Leveraging local knowledge to develop local forecasts: A case study of sea-ice hazard forecasts for marine fisheries in Laizhou Bay, China

Climate change increasingly exposes agricultural communities to natural hazards, yet effective communication of hazard forecasts and warnings remains limited, hindering preparedness and adaptation. This paper presents a systematic approach to developing local hazard forecasts and warnings by integrating local knowledge into existing technocratic systems. A synthesized literature review established a foundational framework for categorizing and incorporating local knowledge to enhance core forecasting and warning pillars and questions. This was followed by a case study on developing local sea-ice forecasts for marine fishery communities in Laizhou Bay, China. An operational framework was proposed, which included four sequential mixed-methods steps: expert consultations, focus group discussions, individual interviews, and eye-tracking experiments, to gather ecological, adaptive, social, and cognitive knowledge related to sea-ice risks and fishery adaptation. The local knowledge was incorporated into the system by addressing five operational questions: who, when, what, through what means, and how to communicate forecasts effectively. Four fishery user groups were identified, and their information needs were analyzed, highlighting the importance of the annual forecast issued on November 20th. Local communication networks were mapped to strengthen both public-facing and inter-agency dissemination. Based on the cognitive experiment findings, a dual-format communication strategy was proposed, integrating official forecasts with localized social messaging to convey both scientific and locally relevant risk indicators using familiar terminology. This research provides a practical solution to the “last mile” challenge in agricultural forecasting and contributes to the broader goal of impact-based forecasts and warnings by leveraging local knowledge.