Learning to Coordinate: Virtual Sampling of the Tropical Air-Sea Transition Zone with Saildrones and Underwater Gliders.

Exchanges of energy, mass and momentum between the atmosphere and the oceans are critical to the Earth’s system, in particular within the tropical region, where they govern the physics of consequential phenomena such as El Niño Southern Oscillation, the Madden-Julian Oscillation as well as tropical cyclones. Due to their characteristic spatiotemporal scales and geographical remoteness, these exchanges remain some of the most difficult processes to observe. Fast-paced advances in uncrewed system (UxS) technology push us to reimagine the sampling of the Air Sea Transition Zone by co-locating multiple observing platforms to achieve simultaneous measurements of the ocean temperature, current and salinity, atmospheric temperature, wind and moisture as well as sea-state properties. While pioneering eld campaigns have demonstrated the potential of co-located UxS deployments, they also showcased their limitations, especially in high-wind regimes. To improve the success of future missions, we need to devise multiple sampling strategies for ASTZ measurements using coordinated UxS and assess their feasibility. We do so by virtually sampling the ASTZ within high-resolution fully-coupled atmosphere-wave-ocean simulations using the Unified Wave Interface-Coupled Model (UWIN-CM). First, we develop realistic dynamical simulators of saildrones and underwater gliders based on force-balance principles and test them against observations from recent deployments. Subsequently, the simulators are plugged into two UWIN-CM simulations. The first reproduces the MJO eastward propagation across the West Pacific and includes both the low- wind regime associated with the trade winds and the high-wind regime tied to the westerly wind burst. The second simulates the extreme conditions associated with the Cat.4 Hurricane Fiona in 2022 in the North Atlantic. For each simulation, we build a hierarchy of sampling strategies of various complexity and scientific purposes.