Warning Value Chain Project
Flagship activities
Outputs

The project delivered:

  • · A high-level value chain framework containing and guidance and tools for more specific and context-appropriate usage of value chain approaches

Value chain approaches to describe, improve, value and co-design early warning systems. WWRP 2024-4, 122 pp.

  • · A glossary of value chain and warning chain terminology in a hydrometeorological context
  • · A Warning Chain Database Questionnaire (template) and Guide for use within the project and by other interested researchers and practitioners.
  • · A Rapid Assessment Template version of the database questionnaire for collecting and displaying data for warning value chain case studies.
  • · A living database of hazardous weather events with rich information covering (as much as possible) the components of the forecast and warning value chain. The database is being implemented at the Warning Research Centre at University College London.
  • · Analysis and advice on best practice warning value chains (from simple to complex) analysed from the database
  • · Integration of practical experiences of national meteorological and hydrological services and their partners with the research community of weather-related natural, social, and interdisciplinary sciences 
  • · Workshops, conference sessions, presentations and publications



Publications:

Golding, B., Ebert, B., Hoffmann, D., & Potter, S. (2023). Preparing for the unprecedented. Advanced in Science and Research, 20, 85–90. https://doi.org/10.5194/asr-20-85-2023

Hoffmann, D., Ebert, E.E., Mooney, C., Golding, B. & Potter, S. (2023). Using value chain approaches to evaluate the end-to-end warning chain. Advances in Science and Research, 20, 73–79, https://asr.copernicus.org/articles/20/73/2023/

Majumdar, S. J., Hoffmann, D., Ebert, E. E., & Golding, B. W. (2024). Bringing the Value Chain for High-Impact Weather Warnings into the Classroom. Bulletin of the American Meteorological Society105(8), E1603-E1609.

Tan, M.L., Hoffmann, D., Ebert, E., Cui, A., & Johnston, D. (2022). Exploring the potential role of citizen science in the warning value chain for high impact weather. Frontiers in Communication, 7:949949. https://doi.org/10.3389/fcomm.2022.949949

Zhang, Q., Ng, C. P., Dai, K., Xu, J., Tang, J., Sun, J., & Mu, M. (2021): Lessons learned from the tragedy during the 100 km ultramarathon race in Baiyin, Gansu Province on 22 May 2021. Advances in Atmospheric Sciences, 38, 1803-1810. https://doi.org/10.1007/s00376-021-1246-0


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