这篇论文把气候预报和供应链风险结合，用哥伦比亚农业数据做了原型验证，适合关注气候风险建模和供应链管理的人看。
该论文提出一个用于实时气候风险评估的方法框架，利用数据驱动的临近预报技术增强哥伦比亚农业供应链的韧性。框架整合基于历史气象观测的短期气候预报与供应链风险建模，构建概念性早期预警系统架构。原型在受控计算环境中实现，使用官方统计和再分析产品的历史气象与农业时间序列，不依赖卫星图像或计算机视觉。实验表明，短期降水临近预报可转化为可操作的风险指标，支持库存、采购和运输的预判决策。
Real-Time Climate Risk Assessment for Supply Chain Resilience: A Data-Driven Nowcasting Framework for Colombian Agriculture
This paper presents a methodological framework for real-time climate risk assessment using data-driven nowcasting techniques to enhance supply chain resilience in Colombian agricultural contexts. Climate variability in Colombia, characterized by irregular rainfall, temperature fluctuations, and recurrent extreme events, has a direct impact on agricultural production and logistics, particularly for time sensitive crops. The proposed approach integrates short term climate forecasting based on historical meteorological observations with supply chain risk modeling to establish a conceptual early warning system architecture. A prototype implementation developed in a controlled computational environment demonstrates the feasibility of the framework using historical meteorological and agricultural time series derived from official statistics and reanalysis products, without reliance on satellite imagery or computer vision components. The methodology addresses the integration of climate nowcasting with supply chain decision making through explicit risk mapping, threshold-based categorization, and stakeholder-oriented risk signals. Results from synthetic and historical data experiments indicate that short term precipitation nowcasts can be translated into actionable risk indicators for agricultural supply chains, supporting anticipatory decisions related to inventory, sourcing, and transport.