| Summary: | Agricultural production frequently suffers from meteorological risks. Timely and accurately estimating yield losses will greatly improve disaster risk management, especially for a useful tool to transfer risks—agricultural insurance. The weather index insurance products have increasingly become promising alternatives to traditional ones. However, the current single-index insurances, mainly based on a statistical model with a lower explanation ability and at an aggregate scale (e.g. county, province), are lack of mechanistic processes and having huge basis risk. Here, we proposed a new framework to quantify maize production risk by running the well calibrated CERES-Maize driven by various chilling scenarios. We first analyzed the chilling risk across Northeast China, then developed a composite chilling index (CCI) and CCI-based vulnerability curves to derive the corresponding yield losses. Finally, the specific pure premium rates were calculated respectively at 16 sites across the studied areas. The results showed that composite-index insurance (RMSE¯ ≤ 721 kg/ha) outperformed (R2 improved by 35%) every single index (RMSE¯ ≈ 1140 kg/ha) in quantifying yield loss. We believe our proposed framework will benefit insurer companies rapidly estimating yield losses and designing more promising products, and potentially apply into other regions for other crops and hazards to transfer climate risk in the future.
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