The Value-Add of Tailored Seasonal Forecast Information for Industry Decision Making

Author:

Goodess Clare MaryORCID,Troccoli Alberto,Vasilakos NicholasORCID,Dorling StephenORCID,Steele Edward,Amies Jessica D.ORCID,Brown Hannah,Chowienczyk Katie,Dyer Emma,Formenton Marco,Nicolosi Antonio M.,Calcagni Elena,Cavedon Valentina,Perez Victor EstellaORCID,Geertsema Gertie,Krikken Folmer,Nielsen Kristian Lautrup,Petitta MarcelloORCID,Vidal José,De Ruiter Martijn,Savage Ian,Upton Jon

Abstract

There is a growing need for more systematic, robust, and comprehensive information on the value-add of climate services from both the demand and supply sides. There is a shortage of published value-add assessments that focus on the decision-making context, involve participatory or co-evaluation approaches, avoid over-simplification, and address both the quantitative (e.g., economic) and qualitative (e.g., social) values of climate services. The 12 case studies that formed the basis of the European Union-funded SECLI-FIRM project were co-designed by industrial and research partners in order to address these gaps while focusing on the use of tailored sub-seasonal and seasonal forecasts in the energy and water industries. For eight of these case studies, it was possible to apply quantitative economic valuation methods: econometric modelling was used in five case studies while three case studies used a cost/loss (relative economic value) analysis and avoided costs. The case studies illustrated the challenges in attempting to produce quantitative estimates of the economic value-add of these forecasts. At the same time, many of them highlighted how practical value for users—transcending the actual economic value—can be enhanced; for example, through the provision of climate services as an extension to their current use of weather forecasts and with the visualisation tailored towards the user.

Funder

European Union

Publisher

MDPI AG

Subject

Atmospheric Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Seasonal forecasting of subsurface marine heatwaves;Communications Earth & Environment;2023-06-26

2. A Novel Bias Correction Method for Extreme Events;Climate;2022-12-23

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