While seasonal outlooks have been operational for many years, until recently the extended‐range timescale referred to as subseasonal‐to‐seasonal (S2S) has received little attention. S2S prediction fills the gap between short‐range weather prediction and long‐range seasonal outlooks. Decisions in a range of sectors are made in this extended‐range lead time; therefore, there is a strong demand for this new generation of forecasts. International efforts are under way to identify key sources of predictability, improve forecast skill and operationalize aspects of S2S forecasts; however, challenges remain in advancing this new frontier. If S2S predictions are to be used effectively, it is important that, along with science advances, an effort is made to develop, communicate and apply these forecasts appropriately. In this study, the emerging operational S2S forecasts are presented to the wider weather and climate applications community by undertaking the first comprehensive review of sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. The value of applications‐relevant S2S predictions is explored, and the opportunities and challenges facing their uptake are highlighted. It is shown how social sciences can be integrated with S2S development, from communication to decision‐making and valuation of forecasts, to enhance the benefits of ‘climate services’ approaches for extended‐range forecasting. While S2S forecasting is at a relatively early stage of development, it is concluded that it presents a significant new window of opportunity that can be explored for application‐ready capabilities that could allow many sectors the opportunity to systematically plan on a new time horizon.

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The publication of the UKCP09 climate change projections for the United Kingdom provides the opportunity for more rigorous inclusion of climate change uncertainty in water resources planning. We set out how the current approach to incorporating climate change and other uncertainties in water resources planning may be updated to incorporate the UKCP09 projections. In an uncertain future, the frequency with which customers will experience water shortages cannot be predicted for sure, so a water company cannot predict definitely whether it will or will not fulfil its Level of Service commitments. We therefore go on to propose that the probability of failing to meet Level of Service (for given populations of customers) provides an appropriate metric of risk, which conveniently summarises the uncertainties associated with supply and demand, including climate change uncertainties. We sketch out how this risk metric can be calculated based upon simulation modelling of the water resource system.

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