General differential equations for multi-objective reachability and optimal planning are used to guide autonomous air and sea drones in hazard-time optimal missions. The vehicles minimize exposure to hazards and travel time, leveraging the dynamic environments with strong flows and steering clear of dynamic hazardous regions. We demonstrate the approach first with an autonomous air drone that crosses the Atlantic Ocean optimizing travel time using trade winds while avoiding hazardous rain storms in the inter-tropical convergence zone. We then consider an air drone that exploits winds and avoids hazardous rains to transport an ocean vehicle to a target destination. The ocean vehicle then completes its own hazard-time optimal mission, leveraging ocean currents and avoiding vessel traffic hazards. In all cases, we predict hazard-time reachable sets, Pareto fronts, and optimal paths. The results highlight the benefits of considering hazards in optimal path planning.