Development of forecast information for institutional decision-makers: landslides in India and cyclones in Mozambique

Abstract

Abstract. 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 decision-makers in early warning systems. There is significant published literature on best practice in communicating risk information but very little to guide and provide advice on the process of how these bulletins have been, or should be, developed. This paper reviews two case studies where bulletins were developed for national and district-level government agencies and humanitarian responders: daily reports in response to cyclones Idai and Kenneth in Mozambique and prototype landslide forecast bulletins in the Nilgiris and Darjeeling districts of India. Primary data were collected from producers and intermediaries of the bulletins via interview, and secondary data were analysed on iterative changes in the bulletin development, minutes from internal discussions, and feedback from users to extract learning on both the content and process of developing the bulletins. 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 multidisciplinary teams, and emphasised the need for strong inter-relationships and the importance and value of preparedness and protocols. A major challenge was the difficulty in balancing science capabilities, including issues related to data scarcity, with user needs, which did not become significantly easier to deal with given more time availability. In particular, there were tensions between developing new forecast products that were urgently needed by users against the limited time for testing and refinement of those forecasts and the risk of misinforming decisions due to uncertainty in the information based on limited data. 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 that is not yet captured in an appropriate format that could be of significant interest and value to those developing forecast information. This paper goes some way to capturing some of the learning from translating scientific forecasts into useful information, in particular on both the content and the process of developing forecast bulletins for decision-making.