Using Value Chain Approaches to Evaluate End-to-End Warning Systems

The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system. Since the generation of weather warning and climate services has become more complex, both technically and organizationally, the value chain concept has become a popular tool for describing and assessing the production, use and benefits of such services.

The end-to-end warning system for high impact weather brings together hazard monitoring, modelling and forecasting, risk assessment, communication and preparedness activities and systems and processes which support people to take timely action to reduce risks. Weather and associated warning services are typically developed and provided through a multitude of complex and malleable value chains (networks), often established through co-design, co-creation and co-provision.  

A 4-year international project under the WMO World Weather Research Programme that started in November 2020 is using value chain approaches to describe and evaluate the end-to-end warning system for high impact weather. Its aims are

• To review value chain approaches used to describe weather, warning and climate services to assess and provide guidance on how they can be best applied in a high impact weather warning context that involves multiple users and partnerships;
• To generate an easily accessible means (an End-to-End Warning Chain Database) for scientists and practitioners involved in researching, designing and evaluating weather-related warning systems to review previous experience of high impact weather events and assess their efficacy using value chain approaches.

We encourage the research and operational community to participate in this project by contributing case studies of high impact events and collaborating in their analysis. Integration of the physical and social sciences in this project will lead to new insights that we hope will ultimately improve the effectiveness of warnings for high impact weather.