Demonstrates a novel use of telecom signals for weather modeling, indicating potential advancements in meteorological monitoring.
Existing weather radar networks suffer from severe spatial blind spots, leaving low-altitude airspace, complex topography, and vast agricultural zones unmonitored at high resolutions. Simultaneously, global satellite constellations and terrestrial 5G/6G networks transmit high-frequency radio signals through the troposphere millions of times per second. Historically, atmospheric degradation of these signals has been treated as interference to be corrected. Opportunistic Atmospheric Radio Tomography (O-ART) inverts this paradigm by treating commercial telecommunications infrastructure as an unexploited, multi-angle atmospheric sensor grid. By applying discrete linear inverse tomographic algorithms to Received Signal Strength Indication (RSSI) telemetry across intersecting space-to-ground and ground-to-ground links, O-ART constructs real-time, 3D voxel models of liquid water content and hydrometeor density without requiring new hardware deployment. However, commercial and operational feasibility remains the primary bottleneck. Ingesting RSSI telemetry at scale requires formal, strategic partnerships with satellite operators like SpaceX/Starlink—a hurdle that may prove difficult, if not functionally impossible, to overcome. Furthermore, while physical CAPEX is near zero, operational expenditure (OPEX) could be substantial: telemetry licensing fees demanded by ground networks and constellation operators may be exorbitant, or the data simply may not be available for purchase at any price.
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Craig Kyrle Strachan Davidson (2026) studied this question.
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