In wireless mobile networks, energy can be saved by using dynamic transmission scheduling with pre-knowledge about channel conditions. Such pre-knowledge can be obtained via profiling as proposed by several existing systems which assumed that the existence of spatial link correlation makes the measured channel status at one location reusable over a long period of time. Our empirical data, however, tells a different story: spatial link correlation only maintains well within a short duration (from seconds to tens of seconds) while decreases significantly afterwards, a phenomena we call ephemeral link correlation. By leveraging this observation, we design and implement a real-time transmission scheduling system, named PreSeer, on the railway platform for cargo transportation, where the transmission of a sink (to cellular towers) can be scheduled intelligently by utilizing future channel status measured by sinks located in front of it on the same train. We have implemented and evaluated the PreSeer system on the collected data extensively over 7,000-kilometer railway routes during a period of one and half years. Results reveal that PreSeer can help save as much as 40% energy, comparing with three base-line algorithms. More importantly, lessons learned from this major effort provide useful guidelines for transmission scheduling in highlydynamic mobile environments, where (i) channel measurements cannot be perfectly aligned due to varying vehicle velocities, and (ii) the accuracy of channelmeasurements is subject to hardware discrepancy as well as environment irregularity.