Chapter 22 - Subseasonal-to-seasonal climate predictions for energy

Soret, A; Gonzalez, PLM; Bloomfield, HC; Masato, G; Goutham, N; Plouhonven, R; Torralba, V

doi:10.1016/B978-0-443-31538-1.00023-3

Chapter 22 - Subseasonal-to-seasonal climate predictions for energy

Lookup NU author(s): Dr Hannah Bloomfield ORCiD

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

The energy sector is undergoing a rapid transformation toward low-carbon renewable energy sources. However, the increasing share of weather-dependent renewables, coupled with climate change impacts, introduces new challenges for energy system stability and market dynamics. Subseasonal-to-seasonal (S2S) forecasts offer a valuable opportunity to anticipate weather-driven fluctuations in electricity and gas markets. While weekly-mean energy demand forecasts retain skill for up to 4 weeks, wind and solar power forecasts lose accuracy beyond 2 weeks. Hydropower, benefiting from slowly varying drivers, exhibits seasonal predictability. Despite their potential, S2S forecasts remain underutilized due to concerns over skill, probabilistic interpretation, and integration challenges. Advancing climate services for energy requires interdisciplinary collaboration between researchers and industry stakeholders. This chapter explores the state of the art in S2S forecasting for energy applications, highlighting opportunities, limitations, and pathways for improving forecast usability and adoption in decision-making.