Global communications without reliance on an engineered communications network make the ionosphere an attractive medium for wireless sensors in remote deployments. However, ionospheric circuits’ temporary availability is a challenge in scheduling transmissions for a sensor with limited power, communications and computational capacity, particularly where cost and antenna constraints limit operation to a single frequency. We describe a technique for scheduling transmissions based on precomputed propagation models. The models predict the time-varying Signal to Noise Ratio (SNR) at the receiver. We describe methods to determine threshold SNR values, using the Weak Signal Propagation Reporter (WSPR) database to determine if a time slot is suitable for transmission.Two techniques are investigated to quantify the failed receptions: the Inverse Square Law method uses a statistical approach and a sampling measurement technique called Goldilocks. The two approaches yielded threshold SNR values of −21 dB and −19 dB, respectively, for a time slot with a 90% successful reception goal. Applying these thresholds to the modelled SNR, we generate a precomputed hourly transmission schedule. With the schedule determined monthly, a 12-month plan requires 36 bytes of wireless sensor storage. A six-day experiment, using a 1677 km path, found that the schedule resulted in an 83% reception rate when used with a power level of 200 mW.