Route based forecasting takes into account how the local geography interacts with the regional climate to produce a detailed model of road surface conditions for every 50m section of road. By knowing which sections of road are likely to fall below the 0°C threshold on a night-by-night basis, highway engineers can selectively treat just the affected routes and make significant savings in salt usage. Since 2006, this forecasting technology has been used by private weather companies around the world.
Following the commercialisation of the original approach, one weather company funded a University of Birmingham research programme to further refine and improve the idea. One of the key findings was the present inability to verify forecasts at the spatial and temporal resolution provided by the forecast. This was often a major issue in convincing the user base to fully utilise the benefits of Route Based Forecasting (i.e. selective salting where the gritting spread rate is controlled by the forecast).
This use of low-cost sensing technology aligned perfectly with the growing Smart City / Internet of Things (IoT) research agenda. The key innovation was the self-contained nature of the device, based on a non-contact thermopile, needing just a small battery for power and communicating via the latest generation of IoT networks. These innovations, combined with the ease of installation (i.e. no need to dig up roads) meant that the sensors could be produced and deployed much more cheaply than traditional alternatives. It meant, that for the first time, affordable observations could be made to complement high resolution forecasts, unlocking the economic benefits of Route Based Forecasting.