Extreme Weather Expertise

Strong ocean surface mean and gust winds associated with deep convection can cause significant damages. It is hard to estimate surface convective wind gusts since they may occur suddenly and become intense quickly. This problem is even more challenging for tropical and subtropical regions over which convection is particularly intense while one has little in-situ and remote sensing data. This paper presents the collocation of several Low-Earth Orbit (LEO)-acquired data sources to observe and estimate ocean surface convective winds. The LEO devices include Sentinel-1 Synthetic Aperture Radar (SAR), ASCAT-A/B/C scatterometers, Windsat, and SMAP radiometers. This combination enables the short and long-term observations of ocean wind pattern variabilities, for instance, a mesoscale squall line and a sub-mesoscale wind cell. Sentinel-1 data can offer convective wind gust estimates at a high spatial resolution while the other sources (SMAP, Windsat, and ASCAT-A/B/C) only estimate wind gusts at a scale larger than 0.25 grid. Also, thanks to the LEO data collocation, one can observe the displacement direction of surface wind patterns and their intensity variabilities (15-25 m/s). Surface wind patterns move according to the horizontal displacement of deep convective clouds aloft observed by the Meteosat geostationary satellite. Likewise, the wind intensity variability and deep cloud brightness temperature evolve accordingly. Using simultaneous rainfall and wind speed measurements from Windsat, this study showed that the high-intensity radar backscattering from C-band Sentinel-1 SAR data is mainly induced by convective winds rather than precipitation.

Abstract Previous studies indicated a relationship between deep convection and sea surface wind patterns; however, it remains difficult to remotely observe a deep Convective System (CS) and its dynamics above the ocean due to the lack of data at the mid atmospheric levels. To collect the details of the CS dynamics, some nearly simultaneous data of three CS features, that is, cloud brightness temperature, vertical wind at the midlevels, and horizontal wind at the sea surface, can be now obtained by a combination of sensors from a geostationary (Meteosat) and two polar‐orbiting satellites (Sentinel‐1 and Aeolus), having corresponding acquisition time and orbit track matching. This work thus illustrates a nearly three‐dimensional view of the CS atmospheric dynamics over the sea, including deep convective clouds observed by Meteosat, intense downdrafts measured by Aeolus, and strong surface winds estimated by Sentinel‐1.

The use of a single source of data - very high-resolution SAR data from polar earth orbiters - allows the computation of several major environmental parameters over ocean surface: high-resolution winds (with a brand-new method), ship detection, oil spill detection, sea-ice detection. These computations are based both on deterministic and machine learning methods The monitoring of all these parameters is gathered in a single operational Web platform that allows and triggers computation on demand.