Quantifying the potential for improved management of weather risk using sub‐seasonal forecasting: The case of UK telecommunications infrastructure

Abstract Reliable and affordable telecommunications are an integral part of service‐based economies, but the nature of the associated physical infrastructure leads to considerable exposure to weather. With unique access to observational records of the UK fixed‐line telecommunications infrastructure, an end‐to‐end demonstration of how extended range forecasts can be used to improve the management of weather risk is presented, assessing forecast value on both short‐term “operational” (weeks) and long‐term “planning” timeframes (months/years). A robust long‐term weather‐related fault‐rate climatology is first constructed at weekly resolution, based on the ERA‐Interim reanalysis. A clear dependence of winter fault rates on large‐scale atmospheric circulation indices is demonstrated. The European Centre for Medium‐Range Weather Forecasts (ECMWF) sub‐seasonal forecast system is subsequently shown to produce skilful forecast of winter weekly fault rates at lead times of three to four weeks ahead (i.e. days 14–20 and 21–28). Forecast skill at a given lead time is, however, a necessary rather than a sufficient condition for improved risk management. It is shown that practical decision‐making leads to dependencies across multiple forecasts times that cannot be modelled using traditional “cost‐loss matrix” methods as errors in previous forecasts influence the value of subsequent forecasts. A parsimonious model representing operational decision‐making for fault repair scheduling is therefore constructed to show that fault‐rate forecast skill does improve both short‐ and long‐term management outcomes (in this case meeting performance targets more often in the short term, or reducing the resources required to achieve these targets in the long term). Consequently, it is argued that new methods are needed for forecast skill assessment in complex decision environments.