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Value chain of Early Warning System

Conveners: Brian Golding (Met Office, United Kingdom), David Hoffmann (Bureau of Meteorology, Australia), Beth Ebert (Bureau of Meteorology, Australia

Since the generation of weather warning and climate services has become more complex, both technically and organizationally, the notion of the value chain or cycle has become a popular conceptual tool in studies trying to assess the use and the net benefits of such services . Weather and associated warning services are developed and provided through a multitude of complex and malleable value chains (cycles, networks), often established through co-design, co-creation and co-provision. The value chain approach facilitates the understanding of the different relationships, processes, inputs, contributions, outcomes, and operational contexts of each stakeholder in the warning chain. The chain can be analysed with different, yet complementary, methods, each emphasizing different sets of characteristics of the value chain and is often represented as a sequence of different scientific disciplines reprocessing information from previous segments and adding additional, unique information. The value chain approach enables assessment of the effectiveness of the service design and delivery process, and options for improvement. Case studies are an effective mechanism to collect and catalogue successes and failures of warning chains for instances of high impact weather. Applying value chain approaches to case studies to characterise and measure the effectiveness of the tools, processes, partnerships, and infrastructure embedded in existing warning chains can provide the evidence to identify shortfalls and propose investments in new capability and partnerships.  We welcome abstracts on:
  • Reviews of existing value chain/cycle approaches, metrics and measures
  • Guidance on how to use value chain/cycle approaches
  • Assessments of high-impact weather case study events using value chain/cycle approaches
  • Challenges, gaps and opportunities arising from using value chains/cycles
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Freie Universität Berlin