Developing forecast information for institutional decision-makers

Abstract

<p>There remains a gap between the production of scientifically robust forecasts, and the translation of these forecasts into useful information such as daily “bulletins” for institutional decision-makers in early warning systems. There is significant published literature on best practice to communicate risk information, but very little to guide and provide advice on the process of how these bulletins have been, or should be, developed.</p><p>This presentation will discuss learning and share best practices of developing such early warning bulletins for institutional decision-makers, providing specific case study examples and drawing on wider experience from Practical Action and the Science for Humanitarian Emergencies And Resilience (SHEAR) programme.</p><p>The session will share lessons from two example case studies where bulletins were developed for national and district-level government agencies and humanitarian responders as part of the SHEAR programme: daily reports in response to Cyclones Idai and Kenneth in Mozambique, and prototype landslide forecast bulletins in Nilgiris and Darjeeling Districts of India.</p><p>There were significant similarities in the type of content included in the bulletins, such as the layout, choice of words, and use of visualisation that was consistent with published best practices. Both case studies experienced challenges dealing with uncertainty, complexity, and whether to include advice. There were also similarities in the processes and approaches taken to develop the bulletins. Both case studies took an iterative approach, developed feedback mechanisms, benefitted from experienced multi-disciplinary teams, emphasised the need for strong inter-relationships, and the importance and value of preparedness and protocols.</p><p>A major challenge was the difficulty of balancing science capabilities with user needs, which did not become significantly easier to deal with given more time availability. The findings indicate that whilst more research is needed into existing or best practice processes to develop content for forecast bulletins, there is an existing body of experiential and intuitive knowledge and learning that already exists but is not yet captured in an appropriate format that could be of significant interest and value to those developing and responsible for providing forecast information.</p><p>This presentation will share key learning from translating scientific forecasts into useful information, in particular on both the content and the process of developing forecast bulletins for decision-making.</p>