| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.1002/2016MS000625 |
| Calibration induced uncertainty of the EPIC model to estimate climate change impact on global maize yield. | |
| Xiong W; Porter CH; Balkovic J; Jones JW; Yang D | |
| 发表日期 | 2016 |
| 出处 | Journal of Advances in Modeling Earth Systems 8 (3): 1358-1375 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical datasets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter results in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation |
| 主题 | Ecosystems Services and Management (ESM) |
| URL | http://pure.iiasa.ac.at/id/eprint/13599/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/130507 |
| 推荐引用方式 GB/T 7714 | Xiong W,Porter CH,Balkovic J,et al. Calibration induced uncertainty of the EPIC model to estimate climate change impact on global maize yield.. 2016. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Calibration%20induce（1570KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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