CERES: A Probabilistic Early Warning System for Acute Food Insecurity

TL;DR

CERES is an innovative probabilistic early warning system that forecasts acute food insecurity up to 90 days ahead for high-risk countries using multiple data streams and provides open-access, verifiable predictions.

Contribution

CERES introduces the first open-access, probabilistic famine early warning system that continuously generates and publicly verifies 90-day ahead forecasts for multiple countries.

Findings

Successfully classified four historical famine events as high risk.

Provides publicly archived, machine-readable predictions for transparency.

Integrates diverse data streams into a unified probabilistic model.

Abstract

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.