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Warning Value Chain Project

Value Chain Approaches to Evaluate the End-to-End Warning Chain 

A joint project of the WWRP HIWeather Project and SERA Working Group

  

Effective warnings of weather-related hazards result from the successful interaction of many people and organisations, each contributing their specific capability and knowledge. The "value chain" provides a useful way to describe the generation and communication of warning data, information, and processes between different stakeholders. By using this approach to study end-to-end warning chains for hazardous weather events, we can learn what worked well and what can be improved.  

 




This project has two main aims: 

  1. To review value chain practices used to describe weather, warning and climate services to assess and provide guidance on how to apply value chains in a weather warning context involving multiple users and partnerships;
  2. To create a searchable Warning Chain Database that researchers and practitioners can use to explore the organisation and performance of actual warning chains for high impact events and assess their effectiveness using value chain approaches.

To develop guidance on how to use value chain approaches we will:

  1. develop a conceptual value chain framework for hydrometeorological services that aligns to WMO's Science to Services focus;  
  2. develop an inventory of existing examples of where the value chain has been applied, based on a systematic review of academic and grey literature and workshops;
  3. create a catalogue of value chain usage types and their suitability for assessing efficiency, planning and execution, evaluating projects, quality control, and testing replicability;
  4. prepare an overview of metrics and methods for measuring aspects of the value chain and the whole value chain; 
  5. provide a high-level value chain framework tool for decision makers, and guidance and tools for more specific usage.

To develop the Warning Chain Database we will:

  1. collect information on relevant high impact weather events from case studies and post event reviews, linking to existing collections such as the emerging WMO Catalogue of Hazardous Events (WMO-CHE), ECMWF Severe Event Catalogue, and DRR databases;
  2. review the governance, structure and organisation of selected weather-related warning systems, including identifying the type of value chain used, to define an outline database classification;
  3. conduct in-depth analysis of selected events that highlight an issue of importance to some or all of the warning chain;
  4. design and build a searchable database (aligned with WMO-CHE) to hold and augment the collected data, to enable easy use of the information to answer questions identified by practitioners.

The project kicked off in November 2020 with an international project team of physical and social scientists. It will run until the completion of HIWeather and deliver:

  1. A high level value chain framework tool for decision makers
  2. Guidance and tools for more specific and context-appropriate usage of value chain approaches in hydrometeorology
  3. A glossary of value chain and warning chain terminology in a hydrometeorological context 
  4. A living database of hazardous weather events with rich information covering (as much as possible) the components of the forecast and warning value chain, that complements WMO efforts such as the WMO Catalogue of Hazardous Events (WMO 2019). 
  5. Analysis and advice on best practice warning value chains (from simple to complex) analysed from the database
  6. Exchange and integration of practical experiences (NMHSs and partners) and weather-related natural, social, and interdisciplinary science (research community)

Some of the many research questions of interest to HIWeather include:

  1. What are the average predictability horizons for different types of HIW events and how do these horizons relate to the dominant governing processes?
  2. What are the improvements in hazard prediction from convection-permitting models related to advanced methods of mesoscale DA, the inclusion of high-resolution observations, or better NWP models?
  3. To what extent have we been able to define, measure, model, and predict constitutive aspects of risk (dynamic exposure, vulnerability, sensitivity) for individual and cumulative (multi-hazard) threats?
  4. What is the efficacy of co-producing/ communicating/sharing this risk and impact knowledge with various actors (i.e., as measured in terms of comprehension, application/use in decision- or policy-making, behavioural intent, behavioural response, impact outcomes)?
  5. What elements of a warning (e.g. hazard, impact, guidance; text, graphics, analogies; scenarios, probabilities, likelihood terms) can be tweaked to ensure a more effective warning and response?
  6. How does the level of uncertainty in the forecast affect the overall impacts i.e. did cases with higher forecast certainty result in better outcomes in terms of action to prevent impacts than those cases with more uncertain forecasts? And if so why? 


The concept proposal gives greater detail on the Value Chain project, including the types of data to be collected and research questions that could be addressed by the warning chain data. You can also hear a brief (4-minute) description of the Value Chain Project at the HIWeather YouTube channel.


We are currently preparing a more detailed plan and will seek funding to support some of the work. 





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