2015; Landsea & Franklin, 2013; Reul et al., 2017). Many studies have devoted efforts to discuss uncertainty with and improvement in estimates of TC wind radii (e.g., Knaff & Sampson, 2015; Landsea & Franklin, 2013; Sampson et al., 2018), but issues still exist (Sampson & Knaff, 2015; Sampson et al., 2017, 2018).…”