Fostering tropical cyclone research and applications with Synthetic Aperture Radar

We examine how, over its first decade, the Sentinel-1 mission has advanced the estimation of ocean surface winds over tropical cyclones, supported their global monitoring, and fostered related research. C-band S1 Synthetic Aperture Radar have been instrumental in refining wind retrieval algorithms, relying on the co- and cross-polarized normalized radar cross-section sensitivity to the ocean wind–waves, especially for major category (3-5) tropical cyclones observed in wide swath modes. Systematic comparisons with airborne multi-frequency radiometer measurements confirm the ability of Synthetic Aperture Radar to provide estimates of the ocean surface wind field at kilometer resolution during a tropical cyclone (bias of 0.08 m/s, standard deviation of 3.84 m/s, correlation of 0.97) and to extract its main characteristics, including the center of the wind circulation, the maximum possible extent of a given wind speed around the tropical cyclone and the radius of maximum wind. Now available globally and in near-real time at operational tropical cyclone forecasting centers, Synthetic Aperture Radar observations are part of the mix used to diagnose the state of the tropical cyclones and issue warning bulletins. Sentinel-1 decametric-backscatter and kilometric-wind resolutions have also been shown to be a reference for interpreting and calibrating other satellite, in situ measurements, and algorithms. Sentinel-1 synoptic observations benefit from new observing systems. Their synergistic use enables us to provide improved temporal resolution of TCs inner core structural parameters. Research efforts exploiting Synthetic Aperture Radar measurements to document such a dynamical system, infer tropical cyclone boundary layer properties, TC-generated waves, and interactions with the upper ocean are presented. This growing increase in acquisitions from multiple C-band Synthetic Aperture Radar missions (e.g. the Radarsat Constellation Mission) over TCs (a factor of 4 over the last decade), combined with other observational data and numerical models, opens opportunities to revisit robust data-driven approaches. These advances shall support a better representation of tropical cyclones in digital twin frameworks. Both algorithm improvements on existing and future Synthetic Aperture Radar missions are attractive perspectives to provide more accurate predictions and a deeper understanding of these complex weather systems.