CERES用概率模型预测全球43国粮食危机,每周更新预警结果。
CERES: A Probabilistic Early Warning System for Acute Food Insecurity
- 融合六类数据构建概率模型,预测90天内饥荒风险
- 历史回测中对4次严重饥荒事件全部提前标记为最高级别
- 系统公开可查、自动存档,支持公众验证预测结果
我们提出CERES(校准的早期预警与风险评估系统),一个自动化概率预测系统,用于急性粮食不安全。CERES针对全球43个高风险国家,每周更新未来90天内发生IPC Phase 3+(危机)、Phase 4+(紧急)和Phase 5(饥荒)状况的概率估计。系统融合六类数据:降水异常(CHIRPS)、植被指数(MODIS NDVI)、冲突事件(ACLED)、IPC分类、食物消费评分(WFP)以及谷物价格指数(FAO/WFP),通过逻辑评分模型,采用作者指定的初始系数和参数化输入扰动区间(共2000次抽样)。在四个数据完整性的历史回测事件中,CERES均成功识别出所有四次事件为TIER-1等级;这些仅为样本内合理性检验,不构成前瞻性性能声明。所有前瞻性预测均带时间戳、加密标识并归档,供公众在90天后与实际IPC结果进行验证。据作者所知,CERES是首个同时具备:(1) 概率性、(2) 开放获取、(3) 持续运行、(4) 预测结果机器可读、(5) 承诺公开验证每次预测的饥荒早期预警系统。
原文摘要 · Abstract (English)
We present CERES (Calibrated Early-warning and Risk Estimation System), an automated probabilistic forecasting system for acute food insecurity. CERES generates 90-day ahead probability estimates of IPC Phase 3+ (Crisis), Phase 4+ (Emergency), and Phase 5 (Famine) conditions for 43 high-risk countries globally, updated weekly. The system fuses six data streams, precipitation anomalies (CHIRPS), vegetation indices (MODIS NDVI), conflict events (ACLED), IPC classifications, food consumption scores (WFP), and cereal price indices (FAO/WFP) - through a logistic scoring model with author-specified initial coefficients and parametric input-perturbation intervals (n=2,000 draws). In historical back-validation against four IPC Phase 4-5 events selected for data completeness, CERES assigned TIER-1 classification in all four cases; these are in-sample sanity checks only, not prospective performance claims. All prospective predictions are timestamped, cryptographically identified, and archived for public verification against IPC outcome data at the T+90 horizon. To the author's knowledge, CERES is the first famine early warning system that is simultaneously: (1) probabilistic, (2) open-access, (3) continuously running, (4) machine-readable at prediction level, and (5) committed to public prospective verification of every prediction made.
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