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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 <italic>in situ</italic> and remote sensing data. This article 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&#x002F;B&#x002F;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 submesoscale wind cell. Sentinel-1 data can offer convective wind gust estimates at a high spatial resolution, whereas the other sources (SMAP, Windsat, and ASCAT-A&#x002F;B&#x002F;C) only estimate wind gusts at a scale larger than 0.25&#x00B0; grid. Also, thanks to the LEO data collocation, one can observe the displacement direction of surface wind patterns and their intensity variabilities (15&#x2013;25 m&#x002F;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 <italic>C</italic>-band Sentinel-1 SAR data is mainly induced by convective winds rather than precipitation.

Different Observations of Sea Surface Wind Pattern Under Deep Convection by Sentinel-1 SARs, Scatterometers, and Radiometers in Collocation