Potential applications of subseasonal-to-seasonal (S2S) predictions

Journal article

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.

Authors: White, CJ; Carlsen, H; Robertson, AW; Klein, RJT; Lazo, JK

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Meteorological Applications
• Volume: 24
• Issue: 3
• Pages: 315-325
• Publication date: 2017-04-06
• Acceptance date: 2016-12-07
• DOI: 10.1002/met.1654
• EISSN: 1469-8080
• ISSN: 1350-4827
• Keywords: extended-range; seasonal prediction; climate prediction; extremes; forecasting; ensemble forecasts; decision-support